World Cotton Research Conference - 5 .Session_1

Cotton Improvement and Biotechnology

Genetic Diversity Analysis in Cotton Germplasm

Prafulla Naphade1, Pandurang Kulkarni1, Rahul Ramekar2, Ashok Jaybhaye2 Chandrashekhar Chaporkar1, Bharat Char2 and Venugopal Mikkilineni2

1Research & Development (Cotton Breeding) 2Research & Development (Molecular Breeding and Applied Genomics),

Maharashtra Hybrids Seeds Co. Ltd., Jalna, India

Abstract—Crop germplasm diversity contributes significantly to the development of improved crop cultivars aimed at increasing crop productivity. In this study, we have selected 192 proprietary inbred lines of Gossypium hirsutum that show variable phenotype for traits such as leaf hair density, leaf texture, boll size, plant architecture (type), fibre quality parameters, maturity group, and response to biotic and abiotic stresses. This germplasm pool was screened with 54 polymorphic Microsatellite markers. It was found that 47 loci out of the 54 loci show polymorphism between any two lines. The similarity index values ranged between 41% to 98%. Three major dendrogram clusters and twelve minor dendrogram clusters were observed. These results suggested that there is a high degree of genetic diversity in the cotton germplasm which was screened.

INTRODUCTION

Allelic diversity naturally present in the germplasm pool and characterization of the allelic diversity determines the genetic diversity present in the germplasm pool. This forms the basis for continuous evolution. Genetic diversity and the knowledge on relationship between genotypes are of great importance for crop breeding. It creates a resource pool of alleles and enables pooling of novel alleles and helps in creating new allelic combinations which result in creation of novel genotypes. From a practical crop breeding perspective, understanding the genetic variability will serve as a guide to choosing the parents from a larger pool of germplasm. Crossing individuals that are genetically distant can result in developing superior hybrids with higher heterotic potential and hence higher yields. Molecular level study of the genetic diversity will also help in situations where quantitative traits are desirable and in field conditions it is difficult to evaluate the lines due to the effect of the environment on the phenotype (Weir, 1990).

Cotton productivity and the future of cotton breeding efforts, as in many other agronomic crops, also depend on genetic diversity of cotton gene pools. Worldwide cotton breeders and producers have expressed concern over the narrow genetic basis of cultivated cotton germplasm that has caused a decline in yield and quality. Globally cotton breeding programme are working with a narrow germplasm pool thus resulting in genetic bottleneck through historic domestication events and selection (Iqbal et al., 1997).

Assessment of the genetic diversity of cotton cultivars is essential to breeding strategies, such as the characterization of individuals, accessions, and for the choice of parental genotypes in breeding programs. For any meaningful plant-breeding programme, accurate determination of genetic diversity is an essential step for an effective utilization of germplasm resources. An accurate estimation of genetic diversity can be invaluable in the selection of diverse parental combinations to generate progenies with maximum genetic variability and heterosis. In addition, introgression of desirable traits from diverse/wild germplasm into the elite cultivars to broaden the genetic base is possible (Ulloa et al., 2007). Estimation of genetic diversity based on the morphological and biochemical markers has its limitations due to environmental variations. Molecular marker techniques on the other hand have evolved as powerful tools for genetic diversity analysis and in establishing relationships between cultivars. Molecular genetic techniques using DNA markers have been increasingly used to characterize and identify novel germplasm for use in the crop breeding process (Zhang et al., 2003). A systematic assessment of genetic resources will also help to identify the specific crosses to be made and hence decrease the number of

1

4 World Cotton Research Conference on Technologies for Prosperity

crosses to be designed in a breeding program. This will enable better utilization and management of germplasm resources and also help enlarge the germplasm base hence removing the bottle necks in breeding (Karp, 2002). Classification of germplasm based on the geographic regions would also be valuable in understanding the structure of the cotton germplasm gene pools.

The development of abundant cotton SSR markers has stimulated more effort in molecular characterization of cotton germplasm around the world (Blenda et al., 2006; Zhang et al., 2008). DNA-based markers, microsatellite or simple sequence repeats (SSR) are co-dominant markers to assess genome level diversity. SSR markers have been used as tools in genotype identification and variety protection, seed purity evaluation, germplasm characterization, diversity studies, gene and quantitative trait locus (QTL) analysis, pedigree analysis and marker assisted breeding. SSR markers have played an important role in the dramatic progress of cotton genetics and genomics. Being both co-dominant and multi-allelic, microsatellites are highly reproducible and informative genetic markers (Morgante et al., 2002; Turkoglu et al., 2010). Another advantage of SSR markers is that they are highly transferable across species especially within a genus (Saha et al., 2004). The objectives of this study are 1) to evaluate the genetic diversity among selected cotton cultivars, and 2) to provide essential information for future marker-assisted breeding and to facilitate a more efficient use of germplasm in cotton breeding.

MATERIALS AND METHODS

One hundred and ninety two Gossypium hirsutum germplasm accessions were included for genetic diversity study. This germplasm is the proprietary core cotton collections developed at Maharashtra Hybrid Seeds Co. Ltd., Jalna, India.

Flow chart illustrating the methodology

Leaf crushing was done on a paint shaker and DNA extraction was done by Silica method (unpublished protocol). To develop a core set of polymorphic markers, we screened 278 markers across 13 elite germplasm lines and identified 54 polymorphic markers which were eventually converted into core set of SSR markers. This core set of 54 polymorphic markers were used to screen the 192 germplasm lines.

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Genetic Diversity Analysis in Cotton Germplasm 7

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REFERENCES [1] Blenda, A., Scheffler J., Scheffler B., Palmer M., Lacape J. M., Yu J. Z., Jesudurai C., Jung S., Muthukumar, S.,

Yellambalase, P., Ficklin, S., Staton, M., Eshelman, R., Ulloa, M., Saha, S., Burr, B, Liu, S., Zhang, T., Fang, D., Pepper, A., Kumpatla, S., Jacobs, J., Tomkins, J., Cantrell, R., and Main, D. (2006). CMD: a Cotton Microsatellite Database resource for Gossypium genomics. BMC Genomics 7:132

[2] Iqbal, M.J., Aziz, N., Saeed, N.A., Zafar, Y., Malik, K.A. (1997). Genetic diversity evaluation of some cotton varieties by RAPD analysis. Theor. Appl. Genet. 94: 139-144.

[3] Karp, A. (2002). The new genetic era: will it help us in managing genetic diversity? In: Managing [4] Plant Genetic diversity. (Eds.): J.M.M. Engels, V.R. Rao, A.H.D. Brown and M.T. Jackson. [5] International Plant Genetic Resources Institute, Rome, Italy, 43-56. [6] Krishnasamy Thiyagu, Narayanan Manikanda Boopathi, Nagasamy Nadarajan, Ayyanar Gopikrishnan, Pandi Selvakumar,

Santoshkumar Magadum and Rajasekar Ravikesavan. (2011) Sampling and exploitation of genetic variation exist in locally adapted accessions using phenotypic and molecular markers for genetic improvement of cotton. Genecon. 10: 129-153.

[7] Morgante, M, Hanafey, M. and Powell, W. (2002). Microsatellites are preferentially associated with nonrepetitive DNA in plant genomes. Nat. Genet. 30: 194-200

[8] Saha, S., Wu, J., Jenkins, J.N., McCarty, J.C. Jr, et al. (2004). Effect of chromosome substitutions from Gossypium barbadense L.3-79 into G. hirsutum L. TM-1 on agronomic and fiber traits. J. Cotton Sci. 8: 162-169.

[9] Turkoglu, Z., Bilgener, S., Ercisli, S., Bakir, M., et al., (2010). Simple sequence repeat-based assessment of genetic relationships among Prunus rootstocks. Genet. Mol. Res. 9: 2156-2165.

[10] Ulloa, M., Brubaker, C. and Chee, P. (2007). Cotton. In: Genome Mapping & Molecular Breeding (Kole C, ed.). Vol. 6. Technical Crops Springer, New York.

[11] Weir, B. S. (1990). Genetic data analysis: methods for discrete population genetic data. Sinauer Associates, Inc. publishers. Sunderland, Massachusetts. 377.

[12] Zhang, Y., Wang, X.F., Li, Z.K., Zhang G.Y. and Ma Z.Y, (2011). Assessing genetic diversity of cotton cultivars using genomic and newly developed expressed sequence tag-derived microsatellite markers. Gen. Mol. Res. 10 (3): 1462-1470.

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Creating Novel Diversity and using Comprehensive Methods for Their Further Use in Hybrid Research—

An Exercise in Gossypium hirsutum L.

Rajesh S. Patil, Bharathkumar, Kasu Pawar, Sudheendra Ashtaputre, Ishwarappa Katageri, Basavaraj Khadi, Bhuvaneshwaragouda Patil,

Shreekanth Patil and Shekhar L.

UAS, Dharwad, India

Abstract—Cotton breeding is a continuous endeavour aiming to produce better genotypes and hybrids. The present exercise involved choosing the F1 hybrids, from national trials, as parents and then employing methods to assess the diversity produced in the F5 segregants leading to identification of elite lines which can be used in further hybrid research. The two parts of study spanning a period of five years began in 2007-08 and was initiated with an objective to isolate superior Gossypium hirsutum genotypes related to yield and fibre properties from double crosses whose F1 parents were chosen for their diversity and superior traits. Segregants from a three-way cross and also the respective single cross parents of double crosses were included in the study. In all there were 115 lines drawn from five double cross, one three-way cross and six single cross hybrids in F5 which were evaluated in an augmented design during kharif of 2010-11.

Five genotypes viz., Line-632, Line-131, Line-642, Line-1151 and Line-1101 had better yields ranging from 8.90 to 21.77 per cent over best check Sahana with mean yields higher than 20.27q/ha. Line-632 had the highest seed cotton yield of 21.70 q/ha which was 21.77 per cent better than Sahana (17.82 q/ha). It also had superior fibre length.

In second part of the study, the diversity generated was assessed through K-means clustering. Seven clusters were formed accommodating the 115 lines. The second step was to employ a simple method called ‘Path-of-productivity’ analysis to identify the different paths the top 12 lines took towards producing higher yields. As expected, they did have differences in their paths to higher yield attributable to their differential genetic makeup. In addition, these 12 genotypes fell in five different clusters identified in the previous step. Considering both tests, 10 genotypes were finally identified to be included in a diallel to pave way for hybrid research. Lines- 632, 131, 642, 1151, 11101, 1081, 531, 391, 8141, and 12111 were the chosen genotypes.

INTRODUCTION

Genetic diversity is at the heart of all plant breeding activities. Crossing over and recombination among the chromosomes of a heterozygote leads to the formation of genetically dissimilar gametes. Such gametes of two heterozygotes can be brought together when we use F1 hybrids as parents of a double cross. Creating and harnessing novel genetic diversity through such conventional means is one method of obtaining superior segregants. In the present study, the F1 hybrids which served as parents of the double crosses were chosen from the different cotton growing zones of India in the hope that geographical diversity would contribute to the diverseness of the hybridization material. Greater the genetic diversity better would be the release of variability in the segregants. In the later generations (say F4/F5), where these desirable segregants are fairly stabilized, they can be evaluated against checks. Productive segregants are isolated in each generation via individual plant selection. After extensive yield performance trials, the new genotypes can be released as new varieties. Freom here starts the next activity. The genetic variability created can be harnessed for heterosis breeding. The new genotypes can be subjected to diversity analysis and diverse groups can be identified from which genotypes can be picked for hybridization. A method called ‘Path-of-Productivity’ has been described and now, can be used in conjunction with diversity analysis to identify genotypes that can serve as parents of new hybrids. The parents can be brought together in a diallel cross to identify superior hybrids. These hybrids will again help in embarking upon a fresh cycle of recombination and creation of diversity.

2

Creating Novel Diversity and using Comprehensive Methods for Their Further Use in Hybrid 9


Six intra-hirsutum hybrids of cotton were identified from the All India Coordinated Crop Improvement Project trials during 2005-06 and were used as parents in producing double crosses and a three-way cross in 2006-07. From 2007-08 onwards, individual plant selections were made based on productivity and fibre properties in each generation till 2009-10. One hundred and fifteen plants belonging to different crosses were identified in 2009-10 for evaluation during 2010-11. These hundred and fifteen genotypes in F4/F5 were obtained through individual plant selection (IPS) from five double crosses, one three –way cross and six single cross (parents) hybrids. The details are given in Tables 1 and 2. These 115 genotypes were evaluated in augmented design with five check varieties during kharif 2010-11 at Agricultural Research Station, Dharwad to identify productive genotypes. Analysis of variance (ANOVA) for augmented design–II (Federer, 1977) for all characters was carried out separately. Parameters based on the mean performance of the varieties and also parameters of genetic variability for the different traits were obtained. GCV and PCV values were calculated as per Burton (1951) and heritability (broad sense) was obtained as per Johnson et al., (1955). Selection efficiency reflected in genetic advance and GAM was assessed as per Johnson et al., (1955). In the present study, a simple method called ‘Path-of-productivity’ (Rajesh Patil et al., 2007), used earlier in arboreum cotton with some degree of success, has been outlined which helps in finding out differences in the trait contributions to the final yield of a genotype. If two such genotypes with different paths to productivity are hybridized one can expect hybrid vigour as there could be underlying genetic differences responsible for their differing path-of-productivity. As an adjunct to this, conventional genetic diversity analysis can be done to decide upon the genotypes to be chosen as parents in a hybridization program. Diversity generated was assessed through K-means clustering using Systat software. The most productive 12 lines were considered for ‘path-of-productivity’ analysis. The 10 lines, selected after the ‘path-of-productivity’ analysis, were allocated to their respective clusters to see if they fell in diverse clusters. Together, the methods can identify parents amenable to a hybridization program.

TABLE 1: HYBRIDS FROM AICCIP TRIALS AND THEIR PERFORMANCE FEATURES ACROSS THE THREE COTTON GROWING ZONES OF INDIA DURING 2005-06 THAT SERVED AS PARENTS OF THE DOUBLE CROSSES

Hybrid North Zone (6 Locations) Central Zone (7 Locations) South Zone (6 Locations)

Seed

Cot

ton

Yie

ld (k

g/ha

)

Fibr

e L

engt

h (m

m)

Fibr

e St

reng

th

(g/te

x)

S:L

Rat

io

Seed

Cot

ton

yiel

d (k

g/ha

)

Fibr

e L

engt

h (m

m)

Fibr

e St

reng

th

(g/te

x)

S:L

Rat

io

Seed

Cot

ton

yiel

d (k

g/ha

)

Fibr

e le

ngth

(m

m)

Fibr

e st

reng

th

(g/te

x)

S:L

rat

io

GSHH-2201 1284 26.40 20.40 0.77 2060 26.90 21.40 0.80 2127 30.20 23.00 0.76 VBCH-2312 1669 30.30 21.90 0.72 1808 30.80 24.10 0.78 1988 29.70 24.40 0.82 CHATRAPATHI 1148 33.10 25.70 0.78 1977 33.30 25.40 0.76 1882 32.80 22.90 0.70 BCHH-1232 1430 31.30 22.20 0.71 2046 29.80 22.70 0.76 2235 32.00 22.50 0.70 JKCH-2022 1228 29.60 22.10 0.75 2103 31.10 22.80 0.73 2709 32.10 22.80 0.71 RATNA 1265 29.70 20.60 0.69 1970 32.70 24.00 0.73 2056 29.50 24.50 0.83

Note: S:L ratio is the fibre strength to length ratio, a combined parameter to judge fibre property

TABLE 2: LIST OF COTTON GENOTYPES DERIVED FROM DOUBLE AND SINGLE CROSS HYBRIDS INCLUDED FOR EVALUATION AT ARS DHARWAD DURING KHARIF 2010-11

Entry No F4 progeny of Cross Progenies Entry No F5 Progeny of Cross Progenies Double Cross Hybrids Single Cross Hybrids

DC-1. GSHH-2201 × RATNA 10 DC-7 GSHH-2201 6 DC-2. VBCH-2312 × RATNA 3 DC-8 VBCH-2312 13 DC-3. CHATRAPATHI × RATNA 17 DC-9 CHATRAPATHI 9 DC-4. BCHH-1232 × RATNA 4 DC-10 BCHH-1232 8 DC-5. JKCH-2022 × RATNA 11 DC-11 JKCH-2022 14

Three-way Cross Hybrids DC-12 RATNA 12 DC-6. RCR 4 x RATNA 7

Note: Altogether, a total of 115 progenies/genotypes were evaluated.


RESULTS AND DISCUSSION

The genotypes were evaluated in augmented design for productivity traits and also for fibre properties. The ANOVA revealed that the variability generated in the experimental material across all the traits was larger. The various genetic parameters have been given in Table 3. The top five genotypes viz., DC-632, DC-131, DC-642, DC-1151 and DC-1101 were superior to the zonal and local check, Sahana, in both yield as well as fibre properties. The performance of selected superior genotypes against the two released check varieties across seed cotton yield and fibre traits has been given in Table 6. Genotypes DC-632 (2170 kg/ha), DC-131 (2064 kg/ha) and DC-642 (1993 kg/ha) were superior to checks Sahana (1782 kg/ha) and RAH-100 (1457 kg/ha). Superiority in fibre length (23.93 % over Sahana in DC-391) and fibre strength (20.08 % over RAH-100 in DC-11101) has been recorded. Genotype DC-632 apart from having a yield superiority of 17.89 per cent over best check was also superior for the fibre properties. Another genotype DC-771 had a fibre length of 31.30 mm and strength of 25.50 g/tex.

TABLE 3: VARIABILITY PARAMETERS FOR DIFFERENT MORPHOLOGICAL CHARACTERS AMONG SINGLE AND DOUBLE CROSS DERIVED LINES AT ARS DHARWAD DURING KHARIF 2010-11

Var

iabi

lity

Para

met

ers

Plan

t Hei

ght (

cm)

Num

ber

of M

onop

odia

Num

ber

of S

ympo

dia

Sym

podi

al L

engt

h at

50

% P

lant

Hei

ght

Num

ber

of N

odes

per

Pl

ant

Inte

r B

oll D

ista

nce

(cm

)

Stem

Dia

met

er

(cm

)

Num

ber

of B

olls

Per

pl

ant

Bol

l Wei

ght (

g)

Num

ber

of S

eeds

Per

Bol

l

Seed

Inde

x (g

)

Lin

t Ind

ex

(g)

GO

T

(%)

Hal

o L

engt

h (m

m)

Seed

Cot

ton

Yie

ld

(g/p

lant

)

Mean 97.20 2.10 22.10 49.40 24.00 7.30 1.20 4.40 4.40 27.70 8.70 4.70 35.30 29.10 19.30 Maximum 140.50 4.00 37.00 70.00 39.00 10.00 1.90 13.10 7.30 35.80 10.00 6.10 39.60 37.80 39.10 Minimum 70.00 0.90 15.40 33.00 17.40 3.80 0.70 1.10 1.70 20.40 6.50 3.40 30.20 21.10 4.30 Vg 105.87 0.06 4.81 17.25 5.85 0.22 0.01 0.49 0.01 1.41 0.48 0.23 2.79 7.55 23.18 Vp 160.68 0.38 11.65 46.85 12.20 0.95 0.08 2.86 0.62 7.77 0.72 0.40 4.86 8.65 59.80 PCV 13.04 29.28 15.44 13.86 14.55 13.37 24.01 38.46 17.95 10.07 9.74 13.52 6.25 10.11 40.07 GCV 10.59 11.86 9.92 8.41 10.08 6.37 9.13 15.84 2.38 4.28 7.95 10.23 4.73 9.44 24.94 h²bs(%) 65.89 16.40 41.30 36.82 47.95 22.69 14.46 16.98 1.76 18.11 66.57 57.18 57.46 87.22 38.76 GA (%) 17.20 0.21 2.90 5.19 3.45 0.46 0.09 0.59 0.03 1.04 1.16 0.75 2.61 5.29 6.17 GAM (%) 17.70 9.89 13.14 10.51 14.38 6.25 7.15 13.45 0.65 3.76 13.36 15.93 7.39 18.16 31.99

TABLE 4: PATH-OF-PRODUCTIVITY ANALYSIS IN THE 12 MOST PRODUCTIVE GENOTYPES OF THE 115 NEW GENOTYPES PRODUCED AND EVALUATED

Mean Values of 12 Most Productive Genotypes for 16 Traits Genotypes 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

DC-632 39.07 105.10 3.00 22.80 24.40 50.00 28.80 8.80 1.50 6.30 6.20 3.60 1.50 32.60 34.84 48.26 DC-131 37.15 82.90 1.50 16.80 17.80 47.20 24.60 7.20 1.44 13.10 2.84 14.90 2.20 34.80 34.17 34.70 DC-642 35.88 106.60 1.00 18.90 21.30 54.00 27.80 7.80 1.30 7.32 4.90 4.30 1.70 32.90 34.91 60.95 DC-1151 35.47 99.50 2.20 21.00 23.00 51.00 27.00 7.20 1.00 6.20 5.72 7.40 4.20 33.80 43.69 22.26 DC-1101 34.95 101.30 2.40 19.20 20.20 50.20 24.80 8.00 1.56 6.70 5.22 14.50 2.30 34.50 37.54 51.30 DC-11101 31.65 103.50 2.10 23.40 25.40 51.00 30.00 6.60 1.10 5.70 5.55 7.60 5.20 34.80 37.71 16.26 DC-1081 31.47 92.30 2.40 19.40 21.40 47.00 28.00 7.80 1.10 5.70 5.52 1.90 1.10 35.20 37.12 34.90 DC-531 31.00 86.40 2.20 16.10 18.30 46.00 30.00 7.60 1.10 9.20 3.37 17.60 4.00 31.70 38.24 43.00 DC-391 30.95 82.40 1.80 22.00 23.00 49.20 31.00 7.30 1.78 6.80 4.55 18.70 4.00 34.80 34.79 54.00 DC-8141 30.93 95.10 3.30 19.60 22.00 49.00 29.60 7.70 1.10 6.50 4.76 3.70 1.30 34.10 38.10 114.62 DC-1131 30.39 92.80 1.80 20.00 22.00 48.00 29.00 8.10 1.00 8.20 3.71 15.10 4.10 34.70 38.70 23.78 DC-12111 29.80 108.00 2.10 23.60 25.80 48.00 29.00 6.70 0.80 5.70 5.23 9.30 5.20 38.00 36.78 44.90 Group Mean 33.23 96.33 2.15 20.23 22.05 49.22 28.30 7.57 1.23 7.29 4.80 9.88 3.07 34.33 37.22 45.74 Overall Mean 19.21 97.15 2.22 22.10 23.96 49.45 28.16 7.29 1.22 4.39 4.36 9.32 2.81 34.83 37.10 52.07

The per se performance and per cent deviation values of the top 12 genotypes from the overall mean for all traits have been given in Table-4&5. Twelve genotypes were considered for ‘path-of-productivity’ analysis as the mean seed cotton yield of these 12 genotypes was higher than the two checks. The group mean of the 12 genotypes was higher than the overall mean for 60 per cent of the traits. Important traits like seed cotton yield, number of bolls, boll weight and photosynthesis had above average expression. Negative but desirable expression was seen in plant height, number of monopodia and length of sympodium at 50 per cent plant height. The per cent deviations across the contributing traits, showed differences among the genotypes. These differences can safely be assumed to be arising out of genetic

Creating Novel Diversity and using Comprehensive Methods for Their Further Use in Hybrid 11

differences among the lines. All the 12 genotypes were high yielding but had different paths to productivity owing to differential gene architecture. The differences among the path to productivity of the 12 genotypes, when 2 lines are compared against each other at a time, shows that lines DC-1101 and DC-1131 showed less than 50 per cent difference with other lines. Both these lines can be conveniently dropped from any hybridization programme. The other 10 lines viz., DC-391, DC-531, DC-642, DC-131, DC-1151, DC-1081, DC-11101, DC-632, DC-12111 and DC-8141 can be used to set up a diallel crossing set which will help ultimately to identify superior hybrids. The line DC-632 can be crossed to any of these three lines viz., DC-131, DC-1081 or DC-531 as all the three pairs of parents showed more than 60 per cent trait difference between the parents of the cross. Using the ‘path-of-productivity’ can thus lead to proper choice of parents for a planned production of hybrids.

TABLE 5: MEAN DEVIATIONS OF TOP GENOTYPE VALUES FROM OVERALL MEAN ACROSS ALL TRAITS

Genotypes 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 DC-632 103.38 8.18 35.14 3.17 1.84 1.11 2.27 20.71 22.95 43.51 42.24 -61.37 -46.62 -6.40 -6.09 -7.32 DC-131 93.39 -14.67 -32.43 -23.98 -25.71 -4.55 -12.64 -1.23 18.03 198.41 -34.96 59.87 -21.71 -0.09 -7.90 -33.36DC-642 86.78 9.73 -54.95 -14.48 -11.10 9.20 -1.28 7.00 6.56 66.80 12.39 -53.86 -39.50 -5.54 -5.90 17.06 DC-1151 84.64 2.42 -0.90 -4.98 -4.01 3.13 -4.12 -1.23 -18.03 41.23 31.21 -20.60 49.47 -2.96 17.76 -57.26DC-1101 81.94 4.27 8.11 -13.12 -15.69 1.52 -11.93 9.74 27.87 52.62 19.64 55.58 -18.15 -0.95 1.19 -1.48 DC-11101 64.76 6.54 -5.41 5.88 6.01 3.13 6.53 -9.47 -9.84 29.84 27.35 -18.45 85.05 -0.09 1.64 -68.78DC-1081 63.82 -4.99 8.11 -12.22 -10.68 -4.95 -0.57 7.00 -9.84 29.84 26.63 -79.61 -60.85 1.06 0.05 -32.98DC-531 61.37 -11.07 -0.90 -27.15 -23.62 -6.98 6.53 4.25 -9.84 109.57 -22.72 88.84 42.35 -8.99 3.07 -17.42DC-391 61.11 -15.18 -18.92 -0.45 -4.01 -0.51 10.09 0.14 45.90 54.90 4.39 100.64 42.35 -0.09 -6.23 3.71 DC-8141 61.01 -2.11 48.65 -11.31 -8.18 -0.91 5.11 5.62 -9.84 48.06 9.14 -60.30 -53.74 -2.10 2.70 120.12DC-1131 58.20 -4.48 -18.92 -9.50 -8.18 -2.93 2.98 11.11 -18.03 86.79 -15.00 62.02 45.91 -0.37 4.31 -54.33DC-12111 55.13 11.17 -5.41 6.79 7.68 -2.93 2.98 -8.09 -34.43 29.84 19.91 -0.21 85.05 9.10 -0.86 -13.77Group Mean 72.96 -0.85 -3.15 -8.45 -7.97 -0.47 0.50 3.80 0.96 65.95 10.02 6.04 9.13 -1.45 0.31 -12.15

Note: Group mean is of 12 genotypes and overall mean is of 115 genotypes

To make this simple test for diversity assessment more comprehensive, the conventional cluster analysis through K-means was also performed. The cluster details are presented in Table-7. The ten genotypes picked up on the basis of ‘path-of-productivity’ analysis fell in 5 different clusters showing their diverse genetic make-up. This analysis also proves the genetic diversity existing among the ten lines which can be used in a hybridization set-up based on the ‘path-of-productivity’ analysis. The parents of each of the three pairs of crosses suggested above also belonged to different clusters making them ideal parents for a heterotic cross.

INDEX FOR THE 16 DIFFERENT TRAITS

1 Seed Cotton Yield (g/plant)

5 Number of Nodes Per Plant

9 Stem diameter (cm) 13 Transpiartion Rate (µmol of H2Om²S¯¹)

2 Plant height(cm) 6 SL at 50% plant height(cm)

10 Number of bolls 14 Leaf temperature (0c)

3 Monopodia per plant

7 Angle of sympodium at 50% plant height (deg)

11 Boll weight (g) 15 Chlorophyll content(mg/gm fresh weight) of leaf)

4 Sympodia per plant 8 Inter boll distance (cm) 12 Photosynthesis (µmol of CO2 m² S¯¹ )

16 RWC (%)

TABLE 6: PERFORMANCE SUPERIORITY OF SELECTED GENOTYPES OVER TWO CHECKS ACROSS YIELD AND FIBRE PROPERTIES

% Improvement over Sahana % Improvement over RAH-100 Seed Cotton Yield (kg/ha) Seed Cotton

Yield Fibre

Length Fibre

Strength Seed Cotton

Yield Fibre

Length Fibre

Strength For Both Seed Cotton Yield and Fibre Properties

DC-632 17.89 13.59 8.48 32.83 9.06 11.16 2170 DC-642 10.56 13.59 8.48 26.87 9.06 11.16 1993

For Fibre Properties Only DC-11101 -1.34 10.70 17.67 17.09 6.02 20.08 -- DC-391 -3.50 23.93 11.26 15.22 19.90 13.85 -- Mean values of checks Sahana RAH-100

1782 kg/ha 26.70 mm 20.50 g/tex 1457 kg/ha 28.10 mm 19.90 g/tex --


TABLE 7: THE SEVEN CLUSTERS SHOWING THE DIVERSITY OF THE TEN GENOTYPES SELECTED ON THE BASIS OF PATH-OF-PRODUCTIVITY

Clusters Number of Genotypes Genotypes Selected on the Basis of Path-of-Productivity I 20 DC-391, DC-531 II 20 DC-642 III 18 DC-131, DC-1151, DC-1081, DC-11101 IV 26 DC-632, DC-12111 V 5 -- VI 10 DC-8141 VII 16 --

REFERENCES [1] Burton, G.W., (1951). Quantitative inheritance in pearlmillet (Pennisetum glaucum S. and H.). Agron., 43:404-417. [2] Federer, W. T., (1977). Experimental design; Theory and Application. McMillan, New York. [3] Johnson, H.W., Robinson, H.F. and Comstock, R.E. (1955). Estimates of genetic and Environmental Variability in soybean.

Agron., 47:314-318. [4] Rajesh, S. Patil, Shreekant S. Patil, Rashmi, Bhuvaneshwargouda, R. Patil and Khadi, Basavaraj M. (2007). ‘Path-of-

Productivity’ – A method to handle genetic material using F1s in cotton (Gossypium arboreum L.). Proceedings of World Cotton Research Conference – 4, Lubbock, Texas, USA.

New Cotton Germplasm as an Intermediate Cycle Called SP 48114 Development by the National

Institute of Agricultural Technology–INTA

A. Tcach Mauricio, A.F. Poisson, Ivan Bonacic, Silvia Ibalo, Alex Montenegro, Daniel Ojeda and Mariano Cracogna

Estación Experimental Agropecuaria INTA Sáenz Peña, Chaco, Argentina

Abstract—Cotton in Chaco, Argentina, is grown under rainfed conditions. The availability of water during flowering determines the retention of fruiting structures. Better performance depends mainly on water availability during the reproductive phase. In varieties with short cycle, the losses due to stress are the most and is becoming necessary to develop varieties as intermediate types helps to compensate losses due to stress at flowering. The objective of this investigation was to select cotton with intermediate habit and agronomic traits equivalent to early types. From the F2 populations of a cross between lines SP 99138 x SP 99035 in 1994/1995 season, selection was made by visual observation and an individual plant was obtained. The selection plant was named as SP48114 after following pedigree method of breeding. During 2004/2005 the elite population was part of a network regional comparative trials conducted at 4 locations for 3 seasons. From the F3 generation onwards it was tested for ginning and the progenies were artificial infected with Xanthomonas axonopodis pv malvacearum. All susceptible plants were discarded. F8 generation was tested for the blue disease caused by cotton leaf roll dwarf virus (CLRDV) through artificial infection and only resistance lines were selected. The line SP 48114 is characterized by greater differentiation of fruiting points on the main stem 5 % more than Guazuncho 3 INTA. This commercial variety has short cycle and high boll retentions in first fruiting branches. The selected line SP 48114 maintains boll retentions in the inferior part of the plant similar to Guazuncho 3 INTA and continued to flower for more days. This feature increases the flowering period for about 10 days and improves the compensation at time of water stress. The fiber parameters viz., fiber length is 29 mm, strength 31 g / tex and lint percentage about 39 to 40.

INTRODUCTION

In Argentina, the main province of cotton-growing area is Chaco, where cotton is grown only under rainfed conditions (SAGPyA, 2009). The precipitation in this area is erratic and irregular during growing season, which increases the risk in the production. It necessiates the research work in the Argentinean cotton industry for improvement in water use efficiency (Payta 2010).

The cotton has xerophytic adaptation, however 53% of the area is cultivated under irrigated conditions in the world (Hearn, 1994). When the cotton plant cross dry conditions, its vegetative grows is terminate, being very difficult to restart vegetative growth and produce more squares and flowers (Hearn 1994). Fryxel (1986) observed various strategies in wild species, of adaptations to arid conditions, life cycle being one of them.

The main objectives of INTA´s programme for cotton breeding is development of varieties with short cycle (Royo et al., 2007). Sekloka et al., 2007 found that varieties with short cycle showed better performance in dry conditions as it may run away to dry period. The problem is that typical sowing date may not run away to dry period. The varieties with short cycle can cluster the flowering and compensate the eventual loss when its peak phase coincides with the stress. Further, flowering can be maintained for more time in varieties with intermediates cycle, without any losses and hence such varieties are to be developed. The objective in this investigation was to select a cotton line with intermediate cycle and agronomic traits equivalent to early materials.

3



The Argentine breeding programme follows the classical pedigree method (Allard 1960; Poisson 2005). From the cross of two different genotypes, the following generations were selfed and individual plants and progeny row selections were carried out from the F2 to successive generations. From the F4 generation onward, the seeds were not selfed and were collected to carry out replicated evaluation trials. In the AES Saenz Peña the germplasm lines were evaluated until the F6 generation. The previous generations were inoculated with the pathogens causing bacterial blight. The F8 were infected with aphids which are vector for virus causing blue disease. After the F7 generation, selected lines were evaluated at four additional localities viz., El Colorado, Reconquista, Colonia Benitez (dryland); and Santiago del Estero (irrigated). Current commercial cultivars were used in all trials for comparison purposes. Several trials in four locations at 3 seasons were conducted. The complete process is shown in the picture No. 1. Trials were planted as a randomized complete block design with four replications in plots of two rows, 10 m long. Plants were separated at a distance of 10 cm. in the row and at one m. between rows. Bolls were hand-picked in each plot to determine the yield. Thirty selected bolls were used to determine GOT by baby ginner lint turnout and using HVI equipped for fiber parameters.

In the last season in 1 meters of row, numbers of fruiting branch and plant height in several trials were also studied. The dates were analysed with Infostat software and averages were separated with test LSD Fisher.


The flow chart for the line development from the F2 populations, the plant that made the progeny row and successive testing generations is show in Fig 1. This material with intermediate cycle finished the process of test in the 2006-2007 season, but is not registered still.

CYCLE

The differentiations of new nodes in the main stem and successive fruit point on fruiting branch were at regular intervals, generating the typical pyramidal shape present in cotton (Hearn 1994). This process can be maintained for more time in SP 48114 compared with Guazuncho 3 INTA, the late variety with short cycle. SP 48114 during 2010-2011showed that ( at 110 days after planting), the growth cycle ended with 2 to 4 more potential fruiting branch than Guazuncho 3 INTA, in addition the final height was 12 to 7 cm more than Guazuncho 3 INTA. Both the parameters are associated with the growth cycle. This feature could allow obtaining better performance in dry conditions. The relative performance is shown in Table 1.

TABLE 1: AGRONOMIC PARAMETERS REGISTERED AT 110 DAYS AFTER SOWING, SEASON 2010-11. PRESIDENCIA ROQUE SÁENZ PEÑA, CHACO. DATAS BY THE SAME LETTER ARE NOT DIFFERENT AT 5% PROBABILITY LEVEL.

Line/ Variety No. of Fruiting Branch Plant Height cm SP 48114 14,25 a 94,25 a SP 8461 12,75 ab 92 ab SP 44825 12,5 ab 74,5 c Poraite INTA 12,1 b 76,7 c Guazuncho 3 INTA 12 b 81,5 bc CV 9,64 10,2

SANITY

The line presented high resistance to bacterial blight caused by Xanthomonas axonopodis pv malvacearum, because in the process of selections it was artificially infected from F3 to F12 (Fig1.). In addition to this process it was also infected with cotton leaf roll dwarf virus (CLRDV) during F8 generations. When the plant developed the symptoms, the resistant lines were selected. The sanitary performance was achieved by INTA´s varieties (Poisson 2002).

New Cotton Germplasm as an Intermediate Cycle Called SP 48114 Development by the National Institute of Agricultural 15

Fig. 1: Process of Breeding Used for Development SP 48114 from Year 1993

YIELD AND FIBER PROPRIETIES

The line was evaluated in several trials from the season 2004-2005 which showed good performance and achieved the first positions in the test in relation to commercial varieties (Royo et al., 2007). During the dry and wet conditions of 2009-2010 and 2010-2011, the line SP 48114 showed better performances than varieties with short cycle (Guazuncho 3 INTA and Poraite INTA). (Table 2 and 3). Both experiments were grown in Presidencia Roque Saenz Peña, Chaco, with four replications each. The differential behaviour can be explained for more possibilities to maintain the process of flowering for more days. Sekloca (et. al., 2007) found that the varieties with intermediate cycle present better performance in medium conditions, related to drought and humidity. The lint turnout % in both experiments for SP 48114 was better (Table 2 and 3). In dry conditions, the fiber length was 1 to 4 mm shorter in SP 48114 in comparision to Guazuncho 3 INTA (Table 2). However, in wet conditions the fiber properties was similar than that of Guazuncho 3 INTA (Table 3).

Thus, it is possible to select lines with more differentiations fruit point at growing stations and maintain similar agronomic parameters as varieties with short cycle.

TABLE 2: LINT YIELD AND QUALITY PARAMETERS FOR PCIA. ROQUE SÁENZ PEÑA, CHACO, 2009-10. THE DATA FROM THE TRIAL WITH 2 COMMERCIAL CULTIVARS, 3 PROMISING LINES, INCLUDING SP 48114. SEASON WITH DRY CONDITIONS DURING FLOWERING. DATE BY THE SAME LETTER ARE NOT DIFFERENT AT 5% PROBABILITY LEVEL

Varieties/ Line Lint Yield (kg/ha) Lint Turnout (%) Length (mm) Strength (g/Tex) Micronaire Index SP 48114 674 a 39,5 a 25,9 ab 28,7 b 4,7 a SP 48666 639 a 38,4 a 25,1b 28,6 b 4,7 a SP 81424 590 a 37,3a 26,05ab 29,8 ab 4,6 a Poraite INTA 452 b 38,1 a 26,6 a 30,4 ab 4,4 a Guazuncho 3 INTA 411 b 39,4 a 26,5 a 31,7 a 4,6 a CV 12,1 6,6 3,3 4,6 11,6

TABLE 3: LINT YIELD AND QUALITY PARAMETERS FOR PCIA. ROQUE SÁENZ PEÑA, CHACO, IN THE YEAR 2010-11. THE DATES FROM THE TRIAL WITH 2 COMMERCIAL CULTIVARS 3 PROMISING

LINE, INCLUDING SP 48114, SEASON WITH WET CONDITIONS. DATE BY THE SAME LETTER ARE NOT DIFFERENT AT 5% PROBABILITY LEVEL

Varieties /line Lint Yield (kg/ha) Lint Turnout (%) Length (mm) Strength (g/Tex) Micronaire Index SP 48114 962 a 41,2 ab 29,3 a 31,3 a 4,7 Poraite INTA 695 b 40,4 b 28,3 a 32,5 a 4,5 SP 48666 645 b 41,2 ab 27,9 b 31,5 a 4,6 Guazuncho 3 INTA 662 c 41,6 a 29,6 b 32,1 a 4,6 SP 6180 494 c 39,3 c 27,2 b 31,6 a 4,5 CV 14,1 1,43 1,74 2,69 4,7

Winter 1993 cross in green house between SP 99138 SP 99035

Season 1993/1994 F1 Generations

Season 1994/1995 F2 Generations Visual Selection of individual Plant

Season 1995/1996 F3 Generations Progeny row

Agronomic characterization and artificial infected with xanthomonas axonopodis pvmalvacearum

Seasons 1996/1997 – 2003/2004 F4-F12 -Generations

Agronomic Testing, artificial infected with xanthomonas axonopodis pv malvacearum andselecting and in F8, artificial infected with cotton leaf rolf duarfvirus (CLRDV) and selecting resistance lines

Seasons 2004/2005 – 2006/2007 Regional comparative trials in 4 locations for 3 seasons


REFERENCES [1] Allard, R. W. (1960). Principles of plant breeding. John Wiley. N.Y. 473 p. [2] Fryxell, P. A. (1986). Ecological adaptations of Gossypium species. pp. 1-7 In Mauney, J.R and Steward, J.McD. (Eds).

Cotton Physiology. The Cotton Foundations, Memphis, TN. [3] Hearn, A. B. (1994). The principles of cotton water relations and their application in management. World Cotton Research

Conference 1:66-92. [4] Paytas, M. (2010). Improving cotton yield under water limiting conditions in Argentina. Repor. ICAC Research Program. [5] Poisson, J. A. F. (2002). Breve historia de la producción de algodón en la Argentina. In: 1923-1 de agosto-2002. De Chacra

Oficial a Estacion Experimental. 79 anos de investigación algodonera en el centro de la provincia del Chaco. Editorial INTA EEA Saenz Pena, Centro Regional Chaco-Formosa.Pag.8

[6] Poisson, J. A. F., Bonacic, I., Royo, O. and Ibalo, Y. S. (2005). Mejoramiento genético de algodón. Ano Agrícola 2004/2005. In: Proyecto Nacional de Algodon. Informe de avance No 1. 2o Reunión anual. Sosa M.A. y O. Peterlin (Ed). Ediciones Instituto Nacional de Tecnología Agropecuaria. Pages 9-11.

[7] Royo, O. M., Poisson Juan, A. F.; Bonacic, I., Montenegro, A., Ibalo, S. I., Mazza, S., and Giménez, L. (2007). Direction of Cotton Breeding in Argentina. In: Proceedings of the World Cotton Research Conference. Lubok Texas

[8] Sekloka, E. And Jacques, L. (2007). Early-compact American and late-vegetative African cotton ideotypes can address the increasing diversity of cropping conditions in Africa. 4 Word Cotton Research.

Introgression of High Fibre Strength Trait to Upland Cotton using Marker-Assisted Selection

Nallathambi Kannan, P. Selvakumar, R. Krishnamoorthy, D. Raja, M. Bhuvaneshwari, V. Subramanian and M. Ramasami

Rasi R and D Centre, Rasi Seeds (P) Ltd., Attur–636102, Tamil Nadu, India

Abstract—Cotton fibre is a basic raw material used in the textile industry. In recent years, changes in spinning technology have resulted in the need of unique and often increased cotton fibre quality, especially fibre strength. In this concern, an attempt was made to improve fibre strength of G. hirsutum by utilizing G. barbadense as donor through Backcross (BC) and Modified Back Cross (MBC) pedigree breeding methods following marker-assisted selection using Simple Sequence Repeats (SSR) markers. The Phenotypic Co-efficient of Variation (PCV), Genotypic Co-efficient of Variation (GCV), heritability and genetic advance was studied in 475 numbers of F2 populations. The result showed fibre strength varied from 18.0 to 36.0 g/tex and 32 % of plants in the population fall under 27.0 to 36.0 g/tex group. The PCV was higher than GCV which shows fibre strength is highly influenced by environment. The moderate heritability and high genetic advance was observed for fibre strength; hence the selection is effective for this trait and the heritability is due to additive genes effect. The identified SSR markers for fibre strength have been utilised to select the high fibre strength plants in each generations. In BC1F1 generation, fibre strength varied from 24.4 to 32.7 g/tex. After continuous selection of high fibre strength plants using molecular markers in each generation, we obtained high productive progenies with high fibre strength that ranged from 30.0 to 35.7 g/tex having more recurrent background genome in BC1F8 generations. High recovery of hirsutum background with high strength and different staple length progenies were obtained in modified backcross population. Thus the high strength hirsutum lines developed will serve as a donor for introgressing the fibre strength to improve the elite parental lines through marker-assisted background selection.

INTRODUCTION Cotton is the most preferred natural fibre in the world and plays a major role in the economy of agriculture and industry. Among the four cultivated species, Gossypium hirsutum is well known for high yield and dominates the world’s cotton fibre production followed by the Gossypium barbadense that is known for superior fibre qualities. In cotton improvement, in addition to yield enhancement of lint, the fibre qualities such as staple length, fibre strength, and fineness and maturity are very important. The demand for improved fibre quality by textile industry will continue. Improvements in textile processing, particularly advances in spinning technology, have led to increased emphasis on breeding cotton for improved fibre characteristics, especially strength. (Rahman and Malik, 2008). The requirements in textile spinning machinery with the adoption of rotor spinning, demands fibres with high strength to meet out spinning productivity. Most of the presently developed cotton varieties have low fibre strength of 18 to 24 g/tex. Genetic variation for the fibre qualities are very limited in most of the currently cultivated Gossypium hirsutum cotton. Thus there is an urgent need to introduce fibre strength characteristics from Gossypium barbadense to upland cotton while maintaining the cotton fibre yield.

Cotton fibre strength trait is governed by several genes located in several loci of chromosomes and are inherited quantitative way and thus influenced by quantitative trait loci (QTLs). Most traits in breeding programs are quantitatively inherited, complicating their manipulation through phenotypic and/or genomic approaches. Each of the QTLs has relatively small effects and is influenced by genotype and environment showing strong GxE interaction, which leads to low genetic advance in cotton improvement (Kohel, 1999ab).

Cotton fibre strength trait is governed by several genes located in several loci of chromosomes and are inherited quantitative way and thus influenced by quantitative trait loci (QTLs). Most traits in breeding programs are quantitatively inherited, complicating their manipulation through phenotypic and/or genomic approaches. Each of the QTLs has relatively small effects and is influenced by genotype and environment showing strong GxE interaction, which leads to low genetic advance in cotton improvement (Kohel, 1999ab).

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The modified backcross method followed for pyramiding of multiple traits is one of the ways by which the inherent fibre strength trait can be transferred to an upland cotton elite line. Experiments in cotton showed the negative linkage between yield and fibre traits and following modified backcross (MBC) is expected to circumvent this effect. However, due to several QTLs involved for both yield and fibre traits, the breeding cycle is expected to be longer.

The identification and utilization of molecular markers make it possible for plant breeders to find a rapid and precise approach of marker-assisted selection (MAS) of desirable plants with target traits. Introgressing the traits of interest can be followed using molecular markers that are mapped flanking or tightly linked with the traits being incorporated. Following the advancement of MAS and MBC method, it is expected to have selection for both recurrent parent background as well as genes to be introgressed from non-recurrent parent. The use of MAS facilitates a faster introgression since plants can be sampled and genotypes with target traits can be identified even at the early stage of development. Among the available types of molecular markers, microsatellite markers simple sequence repeats (SSR) have shown to be the most adequate for breeding programs due to their co-dominance and multi-allelic characteristics, and for their ability to automate the process.

The main objective of the study has been to improve fibre strength of G. hirsutum by introgression of QTLs associated with fibre strength from G. barbadense by means of backcross (BC) and modified backcross (MBC) pedigree breeding methods using fibre strength QTL SSR markers. Thus a combination of MBC with MAS for selection of desirable cotton lines with enhanced yield and high fibre strength was followed in our breeding strategy.

The present investigation was also undertaken to study the phenotypic and genotypic coefficient of variability, phenotypic and genotypic variances, heritability and genetic advance of the variation existed in F2 and F3 population originated from the inter-specific crosses in cotton.


In the present study, the field experiments were conducted at the Rasi Seeds (P) Ltd., Research Farm, Attur, Salem (District) Tamil Nadu state (INDIA).

The salient features of parents involved in the backcross and modified backcross are furnished in Table 1. The breeding scheme, number of plants raised and number of plants selected in each generation of backcross and modified backcross are shown in Figs. 1 to 4. The experiments were raised in the winter season (August – February). All the recommended cultural practices of cotton production in the area were done periodically.

TABLE 1: SALIENT FEATURES OF PARENTS INVOLVED IN THE STUDY

Parents Species Used as Boll Weight (g)

Ginning % Span Length (mm)

Lint Index Fibre Strength (g/tex)

Fineness (Mic)

Uniformity Ratio

RC 64 G. hirsutum Recurrent

Medium (4.0-4.8)

Medium (33-36)

Long (30-32)

Medium 4.5-5.5

Medium (24-26)

Medium (4.0-4.2)

Excellent (47-49)


Medium to Big (4.9-5.6)

Low (31-33)

Extra Long(33-35)

Medium 4.0-5.0

Strong (26 – 28g/tex)

Fine (3.3-3.7)

Excellent (47-48)


Medium to Big (4.8-5.8)

Low (30-32)

Extra Long(34-36)

Medium 4.0-5.0

Strong (25-27)

Fine (3.5-3.8)

Excellent (47-48)


Big (5.3-6.0)

Medium (33-35)

Extra Long (33-35)

Medium 4.0-5.0

Medium (24-25)

Fine (3.5-3.7)

Excellent (47-49)

RC 45SB G. barbadense Donor Small (2.8-3.7)

Low (25 -28)

Extra Long(37-40)

Medium 4.0-5.0

Very Strong (33-36)

Very Fine (2.8-3.1)

Excellent (48-50)

Phenotypic Characters

Selected plants in each single plant progeny were observed and their biometrical and fibre quality traits were recorded. The genetic analysis for the traits such as boll weight (g), Number of bolls/plant, ginning percentage (GP %), lint index (LI), seed index (SI), single plant yield (g) and fibre quality parameters

Introgression of High Fibre Strength Trait to Upland Cotton using Marker-Assisted Selection 19

were done in the F2 population along with their parents. The fibre quality traits viz., 2.5% span length (mm), uniformity ratio (%), fibre fineness (micronaire), fibre strength (g/tex) and elongation were estimated by High Volume Instrument USTER® HVI Spectrum in ICC mode.

Fig. 1: The Breeding Scheme, Number of Plants Raised and Number of Plants Selected Based on MAS in the Backcross Population

Fig. 2: The Breeding Scheme, Number of Plants Raised and Number of Plants Selected Based on MAS in the Modified Backcross Population (I)

First G.hirsutum (RC64) x G.barbadense (RC45SB)Season2002(W) Identification of polymorphic markers of both parents (658 markers were screened and 454 were pol

Second G.hirsutum (RC 64 ) x F1Season F1 backcross with the recurrent parent2003(W)

475 F2 individuals were rasied and genotyping were done with 158 polymorphic markers based on low and high Third BC1F1 1. 276 plants were raisedSeason 2. 15 high fibre strength plants with more recurrent background were selected 2004(W) based on phenotypic and genotypic data (MAS) and forwarded to next generation

Fourth BC1F2 1. Individual 15 plant progenies were grown. (40 plants/progeny)Season 2. 8 high fibre strength plants with more recurrent background were selected 2005(W) based on phenotypic and genotypic data (MAS) and forwarded to next generation

Fifth BC1F3 1. Individual 8 plant progenies were grown. (21 plants/progeny)Season 2. Homozyous progenies similar to recurrent2006(S) parent with high fibre strength 17 plants were selected based on phenotypic and genotypic data (MAS)

3.Recurrent plant type with high fibre strength plants will be forwarded from superior progenies

Sixth BC1F4 1. Individual 17 plant progenies were grown. (20 plants/progeny)Season 2. Homozyous progenies similar to recurrent2006(W) parent with high fibre strength 67 plants were selected based on phenotypic and genotypic data (MAS)


Seventh BC1F5 1. Individual 67 plant progenies were grown. (20 plants/progeny)Season 2. Homozyous progenies similar to recurrent2007(W) parent with high fibre strength 82 plants were selected based on phenotypic and genotypic data (MAS)


Eighth BC1F6 1. Individual 82 plant progenies were grown. (20 plants/progeny)Season 2. Homozyous progenies similar to recurrent2008(W) parent with high fibre strength 148 plants were selected based on phenotypic and genotypic data (MAS)


Ninth BC1F7 1. Individual 148 plant progenies were grown. (20 plants/progeny)Season 2. Homozyous progenies similar to recurrent2009(W) parent with high fibre strength 54 plants were selected based on phenotypic and genotypic data (MAS)


Tenth BC1F8 1. Individual 54 plant progenies were grown. (20 plants/progeny)Season 2. Homozyous progenies similar to recurrent2010(W) parent with high fibre strength 36 plants was selected and forwarded



475 F2 individuals were rasied and genotyping were done with 158 polymorphic markers based on low and high Third RC 62 X BC1F1 1. 276 plants were raisedSeason 2.More G.hirsutum plant type with high fibre strength plants2004(W) to be crossed with G.hirsutum recurrent parent(RC62)

Fourth MBC1F1 1. 309 plants were raisedSeason 2. High fibre strength plants with more recurrent background were selected 2005(W) based on phenotypic and genotypic data (MAS) and forwarded to next generation

Fifth MBC1F2 1. Individual 305 plants were raisedSeason 2. 71 high fibre strength plants with more recurrent background were selected 2006(W) based on phenotypic and genotypic data (MAS) and forwarded to next generation

Sixth MBC1F3 1. Individual 71 plant progenies were grown. (20 plants/progeny)Season 2. Homozyous progenies similar to recurrent2007(W) parent with high fibre strength 44 plants were selected based on phenotypic and genotypic data (MAS)


Seventh MBC1F4 1. Individual 44 plant progenies were grown. (20 plants/progeny)Season 2. Homozyous progenies similar to recurrent2008(W) parent with high fibre strength 17 plants were selected based on phenotypic and genotypic data (MAS)


Eighth MBC1F5 1. Individual 17 plant progenies were grown. (10 plants/progeny)Season 2. Homozyous progenies similar to recurrent2009(W) parent with high fibre strength 25 plants were selected based on phenotypic and genotypic data (MAS)


Ninth MBC1F6 1. Individual 25 plant progenies were grown. (10 plants/progeny)Season 2. Homozyous progenies similar to recurrent2010(W) parent with high fibre strength 27 plants were selected and forwarded


Fig. 3: The Breeding Scheme, Number of Plants Raised and Number of Plants Selected in the Modified Backcross Population (II)

Fig. 4: The Breeding Scheme, Number of Plants Raised and Number of Selected Based on MAS in the Modified Backcross Population (III)

Mean values were used for different statistical analysis. Analysis of variance and genotypic and phenotypic variation were calculated following Singh and Chaudhury (1985). Phenotypic coefficient of variation (GCV), Genotypic coefficient of variation (PCV) were estimated using the formula suggested by Burton (1952), while genetic advance (GA) as percent means and genetic advance as percentage of mean (GA %) was estimated by the formula given by Lush (1949) and Johnson et al. (1955). The estimates of broad-sense heritability were computed as suggested by Allard (1960).




Fourth MBC1F1 1. 260 plants were raisedSeason 2. High fibre strength plants with more recurrent background were selected 2005(W) based on phenotypic and genotypic data (MAS) and forwarded to next generation*

Fifth MBC1F2 1. Individual 432 plants were raisedSeason 2. 51 high fibre strength plants with more recurrent background were selected 2006(W) based on phenotypic and genotypic data (MAS) and forwarded to next generation*





Eighth MBC1F5 1. Individual 23 plant progenies were grown. (10 plants/progeny)Season 2. Homozyous progenies similar to recurrent2009(W) parent with high fibre strength 33 plants were selected based on phenotypic and genotypic data (MAS)


Ninth MBC1F6 1. Individual 33 plant progenies were grown. (10 plants/progeny)Season 2. Homozyous progenies similar to recurrent2010(W) parent with high fibre strength plants 20 were selected based on phenotypic and genotypic data (MAS)




Fourth MBC1F1 1. 281 plants were raisedSeason 2. High fibre strength plants with more recurrent background were selected 2005(W) based on phenotypic and genotypic data (MAS) and forwarded to next generation

Fifth MBC1F2 1. Individual 251 plants were raisedSeason 2. 14 high fibre strength plants with more recurrent background were selected 2008(W) based on phenotypic and genotypic data (MAS) and forwarded to next generation






Genotyping using SSR Markers F2 mapping populations were developed from the interspecific cross between G.hirsutum (RC 64) and G.barbadense (RC 45SB) for the identification of SSR markers associated with fibre strength trait. Young leaf samples were collected from 475 F2 individuals and DNA was extracted using modified Davis protocol. PCR was conducted in a total volume of 10 μl with 10 ng of cotton DNA, 1 x PCR buffer (without MgCl2), 1.5 mM MgCl2, 0.1 μM dNTPs, 0.2 μM of each primer and 0.5 units of Taq DNA polymerase. The cycling conditions for PCR were as follows: 5 min for 94° C; 35 cycles of 94°C for 45 s, 57°C for 45 s, 72°C for 60 s; 72°C for 5 min; 4°C for preservation. Amplified DNA fragments were resolved in 6% denatured polyacrylamide gel [(acryl amide: bisacrylamide (19:1)] and stained with silver nitrate.

We employed 658 SSR primers including BNL, NAU, JESPR and CIR etc., for the identification of polymorphism between the two parents. The polymorphic primers were used to screen the bulked low and high fibre strength DNA samples and selected primers were subsequently used to genotype the F2 individuals. Only unambiguous distinct bands were scored. QTLs for cotton fibre strength in F2 population were identified using MAPMAKER 2.0 and QTL CARTOGRAPHER (version 1.15) respectively. The SSR markers associated with the fibre strength QTL were used in the backcross and modified backcross breeding program.

Genotyping the BC and MBC Samples Marker-assisted selection was conducted for every generation of backcrossing and modified backcrossing with the markers associated with fibre QTLs based on the F2 population. The markers covering the fibre strength QTLs that were used in MAS are RAS 72, RAS 158, RAS 215, RAS 223, RAS 224, RAS 230, RAS 306 and RAS 304.The selection of plants with high fibre strength trait at every generation was based on the markers and phenotypic data.

RESULTS AND DISCUSSION The first and foremost criterion to be considered in any breeding programme is the magnitude of the genetic variability present in the base population which is prime requirement for starting a judicious breeding programme for combining desirable characters into the elite lines. In the present investigation the estimates of mean, range, phenotypic and genotypic coefficients of variation, heritability and genetic advance as per cent of mean in F2 generation are calculated and presented in Table 2. There were large differences in the variances for most of the characters under study. The high variance (10.2) of fibre strength character in F2 population indicates that the presence of sufficient amount of variability which had been generated in segregating populations (Pradeep and Sumalini, 2003). The distribution of fibre strength in F2 generations is given in Fig. 6. The distribution range of fibre strength in F2 was between 18 g/tex to 36 g/ tex. The 27% of plants out of 475 plants showed moderate fibre strength (26-28 g/tex). Furthermore, 3 plants in F2 showed above 34 g/tex which was higher than the donor parent, suggesting transgressive segregation for the trait. The variation and transgressive segregation observed for fibre strength has practical implication for combining fibre strength in upland cotton.

TABLE 2: THE ESTIMATES OF MEAN, RANGE, HERITABILITY, GENETIC ADVANCE, GENETIC ADVANCE PER CENT OF MEAN, PCV AND GCV OF F2 GENERATION (RC 64 X RC 45 SB)

Characters Mean Range Variance Heritability (h2 %) GA GA% of Mean PCV % GCV% Boll Weight (g) 3.3 1.9-4.6 0.4 84.5 1.3 39.1 19.0 17.5 Number of bolls/plant 67.5 32.0-127.0 445.8 46.9 43.5 64.4 31.3 21.4 Ginning percentage (%) 29.5 22.5-38.7 9.3 56.1 6.3 21.3 10.3 7.7 Lint index 3.8 1.9-6.6 0.6 8.9 1.6 41.5 20.1 6.0 Seed index 9.2 5.4-14.0 2.4 15.1 3.2 34.3 16.7 6.5 2.5% span length (mm) 32.5 26.1-38.1 6.3 83.1 5.2 15.9 7.7 7.0 Fibre strength (g/tex) 43.7 40.6-47.5 10.2 59.1 6.6 24.0 11.6 9.0 Uniformity ratio 27.4 18.4-36.1 1.7 78.4 2.7 6.1 3.0 2.6 Elongation 5.6 4.0-12.0 0.7 65.8 1.7 30.5 14.8 12.0 Micronaire 2.8 2.0-4.2 0.2 39.6 0.9 31.3 15.2 9.6 Seed cotton yield (g)/plant 152.5 82.3-266.7 2482.5 30.1 102.6 67.3 32.7 17.9

Although range can provide a preliminary idea about the variability but coefficient of variation is reliable as it is independent of unit of measurement. The extent of variability as measured by PCV and GCV also gives information regarding the relative amount of variation.


Fig. 5: Frequency Distribution of Fibre Strength Trait in F2 Population (475 Plants)

The estimates of phenotypic coefficients of variation (PCV) ranged from 2.98 for fibre uniformity ratio to 32.68 % for seed cotton yield per plant and the corresponding values for genotypic coefficients of variation (GCV) were 2.64 % for fibre uniformity ratio and 21.83 % for number of bolls per plant (Table 2). The phenotypic coefficient of variation which measures total variation was found to be greater than genotypic coefficient of variation for all the characters indicating some degree of environmental influence on the traits.

It is not the magnitude of variation but the extent of heritable variation, which matters most for achieving gains in selection programme. The coefficient of variation indicates only the extent of variation for a character and does not discriminate the variability into heritable and non-heritable portion. The heritability worked out in broad sense would suggest how far the variation is heritable and selection is effective. A perusal of heritability estimates indicated that the characters such as boll weight, fibre length, uniformity ratio and fibre elongation have high heritability (Table 2). Such high heritability estimates have been found to be helpful in making selection of superior genotypes on the basis of phenotypic performance for quantitative characters. The characters viz., number of bolls per plant, ginning percentage, fibre strength, mircronaire and seed cotton yield per plant had moderate heritability. Though the heritability estimates are the true indicators of genetic potentiality of the genotypes which can be used as a tool for selection, changes in the values of the heritability due to fluctuations of the environmental factors detract for total dependence on such estimates. However, heritability estimates when considered in conjunction with the predicted genetic gain form a reliable tool for selection. They indicate the expected genetic advance of a character in response to the certain selection pressure imposed on them and also provide an idea about the gene action involved in the expression of various polygenic traits involving several QTLs.

High heritability coupled with high genetic advance as per cent of mean was noticed for the characters boll weight and elongation. This indicates that additive gene action was responsible for the inheritance of these traits and the selection in the early generation could be fruitful in improving these characters (Kumaresan, et. al., 2000). In contrast the characters lint index and seed index have low heritability and high genetic advance as per cent of mean. The fibre strength character has moderate heritability and high genetic advance as per cent of mean indicates that success through simple selection could be expected in the early generation as this trait is having the additive gene action.

Marker-Assisted Selection (MAS) using Simple Sequence Repeats (SSR)

Based on limited DNA polymorphism in upland cotton for markers available to date, and limited application of markers for cotton improvement, sound MAS breeding strategy is important for incorporating QTLs associated with fibre traits are successfully used in crop improvement. We have screened 658 SSR primers for the identification of polymorphism between the two parents. Of the 658 primer, 454 primers were polymorphic between the parents, 158 primers were polymorphic between bulked low and high fibre strength samples (Fig. 6). Subsequently 158 polymorphic primers obtained in

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TABLE 3: THE ESTIMATES OF MEAN, RANGE AND VARIANCE OF BACKCROSS POPULATIONS (RC 64 X (RC 64 X RC45 SB)

Generation Number of bolls/Plant

Boll Weight (g)

Ginning Percentage (%)

Lint Index

Seed Index

2.5% Span Length (mm)

Fibre Strength (g/tex)

Uniformity Ratio

Elongation Micronaire

BC1F1 Mean 58.0 3.8 31.8 5.0 10.7 35.1 27.2 48.9 6.1 3.5 Range 16.0-185.0 2.5-5.5 22.1-38.6 2.3-7.6 5.5-19.2 30.3-38.3 24.4-32.7 43.3-54.4 3.6-9.9 2.4-5.1 Variance 584.1 0.4 7.1 0.7 3.7 2.6 4.9 5.4 1.9 0.3








RC 64 (Recurrent Parent)

Mean 143.0 5.5 33.3 6.4 12.9 31.6 24.1 47.8 5.4 6.7

RC 45SB (Donor Parent)

Mean 127.0 3.6 28.4 4.7 12.0 38.0 33.1 49.7 2.8 4.8

The introgression of fibre strength character into upland cotton utilizing Gossypium barbadense as donor through back cross and modified back cross method was done in the present investigation. Since the fibre strength trait is controlled by several QTLs, the introgression was done by one back cross followed by pedigree method. The mean, range and variance of observed characters for back cross generations are given in the Table 3. The mean values of fibre strength in all the backcross generations (BC1F1 - BC1F8) indicates that the progenies are having high fibre strength (>27 g/tex). The high fibre strength plants in each back cross generations were selected based on phenotypic selection coupled with genotypic selection utilizing identified fibre strength linked SSR markers. The high fibre strength plants with recurrent parent background were selected by utilizing molecular markers and phenotypic data. The distribution range of fibre strength in backcross population (Fig. 9) reveals that in each generation the number of plants fall under the high fibre strength group has been increased by the effective selection of combining phenotypic and genotypic information. In BC1F1 generation the frequency of plants fall under high fibre strength (>30g/tex) is 14 per cent while in the BC1F8 generation the frequency is 60 per cent. Furthermore in BC1F8 generation, the fibre strength values were ranged from 26.9 to 35.7 g/tex and seven plants were having highest fibre strength values of above 34 g/tex. The high fibre strength plants in the advance generations are have high phenotypic similarities to the recurrent parent type and thus the molecular markers are effectively used in the selection of target alleles with high background of recurrent parent.


Fig. 9: Frequency Distribution of Fibre Strength Trait in Backcross Generations

The modified backcross method has been used for pyramiding the multiple traits into upland cotton besides the introgression of fibre strength traits. The three upland cotton lines namely RC 62, RC 67 and RC 92 were utilized as recurrent parent and high fibre strength BC1F1 plants were used as donor plant to develop a three modified back cross population (Figs. 2- 4) The advantage of this proposed modified backcross breeding method was to obtain the more recurrent genome background with high fibre strength as the frequency of the undesirable genes from the donor parents was reduced similar to the reported by Li and Pan, 1990.

TABLE 4: THE ESTIMATES OF MEAN, RANGE AND VARIANCE OF MODIFIED BACKCROSS (I) POPULATIONS

Generation Number of Bolls/Plant

Boll Weight (g)


Lint Index

Seed Index



Uniformity Ratio


MBC1F1 Mean 90.1 4.6 31.1 5.0 11.1 35.6 26.5 44.7 4.8 3.4 Range 56.0-154.0 3.1-5.9 25.8-36.1 3.7-6.0 8.5-

14.1 32.2-38.4 25.0-28.6 43.2-46.6 3.6-6.0 2.6-4.1

Variance 501.1 0.5 5.6 0.4 1.6 2.4 0.5 0.6 0.3 0.2 MBC1F2 Mean 85.4 3.6 31.7 4.5 9.5 32.8 27.1 45.5 5.5 3.1

Range 19.0-176.0 2.1-5.6 2.2-42.4 2.9-6.9 3.55-14.4

29.1-37.5 25.7-30.1 42.8-47.2 4.2-7.2 1.8-4.7


Range 56.0-135.0 2.8-5.4 25.6-39.9 3.8-6.3 7.5-14.4

28.3-38.1 25.9-30.8 42.0-47.2 4.1-7.1 2.6-4.4


Range 45.0-142.0 2.0-6.5 23.4-37.7 2.9-7.0 6.3-14.4

28.7-36.2 25.0-29.9 41.9-47.3 5.0-8.3 2.4-5.3


Range 68.0-116.0 2-5.5 24.7-46.0 3.6-6.9 5-14.25

30.6-35.8 25.7-31.8 44.0-47.2 4.3-6.5 2.6-4.5


Range 19.0-122.0 2.9-5.9 21.4-36.9 4.1-7.4 8.35-16.86

29.2-35.2 25.2-32.3 44.0-47.9 4.6-6.8 2.9-5.1

Variance 457.3 0.3 3.4 0.4 1.8 2.1 1.9 0.6 0.2 0.1 RC 64 (Recurrent Parent)

Mean 143.0 5.5 33.3 6.4 12.9 31.6 24.1 47.8 6.7 5.4


Mean 66.0 4.9 31.3 5.9 12.9 37.2 28.5 47.2 5.9 3.8


Mean 127.0 3.6 28.4 4.7 12.0 38.0 33.1 49.7 2.8 4.8

0102030405060708090

100

18‐20

20‐22

22‐24

24‐26

26‐28

28‐30

30‐32

32‐34

34‐36

36‐38

Freq

uency in %

Range

BC1F1

BC1F2

BC1F3

BC1F4

BC1F5

BC1F6

BC1F7


In the modified backcross generations the high fibre strength has been improved significantly. The mean, range and variance of fibre strength for modified back cross generations are given in the Table 4 to 6. The fibre strength values of modified backcross generations ranged from 27.2 to 37.6 g/tex in MBC1F4 (III), 25.3 to 32.4 g/tex in MBC1F6 (I) and 24.4 to 32.8 g/tex in MBC1F6 (II). The marker based selected advanced progenies in the modified backcross generations are having uniform high fibre strength with high similar phenotypic characters of the recurrent parents. The selected high strength progenies were grouped into different staple length group in order to meet out the textile industry requirement of various counts.

TABLE 5: THE ESTIMATES OF MEAN, RANGE AND VARIANCE OF MODIFIED BACKCROSS (II) POPULATIONS


Boll Weight (g)


Lint Index

Seed Index

2.5% span Length (mm)


Uniformity Ratio


MBC1F1

Mean 92.7 4.6 32.2 5.3 10.9 36.3 44.5 26.9 5.2 3.6 Range 38.0-178.0 3.8-6.5 28.7-36.2 4.3-6.3 5.8-13.3 33.0-39.7 43.2-46.0 26.0-29.3 4.4-7.5 3.0-4.5 Variance 921.6 0.4 3.6 0.3 2.2 3.4 0.5 0.7 0.4 0.2

MBC1F2


MBC1F3


MBC1F4


MBC1F5


MBC1F6


RC 64 (Recur-rent Parent)

Mean 143.0 5.5 33.3 6.4 12.9 31.6 24.1 47.8 6.7 5.4

RC 67 (Recur-rent Parent)

Mean 93.0 5.0 31.8 5.9 12.6 37.0 27.3 47.7 3.3 6.1


Mean 127.0 3.6 28.4 4.7 12.0 38.0 33.1 49.7 2.8 4.8

TABLE 6: THE ESTIMATES OF MEAN, RANGE AND VARIANCE OF MODIFIED BACKCROSS (III) POPULATIONS


Boll Weight (g)


Lint Index

Seed Index



Uniformity Ratio


MBC1F1


MBC1F2 Mean 97.0 4.1 34.2 5.5 10.6 33.3 27.4 45.8 4.8 4.9 Range 75.0-124.0 2.0-6.1 28.0-40.4 3.6-7.8 7.4-14.4 0.5-36.6 26.0-30.7 43.6-47.9 2.7-7.7 2.6-9.2 Variance 270.9 0.7 6.9 0.8 2.8 1.7 1.2 0.8 1.5 3.2

MBC1F3 Mean 74.3 4.2 33.7 5.6 10.9 31.0 29.1 46.9 5.4 4.0 Range 50.0-111.0 2.5-6.0 29.9-38.6 3.1-7.6 7.3-14.4 25.9-36.2 25.8-33.7 44.7-49.9 4.5-6.3 2.5-5.5 Variance 151.5 0.6 5.6 0.8 2.2 4.2 3.0 1.5 0.2 0.6

MBC1F4

Mean 51.5 4.2 33.1 5.8 11.7 31.3 31.4 46.7 5.4 4.9 Range 18.0-98.0 2.6-6.8 26.7-45.3 2.6-7.9 5.9-17.1 26.8-41.3 27.2-37.5 42.7-49.3 4.2-7.4 3.4-5.6

Variance 228.0 0.5 4.7 0.5 2.2 3.3 2.8 0.9 0.3 0.2 Table 6 (Contd.)…


…Table 6 Contd.


Mean 143.0 5.5 33.3 6.4 12.9 31.6 24.1 47.8 6.7 5.4


Mean 78.0 5.6 34.6 7.6 14.3 35.8 28.4 49.2 6.6 3.6


Mean 127.0 3.6 28.4 4.7 12.0 38.0 33.1 49.7 2.8 4.8

The application of DNA markers in backcross breeding program is dependant by the precision of associated markers as well as by the cost effectiveness of marker-assisted selection. Marker-assisted selection was found useful in developing genotypes with combinations of favourable alleles. The main reasons supporting the utilization of molecular markers in cotton breeding programs are the 100% heritability of the markers and their lower cost. Hence, the molecular markers were used in a backcrossing scheme to improve the fibre strength traits in upland cotton efficiently.

Further to the present investigation the selected BC1F8 and MBC1F6 plants will be forwarded to the next generation. The progeny test row may be conducted to select the best uniform high yielding progenies with high fibre strength. Thus the developed introgressed high fibre strength upland cotton line can be utilized for introgressing the fibre strength to improve the available elite parental lines through marker assisted background selection to develop high fibre strength hybrids.

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overlapped RILs to dissect genetically clustered QTL for fibre strength on Chro.D8 in Upland cotton. Theor. Appl. Genet., 119: 605–612.

[4] Dudley, J.W. and R.H. Moll.1969. Interpretation and use of estimates of heritability and genetic variances in plant breeding. Crop. Sci., 9(3):257-262.

[5] Johnson, H. W., H.F. Robinson and R.E. Comstock. 1955. Genotypic and phenotypic correlation in soybean and their implications in selection. Agron. J., 47 : 477-483.

[6] Kohel, R.J.1999a. Cotton Improvement: A Perspective. Cotton World 1: (in press). [7] Kohel, R.J.1999b. Cotton germplasm resources and the potential for improved fibre production and quality, In: A.S. Basra

(Ed.), Cotton fibres, pp. 167–182. The Haworth Press, Inc, NY. [8] Kumaresan, D., J. Ganesan and S. Ashok. 2000. Genetic analysis of qualitative characters in cotton (Gossypium hirsutum

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[10] Li, W.H and J.J. Pan. 1990. Effect of modified backcross in breeding upland cotton cultivars. J. Nanjijng. Agri. univ., 13: 232-235.

[11] Lush, J.N. 1949. Animal breeding plans. The collegiate Press. Amer. Iowa Ed. 3. [12] Pradeep, T. and K. Sumalini. 2003, Impact of mating systems on genetic variability in segregating generation of Asiatic

cotton (Gossypium sp.). Indian J. Genet., 63 : 143-147. [13] Rahman,

S

and T.A. Malik. 2008. Genetic analysis of fibre traits in cotton. Int. J. Agri. Biol., 10: 209–212.

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Estimation of Genetic Parameters for Yield and Fibre Quality Traits in Inter-Specific

Crosses of Cotton (Gossypium spp.)

Gunasekaran Mahalingam, Krishnasamy Thiyagu and Nagasamy Nadarajan

Department of Cotton, Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore–641003 India

Abstract—To study the nature and magnitude of gene effects for seed cotton yield and fibre quality traits in cotton (Gossypium spp), the generation mean analysis was carried out using the following four crosses of different cotton cultivars: SVPR 2 × Suvin, SVPR 2 × Barbados, TCH 1218 × Suvin and TCH 1218 × Barbados. The P1, P2, F1, F2, B1 and B2 of these generations were studied for yield and fibre quality traits. The analysis showed the presence of additive, dominance and epistatic gene interactions for these characters. Duplicate type epistasis played a greater role than complementary epistasis. To harness the additive gene action, simple selection procedures or pedigree method of breeding is sufficient. Heterosis breeding procedures are effective in harnessing dominance gene action to the full extent. When additive and dominant gene actions are pre-dominant, the bi-parental mating design or reciprocal recurrent selection can be used for further recombination of alleles to produce desirable segregants.

INTRODUCTION

Cotton is an important natural fibre crop of global importance grown commercially in about 111 countries with a global area of 30.29 million hectares accounting for 105.06 million bales (217.724 kgs) of production with a productivity of 755 kg/ha. In India, cotton is cultivated in an area of nearly 10.17 million hectares which is the largest in the world, with a production of 29.20 million bales (2009-10) ranking second next to China. Cotton plays a key role in the national economy by way of its contribution in trade, industry, employment and foreign exchange earnings. The average productivity of cotton in India is the lowest among cotton-growing nations of the world.

Though India is a pioneer in cultivation of hybrids on a commercial scale, the productivity of cotton has been practically stagnant during last few years. In order to increase the yield potential, it is desirable to efficiently utilize the available genetic variability. Genetic analysis of quantitative traits further helps to elucidate the nature and magnitude of genetic variation present in the population. The estimates of gene effects in a plant improvement programme have a direct bearing upon the choice of breeding procedure to be followed. Additive gene effects are useful in the development of pure lines whereas dominance and epistatic effects can be used to exploit hybrid vigour. In tetraploid cotton, various studies have been conducted to study the nature and magnitude of gene effects in the inheritance of different quantitative characters and involvement of both additive and non-additive gene effects have been reported by many workers (Nadarajan et al., 1999; Patel et al., 2007). In the present investigation, additive dominance and epistatic gene effects were estimated by Generation mean analysis for yield and fibre quality traits in four inter-specific crosses involving G. hirsutum and G. barbadense and suggest suitable breeding methods for genetic improvement of cotton.


The genetic materials used in this study consisted of two each of G. hirsutum and G. barbadense genotypes namely SVPR 2 and TCH 1218; and Suvin and Barbados respectively. Two G. hirsutum genotypes have good combiner, good adaptability, jassid resistance, drought tolerance and higher yield and the remaining two G. barbadense genotypes have good fibre length, strength and fineness. The experiment was performed with a set of six generations viz., P1, P2, F1, F2, B1 and B2 in four cross combinations viz., SVPR 2 × Suvin (cross 1), SVPR 2 × Barbados (cross 2), TCH 1218 × Suvin (cross 3)

5

Estimation of Genetic Parameters for Yield and Fibre Quality Traits in Inter-Specific Crosses of Cotton (Gossypium spp.) 29

and TCH 1218 × Barbados (cross 4) to study the presence of interaction effects in governing the traits of seed cotton yield and yield attributes and fibre quality traits. The F1 plants were randomly chosen from each cross and used as male parent for back crossing programme, whereas the concerned parents of each cross were used as female parents to produce B1 (P1 × F1) and B2 (P2 × F1) progenies. Simultaneously, F2 seeds were produced by selfing F1 plants. All these generations were produced during two cropping seasons and, as such, all the six generations had to be grown together during the same cropping season.

The F1, F2, B1 and B2 generations of the four crosses were raised along with their parents in a randomized block design (RBD) with two replications during winter 2008–09 at Department of Cotton, Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore. Four different crosses were randomized in a block followed by different generations within each cross. The spacing was 90 × 60 cm. Ten plants in a row is same for all the generations of each crosses but the number of rows varied as two rows each for non-segregating population such as P1, P2 and F1; 40 rows for F2 and 20 rows for each of B1 and B2. Since the non-segregating generations represent the homogeneous population while the segregating generations represent the heterogeneous population the sample size (i.e. number of plants analyzed) varied as 20 plants for P1, P2 and F1, 400 plants for F2 and 200 plants in each of B1 and B2. The recommended agronomic practices and need-based plant protection measures were followed to obtain good crop stand. Observations were recorded on number of bolls per plant (NB), boll weight (g) (BW), seed cotton yield per plant (SCY), ginning percentage (%) (GP), 2.5 per cent span length (mm) (SL) and bundle strength (g/tex) (BS).

The generation means were calculated by taking the average over all the replications for each generation. The variance and the corresponding standard errors of the means were calculated from the deviations of the individual values from the pooled mean for each of the generation for every cross. To test the adequacy of the additive-dominance model the individual scaling test given by Mather (1949) as well as joint scaling test by Cavalli (1952) were applied. First, simple additive-dominance model consisting of mean [m], additive [d] and dominance [h] gene effects was tried and the adequacy of the model was tested statistically by examining the goodness of fit between the estimated generation means and the observed generation means from the above three parameters for three degrees of freedom. Wherever the data failed to fit the simple additive dominance non-epistatic-model, the analysis was proceeded further by perfect fit estimate of the six parameters m, [d], [h], additive × additive [i], additive × dominance [j] and dominance × dominance [l] on the assumptions of an additive dominance model with digenic interactions as proposed by Jinks and Jones (1958).


The mean of the six generations with four crosses for six traits are presented in Table 1, with the mean values for the scaling, joint scaling and their interaction effects being presented in Table 2.

Among the parents, P1 generation showing higher performance for boll weight, ginning percentage and seed cotton yield per plant in all the crosses except TCH 1218 × Barbados, where P2 mean was higher for seed cotton yield per plant. With respect to 2.5 per cent span length and bundle strength, P2 was superior than P1 in all the four crosses. Among the different generations all the F1’s performed better for number of bolls per plant and seed cotton yield per plant. With regard to 2.5 per cent span length and bundle strength, F1 mean was lower than the greater parent in all the crosses. Among the segregating generations of F2, B1 and B2, the B1 generation showed higher mean performance in all the crosses for all the traits except 2.5 per cent span length and bundle strength were B2 showed its superiority over B1 generations.

A simple additive dominance model was non-adequate as inferred the significance of any one of the scales and joint scaling test. Hence, an epistatic digenic interaction model was found to be fit for all the six traits. The additive, dominance and epistatic types of gene interaction in each cross for different trait were found to be different from each other.


TABLE 1: MEAN VALUES OF DIFFERENT CHARACTERS OVER SIX GENERATIONS IN SIX CROSSES OF COTTON

Characters and Generations

SVPR 2 × Suvin SVPR 2 × Barbados TCH 1218 × Suvin TCH 1218 × Barbados

Number of Bolls Per PlantP1 26.90 ± 0.50 25.50 ± 0.43 24.70 ± 0.56 23.70 ± 0.56 P2 20.70 ± 0.37 27.80 ± 0.42 16.20 ± 0.53 28.70 ± 0.54 F1 41.70 ± 0.54 45.70 ± 0.73 28.90 ± 0.64 40.80 ± 0.84 F2 23.64 ± 0.31 22.41 ± 0.32 19.69 ± 0.29 26.75 ± 0.38 B1 24.63 ± 0.44 27.00 ± 0.51 20.58 ± 0.39 27.34 ± 0.56 B2 22.77 ± 0.50 25.07 ± 0.50 20.33 ± 0.40 29.42 ± 0.58

Boll Weight (g)P1 4.82 ± 0.09 4.74 ± 0.06 4.68 ± 0.08 4.84 ± 0.05 P2 4.13 ± 0.06 4.01 ± 0.05 4.09 ± 0.04 4.07 ± 0.04 F1 3.73 ± 0.03 3.71 ± 0.05 4.57 ± 0.05 4.55 ± 0.05 F2 2.79 ± 0.04 3.08 ± 0.03 2.77 ± 0.04 3.66 ± 0.04 B1 3.02 ± 0.06 3.44 ± 0.05 3.37 ± 0.05 3.73 ± 0.05 B2 2.74 ± 0.06 2.86 ± 0.04 2.61 ± 0.04 3.51 ± 0.05

Seed Cotton Yield Per PlantP1 104.65 ± 3.32 100.76 ± 2.34 100.37 ± 2.87 95.14 ± 2.21 P2 61.28 ± 2.41 96.53 ± 2.06 56.28 ± 2.28 96.99 ± 1.17 F1 134.97 ± 2.64 149.38 ± 2.92 114.16 ± 2.80 169.78 ± 3.45 F2 50.31 ± 1.19 60.36 ± 1.44 45.49 ± 1.21 81.74 ± 1.92 B1 60.99 ± 1.93 83.60 ± 2.29 54.12 ± 1.60 90.36 ± 2.56 B2 47.38 ± 1.87 62.75 ± 2.06 42.69 ± 1.47 87.73 ± 2.76

Ginning Percentage (%)P1 36.97 ± 0.40 36.31 ± 0.33 34.87 ± 0.47 34.06 ± 0.62 P2 33.77 ± 0.47 32.87 ± 0.32 30.56 ± 0.32 33.99 ± 0.45 F1 33.29 ± 0.35 32.00 ± 0.37 34.07 ± 0.57 33.22 ± 0.38 F2 30.22 ± 0.20 31.54 ± 0.19 30.44 ± 0.17 30.78 ± 0.17 B1 32.93 ± 0.33 33.94 ± 0.30 31.25 ± 0.22 32.75 ± 0.23 B2 29.68 ± 0.29 31.55 ± 0.28 31.67 ± 0.23 30.80 ± 0.26

2.5% Span Length (mm)P1 25.46 ± 0.36 25.36 ± 0.31 30.00 ± 0.42 30.06 ± 0.49 P2 37.28 ± 0.32 34.56 ± 0.29 37.08 ± 0.40 34.54 ± 0.28 F1 34.20 ± 0.24 33.56 ± 0.25 36.26 ± 0.42 35.10 ± 0.37 F2 30.34 ± 0.26 29.49 ± 0.23 31.25 ± 0.35 31.45 ± 0.24 B1 28.47 ± 0.45 28.18 ± 0.38 31.19 ± 0.53 31.28 ± 0.40 B2 34.94 ± 0.16 31.96 ± 0.38 33.60 ± 0.42 32.16 ± 0.38

Bundle Strength (g/tex)P1 18.36 ± 0.21 18.22 ± 0.10 21.18 ± 0.33 21.18 ± 0.33 P2 27.12 ± 0.15 26.94 ± 0.29 27.20 ± 0.15 26.86 ± 0.27 F1 24.26 ± 0.26 25.00 ± 0.35 24.36 ± 0.41 24.70 ± 0.41 F2 22.49 ± 0.26 21.90 ± 0.20 22.91 ± 0.51 23.44 ± 0.23 B1 20.83 ± 0.39 21.06 ± 0.32 21.19 ± 0.66 22.23 ± 0.30 B2 25.48 ± 0.39 25.39 ± 0.33 25.18 ± 0.54 25.50 ± 0.41

Number of Bolls Per Plant

Among the genetic effects, the mean effect was higher in SVPR 2 × Suvin and TCH 1218 × Barbados. The additive effect (d) was found to be positively significant in SVPR 2 × Suvin and TCH 1218 × Suvin, while dominance effect (h) was positive in SVPR 2 × Barbados and TCH 1218 × Barbados. This indicated the pre-dominance of both additive and dominance main effects. In case of interaction effects, the dominance × dominance was positively significant for all the crosses, while the additive × additive interaction effect was positive for all the crosses and significantly positive in SVPR 2 × Barbados and TCH 1218 × Barbados. The additive × dominance effect was negatively significant in TCH 1218 × Suvin and positively significant in SVPR 2 × Barbados. The signs of (h) and (l) were opposite in SVPR 2 × Suvin and TCH 1218 × Suvin, while in the same direction in SVPR 2 × Barbados and TCH 1218 ×


Barbados. This indicated the presence of both complementary and duplicate epistasis for this trait. In general, both additive and dominance main effects, predominant of dominance × dominance and additive × additive interaction effects along with both complementary and duplicate dominance epistasis were noticed for number of bolls per plant. Shanti (1998), Esmail et al. (1999) and Ramalingam and Sivasamy (2003) reported additive, dominance × dominance and additive × additive interaction effects for this trait.

TABLE 2: SCALING TEST AND GENETIC EFFECTS FOR DIFFERENT CHARACTERS IN FOUR CROSSES OF COTTON

Cross A B C D JST m (d) (h) (i) (j) (l) 1 2 3 4 SCY C1 ** ** ** * ** 67.46**

± 7.47 21.69* ±

2.05 -36.10** ±

19.91 15.51* ±

7.19 -8.08* ±

3.38 203.61** ± 13.54

-6.27 157.79 227.20 DE

C2 ** ** ** ** ** 47.36** ± 8.58

2.12 ± 1.56

-50.04* ± 22.47

51.28** ± 8.44

18.74** ± 3.45

152.06** ± 15.13

-23.66 52.16 222.08 DE

C3 ** ** ** - ** 66.67** ± 6.77

22.04** ± 1.83

-132.19** ± 17.38

11.65 ± 6.51

-10.62** ± 2.84

179.68** ± 12.00

-6.00 154.23 201.95 DE

C4 ** ** ** ** ** 66.83** ± 0.82

-0.93 ± 1.25

-43.31 ± 27.79

29.24** ± 0.75

3.56 ± 3.97

146.27** ± 18.43

46.67 44.24 179.07 DE

NB C1 ** ** ** - ** 23.57**

± 1.84 3.10** ±

0.31 -17.84** ±

4.82 0.23 ± 1.82

-1.25 ± 0.74

35.97** ± 3.19

-5.75 20.94 37.45 DE

C2 ** ** ** ** ** 12.14** ± 1.95

-1.15** ± 0.30

7.49 ± 5.15

14.51** ± 1.92

3.08** ± 0.78

26.06** ± 3.52

-6.52 8.64 43.65 CE

C3 ** ** ** - ** 17.40** ± 1.67

4.25** ± 0.39

-2.33 ± 4.32

3.05 ± 1.62

-4.00** ± 0.68

13.84** ± 2.95

-0.55 6.58 20.89 DE

C4 ** ** ** ** ** 19.67** ± 2.26

-2.50** ± 0.39

7.18 ± 5.90

6.53** ± 2.22

0.42 ± 0.89

13.95** ± 4.02

-2.87 9.68 20.9 CE

BW C1 ** ** ** - ** 4.12** ±

0.22 0.34** ±

0.06 -4.94** ±

0.58 0.36 ± 0.21

-0.06 ± 0.10

4.55** ± 0.37

-14.53 5.28 4.98 DE

C2 ** ** ** - ** 4.09** ± 0.19

0.36** ± 0.04

-3.66** ± 0.49

0.28 ± 0.18

0.22** ± 0.08

3.28** ± 0.32

-10.17 4.02 3.78 DE

C3 ** ** ** ** ** 3.50** ± 0.20

0.29** ± 0.05

-4.01** ± 0.51

0.88** ± 0.20

0.47** ± 0.08

5.08** ± 0.33

-13.83 4.30 6.43 DE

C4 ** ** ** - ** 4.63** ± 0.21

0.39** ± 0.03

-3.79** ± 0.55

-0.18 ± 0.21

-0.18* ± 0.08

3.71** ± 0.36

-9.72 4.18 4.07 DE

GP C1 ** ** ** ** ** 31.03**

± 1.23 1.60** ±

0.31 -5.49 ±

3.24 4.34** ±

1.19 1.65** ±

0.54 7.75** ±

2.15 -3.43 7.09 13.74 DE

C2 - * ** ** ** 29.76** ± 1.13

1.72** ± 0.23

4.86 ± 2.97

4.83** ± 1.10

0.67 ± 0.47

-2.62 ± 1.99

2.83 6.58 8.13 DE

C3 ** - ** ** ** 28.63** ± 0.97

2.15** ± 0.28

1.79 ± 2.54

4.08** ± 0.93

-2.57** ± 0.42

3.65** ± 1.92

0.83 3.94 10.3 CE

C4 * * ** ** ** 31.03** ± 1.23

1.60** ± 0.31

-5.49 ± 3.24

4.34** ± 1.19

1.65** ± 0.54

7.75** ± 2.15

-3.43 7.09 13.74 DE

*Significant at 5% level, **Significant at 1% level; C1–SVPR 2×Suvin; C2–SVPR 2×Barbados; C3 –TCH 1218×Suvin; C4–TCH 1218×Barbados; A, B, C, D–Scales; JST–Joint scaling test; m–mid parent; (d)–additive; (h)–dominance; (i)–additive × additive; (j)–additive × dominance; (l)–dominance × dominance; 1–h/d; 2–Total main effect; 3–Total interaction effect; 4–Type of epistasis; CE– Complementary Epistasis; DE–Duplicate Epistasis

Boll Weight

Among the genetic effects estimated, the additive main effect (d) was pre-dominant and showed positively significant values in all crosses and was greater than dominance effects (h) where negatively significant interaction effect was noticed in all the crosses. The dominance × dominance interaction effect (l) was found to be positively significant in all crosses. The additive × dominance interaction effect (j) was positively significant in SVPR 2 × Barbados and TCH 1218 × Suvin, while additive × additive interaction was positively significant in TCH 1218 × Suvin. Duplicate dominance epistasis was confirmed in all the crosses due to the opposite signs of (h) and (l). On the whole, additive gene effects and epistatic effects, especially of dominance × dominance and additive × dominance type were found to


govern this trait along with duplicate type of epistasis. This is in conformity with the results of Sandhu et al. (1992). Rajendra Kumar and Raveendran (2001) reported the presence of additive effects for boll weight. Ramalingam and Sivasamy (2003) expressed dominance × dominance and additive × dominance interaction effect for this trait.

Seed Cotton Yield Per Plant

The perusal of six generations using generation mean analysis indicated that additive gene effects were prevalent for majority of the crosses viz., SVPR 2 × Suvin, SVPR 2 × Barbados and TCH 1218 × Suvin. In SVPR 2 × Suvin and TCH 1218 × Suvin, additive effect was positively significant. The dominance effect (h) was negatively significant in all the crosses except TCH 1218 × Barbados which had negative effect. The dominance × dominance interaction effect (l) was pre-dominant in all the crosses where it was positively significant followed by additive × additive effect which was also positively significant in all the crosses except TCH 1218 × Suvin. The additive × dominance interaction effect (j) was positively significant in SVPR 2 × Barbados and negatively significant in SVPR 2 × Suvin and TCH 1218 × Suvin. The signs of (h) and (l) were opposite in direction in all the crosses. This indicated that seed cotton yield per plant was found to be governed by additive gene effects and interaction effects pre-dominantly of dominance × dominance type followed by additive × additive with duplicate type of epistasis. All the three types of interaction for this trait were reported by Singh and Chahal (2004) and Singh et al. (2008). Shanti (1998) reported additive effect while Esmail et al. (1999) reported additive × additive gene interactions but Jagtap (1995) reported both type of gene actions for this trait.

Ginning Percentage

Among the genetic effects estimated, interaction effects were witnessed in all crosses. In these crosses, the additive genetic effect was positive in TCH 1218 × Barbados and significantly positive in rest of the crosses viz., SVPR 2 × Suvin, SVPR 2 × Barbados and TCH 1218 × Suvin, while the dominance gene effects (h) was found to be positive in SVPR 2 × Barbados and TCH 1218 × Suvin and negative in SVPR 2 × Suvin and TCH 1218 × Barbados. The additive × additive interaction effect was found to be positively significant in all the crosses. The additive × dominance effect (j) was positively significant in SVPR 2 × Suvin and TCH 1218 × Barbados and positive for SVPR 2 × Barbados. The dominance × dominance effect (l) was positively significant in SVPR 2 × Suvin and TCH 1218 × Suvin, positive in TCH 1218 × Barbados and negative in SVPR 2 × Barbados. The signs of (h) and (l) were dissimilar in all crosses except TCH 1218 × Suvin. Hence it appears that, the additive effect along with all the three types of interaction with duplicate dominance epistasis existed pre-dominantly for ginning percentage. Panchal et al. (1994) reported the presence of additive, additive × additive, additive × dominance and dominance × dominance interactions for ginning percentage. Rajendra Kumar and Raveendran (2001) and Shanti (1998) reported additive gene effects and Sandhu et al. (1992) reported all the three types of epistasis gene interactions.

Per Cent Span Length

The mean effect estimated by the perfect fit method for digenic interactions in all the crosses was highly and positively significant. The interaction effects were witnessed in all crosses. In these crosses, the dominance genetic effect was positive in SVPR 2 × Barbados and TCH 1218 × Suvin, positively significant in SVPR 2 × Suvin and negative in TCH 1218 × Barbados, while the additive gene effect (d) was found to be negatively significant in all the four crosses. The additive × additive interaction effect was found to be positively significant in SVPR 2 × Suvin and TCH 1218 × Suvin and positive for the rest of the crosses. The additive × dominance (j) and dominance × dominance effect (l) were positively significant for TCH 1218 × Barbados, positive for SVPR 2 × Barbados and TCH 1218 × Suvin and negative for SVPR 2 × Suvin. Hence it appears that, the dominance effect along with additive × additive gene action followed by additive × dominance and dominance × dominance gene action with duplicate and complementary epistasis exists for 2.5 per cent span length. Mehetre et al. (2003) reported the


presence of dominance, additive × additive and dominance × dominance interaction for 2.5 per cent span length. Thangaraj et al. (2002) and Singh and Chahal (2004) reported additive, dominance and duplicate epistasis for 2.5 per cent span length.

Bundle Strength

The mean effect was positively significant and higher than other genetic effects. The interaction effects were witnessed by significance of scale C in all crosses. The dominance effect (h) was positively significant in SVPR 2 × Barbados and positive for SVPR 2 × Suvin and TCH 1218 × Barbados and negative in TCH 1218 × Suvin. The additive effect (d) was negatively significant in all crosses. The additive × additive effect (i) was positive in all the crosses except SVPR 2 × Barbados, where it was positively significant. The additive × dominance effect (j) was positive in SVPR 2 × Barbados and negative in SVPR 2 × Suvin, TCH 1218 × Suvin and TCH 1218 × Barbados. The dominance × dominance interaction effect (l) was negative in SVPR 2 × Suvin and SVPR 2 × Barbados and positive for rest of the crosses. The signs of (h) and (l) were opposite in all crosses except TCH 1218 × Barbados indicating the presence of duplicate dominance epistasis. To conclude, this trait was controlled by dominance gene effects and interaction effects mainly of additive × additive with duplicate dominance type of epistasis. Mehetre et al. (2003) reported additive, dominance and additive × additive gene effects. Hendawy et al. (1999) reported additive and additive × additive with duplicate type of epistasis for this trait.

CONCLUSION

The gene action analyzed through generation mean analysis indicated that both additive and dominance gene effects were found to control most of the important yield contributing and fibre quality traits viz., number of bolls per plant, boll weight, seed cotton yield per plant and ginning percentage, while dominance gene action was prevalent for the traits viz., 2.5 per cent span length and bundle strength. One or more type of epistatic interaction effects was prevalent for all the characters. Duplicate dominance type of epistasis was witnessed in all characters, while complementary epistasis was also noticed in certain crosses for the traits number of bolls per plant and 2.5 per cent span length.

To harness additive gene action, simple selection procedures or pedigree breeding method is sufficient. But the presence of dominance gene action in most of the characters warrants postponement of selection to later generations after effecting crosses. Heterosis breeding procedures are effective in harnessing dominance gene action to the full extent. Both additive and dominance gene actions play major role in several characters. In such circumstances biparental mating design or reciprocal recurrent selection can be followed which allows further recombination of alleles to produce desirable segregants. These methods can also be well adopted in order to harness the epistatic interactions by way of breaking the undesirable linkages. Diallel selective mating system could also be followed to break such undesirable linkages between two or more genes and to produce desirable recombinants.

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Introgression of Desirable Characters for Growing Cotton in Pakistan

Abid Mahmood, Jehanzeb Farooq and Noor-Ul-Islam

Cotton Research Institute, Ayub Agricultural Research Institute, Faisalabad, Pakistan

Abstract—Cotton crop face both biotic and abiotic stresses. Keeping in view the emerging problems of cotton in Pakistan, a breeding programme was initiated to develop cotton varieties which can withstand under changing environment especially at high temperature and Cotton Leaf Curl Virus (CLCuV) conducive conditions. A series of experiments was conducted to select parental lines which can contribute for high temperature tolerance, low input requirements, earliness, good fibre squality traits, CLCuV tolerance and plants suitable for high density planting. A comprehensive breeding programme was initiated to combine desirable characters in resulting breeding material. Screening of breeding material was carried out in CLCuV hot spot areas. At the same time fibre quality, earliness and high yield were also considered during selection. For low input requirement varieties like FH-113 and FH-942 were developed. For heat and CLCuV tolerance 24 Lines were developed. Some of the lines like MNH-886, FH-142 and MNH-456 showed promising results in this respect. For high density planting of cotton, the line FH-114 showed good performance at densities of 10,0000 plants per hectare. It was recommended that for late sowing of cotton, plant to plant distance of FH-114 may be reduced to 12cm to achieve desirable yield per unit area. The varieties developed during these studies exhibited the highest yield with good fibre quality in CLCuV hot spot areas. It is expected that in future more improved germplasm will be available which will enhance the productivity of cotton in Pakistan.

INTRODUCTION

The importance of upland cotton, (Gossypium hirsutum L), is evident from the fact that it is the world’s leading fibre producing species (Dutt et al., 2004; Fryxell, 1992). It contributes 60% in the total foreign exchange through the exports of value added products (Iqbal et al. 2005). Cotton accounts for 8.6 % of the value added in agriculture and about 1.8 % to GDP of Pakistan (Anonymous, 2007). Pakistan is the 4th largest cotton producing country in the world after Peoples Republic of China, USA and India, and 3rd largest consumer of cotton after People Republic of China and India (Akhtar, 2005).

Keeping in view the geographical situation and farming system of Pakistan breeding of cotton for the development of earliness, heat tolerance, low input requirements, CLCuV resistance and better quality traits are the main objectives. These breeding objectives help to protect environment, boost cotton productivity and make cotton production a profitable venture. Most of the cotton growers in Pakistan are poor and cannot afford heavy expenses of inputs like fertilizer, pesticides and irrigation water. Varieties having deep root system and higher stature require less irrigation water thus can meet the needs of the farmer.

Similarly the varieties with Bt gene provide resistance against bollworms thus reduce the cost of pesticides to control these insects. Bt. Cotton provides an alternative by replacing insecticides with a toxin within the plant. According to Layton et al. (1997) overall performance of Bt. Cotton was better than conventional varieties. Transgenic Bt. cotton can effectively control specific lepidopterous species (Arshad et al., 2009).

For the last many years one of the main causes of low per acre yield of cotton in Pakistan is CLCuV attack. In the early nineties cotton varieties like CIM-1100, CIM-448, CIM-446, CIM-443, MNH-552, MNH-554 were developed which were having resistance against CLCuV. Build up of this disease in the recent years resulted in high inoculum pressure under which varieties which were initially showing some tolerance later became susceptible (Mahmood et al., 2003; Shah et al., 2004).

In several districts of Punjab and Sindh severe summer temperatures exceeding 450C cause considerable damage to cotton crop (Rehman et al., 2004). Fruit setting in upland cotton is severely

6


effected if day temperature of >300C remained for a period of 13 hrs or more (Reddy et al., 1992). Further, it is the need of the day to improve fibre quality in the Hirsutum genotypes, to fulfill the requirements of growing textile industry.

Cotton plant sets its bolls (fruit) over a period of about 80 days. Delayed in that period allows various environmental factor to act and effect maturation period (Iqbal et al., 2003). Late maturating types are ultimately affected by a later pest pressure. Cotton fiber quality is primarily influenced by late maturity of the genotype and by environmental conditions as the secondary factors (Subhan et al., 2001). Earliness in cotton is a complex polygenic trait influenced by a number of factors like morphology, phenology, physiology and environmental attributes (Shah et al., 2010). Earliness allows development of crop during period of favorable moisture and timely picking prevent the crop from unfavorable weather (Rauf et al., 2005). The benefit of growing early maturing cotton cultivars is the provision of proper time for rotation of other crops allowing timely sowing of wheat in cotton – wheat – cotton cropping system as in Pakistan (Ali et al., 2003). The cultivation of early maturing cultivars not only minimizes the use of pesticides, but the expenses incurring on other inputs like irrigation water and fertilizer will also be reduced.

In Pakistan under cotton – wheat – cotton rotation system planting of cotton become late due to delayed harvesting of wheat crop. Delayed planting of cotton poses many problems including severe insect pest attack, incidence of CLCuV and poor growth of the plants. To get better yield in late plantings (high plant population) might be beneficial provided that the late sown genotypes be CLCuV tolerant and fit to high population. Close row spacing and high plant populations in ultra-narrow rows lead to more rapid canopy closure than in wider rows (Robinson, 1993), which leads to increased light interception and reduced weed competition (Kreig, 1996).

The main objective of these studies was to develop germplasm having combination of characters including Bt (Cry-1 Ac), earliness, heat tolerance, resistance to CLCuV and less fertilizer requirement. In addition this germplasm should fit in cotton-wheat-cotton rotation system.


In order to combat the threats of cotton bollworms, CLCuV, heat stress and for the development of varieties having less fertilizer requirement comprehensive breeding programme was initiated. For this purpose parents having desirable characters were identified. The detail of characteristics of the parent lines is given in Table 1.

TABLE 1: NAMES AND VARIOUS CHARACTERISTICS OF THE LINES USED AS PARENT IN VARIOUS EXPERIMENTS INCLUDED IN THESE STUDIES

Parents Distinctive Features FH-925 Early sympodial type variety with medium boll. Having tolerance to heat and CLCuV.

Nucot-N33B An Australian line with Bt gene and was used to transfer Bt in local germplasm possessing good fibre and plant traits.

FH-925 Early sympodial type variety with medium boll. Having tolerance to heat and CLCuV.

Nucot-N33B An Australian line with Bt gene and used for transfer it in local germplasm possessing good fibre and plant traits.

FH-900(S) Resistance against CLCuV, relatively tolerant to heat stress, good fiber quality, fitness in cotton-wheat rotation system and adaptability to wider range of environments

CIM-125 Medium in maturity, intermediate in growth habit and possess good fibre traits.

FH-207 Tall with long sympodial branches, moderately resistant to sucking pest and bollworms. Suitable for Low CLCV intensity areas of non-core zone.

MNH-770 Medium tall plant with tolerance to CLCuV and heat. Its distinctive feature is yellow pollen. MNH-609 Medium tall plant with tolerance to CLCuV and heat.

A systematized crossing programme was carried out to combine the desirable characters in resulting breeding material. For this purpose after crossing F1 and F2 were raised. In F2 single plants with desirable characters were selected. Progeny selection was carried out from F3 to F6 on the basis of seed cotton yield and fibre quality. The detail of the selected genotypes included in the studies is given in Table-2.

Introgression of Desirable Characters for Growing Cotton in Pakistan 37

TABLE 2: PEDIGREE AND VARIOUS TRAITS OF LINES INCLUDED IN VARIOUS EXPERIMENTS CONDUCTED AT COTTON RESEARCH INSTITUTE, FAISALABAD

Genotypes Parentage Distinctive Features

FH-113 FH-925 × NuCot-N33B Tall growing Bt variety possesses moderate tolerance to CLCuV. It has strong stem, prolonged flowering duration and require low inputs.

FH-114 FH-925 × NuCot-N33B A compact input intensive Bt variety with high tolerance to CLCuV and heat stress. Best suited to high plant population in late sowing.

FH-942 FH-900(S) × CIM-121 A spreading growth habit variety most suitable for water-scarce areas. Possess good boll size and fibre quality of national standards.

MNH-886 FH-207 × MNH-770 A revolutionary variety with respect to CLCuV. Intermediate to spreading in its growth habit. Boll size of this variety is medium and can tolerate heat stress in core areas of Punjab.

MNH-456 FH-207 x MNH-609 Highly tolerant to CLCuV A series of experiments were carried out in targeted environments and conditions to find out various

lines of cotton. The studies were carried out at experimental area of Cotton Research Institute, Faisalabad. The soil had pH was 8.2, EC 1.3 dSm-1, nitrogen 0.030% and available Phosphorous 7.0 mg kg-1. The detail of experiments is as under.

Experiment 1: Selection of Lines for Low Fertilizer Requirement

These studies were conducted following Split Plot design with 4 replications. The fertilizer doses were randomized as main plots and genotypes as sub-plot. The line to line distance was kept as 75cm and plant to plant distance at 30cm. Each plot was consisted of 5 lines with 5 meter length. Three genotypes viz., FH-113, FH-942 and FH-1000 were included in these studies. Sowing of the genotypes was carried out on May 3 in 2003-04 and on May 12 in 2004-05. The phosphorus and potash were applied basaly at the time of sowing while the nitrogen was applied in three splits i.e., with first irrigation, at the time of start of square formation and at blooming stage. There were three treatments, i.e full doze of recommended fertilizer (NPK, 114:54:62), half dose of fertilizer (NPK, 57:27:31) and control, (where no fertilizer was applied). Before the experiment the soil was exhausted by growing maize crop in the field. All other agronomic practices and insect control measures was carried out as standard procedure. At maturity data of seed cotton yield/ha was recorded. Analysis of variance was carried out and means of genotypes were compared by LSD.

Experiment 2: Selection of CLCuV Tolerant Lines

In this experiment high yielding with good fibre quality character lines were included. Twenty four advance lines of different genetic background were sown in three replications to identify lines tolerant to CLCuV. Each genotype was planted in two rows with row length of 5 meter. Standard agronomic practices were applied. To maximize CLCuV inoculum pressure the pesticide for whitefly was not applied throughout the experiment. Data for CLCuV was recorded following the rating system described by Akhtar et al, 2010. The procedure of rating CLCuV incidence is briefly mentioned in Table 3.

TABLE 3: DISEASE SCALE FOR RATING COTTON LEAF CURL VIRUS DISEASE

Symptoms Disease Index%

Rating Disease Response

Complete absence of symptoms 0 0 Immune Thickening of few small scattered veins or only presence of leaf enations on one or few leaves of a plant observed after careful observations. 0.1–10 1 Highly resistant

Thickening of small group of veins, no leaf curling, no reduction in leaf size and boll setting. 10.1-20 2 Resistant

Thickening of all veins, minor leaf curling and deformity of internode with minor reduction in leaf size but no reduction in boll setting. 20.1-30 3 Moderately

resistant Severe vein thickening, moderate leaf curling followed by minor deformity of internodes and minor reduction in leaf size and boll setting. 30.1-40 4 Moderately

susceptible Severe vein thickening, moderate leaf curling and deformity of internodes with moderate reduction in leaf size and boll setting followed by moderate stunting. 40.1-50 5 Susceptible

Severe vein thickening, leaf curling, reduction in leaf size, deformed internodes and stunting of the plant with no or few boll setting. >50 6 Highly

susceptible Foliar outgrowths (enation) will be marked with ‘‘E’’ where observed.


To calculate severity index (SI) and per cent disease index (PDI) of the genotype under study, Individual symptomatic plant ratings for each genotype was added and divided by the number of infected plants to calculate the corresponding SI. The PDI was calculated using the following formula:

Percent Disease index= Sum of all disease ratings of the selected plants at random × 100 Total no. of plants assessed. 6

Experiment 3: High Density with Late Cotton Sowing Studies

These studies were carried out to find out suitable lines for high density planting of cotton. For this purpose cotton lines with short sympodia (FH-114 and FH-2015) and intermediate sympodia FH-113 were selected. The cotton was sown after the harvesting of wheat. The trial was sown on June 10, 2004-05. All agronomic practices were carried out as standard except line to line distance was kept 37cm and plant to plant was 12cm. Plant population 43000 and 10,0000/ha was maintained. At maturity, data on seed cotton yield and yield components were recorded. Ginning out turn was calculated after ginning of 50 gm sample of seed cotton and other fibre quality traits like staple length, maturity and fineness was measured.

Experiment 4: Heat Tolerance Studies

For the identification of heat tolerant cotton genotypes the same 24 genotypes which were studied in CLCuV screening experiment were included. The genotypes showed maximum boll retention at highest temperature of the flowering period of cotton was identified as heat tolerant. The experiment was sown on April, 15 in 2003-04 and on April, 12 in 2004-05. The data for boll retention was recorded from June 15 to July 15 each year. These studies were carried out at two locations i.e., Faisalabad and Multan. The data of maximum temperature of experimental sites is given in Table 4. The location of Multan was included in this study as it has the highest temperature in Punjab. Boll retention percentage was calculated by dividing the number of retained boll by total number of flowered fruiting sites.

TABLE 4: MAXIMUM TEMPERATURE FOR THE MONTH OF JUNE AND JULY DURING 2003-04 AND 2004-05

Location Month Temperature (0C) 2003-04 Temperature(0C) 2004-05

Multan June 43.50C 430C July 44.50C 440C

Faisalabad June 41.00C 410C July 42.00C 41.50C


The results of the fertilizer trial in two year study i.e. 2003-04 and 2004-05 indicated highly significant differences (P>0.05) for varieties, fertilizer doses and their interaction. On the basis of first year, FH-113 surpassed all varieties by producing a yield of 2860kg/ha at full dose of fertilizer followed by FH-942, (2770kg/ha) and FH-1000 (2133kg/ha). At half dose of fertilizer FH-113 also produced maximum yield of 2470kg/ha followed by FH-942 (2120kg/ha) and FH-1000 (1880kg/ha). At control, FH-113 produced maximum yield of 1560kg/ha. During second year again FH-113 produced maximum yield of 2903kg/ha at full dose of fertilizer than FH-942 (2685kg/ha) and FH-1000 (2237kg/ha). At half dose FH-113 showed its superiority by producing yield of 2575kg/ha which is significantly higher than the other two varieties. It is evident from the results of both years that the variety FH-113 not only performed well at full dose of fertilizer but also produced highest yield at half dose of fertilizer. Khan et al. (1994) and Latif et al. (1994) were of the view that 100 kg N was the optimum N requirement for cotton under Faisalabad and Sakrand conditions, respectively. But in present studies FH-113 produced promising yield at half dose of fertilizer also. The detailed results of analysis of variance and means of the genotypes at three levels of fertilizer are given in Table 5 and 6.


Results of the screening experiment against CLCuV revealed that three genotypes viz., MNH-609, MNH-886 and MNH-456 showed resistance to CLCuV by showing disease severity of 1.65, 1.69 and 1.74 respectively and disease index of 17.8, 18.7 and 19.3% respectively (Table 7). These genotypes possess Cry1 Ac gene and hence have no attack of boll worms. However, FH-114, FH-941, FH-942 and BH-168 were among moderately susceptibility genotypes as the disease index of these genotypes was below 50%. Remaining seventeen genotypes showed high susceptibility ranging from 58.35 to 80.12%. The strains resistant to CLCuV sometimes again become susceptible due to the emergence of new strains of virus which ultimately results in resistance break down (Mansoor et al., 2003, Akhtar et al., 2002). In Pakistan, previously successful efforts have been made to develop virus resistant varieties resulted in recovery of production that was improved from 8.04 million bales in 1993-94 to 11.17 million bales in 1999-2000, (Anonymous, 2001). In the present studies resistance to CLCuV exhibited by some lines is encouraging though continued efforts are needed to develop resistant germplasm against CLCuV and various new strains of virus.

For high population studies the genotypes with compact structure, FH-114, FH-2015 and intermediate growth habit (FH-113) were evaluated. The morphological (plant height, sympodia per plant, bolls per plant, boll weight, seed cotton yield) and fibre quality traits like ginning out turn%, fibre length, strength and fineness were studied at population densities of 43000 and 10,0000 plants/ha. FH-114 gave a mean plant height of 96.4cm, 12.8 sympodial per plant, 12.0 bolls per plant, 2.6g boll weight and seed cotton yield of 1300kg/ha at plant population of 43000 but at plant population of 10,0000 the yield was 1900kg/ha. The plant height at this density reduced and remained at 88.7cm. However, boll number and number of sympodia almost remained the same but boll weight reduced to 2.4g. Ginning out turn, fibre length, fibre strength and fibre fineness at plant population of 43000 was recorded at 38.0%, 27.7mm, 97.63tppsi and 4.9µg/inch respectively and at plant population of 10,0000/ha these values remained at 37.5%, 27.5mm, 98.0tppsi and 5.1 µg/inch respectively. The intermediate growth habit variety FH-113 produced a yield of 1050kg/ha at 43000 plants per hectare and at 10,0000 plants per hectare it produced a yield of 1600 kg/ha. It attained a plant height of 100.0 cm at 43000 and 93.0cm at 10,0000 plants/ha. Similarly, for boll weight, almost similar values were found at both plant denstities but boll number reduced at 10,0000 plants/ha. In terms of fiber quality traits same pattern of variation existed with little reduction in all the studied traits (Table 7). FH-2015 another compact variety evaluated at both population densities however it was not successful as it produced a very low yield of 700 and 1100 kg/ha at both populations. Its low yield is evident from less sympodia per plant, less boll number and reduced boll weight. In terms of fibre quality traits it is most affected by the environment and showed poor results. Results at both densities showed that FH-114 can be exploited in late sown conditions as it can tolerate CLCuV to greater extent as compared to other genotypes hence produced more yield. The current results are in conformity with the results of Krishna et al., (2009) who proposed that by growing cotton in narrow rows can produce more seed cotton yield than the wider rows.

The same genotypes that were tested for screening against CLCuV also tested for heat stress tolerance. The genotypes namely, MNH-456, FH-114 and MNH-886 showed boll retention percentage of 82.2, 80.4 and 70.9% respectively (Table 8).These genotypes can tolerate the temperature of 400C and can be grown most successful at high temperature regions. The remaining genotypes showed variable range from 29.3% to 75.4% boll retention (Table 8). High temperature results in poor pollen germination and pollen tube growth affecting yield to greater extent. Temperature beyond 450C severely reduces the growth and development of cotton plant (Khan et al., 2005). The results are encouraging as the genotypes like MNH-886, MNH-456 and FH-114 have been developed by keeping in view the improvement in multi-traits. These varieties not only can cover the threat of CLCuV but also can tolerate heat and have good fiber quality traits. The further studies are underway to develop better varieties which can withstand in CLCV conditions and having heat tolerance, good yield and fiber quality.


TABLE 5: MEAN SQUARES FOR SEED COTTON YIELD

Source DF MS (2003-04) MS (2004-05) Reps 3 135503* 42879* Doses 2 3479470 4134993 Error 6 12754 11215 Varieties 2 836480* 996353* Doses x Varieties 4 66963* 18952* Error 18 16120 16031

TABLE 6: YIELD (KG/HA) PERFORMANCE OF VARIETIES AT DIFFERENT DOSES OF FERTILIZER

Fertilizer Doses Control (0-0-0) Half Dose of Fertilizer(57:27:31) Full Dose of Fertilizer (114:54:62) Varieties 2003-04 Variety Mean FH-113 1560 2470 2860 2297 FH-942 1340 2120 2770 2077 FH-1000 1328 1880 2133 1780 Fertilizer doses mean 1409 2157 2588 Varieties 2004-05 Variety Mean FH-113 1644 2575 2903 2374 FH-942 1390 2237 2685 2104 FH-1000 1160 2010 2250 1807 Fertilizer doses mean 1398 2274 2613 LSD(0.05): For fertilizer doses(2003-04)=112.82 LSD(0.05):For fertilizer doses(2004-05) =106.79

LSD (0.05): For varieties (2003-04) =108.90 LSD (0.05): For varieties (2004-05) =106.60

TABLE 7: PER CENT DISEASE INDEX (PDI), SEVERITY INDEX (SI) AND DISEASE REACTION OF VARIOUS GENOTYPES TESTED AT COTTON RESEARCH INSTITUTE, FAISALABAD

Region Genotypes PDI (%) SI Disease Reaction

Faisalabad

FH-113 63.73 3.82 HS FH-114 39.27 2.47 S FH-941 44.84 3.12 S FH-942 48.05 2.88 S FH-1067 80.12 4.81 HS

Sahiwal SLH-284 70.97 4.26 HS SLH-317 76.12 4.57 HS

Bahawalpur

BH-162 58.85 3.53 HS BH-167 62.98 3.78 HS BH-168 49.49 3.06 S BH-197 74.78 4.49 HS

Multan

MNH-93 58.35 3.5 HS MNH-149 67.09 4.02 HS MNH-253 57.55 3.45 HS MNH-456 19.32 1.74 R MNH-609 17.82 1.65 R MNH-700 68.23 4.04 HS MNH-752 75.25 4.51 HS MNH-784 63.9 3.83 HS MNH-787 64.77 3.89 HS MNH-789 63.14 3.79 HS MNH-886 18.67 1.69 R

Vehari VH-144 65.43 3.93 HS VH-278 76.06 4.56 HS

TABLE 8: PERFORMANCE OF VARIETIES AT DIFFERENT PLANT POPULATION FOR VARIOUS MORPHOLOGICAL AND FIBRE TRAITS

Varieties Plant Population

ha-1

Plant Height (cm)

Sympodia Per plant

Bolls Per

Plant

Boll Weight

(g)

Seed Cotton Yield

(kg/ha)

GOT%

Fibre Length (mm)

Fibre Strength (tppsi)

Fibre Fineness (µg/inch)

FH-114 43000 96.4 12.84 12.08 2.61 1200 38.0 27.7 99.6 4.9 10,0000 88.72 11.68 11.48 2.36 1900 37.5 27.5 98.0 5.1

FH-113 43000 100.08 11.04 7 3.32 1050 38.3 28.5 97.3 5.1 100000 93 13 10 3 1600 38 28.0 96.5 5

FH-2015 43000 75.4 7 7 2.10 700 37.0 27.6 94.7 5.2 10,0000 70.4 6 5 1.90 1100 36.3 27.3 94.2 5.4


TABLE 9: BOLL RETENTION PERCENTAGES OF VARIOUS GENOTYPES TESTED FOR HEAT TOLERANCE

Region Genotypes Boll Retention (%)

Faisalabad Region

FH-113 65.0 FH-114 80.4 FH-941 50.0 FH-942 55.2 FH-1067 71.0

Sahiwal SLH-284 67.2 SLH-317 50.0

Bahawalpur

BH-162 54.4 BH-167 62.1 BH-168 54.1 BH-197 42.2

Multan

MNH-93 45.1 MNH-149 31.7 MNH-253 65.0 MNH-456 82.2 MNH-609 40.0 MNH-700 70.0 MNH-752 42.6 MNH-784 29.3 MNH-787 40.9 MNH-789 65.3 MNH-886 70.91

Vehari VH-144 75.4 VH-278 50.4

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Temporal Changes in Metabolically Important Enzymes and Solutes act as Trigger for Epidermal

Cell Conversion to Fibre Initials in Cotton

Gopalakrishnan N.1, A.H. Prakash2 and Y.L. Balachandran3

1Assistant Director General (Commercial Crops), ICAR, New Delhi, India 2Central Institute for Cotton Research, Regional Station, Coimbatore, India

3Department of Biotechnology, Bharathiyar University, Coimbatore, India

Abstract—As one of the longest single-cell seed trichomes, cotton fibres act as an excellent model for unraveling fundamental biological processes such as cell differentiation, cell expansion and cell wall biosynthesis. In order to probe better cotton fibre production through effective fibre development processes, temporal changes in the oxidative enzymes and solute contents were studied in near isogenic lines of linted cotton cv. MCU 5 and its lintless mutant MCU5 LL. The ovules were quantified for Peroxidase (POD), Catalase (CAT), Ascrobate peroxidase (APX) and Superoxide dismutase (SOD) from ten days pre anthesis to six days post anthesis (DPA). The POD activity in MCU 5 was maintained around 0.06 units per /g fresh weight ovules pre anthesis and enhanced to 0.08 at anthesis and further to 0.1 units at 2 DPA and later declined, while in MCU 5LL, the POD activity reduced to 0.01units 3 days prior to anthesis and later increased to 0.04 units at anthesis and further to 0.05 till 6 DPA. The CAT and APX activities were very low in MCU 5 LL ovules all through, while the MCU 5 ovules had higher activities during pre anthesis (around 1.6 units) and 0.8 units post anthesis. The SOD activity shot up to 4.0 units at anthesis and later maintained at 3.0 units during the fibre initiation process, while MCU 5 LL ovules showed a marginal increment in SOD activity. Biochemical analysis of the lintless mutant ovules revealed a marked reduction in the synthesis of reducing sugars, total free amino acids and total soluble protein content, while there was no effect on the proline and phenol content of ovules from 0 to 5 DPA. The RAPD analysis revealed that two primers were found non-polymorphic with two extra bands at 2040±10 bp and 630 ±10 bp in MCU 5. The failure to trigger the production of anti-oxidants and synthesis of solutes at anthesis can be assigned as crucial factors for non-conversion of epidermal cells to fibre initials in lintless mutant and provide enough clues as biochemical determinants for better fibre development process in cotton.

INTRODUCTION

Cotton fibre quality improvement is of vital importance to textile industry. The fiber elongation and secondary deposition of cellulose are highly sensitive to immediate surroundings. Cotton fibres are a subset of single epidermal cells that elongate from the seed coat to produce cellulose strands or lint. As one of the longest single-cell seed trichomes, fibers provide an excellent model for studying fundamental biological processes such as cell differentiation, cell expansion and cell wall biosynthesis. The molecular and metabolic mechanisms associated with differentiation of epidermal cells of ovules to trichomes are still a mystery. In order to enhance the quality attributes of cotton fiber, there is an imperative need to study the regulation of cotton fiber cell expansion, a vital process controlled by genetic, environmental and hormonal factors.

Cotton fiber cells are tubular outgrowth of single celled trichomes which arise in near synchrony from the epidermis of the ovule and may elongate at peak rates in excess of 2 mm per day during the rapid polar expansion phase of development (Basra and Malik, 1984). Developing cotton seeds are an excellent system to study diverse patterns of carbon partitioning including cellulose, starch and oil biosynthesis (Ruan and Chourey, 1998). There has been a substantial progress in our understanding of cellulose synthesis in developing cotton fibers. However, little is known about the early events controlling fibre cell initiation. Morphologically, the initiation of each fiber cell is associated with the spherical expansion and protrusion of one epidermal cell above the ovular surface during anthesis (Basra and Malik, 1984). Genetic variation between plants for a trait controlled by a single or a few genes inherited in a single Mendelian fashion is easy to manipulate through breeding. There has been a number of reliable markers such as protein or, more specifically, allelic variants of several characters such as

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lipid or sugars must be considered (Prakash et al. 2002). Isozyme numbers are limited and their expression is often restricted to a specific developmental stage of tissues; and their presence can be determined by electrophoresis and specific staining.

There are numerous in vitro studies which have thrown light on the basic processes of fiber initiation and the factors that may have a role thereon. Fiber initiation and development are known to be influenced by the age of the ovule (Graves & Stewart, 1988), temperature (Xie et al., 1993), plant growth regulators (DeLonge, 1986) and inorganic nutrients (Eid et al., 1973) in the culture medium. Plant growth regulators like indole-acetic acid, gibberellic acid, ethylene and abscisic acid play a decisive role in fiber development (Prakash et al., 2002; Kosmidou-Dimitropoulou, 1986). In the present study, the metabolic process, biochemical constituents and the RAPD technique were used to study the factors associated in differentiation of ovular epidermal cells into fiber initials using a normal cotton genotype and its lintless mutant, as they provide contrasting genetic material for studying the molecular events specific for fibre development.

The present work aims at investigating the enzymatic changes in the pre and post anthesis period from -10 to + 6 days anthesis and accumulation of biochemicals in post anthesis for + 60 DAA. Furthermore RAPD profile technique was used to study the factors associated in differentiation of ovular epidermal cells into fiber initials using a normal cotton genotype and its lintless mutant, as they provide contrasting genetic material for studying the molecular events specific for fibre development.


Plant Materials

Cotton (Gossypium hirsutum L.) near isogenic lines-MCU 5, and its lintless mutant MCU 5LL were grown under field conditions with optimum agronomic practices at Central Institute for Cotton Research, Regional Station, Coimbatore. The initiated squares were tagged and the ovules were excised at different growth stages. Harvested ovules at various developing stages were frozen in liquid nitrogen till extraction. Developing seeds and fibers were analyzed at regular intervals for reducing sugar (Somogyi, 1952), soluble proteins (Lowry et al., 1951) and total phenols (Bray and Thorpe, 1965). The whole ovules were used for biochemical analysis.

Isolation of Genomic DNA from the Ovules

Fresh ovules (100 mg) were isolated and ground to fine powder with liquid nitrogen and the genomic DNA was extracted following CTAB method (Doyle and Doyle, 1984). The cotton ovules had higher polyphenolic compounds which initially interfered in the yield of the DNA which was later removed by the addition of the PVP- 40 in the extraction buffer which increased the yield and the purity of the DNA obtained (Porebski et al., 1997). Additional precipitation steps with isopropanol helped in removal of protein and polysaccharides (Padmalatha & Prasad., 2006.).

RAPD - PCR Analysis

RAPD analyses were carried out according to Sambrook & Russell (2001). One hundred 10 – mer oligonucleotides (Sigma Aldrich) were selected for initial screening of gene specific sequences. 20 primers were selected for the final RAPD – PCR analysis (Table 1). Amplification reactions were performed in a 20 µl reaction mixture containing 1.5 μl of Taq DNA polymerase (Bangalore Genei, Bangalore), 0.2 mM dNTPs, 2µL of 10X PCR buffer with MgCl2, 0.4 µM of 10-base primer and 50 ng of DNA as the template. Amplifications were performed in a Gradient Mastercycler (Eppendorf, Germany.) by the following program: initial denaturation temperature of 94oC for 5 min; 30 cycles each with denaturing at 94oC for 30s, annealing at 55oC for 30s and extension at 72oC for 1 minute; and final extension at 72oC for 5 min. Reaction products were then loaded on to 1.4% agarose gel for electrophoresis. Gels were documented under UV following EtBr staining with Alpha Imager systems, UK. A negative control, without DNA, was included in all reactions.

Temporal Changes in Metabolically Important Enzymes and Solutes act as Trigger for Epidermal Cell Conversion 45

TABLE 1: LIST OF 10-MER PRIMES USED FOR RAPD ANALYSIS OF 2 DAYS POST ANTHESIS OVULES OF MCU 5 AND MCU 5LL.

S. No. Primer Sequence 1 TGAGGGCCGT 2 TCGTTCACCC 3 CATAGAGCGG 4 CCACCACTTC 5 CCTGTCAGTG 6 GGGGAAGACA 7 GTGTCAGTGG 8 CTGGCTCAGA 9 TGCCACGAGG

10 CTGAAGCGCA 11 AAGACCGGGA 12 CCGAGCAATC 13 TGTGGACTGG 14* GAGAGGCTCC 15* TCCGTGCTGA 16 TGCCTGGACC 17 GGCAGGTTCA 18 CTGGTGCTGA 19 GACAGTCCCT 20 TGGTCGGGTG

ESTIMATION OF ENZYMES

Peroxidase activity (POD) was determined by using the method described by Shannon et al. (1966). The change in absorbance was recorded at 470 nm at an interval of 15 sec for 2 min. The enzyme activity was expressed as units (mg protein)-1. Ascorbate peroxidase (APX) activity was assayed by monitoring the ascorbic acid-dependent reduction of H2O2, as described by Anderson et al. (1992). Ascorbate peroxidase activity was expressed as nmol ascorbate oxidised (mg protein) –1min–1. Catalase activity (CAT) was estimated by the method of Aebi (1984). The absorbance was recorded at 240nm at an interval of 15 sec for 2 minutes immediately after the addition of enzyme extract. The enzyme activity was expressed as mmol H2O2 decomposed (mg protein)–1min–1. The superoxide dismutase (SOD) enzyme activity was assayed by the method of Giannopolitis and Ries (1977). The absorbance was read at 560 nm. One unit of SOD was defined as the level of enzyme activity that inhibited the photoreduction of NBT to blue formazan by 50 % (expressed as units SOD mg protein–1).


The normal phenological boll development in MCU 5 and its lintless mutant has been depicted in (Figure 1A& 1B)). Boll bursting stage shows the clear picture of seeds bearing the lint and lintless. Morphology difference between the bolls at the later stages of anthesis is evident. The difference could be caused due to the elongation of the fibers in the cultivar MCU 5 in the later stages of the days post anthesis.

Fig. 1: Digital Images of the Various Stages of the Bolls from the Cultivar (a) MCU 5 and its Mutant (b) MCU 5LL


To explore the biochemical changes among the two cultivars MCU 5 and its mutant variety MCU 5LL, total soluble proteins and antioxidant enzymes peroxidase (POD), ascorbate peroxidase (APX), catalase (CAT) and superoxide dismutase (SOD) were studied in ovules from 10 days prior anthesis to 6 days after thesis. The analysis was done upto 6 days after anthesis based on the earlier observations made by Hovav et al 2008 and Chaudhary et al 2008, that the oxidant and antioxidant genes are up- or down-regulated early in fiber development, but not later. Highest number of genes were up-regulated in the early stage (2 days after anthesis), where at later stages of fiber development, there were only few such genes (Chaudhary et al 2008).

The total soluble protein concentration was low from -2 days to + 2 days of anthesis in the mutant variety (MCU 5LL), while MCU 5 showed higher levels at – 4, 0 and + 2 days after anthesis and remained low in -2 and + 4 days anthesis (Fig-2). There was significantly lower level of soluble protein content in the ovules at anthesis in the lintless mutant (26.36 mg.g-1FW) as compared to MCU 5 (46.71 mg.g-1FW). With progress in time, the protein content in the mutant seeds increased and by 10 DPA, it was on par with the normal seeds (Gopalakrishnan et al., 2010). Turley and Ferguson (1996) made a comparative analysis of the fls mutant SL 171 against an unrelated FLS inbred using two dimensional PAGE analysis of the total ovular protein. Of the numerous Coomassie blue-stained spots, only five polypeptides are unique to the mutant. Hence, it is difficult to assign any physiological significance to these differences because these proteins are of an unknown nature. Similarly, even though there was a distinct reduction in the protein synthesis in lintless mutant (MCU 5 LL), it is difficult to pin point the type of protein. Hence, the genomic DNA from the ovules was extracted and subjected further for the PCR based RAPD.

Fig. 2: Changes in the Total Soluble Proteins in the Cultivars MCU 5 and MCU 5LL

In our study, PCR based RAPD technique was used with randomly generated synthetic oligonucleotides of 10 bases. The high sensitivity of the method applied to pre-digest DNA permitted the tagging of specific locus for some characters in nearly isogenic lines of cotton (Arshad & Haidar, 2000). RAPD PCR analysis among the MCU 5 and its mutant MCU 5LL was initially done with 100 primers. Majority of the primers failed to amplify in both the genotypes (data not shown) and only 20 primers gave the best banding pattern. The band size ranged from 2800 bp to 100 bp. The amplified products of the primer 3` GAGAGGCTCC 5` gave two additional bands of the size of 2040(± 10) bp and 630 (± 10) bp, while a band sized 1160 (± 10) bp of the primer sequence 3`TCCGTGCTGA 5’ in the MCU 5 which are lacking in the MCU 5LL (Figure – 4a). All the other eighteen primers gave similar banding pattern and 100 % polymorphism among the genotypes (Table - 1).

Though many RAPD studies in cotton are done to find their genetic diversity among the cultivar identification of cotton (Rana & Bhat 2004), there are few studies done to differentiate among the mutants using RAPD. In the present study, a different banding pattern in two of the primers which gave extra bands in linted genotype that were absent in the lintless genotype. From the result, we can infer that these extra bands may have an important role in the fiber initiation and in early fiber elongation process from 0 days to 5 days of the development of the fibers. Compared with the Arabidopsis trichome, little is


known about the molecular control of the cotton fiber development. So far, a number of genes differentially expressed during different stages of fiber development have been identified, but their roles in cotton development are not yet clear (Hu¨lskamp et al., (1994). Ji et al (2003) studied on the genes which preferably expressed during the early fiber development through cDNA microarray analysis of 0 to 10 DPA ovules, which showed that 172 genes were significantly up-regulated during the course and are involved in energy metabolism, cell turgor generation and primary and secondary wall biogenesis, which again showed that turgor pressure is crucial for fibre initiation.

The relationship between the fiber initiation and antioxidant response was studied in ovules from -10 days pre anthesis to + 6 days post anthesis. The highest activity was observed in the -4 and +2 days anthesis ovules and the lowest with -2 days anthesis ovules Fig-3a). Lintless mutant shows low level of peroxidase than that of the MCU 5. Maximum decrease in the peroxidase content -2 days anthesis was seen and recovering in 0 and 2 days to slightly higher levels. Similar pattern of ascorbate peroxidase activity as such as POD was noticed with MCU 5 (Figure 3b). Increase levels in APX enzymes in days -4 and + 2 days anthesis, with minimal level of APX in days -2 and 0 days anthesis was seen. To the contrary, lintless mutant showed higher level of APX in days -2 and 0 anthesis, while rest of the ovule stages displayed somewhat similar levels with not much different changes (Figure 3b). Mutant variety MCU 5LL showed a low level CAT activity at -10 days anthesis and later increased till 0 days anthesis (Figure 3c). There was a decline in the activity in +2 and +4 days of anthesis and normalized by +6 days post anthesis. The CAT activity in MCU 5 showed slight increase during 0 to +2 post anthesis. The mutant MCU 5LL showed decreased antioxidant enzymes activity during the fiber initial process. Most of the enzymes maintained low activity after anthesis, while MCU 5 showed higher enzyme activity during anthesis. The increase of antioxidant activity could be due to the increase in the production H2O2 level. The increase of H2O2 levels has been shown to enhance antioxidant content and antioxidant enzymes in many plants (Mitler and Tel-Or, 1992 and Lechno et al 1997). Low levels of H2O2 stimulate expression of necessary genes for the onset of secondary wall cellulose biosynthesis. The elevated levels of the H2O2 would result in the accumulation of H2O2- dependent reaction products which could trigger the programmed cell death response, eventually this could trigger the activation of a cell-death process, which for the cotton fiber cells constitutes a form of terminal differentiation (Potikha et al 1999). The role of APX in regulation of intracellular ROS levels by reduction of H2O2 to water using ascorbate as an electron donor and multiple fold increases in the cotton APX genes was seen till + 5 days anthesis., The increase in the expression of genes corresponding to POD and APX in + 2 days post anthesis which are associated with ROS metabolism has also been reported (Chaudhary et al 2009). These reports are in concurrence to our results, where the highest peroxidase and ascrobate activity was seen in + 2 days anthesis ovules in MUC 5. Lower levels of these antioxidant enzymes may result in the higher level of the H2O2 in the ovules resulting in destruction of the cells that trigger fiber initiation and elongation process.

Fig. 3: Differential Antioxidant Enzyme Activity in Different Ovular Stages form -10 Days Pre Anthesis to + 6 Days Post Anthesis from of MCU 5 and MCI 5LL Mutant. (a) POD, (b) APX, (c) CAT, and (d) SOD. Values are the Means of Three sets of Observations


Fig. 4: (a) 0.8% Agarose Gel Picture of Genomic DNA of + 2 Days Post Anthesis Ovules of lint (Lane 2 -L) and its lintless (Lane 3-LL) mutant. The lane 1 M Corresponds to the Size Marker DNA (ECorI / Hind III Double Digested). (b) The RAPD Profile of MCU 5( L) and its Mutant MCU 5LL(LL). The White Arrow

Mark Indicated the Extra Band. 10kbp (Lane 1) and 1kbp(Lane 2) Marker DNA are used as the Ladder

Biochemical accumulation of reducing sugars, total free amino acids, proline and total phenols in ovules from 0 days anthesis to boll bust was studied in MCU 5 and its lintless mutant 5LL and similar biochemical compounds were studied in fibers from day anthesis to boll bust in MCU 5. Characteristic accumulation of reducing sugars (Fig 5a) and total free amino acids (Fig 5b)was noticed in developing seeds of lintless mutant as compared to linted MCU 5. It has been reported that of larger amount of sugar molecules is synthesied during secondary wall formation (Fukuda, 1991, 1996). The secondary wall of developing cotton fiber consists of nearly pure cellulose and is devoid of hemicellulose and lignin (Basra and Malik, 1984; Ryser, 1985). Rates of cellulose synthesis increase was reported to occur abruptly to about 100-fold at around 24 days post anthesis of secondary wall formation (Meinert and Delmer, 1977). Furthermore, development occurs synchronously for nearly all fibers within a boll, with the transition to secondary wall formation beginning abruptly in varieties of cotton at about 14 to 16 DPA, which is a few days prior to the cessation of fiber elongation (Meinert and Delmer, 1977). The higher activity in day 25 of ovules and day 15 for fibers of MCU 5 observed in our study is consistent with the above literature reports. Proline in lintless mutant showed elevated levels in 30 post anthesis. It is reported that the proline-rich proteins accumulate in later stages during active secondary cell wall formation, indicating possible regulation at the translational level and function in the secondary cell wall assembly. The proline content (Fig 5c) was high and ranged around 55 to 65 mg.g-1 till 15 DAA and there after lesser accumulation was observed in both fibre (0.5-2.0 mg.g-1) and ovules (20-50 mg.g-1).

Fig. 5: Measurement of Biochemical Constituents during 0- 60 Days Post Anthesis in Ovules of MCU 5 and MCU 5LL. Changes in Bio-constituents (a)

Reducing Sugars, (b) Total Free Amino Acids, (c) Proline, and (d) Total Phenols in Ovules


CONCLUSION

The process of modification of epidermal cells to fibre initials starts 4-6 days before anthesis that has been clearly shown by the up and down regulation of biochemical constituents as observed in MCU 5 and its mutant (MUC 5 LL). The final trigger is provided at anthesis where the solutes help in fibre initiation and elongation processes accounting for the involvement of multiple components. The failure to trigger the production of anti-oxidants and synthesis of solutes at anthesis can be assigned as crucial factors for non-conversion of epidermal cells to fibre initials in lintless mutant and provide enough clues as biochemical determinants for better fibre development process in cotton.

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Study of Interspecific Hybrids (Gossypium hirsutum x G. barbadense) for Heterosis and Combining Ability

K.P.M. Dhamayanthi

Central Institute for Cotton Research, Regional Station, Coimbatore-641 003, India

Abstract—Forty nine inter-specific F1 combinations were made using two tetraploid cotton species Gossypium hirsutum and G. barbadense. Observations on seed cotton yield, its component traits and ginning per cent were recorded on parental lines and F1 hybrids during the year 2007-08 and 2008-09. Among the females BRS-53-53 was found to be good general combiner for boll per plant and seed cotton yield. Amongst the male parents, ICB-260 and Pima S4 were found to be the best general combiner on the basis of seed cotton yield and it’s per se performance, however B-4 was the best for the majority of the yield components. Five crosses were identified as the best crosses on the basis of per se performance, combining ability and heterosis. High heterotic crosses viz., which have shown more than 40% heterosis for seed cotton yield and its component traits could be exploited for increasing yield in inter-specific cotton hybrids.

INTRODUCTION

Cotton the king of fibre is a premier cash crop of our country grown in about 9 million hectares, which represent 29 per cent of the world cotton area. India is a pioneer country for the cultivation of cotton hybrids on commercial scale. Exploiting heterosis is one of the methods to increase cotton yields that have stagnated in recent years. It has the potential of increasing yield from 10 to 20% and of making improvements in fibre properties. Increased yield and fibre qualities are vital to keep Indian cotton competitive with synthetics and foreign production. In India, 40% of cotton production is derived from intra-specific hybrids of G. hirsutum, and 8% of its production is from G. hirsutum x G. barbadense hybrids (Singh and Chaudhry, 1997). Yield increase of hybrids over the better parent or best commercial cultivar (useful heterosis) has been documented earlier showed an average useful heterosis of 21.4% for F1 hybrids (Singh et al., 2003). In recent years, breeding progress for increased yield has greatly decreased. Research on plant breeding needs to address all possibilities to increase yield, including the use of heterosis. In hybrid development programme, improving the qualitative and quantitative characters are possible by better commercial exploitation of hybrid vigour (Rajamani et al., 2009). The concept of combining ability is important in designing the plant breeding programmes. It is highly useful to study and compare the performance of lines in hybrid combinations. Information concerning to different types of gene action, relative magnitude of genetic variance and combining ability estimates are significant markers to shape the genetic make up of a crop like cotton. This important information could prove an essential strategy to the cotton breeders in screening of better parental combinations for further enhancement. Cotton breeders have the challenge of finding good combiners by the use of heterosis.

In cotton, high heterosis has been reported at inter-specific and intra-specific levels both in diploid and tetraploid cotton (Singh and Kalsey, 1983). In recent past, there are hundreds of long and medium staple hybrids being cultivated in South and Central zone. But in extra long staple category, hybrids are very limited and the current production of extra long staple cotton is not sufficient to meet the domestic textile requirement of our country. There is a need to develop suitable high yielding extra long staple hybrids with desirable fibre qualities to cater the need of the Indian Textile Industry. Hence, in the course of developing extra long staple inter-specific hybrids, an attempt was made to find out the extent of heterosis for seed cotton yield and its components in 49 inter-specific F1 hybrids obtained from seven diversified G. hirsutum female parent and seven elite male genotypes of G. barbadense.


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Seven diversified female genotypes of Gossypium hirsutum viz. BRS-53-53, CCH-510-4, CCH-724, CCH-4, TK-36, ENT- 4, LK-18, and seven male genotypes of G. barbadense viz. B-4, B-5, ICB-20, ICB-74, ICB-201, ICB-260 and Pima S-4 were identified for better fibre properties to generate 49 hybrids in a line x tester mating design along with 14 parents and a check hybrid DCH-32 in a randomized block design with three replications. Two rows of each parents and crosses were sown at a spacing of 90 cm between rows and 60 cm between plants during August 2006. Ten plants were chosen from two rows of each genotype to record data on seed cotton yield (g), plant height(cm), number of monopodia/plant, number of sympodia/plant, boll weight (g), number of bolls/plant, ginning outturn, 2.5 percent span length (mm), fibre strength (g/tex) and fibre fineness (µ/inch). Heterobeltiosis over better parent and standard heterosis over check DCH-32 were calculated by the following formula;

Heterobeltiosis over BP = (F1-BP/BP) x 100; Standard heterosis = (F1-SH/SH) x 100 Where F1 = Mean value of the F1; BP = Mean value of the better parent of the particular cross SH= Mean value over replication of standard hybrids


The analysis of variance showed highly significant differences among the progenies, hybrids and parents (Table 1). The partioning of hybrid mean square indicated that the variance due to males and females and an interaction of males x females was significant for all the characters indicating the manifestation of parental genetic variability in their crosses. Mean, range, coefficient of variation for important ten characters were studied and presented in Table 2. The maximum variability of 16.38 % was recorded for seed cotton yield followed by 14.31% of sympodial branches/plant. The coefficient of variability for the plant height was 12.34 %.

TABLE 1: ANALYSIS OF VARIANCE FOR DIFFERENT CHARACTERS IN INTER-SPECIFIC HYBRIDS (GOSSYPIUM HIRSUTUM L X G. BARBADENSE L )

Source of variation d.f. Pt. Height Boll wt. Bolls/pt. Seed Cotton Yield/pt. GOT % Replication 2 4.24 0.01 3.17 27.18 0.51 Progenies 62 507.60** 17.08** 78.20** 168.19** 5.33** Hybrids 48 148.26** 9.27** 82.64** 132.60** 5.27** Parents vs hybrids 1 7218.03** 173.91** 293.91** 55.18** 3.81** Lines -females 6 178.63** 147.67** 133.62** 147.27** 1.97** Tests-male 6 619.34** 28.33 255.13** 543.07** 87.41** Line x Testers 36 86.29** 162.13** 33.41 97.32** 22.69** Errors 124 18.29 0.43 11.64 27.56 0.33

*significant at 0.01 level of probabilty

The coefficient of variation among the qualitative characters, ginning outturn, bundle strength and micronaire value expressed the least value of 2.67, 2.46 and 1.55 respectively. Highest percentage of heterosis (91.35%) over best parent was recorded in number of bolls/plant followed by seed cotton yield (73.61%) and number of monopods/plant (73.33%).

TABLE 2: MEAN, RANGE, COEFFICIENT OF VARIATION AND HETEROSIS FOR VARIOUS CHARACTERS OF INTER-SPECIFIC HYBRIDS (G. HIRSUTUM X G. BARBADENSE)

Characters Mean ± SE CV Range Heterosis Over Best Parent Seed cotton yield (kg/ha) 984.54 ± 127.42 16.38 719-2435 73.61 Plant height (cm) 119.01 ± 13.56 12.34 110-17-124.60 16.31 Monopods/plant 3.33 ± 0.49 9.60 1.30-6.00 73.33 Sympods /plant 9.41 ± 1.65 14.31 5.13-15.3 31.27 Boll wt. (g) 3.86 ± 0.12 8.32 3.5-5.61 23.81 Bolls/plant 57.66 ± 2.53 9.16 41.24-77.20 91.35 Ginning outturn (%) 30.07 ± 1.03 2.67 28.14-36.01 7.26 2.5% span length (mm) 35.24 ± 0.08 3.5 2 34.23-37.20 4.11 Strength (g/tex) 30.05 ± 0.23 2.46 27.34-33.01 -24.05 Micronaire (µ/inch) 3.62 ± 0.03 1.55 3.05-4.1 35.37

Study of Interspecific Hybrids (Gossypium hirsutum x G. barbadense) for Heterosis and Combining Ability 53

The per se performance and heterosis over best parent (standard heterosis) for the character under study is presented in Table 3. The range and mean value among the inter-specific crosses for seed cotton yield varied from 791-2435 kg/ha. The highest and the lowest seed cotton yield was recorded in the cross combinations of BRS-53-53 x ICB-260 and LK-8 x B-5 respectively. The hybrid combination CCH-510-4 x B-4 ranked second in seed cotton yield with 2418 kg/ha, followed by BRS 53-53 x B-4 (2360 kg/ha), CCH-724 x B-4 (2313 kg/ha), BRS-53-53 x Pima S4 (2286 kg/ha) and CCH-510-4 x ICB-260 (2207 kg/ha). The crosses namely BRS-53-53 x ICB-260 and BRS-53-53 x Pima-S4 exhibited the highest value for 2.5% span length of 37.3 mm and 37.1 mm respectively. The crosses CCH-510-4 x Pima S-4 (36.8 mm) and CCH-510-4 x B-4 (36.7 mm) also had better 2.5 % span length followed by CCH-724 x B-5 and CCH-4 x ICB-74 each with 36.5 mm length. Maximum number of bolls was recorded in BRS-53-53 x ICB-260 (77.2) followed by CCH-510-4 x B-4 (73.4). The crosses BRS-53-53 x Pima- S4 and CCH-724 x B-5 recorded the maximum boll weight of 5.6g and 5.1 g respectively. Regarding ginning percentage, the hybrid CCH-510-4 x B-5 had the maximum ginning outturn of 35.1 % followed by BRS-53-53 x B-4 (34.5%). The maximum fibre fineness of 4.1µ/inch was recorded in the crosses BRS-53-53 x ICB-260 and CCH-510-4 x Pima S-4 followed by CCH-510-4 x ICB-260, CCH-724 x ICB-20 and ENT-4 x B-5 each with 4.0 µ/inch.

TABLE 3: PER SE PERFORMANCE OF 49 INTER-SPECIFIC (H X B) HYBRIDS FOR SEED COTTON YIELD AND ITS QUALITATIVE CHARACTERS

S. No

Crosses SCY (kg/ha)

Plant ht (cm)

Sympod/ plant

Bolls/ plant

Boll wt (g)

GOT (%)

2.5% S.L (mm)

B.S/ (g/tex)

Mic µ/inch

1 BRS-53-53 x B-4 2360** 121.6 15.3 73.4 4.2 34.5 35.1 30.3 3.7 2 BRS-53-53 x B-5 1982 118.3 13.5 61.8 3.9 30.6 32.7 27.1 3.3 3 BRS-53-53 x ICB-20 1908 116.3 11.9 49.1 3.4 28.3 33 26.9 3.4 4 BRS-53-53 x ICB-74 1893 118.6 13.2 51.3 3.4 27.8 33.2 28.4 3.4 5 BRS-53-53 x ICB-201 1988 119.2 14.3 55.4 3.7 28.1 32.6 26.8 3.6 6 BRS-53-53 x ICB-260 2435** 123.2 13.1 77.2 4.6 33 37.3 31 4.1 7 BRS-53-53 x Pima-S4 2286* 120.4 10.5 69 5.6 33.4 37.1 31 3.6 8 CCH-510-4 x B-4 2418** 124.6 11.4 61.1 4.3 35.1 36.7 30.2 3.6 9 CCH-510-4 x B-5 1965 121.5 13.4 56.7 3.9 30.8 35.1 32.7 3.6 10 CCH-510-4 x ICB-20 2093* 115.9 11.4 63.4 4.1 35.3 35.6 29.6 3.4 11 CCH-510-4 x ICB-74 1901 117.1 13.3 54.2 3.5 29.1 34.2 26.4 3.9 12 CCH-510-4 x ICB-201 1989 114.3 13.7 51.6 3.6 27.5 32.5 28.9 3.5 13 CCH-510-4 x ICB-260 2207** 119.3 13.4 67.2 4.3 34.1 36.4 29.8 4.0 14 CCH-510-4 x Pima -S4 2198* 123.1 10.6 68.1 4.8 34 36.8 33 4.1 15 CCH-724 x B-4 2313** 110.3 11 37.8 3.6 32.5 35.4 28.6 3.8 16 CCH-724 x B-5 1919 118.2 11.2 70.1 5.1 35.2 36.5 30.4 3.5 17 CCH-724 x ICB-20 2010 116.3 12.1 55 4.1 33.4 33.6 27.4 4.0 18 CCH-724 x ICB-74 2096* 119.3 9.8 59.4 4.2 29.1 35.3 30.2 3.6 19 CCH-724 x ICB-201 1976 120.1 11.3 46.5 3.5 28.1 34.6 28.7 3.9 20 CCH-724 x ICB-260 2031* 118.3 9.9 39.7 3.8 29.2 35.4 30.3 3.4 21 CCH-724 x Pima S-4 1977 113.5 10.5 44.6 3.7 30.2 36.5 29.6 3.6 22 CCH-4 x B-4 2002* 112.3 10.5 55.8 4.0 30.3 35.2 31.1 3.6 23 CCH-4 x B-5 1956 116.4 11.2 61.3 3.7 27.8 36.2 28.4 3.3 24 CCH-4 x ICB-20 1999 115.9 9.7 51.7 3.6 29.1 35.7 26.5 3.6 25 CCH- 4 x ICB-74 1866 117.3 11.3 53.7 3.5 28.5 36.5 30.1 3.3 26 CCH- 4 x ICB-201 1885 113.5 12.4 55.7 3.6 28.9 35.2 27.6 3.6 27 CCH- 4 x ICB-260 1961 122.2 14.2 59.6 4.2 31.1 34.9 30.8 4.2 28 CCH- 4 x Pima S-4 2001* 111.3 10.8 51.5 4.0 28.2 35.6 28.4 3.9 29 TK-36 x B-4 2100* 115.2 8.9 48.6 3.6 30.2 34 29.4 3.8 30 TK-36 x B-5 1804 112.6 11.5 59.3 3.5 29.4 36.1 28.5 3.9 31 TK-36 x ICB-20 1965 110.4 10.4 54.8 3.4 27.8 35.3 27.4 3.3 32 TK-36 x ICB-74 2033* 112.6 13.7 58.4 3.4 27.1 34.8 26.7 3.2 33 TK-36 x ICB-201 1968 99.8 12.1 42.8 3.5 26.6 35.1 29.2 3.7 34 TK-36 x ICB-260 2042* 116.3 13.8 64.1 3.7 28.3 36.1 28.6 3.4 35 TK-36 x Pima S-4 1956 120.7 11.3 46.1 4.3 32.0 35.5 30.1 3.6 36 ENT -4 x B-4 2004* 118.2 13.2 56.4 4.0 30.3 36.5 29.5 3.7

Table 3 (Contd.)…


…Table 3 Contd. 37 ENT -4 x B-5 1993 115.6 12.8 61.3 4.3 28.6 36.7 28.4 4.0 38 ENT -4 x ICB-20 1923 101.3 9.6 55 3.9 27.3 34.2 26.8 3.6 39 ENT -4 x ICB-74 1996 99.8 10.3 56.7 3.8 28.4 35.1 28.3 3.9 40 ENT -4 x ICB-201 1919 110.5 11.6 51.3 3.6 26.8 35.4 26.5 3.5 41 ENT -4 x ICB-260 2090* 113.8 10.5 62.5 4.1 32.4 36.6 28.9 3.7 42 ENT -4 x Pima -S4 1991 110.2 11.1 54.5 3.5 28.1 35.2 27.6 3.6 43 LK-18 x B-4 1955 111.5 10.4 55.3 3.6 27.6 36.4 29.1 3.6 44 LK-18 x B-5 1791 103.5 13.1 58.1 3.9 29.4 35.6 27.6 3.8 45 LK-18 x ICB-20 1907 99.6 10.4 49.3 3.4 28.5 36.7 26.5 3.5 46 LK-18 x ICB-74 1900 110.4 9.9 44.5 3.6 28.6 35.6 28.4 3.7 47 LK-18 x ICB-201 1888 108.5 11 51.7 4.1 29.5 34.5 28.8 3.6 48 LK-18 x ICB-260 1918 110.2 10.6 52.4 3.8 28.7 35.4 27.9 3.5 49 LK-18 x Pima-S4 1882 101.5 9.9 48.2 4.1 29.3 35.7 28.3 3.6 50 DCH-32 (c) 1618 102.4 11.7 41.9 4.1 30.2 36.1 28.6 3.7 CD @ 5% 197.01 32.13 1.68 4.3 0.4 0.78 0.81 0.17 0.34 The partitioning of hybrid mean sum of square indicated that the variance due to male and female

interaction was significant for all the characters. The parents possessed high per se performance coupled with good gca to be selected for crossing programme. The estimate of parents over the best hybrids revealed that among the male parents, ICB-260 and Pima S-4 were found to be the best general combiners on the basis of seed cotton yield. B-4 was the other male parent having good general combining ability effects for the seed cotton yield (Table 4). The heterosis for number of bolls/plant was found in positive direction for 6 cross combination out of 49 crosses. The maximum heterosis for number of bolls/plant was observed in crosses BRS-53-53 x Pima-S-4 (89.26%) followed by BRS-53-53 x B-4 (49.53%). Rajamani et al., (2009) reported high heterosis for bolls/plant in intra hirsutum hybrids. The heterosis for number of sympodia /plant is in positive direction for cross BRS-53-53 x ICB-260 (19.41 %). The heterosis for ginning out turn is in positive direction in 5 cross combinations out of 49 crosses. Tuteja et al., (2006) and Verma et al. (2006) reported high heterosis for ginning outturn in G. hirsutum. The maximum heterosis for ginning percentage was observed in CCH-510-4 x B-4 (26.14%). The heterosis for boll weight was found in positive direction in 4 combinations out of 49 crosses.

TABLE 4: ESTIMATES OF HETEROSIS OVER BEST PARENT OF 17 PROMISING INTER-SPECIFIC HYBRIDS (H X B) FOR DIFFERENT CHARACTERS

S. No.

Crosses SCY kg/ha

Pt. ht (cm)

Monopod/Plant

Sympod/Plant

Bolls/ Plant

Boll Wt. (g)

GOT (%)

2.5% SL

(mm)

B.S g/tex

Mic µ/inch

1 BRS-53-53x ICB-260 73.64** -9.58 53.24* 19.41* 33.25* 19.08** -3.61 9.79* -16.51 -8.33 2 CCH-510-4xB-4 61.22** -8.56 -52.67 -14.22 7.91 7.31 26.14* 3.19* -13.24 -11.253 BRS-53-53xB-4 54.31** -21.62 24.65** 22.55** 49.53* 6.07 -1.83 -4.52 -5.34 33.67 4 CCH-724 x B-4 48.42** -18.13 -29.38 -16.4 -32.61 24.34* 6.4 -4.08 -13.11 -17.665 BRS-53-53xPima-S4 37.23** -20.34 48.27** 1.82 89.26* 14.16* -0.97 15.56** -9.17 -15.626 CCH-510-4xICB-260 32.56** -2.67 -36.19 -3.34 50.22* -10.25 6.18* 7.63* -18.13 -12.617 CCH-510-4xPima-S4 27.41** 9.03 -19.26 -39.41 -28.34 -5.06 -1.39 -5.18 -17.91 -8.27 8 TK-36xB-4 25.60* -21.3 -91.34 -2.11 16.25* 18.12* 0.09 -2.69 -8.24 -10.0 9 CCH-724xICB-74 21.30* -18.24 -47.37 25.37** 3.84 -6.01 16.2* 6.64* -15.81 -3.21 10 CCH-510-4xICB-20 19.04* -16.71 -26.11 2.33 6.59 -11.16 -1.82 -1.08 -15.88 -15.2 11 ENT-4xICB-260 14.56* -22.15 -6.44 -16.74 22.41* 1.02 -1.76 -7.07 -15.09 -33.4 12 TK-36xICB-260 11.34* -7.46 -81.27 -19.54 -5.06 2.16 5.64* 16.03** 3.16* -12.7 13 TK-36xICB-74 8.29* -17.59 -61.48 22.15* -18.54 -7.71 -2.57 -4.1 -10.19 -15.2314 CCH-724xICB-260 3.66* -4.57 -14.2 -51.6 -6.51 3.05 -21.5 -2.5 -18.31 -16.4315 ENT-4xB-4 2.58* -16.5 -36.19 -23.18 -36.41 11.01 24.21* 1.08 -23.14 -3.87 16 CCH-4x B-4 2.07* 6.31 -26.28 -26.71 3.44 1.35 -1.04 -3.62 -13.34 -1.07 17 CCH-4xPima S-4 1.94* -2.25 -16.33 -43.62 -42.11 1.08 0.16 -1.07 -11.28 -8.34 SE + 46.37 12.38 0.53 0.94 1.82 0.28 0.51 0.63 0.36 0.09 CD@5% 78.59 23.59 0.79 1.83 4.07 0.57 0.94 0.91 0.78 0.16 CD@1% 112.14 31.17 1.08 2.67 7.08 0.79 1.31 2.15 0.81 0.19

Study of Interspecific Hybrids (Gossypium hirsutum x G. barbadense) for Heterosis and Combining Ability 55

The maximum heterosis for boll weight was observed in cross CCH-724 x B-4 (24.34%). The result indicated that there is ample scope for developing productive inter-specific hybrids with desirable cross combinations for seed cotton yield and its components characters having superior fibre quality traits. Tuteja et al., (2006) and Verma et al., (2006) and Gaurav Khosla et al., (2007) reported similar findings in intra hirsutum hybrids. The high mean values were associated with high gca effects. However, it was not in all the cases hence, the choice of parents for crossing should be based on traits that have consistent and significant gca effects. Similar observation was made by Patel et al., (2009) and Pathak and Parkash Kumar (2011) in G. hirsutum. The plant height, bundle strength and micronaire showed no desired heterosis effect in 49 cross combinations. The potential female parents i.e. BRS-53-53 and CCH-510-4 were isolated as the general combiners for seed cotton yield, number of sympodia, no. of bolls/plant and thus indicated that it could be exploited for further hybridization programme. The estimate of sca effect revealed that out of 49 crosses, 17 crosses had significant positive sca effect for seed cotton yield. The crosses BRS-53-53 x ICB-260 and CCH-510-4 x B-4 were identified as the best cross combination for sca, number of bolls /plant, 2.5 % span length, bundle strength and micronaire. Five promising hybrids viz. BRS-53-53 x ICB-260, CCH-510-4 x Pima-S-4 were identified on the basis of per se performance, combining ability and heterosis. High heterotic crosses which have shown more than 40% heterosis for seed cotton yield and its component traits could be exploited for increasing yield in inter-specific cotton hybrids. The present study indicated that there is tremendous scope for heterosis breeding for commercial exploitation and also manifestation of considerable amount of heterosis for improving productive inter-specific extra long staple cotton hybrids with desirable fibre qualities.

REFERENCES [1] Gaurav Khosla, Gill, B.S. and Sohu. R. S. (2007). Heterosis and combining ability analysis for plant and seed characters in

upland cotton (Gossypium hirsutum, L). J. Cotton Res. Dev. 21:12-15. [2] Pathak. R. S. and Prakash Kumar (2011). A study of heterosis in upland cotton (Gossypium hirsutum L.) Theoretical and

Applied Genetics. 47: 45-49. [3] Patel, K.G, Patel, Rita B., Patel, Madhu I. and Kumar, V.( 2009). Studies on heterosis and combining ability through

introgression in diploid cotton. J. Cotton Res. Dev. 23:23-26. [4] Rajamani, S., Mallikarjuna Rao, CH and Krishna Naik, R. (2009). Heterosis for yield and fibre properties in upland cotton

Gossypium hirsutum, L. J. Cotton Res. Dev. 23(1): 43-45. [5] Singh, R.K. and Chaudhry, (1997). Biometrical methods in quantitative genetic analysis (Revised ed.1979). Kalyani

Publisher, New Delhi, pp.191-200. [6] Singh, P., Loknathan, T. R., and Agarwal, D. K. (2003). Heterosis for fibre properties in intra-hirsutum crosses (Gossypium

hirsutum L.) Indian J. Genet. 63 (4): 325-27. [7] Singh, P and Kalsey, H.S. (1983). Heterosis in G.hirsutum, L. Indian J. agric. Sci. 53: 624-28. [8] Tuteja, O.P., Sunil Kumar, Singh. Mahendar and Luthra Puneet (2006). Heterosis for seed cotton yield and fibre quality

characters in cotton (Gossypium hirsutum, L). J. Cotton Res. Dev. 20: 48-50. [9] Verma, S. K., Tuteja, O.P, Sunil Kumar Ram Prakash, Ram Niwas and Monga, D. (2006). Heterosis for seed cotton yield

and its qualitative characters of Gossypium hirsutum L. in cotton. J. Cotton Res. Dev. 20: 14-17.

Predicting F1 Performance from Their Parental Charectaristics in Upland Cotton

(Gossypium hirsutum L.)

R.K. Gumber, Pankaj Rathore and J.S. Gill

Punjab Agricultural University Regional Station, Faridkot-151203, India

Abstract—Attempts were made to find out whether various characteristics of parental lines viz., the genetic distance between parents determined from Amplified Fragment Length Polymorphism (AFLP) data, means of two parents ( P ) i.e. (P1+P2)/2, and absolute difference between the means of two parents (| P1 - P2 |) can be used to predict the per se performance and economic heterosis of F1 hybrids. The line PIL43 with okra leaves was most diverse from other lines. It was found that genetic distance estimated from AFLP markers was not necessarily associated with geographical diversity of the parents. The genetic distance was comparatively high between those parental lines that differ largely for morphological characters. Genetic distance among parents determined from AFLP data proved to be a good predictor of per se performance and economic heterosis of hybrids for seed cotton yield and boll weight. The means of the parents were a good predictor for seed cotton yield and boll number. Significant association of absolute difference between means of the two parents with per se performance and heterosis of F1 hybrids was observed for seed cotton yield, ginning out turn and seed index, suggesting that (| P1 - P2 |) is a good predictor for these traits.

INTRODUCTION In India, for the first time in the world, two hybrids viz., Hybrid 4 (Patel 1971) and Varalaxmi (Katarki 1972) were released in Gujarat and Karnataka states, respectively. Thereafter many hybrids have been released for commercial cultivation in the country. As a result, the cotton production in India increased from 2.79 million bales (1 bale = 170 Kg lint) in 1947-48 to 295 million bales in 2009-10 (Anonymous 2010). With the development and cultivation of cotton hybrids, India has become cotton surplus state. In India, hybrid cotton occupies about 80% of the total cotton area and contributes about 90% to national annual production. Development of hybrid varieties is considered to be the quickest breeding method for exploiting the heterosis to improve yield potential of crop plants (Nassimi et al., 2006; Radoev et al., 2008 and Rameeh 2011). Genetic diversity between parents is important for hybrid breeding and for maximum usefulness of a cross in pure line breeding. Generally it is assumed that crosses among genetically diverse parents produce superior hybrids and progenies in the segregating generations (Rameeh 2011). However, wide crosses suffer from poor adaptation in the target environment and recombination losses owing to disruption of favourable epistatic gene combinations ( Schill et al., 1998). Therefore, selection of suitable parents is one of the most important criteria used to allocate resources to the most promising crosses and to increase the efficiency of breeding program. The identification of promising F1 crosses and superior segregants requires the development of a large number of crosses and their multi-location field evaluation which is very laborious and resource demanding (Melchinger et al 1998). On prediction of test cross variance in maize, Melchinger et al., 1998) reported that the efficiency of a breeding program may be enhanced if the breeding potential of F1 crosses could be predicted in advance. Molecular markers play an important role in crop improvement program and have been used extensively to predict heterosis and F1 performance (Gutirrez et al., 2002 and Selvaraj et al., 2010). The usefulness of molecular genetic distance as a predictor of hybrid performance has been studied in several crops. Genetic distance estimated using different molecular markers was found to have significant associations with hybrid performance in maize (Lee et al., 1989; Smith et al., 1990; and Lanza et al., 1997) and sunflower (Cheres et al., 2000). However, the association between marker based parental genetic distance and hybrid performance has not been well documented in cotton. Therefore, the present study was conducted to predict the mean performance and economic heterosis of F1 hybrids from genetic distances based on molecular markers, means of the parents ( P ), and the absolute difference between means of the parents (| P1 - P2 |).

9

Predicting F1 Performance from Their Parental Charectaristics in Upland Cotton (Gossypium hirsutum L.) 57


Field Experiment

In the present study, 16 F1 crosses involving 11 diverse parents were evaluated in a randomized complete block design with three replications at Punjab Agricultural University, Regional Station, Abohar in 2007. Out of 11 parental lines, nine parents were either approved cultivars or improved lines under cultivation in different states of India. The parental lines LH 1556, F 1861, F 505, F 846 and LH 900 were the approved cultivars of American cotton and have been recommended for commercial cultivation in Punjab state. LH 900 is an early maturing variety having short and compact plant type suitable for late sown conditions. The parental lines PIL 43 and PIL 8 were the female and male parents, respectively of approved cotton leaf curl disease resistant hybrid LH 144 (Gill et al., 2008). Likewise, RS2013 is an approved cultivar from Rajasthan state and has medium size round bolls. GSH 4 is a sympodial cultivar from Gujarat state, while HS 253 is an advanced line from Haryana. The cultivar Udangsuper is a jassid susceptible non-descript variety having short stature plant and medium size bolls. The approved hybrid LHH 144 and open- pollinated cultivar LH 1556 were included as standard checks. Each test hybrid was accommodated in two rows plot of 8 m length. Rows were kept apart at 67.5 cm while plant-to-plant spacing was maintained at 75 cm for hybrids and 60 cm for open-pollinated check cultivar. Recommended agro-managements were carried out. The seeds were sown in the first week of May. The observations were recorded on five competitive plants for seed cotton yield plant-1 (g), number of bolls plant-1, boll weight (g), seed index (g), and ginning out turn (%). The economic heterosis in terms of improvement in per se performance of F1 hybrids over check hybrid LHH 144 and standard cultivar LH 1556 was calculated and expressed as percentage:

Economic Heterosis

F1 mean– Check meanx 100

Check meanKarl Pearson’s correlation coefficients (r) were computed as described by Panse and Sukhatame

(1967) to determine the relationship of F1 performance and economic heterosis with different characteristics of parental lines.

DNA Analysis

Amplified Fragment Length Polymorphism (AFLP) analysis was performed as per the protocol given by Vos et al., (1995) to study the molecular diversity among 11 cotton genotypes. For this purpose, a sample of 250 ng aliquant of genomic DNA was digested with restriction enzymes EcoR1 and Mse1 (1.25 µ µl-1) with incubation at 370C for two hours followed by 700C for 15 minutes to inactivate the enzymes. In the second step, the following adapter sequences were ligated to the restricted DNA fragments:

5’-CTCGTAGACTGCGTACC CATCTGACGCATGG-3’ 3’-GACGATGAGTCCTGAG TACTCAGGACTCAT-5’

Seven primers were used for the pre-amplification and amplification with the following extensions: ACT/CAC, ACC/CAC, ACG/CAG, ACT/CTC, AAC/CTG, ACG/CTG, and AGG/CTG,

Where the sequence before the slash refers to the primer extension for EcoR1 and that after the slash refers to the primer extension for the Mse1. The PCR products were separated by electrophoresis on a denaturing polyacrylamide gel. After drying, the gels were exposed to phospho-imager plates for 16 hours. The imager plates were scanned with a phospho-imager and polymorphic bands were coded in a binary form by 1 and 0 for presence or absence in each genotype, respectively.


Estimation of Genetic Distances

The estimates of genetic distances (GD) between all possible combinations of 11 genotypes were computed using the formula given by Nei and Li (1979):

GDij = (Ni + Nj – 2 Nij) / (Ni + Nj), here GDij is the genetic distance between two genotypes i and j, Nij is the number of common bands between genotypes i and j, and Ni and Nj are the total number of bands in genotypes i and j, respectively, related to all primer pairs considered in AFLP analysis. Thus GD reflects the proportion of bands in common between two genotypes and may range from 0 (identical profiles for two genotypes) to 1 (no common bands).


Estimation of Genetic Distance

The estimation of genetic distances between parental lines using AFLP markers ranged from 0.111 between parental lines F 1861 and Udangsuper to 0.705 between PIL 43 and PIL 8 (Table 1). PIL 43 is a female parent of an approved hybrid LHH 144 and this line has okra type narrow leaves with deep lobes. Its bolls are ovate and of very big just like the hybrid LHH 144. On the contrary PIL 8 is the male parent of hybrid LHH 144 with medium size normal green leaves and elliptic bolls. The genetic distance was also high (0.679) between PIL43 and Udangsuper. Udangsuper is a local collection from the farmers’ field. It has small normal green leaves with medium size round bolls. It has high tolerance to bollworms. The high genetic distance was reported between parents LH 1556 and GSH 4 (0.52). Low genetic distance was observed between the parents of LH 1556 and Udangsuper, GSH 4 and Udangsuper, LH1556 and PIL8, F1861 and PIL8, GSH4 and PIL8, F505 and PIL8, HS253 and GSH4 and Udangsuper and HS253 (Table 1). There was no association between genetic distance estimated from AFLP markers and geographical diversity of the parents. The genetic distance was comparatively high between those parental lines that differ largely for morphological characters.

TABLE 1: ESTIMATES OF GENETIC DISTANCE (GD), MEANS OF THE PARENTS ( P ) AND ABSOLUTE DIFFERENCES BETWEEN MEANS OF PARENTS (| P1 - P2 |) FOR DIFFERENT CHARACTERS

Cross/hybrid Genetic Distance

(GD)

Seed Cotton Yield plant-1

(g)

Number of Bolls Plant-1

Boll Weight (g)

Ginning Out Turn

%

Seed Index

Mean | P1 -

P2 |

Mean | P1 -

P2 |

Mean | P1 -

P2 |

Mean | P1 -

P2 |

Mean | P1 -

P2 | LH1556x Udangsuper 0.147 105.5 71 34.0 22 2.96 0.11 32.1 -0.5 9.0 1.1 F1861 x Udangsuper 0.111 87.5 35 31.5 17 3.10 0.40 32.5 0.3 8.8 0.2 PIL43 x Udangsuper 0.679 80.0 20 26.0 6 3.50 1.20 32.1 -0.4 9.0 -1.0 GSH4 x Udangsuper 0.131 67.5 -5 23.5 1 3.25 0.70 32.9 1.1 8.6 -0.2 LH900 x Udangsuper 0.281 71.0 2 26.0 6 3.00 0.20 32.6 0.5 8.5 -0.9 F505 x Udangsuper 0.118 79.0 18 28.5 11 2.95 0.10 32.1 -0.4 8.4 0.6 LH1556 x PIL8 0.111 113.0 56 7.5 15 3.07 -1.19 32.6 -1.6 8.5 2.0 F1861x PIL8 0.153 95.0 20 35.0 10 3.75 -0.90 33.0 -0.8 8.6 1.1 PIL43 x PIL8 0.705 87.5 5 29.5 -1 4.15 -0.10 32.7 -1.5 8.8 -0.1 GSH4 x PIL8 0.160 75.0 -20 27.0 -6 3.90 -0.60 33.4 0.0 8.5 0.7 LH900x PIL8 0.309 78.5 -13 29.5 -1 3.65 -1.10 33.1 -0.6 8.3 0.0 F505 x PIL8 0.134 86.5 3 32.0 4 3.60 -1.20 32.7 -1.5 8.2 1.5 HS253 x GSH4 0.152 83.5 37 33.5 19 3.40 -0.40 33.0 -0.8 8.4 0.0 LH1556 x GSH4 0.520 103.0 76 34.5 21 3.31 -0.59 32.6 -1.6 8.9 1.3 RS 2013 x F846 0.272 100.5 11 47.0 10 3.10 -0.40 33.0 -0.8 8.4 0.8 Udangsuper x HS253 0.134 86.0 -32 33.0 -20 3.05 -0.30 32.5 -0.3 8.5 0.2


Prediction of Mean Performance and Economic Heterosis

Genetic distance among parental lines estimated by using AFLP markers, means of the parents (P1+P2/2), and the absolute difference between means of the parents (| P1 - P2 |) were used to predict the mean performance and economic heterosis of F1 hybrids. The significant positive correlations of genetic distance with mean performance (0.472*) and economic heterosis (0.472*) was observed for seed cotton yield only, indicating that genetic distance between parents is a good predictor of mean performance and heterosis for this character (Table 2). The associations of genetic distance with mean and economic heterosis for number of bolls (0.207), boll weight (0.351 & 0.464) and seed index (0.157 & 0.180) were positive but their magnitude was too low to be of any predictive value. In upland cotton, Solomon et al., (1989) found that AFLP based genetic distance is not a good predictor of heterosis or F1 performance for yield and most agronomic traits. However, they found positive correlations between AFLP based genetic distance and F1 performance for harvest index. Our results are in contrary to that of Meredith and Brown (1998) who concluded that heterosis for seed cotton yield and boll weight in cotton can not be predicted from the molecular genetic diversity of the parents. In a study on G. arboreum (Asiatic cotton), Singla (2008) reported that the mean performance of F2 populations could not be predicted from the genetic distance among parental lines. Gutierrez et al .,(2002) found that the performance of F2 bulk populations in upland cotton is not always associated with the genetic distance of the parents but on the genetic background of the parental germplasm. The significant and positive correlations of means of the parents ( P ) with per se performance (0.529*) and economic heterosis (0.529*) of F1 hybrids for seed cotton yield and number of bolls/plant (0.497* each) suggested that parental means had very high predictive power. For other traits, this association was very weak. The absolute difference between the means of the parents (| P1 - P2 |) was found to be good predictor of per se performance and economic heterosis of F1 hybrids for seed cotton yield, ginning out turn and seed index. It had significant and positive associations with seed cotton yield for per se performance (0.497*) and heterosis (0.497*). There was positive and significant correlations with ginning out turn for per se performance (0.558*) and economic heterosis (0.562*). However, the association for seed index was negative for per se performance (-0.429*) and heterosis (-0.448*). Although, the correlations for number of bolls/plant (0.10) was positive but of very low values and has no predictive power.

The result indicated that mean performance and economic heterosis of F1 hybrids for seed cotton yield can be predicted accurately from all the three properties of parental lines, viz. genetic distance, parental means and absolute difference between the means of parents and are supported by theoretical expectations of Melchinger (1987). Lamkey et al.,(1995) and Melchinger et al., (1998) have reported that test cross means of F2 or backcross populations or later selfing generations derived from them are predictable from the genetic distance and testcross means of the parents in maize. The prediction of F1 performance from the parental means has advantages- 1) the required information on the performance of the parents can be obtained within one year across locations 2) the performance of n (n-1) F1 hybrids can be predicted from the mean performance of just n parents. However genetic distances estimated by AFLP markers and the absolute difference between the mean of two parents could not predict the mean of F1 hybrids for other characters. The parental means ( P ) for boll weight, ginning out turn and seed index and | P1 - P2 | for number of bolls per plant and boll weight could not predict F1 performance and economic heterosis in the present study. The molecular markers based genetic distance provides data covering the whole genome, whereas genetic variance is composed exclusively of quantitative trait loci (QTL) effects which are segregating in the populations. Since the distribution of molecular markers and QTLs responsible for genetic variance are unlinked to any marker and some of the markers are unlinked to QTLs. Under such circumstances, there is a probability of reduction in the association between genetic distance and heterosis (Bernardo 1992; Charcosset and Essioux 2004). Melchinger et al., (1998) has given the theoretical explanations for the absence of correlation between F1 heterosis and various predictors. In the present study, we wanted to determine the associations between F1 performance (F1) and various predictors, (y). However, we actually estimated correlations between the estimates of both variables (Melchinger et al., 1998). As a result, error in estimation of F1 means or ŷ will reduce the


correlations r(F1,ŷ) relative to r(F1,y). This is supported by high standard derivations for F1 means and ŷ

for most of characters (data not given). This indicated large replication variance for seed cotton yield/plant, number of bolls/plant, plant height and seed index which could be reduced by increasing the number of replications. The larger standard error is due to small sample size of F1 hybrids and their evaluation in one environment only. Decreasing the standard error of F1 means and predictors would require increasing the number of plants in each F1 hybrid and their evaluation in several environments. However, this would be extremely resource demanding. Sizeable errors were also associated in estimation of genetic distance and other predictors.

TABLE 2: ESTIMATES OF CORRELATIONS OF GENETIC DISTANCE AMONG PARENTS (GD), MEANS OF THE PARENTS ( P ) AND ABSOLUTE DIFFERENCE BETWEEN MEANS OF THE PARENTS

(| P1 - P2 |) WITH PER SE PERFORMANCE AND ECONOMIC HETEROSIS FOR DIFFERENT CHARACTERS IN COTTON

Character Correlations with Genetic Distance

(GD) Mean of the

Parents( P ) Difference between two Parents (| P1 - P2 |)

Seed cotton yield/ Plant

Per se performance 0.472* 0.529* 0.497* Economic heterosis over LH1556

0.472* 0.529* 0.497*

Number of bolls/ plant

Per se performance 0.207 0.497* 0.100 Economic heterosis over LH1556

0.207 0.497* 0.101

Boll weight Per se performance 0.351 0.177 -0.048 Economic heterosis over LH1556

0.464 0.176 -0.049

Ginning outturn Per se performance -0.336 -0.216 0.558* Economic heterosis over LH1556

-0.337 -0.210 0.562*

Seed index Per se performance 0.157 0.132 -0.429* Economic heterosis over LH1556

0.180 0.146 -0.448*

*Significant at 5% level of significance

CONCLUSION

We conclude from the present study that the per se performance and economic heterosis of F1 hybrids for seed cotton yield can be predicted from AFLP based genetic distance between parents, means of the parents ( P ) and absolute difference between means of the parents (| P1 - P2 |) in upland cotton. The means of the parents for number of bolls and seed cotton yield; and absolute difference between means of the parents for seed cotton yield and ginning out turn and seed index are the good predictors of per se performance and economic heterosis of F1 hybrids in upland cotton.

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report. Coimbatore, Tamil Nadu-641 003. [2] Bernardo, R., (1992). Relationship between single-cross performance and molecular marker heterozygosity. Theor. Appl.

Genet., 83, 628-34. [3] Charcosset, A. and Essioux L., (2004). The effect of population structure on the relationship between heterosis and

heterozygosity at marker loci. Theor. Appl. Genet., 89, 336-343 [4] Cheres, M.T., Miller J.F., Crane J. M. and Knapp, S. J. (2000). Genetic distance as a predictor of heterosis and hybrid

performance within and between heterosis groups in sunflower. Theor. Appl. Genet., 100: 889-894. [5] Gill, M.S., Gumber R.K., Gill J.S., Sohu R.S. and Rathore P., (2008). Varietal impovement program of cotton in Punjab.

Proceedings of the Annual Group Meeting of AICCIP, April 9-10, Ludhiana, pp: 13-24. [6] Gutierrez, O.A., Basu, S., Saha S., Jenkins, J.N., Shoemaker, D. B., Cheatham, C. L. and McCarty, J.C. Jr., (2002). Genetic

distance among selected cotton genotypes and its relationship with F<sup>2</suup> performance. Crop Sci., 42: 1841-47. [7] Katarki, B.H., (1972). Varalaxmi: A high yielding hybrid cotton of quality. Indian Farming, 21:35-36 [8] Lamkey, K.R., Schnicker B.J. and and Melchinger A.E., (1995). Epistasis in an elite maize hybrid and choice of generation

for inbred line development. Crop Sci. 35: 1272-1281.


[9] Lanza, L. L. B., Souza, C. L. Jr. de, Ottoboni, L. M. M., Vieira, M. L. C. and Souza, A. P. de, (1997). Genetic distance of inbred lines and prediction of maize single-cross performance using RAPD markers. Theor. Appl. Genet., 94: 1023-1030.

[10] LeeGodshalk , M., E.B., Lamkey, K. R. and Woodman, W. W., (1989). Association of restriction fragment length polymorphism among maize inbreds with agronomic performance of their crosses. Crop Sci., 29: 1067-1071.

[11] Melchinger, A.E., (1987). Expectation of means and variances of testcrosses produced from F2 and backcross individuals and their selfed progenies. Heredity, 59: 105-115.

[12] Melchinger, A. E., Gumber, R. K., Leipert, B., Voylsteke, M. and Kuiper, M., (1998). Prediction of testcross means and variances among F3 progenies of F1 crosses from testcross means and genetic distances of their parents in maize. Theor. Applied Genet., 96: 503-512.

[13] Meredith, W. R. Jr. and Brown, J. S., (1998). Heterosis and combining ability of cottons originating from different regions of the United States. J. Cotton Sci., 2:77-84.

[14] Nassimi, A.W., Raziuddin Sardar, A. and Naushad, A., (2006). Study on heterosis in agronomic characters of rapeseed (Brassica napus L.) using diallel. J. Agron., 5: 505-508.

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[16] Panse, V.G. and Sukhatme, P. V., (1967). Statistical methods for agricultural workers. ICAR, New Delhi. [17] Patel, C.T., (1971). Hybrid H4: A new hope towards self-sufficiency in cotton in India. Cotton Dev., 1:1-5 [18] Radoev, M., Becker, H .C. and Ecke, W., (2008). Genetic analysis of heterosis for yield and yield components in rapeseed

(Brassica napus L.) by quantitative trait locus mapping. Genet., 179: 1547-1558. [19] Rameeh, V., (2011). Heterosis and combining ability assessment for phenological traits, plant height and grain yield in

Winter x Spring combinations of rapeseed varieties. Int. J. Plant Breed. Genet., 5: 349-57 [20] Selvaraj, Immanuel, Pothiraj Nagarajan, Kattiyanan Thiyagarajan, and Maruddapan Bharathi, (2010). Predicting the

relationship between molecular marker heterozygosity and hybrid performance using RAPD markers in rice (Oryza sativa L.). African J. Biotech., 9: 7641-7653

[21] Schill, B., Melchinger, A. E., Gumber, R. K. and Link, W., (1998). Comparison of intra- and inter-pool crosses in faba bean (Vicia faba L) II. Genetic effects estimated from generation means in Mediterranean and German environments. Plant Breeding, 117: 351-359

[22] Singla, J., (2008). Prediction of F2 performance in Gossypium arboreum L. based on genetic diversity of parental lines at molecular level. M.Sc Thesis, Punjab Agricultural University Ludhiana.

[23] Smith, O.S., Smith, J. SC., Bowen, S.L., Tenborg, R. A. and Wall, S.J., (1990). Similarities among a group of elite maize inbreds as measured by pedigree, F1 grain yield, grain yield, heterosis and RFLPs. Theor. Appl. Genet., 80: 833-840.

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Thermosensitive Genetic Male Sterility System in Cotton (G. arboreum L.)

S.M. Palve1, V. Santhy2, S.R. Bhat2, S. Laxman2, Rajesh Patil2, B.M. Khadi2, Sonali Virkhede2 and Priyanka Bihariya2

1Principal Scientist, Division of Crop Improvement, Central Institute for Cotton Research, Nagpur–440010 India

2Central Institute for Cotton Research, Post Bag No. 2, P.O. Shankar Nagar Nagpur–440010 India

e-mail: [email protected]

Abstract—Thermosensitive Genetic Male sterility (TGMS) is a two line method of hybrid seed production where the sterile flowers are converted into fertile and fertile into sterile at a particular temperature. Once this is stabilized it is possible to convert any elite variety into TGMS and develop heterotic hybrids. TGMS system in G. arboreum and photoperiod-sensitive genetic male sterility (PGMS) system in G. hirsutum has been identified for the first time. The line remains sterile till temperature reaches 240C and show complete pollen fertility at temperature less than 180C. PGMS lines in G. hirsutum show complete pollen sterility when temperature rises above 40 0C for continuous period of time.

TGMS line 1-1 has been characterized and stabilized by continuous selfing. This line was also grown under phytotron conditions for confirming the phenomenon. Varying minimum/night temperature and a fixed maximum temperature was provided in the phytotron to study pollen viability in G. arboreum and the phenomenon of reversion to complete fertility at 16 0C was confirmed. The period in between the completely fertile and completely sterile phase which produced partially fertile/partially sterile flowers were observed to be the sensitive stage. The flower behaviour during normal growing season in the field condition was observed continuously (2007, 2008, 2009 and 2010) in this lines and correlated with the prevailing weather conditions during the period. During the years 2007, 2008 and 2009, the flowers produced at the onset (i.e. during last week of August to first week of September depending on the sowing date) were sterile with very small white anthers. The mean minimum temperature during the period was 240C with continuous and good sunshine hours. As the temperature reduced towards the end of September and beginning of October, the flowers started turning fertile with yellow anthers. The flowers turned completely fertile with almost full yellow anthers when the mean minimum temperature reduced to 180C during the following month. Highest fertility was recorded during the months of October – November which later decreased as the temperature went down.

INTRODUCTION

India is the only country to grow all four species of cultivated cotton Gossypium arboretum, G. herbaceum, G. barbadense and G. hirsutum. G. hirsutum represents 90% of the hybrid cotton production in India. India has the largest area under cotton (110 lakh hectares in 2010-11) with an estimated 6 million farms. The rainfed lands produce 65% of India’s cotton while the remaining 35% is attributed to irrigated lands. The rapid growth in yields between 2002-03 to 2007-08 is attributed to the introduction and expansion of Bt cotton hybrids and improved cotton varieties, improved crop management practices and overall favourable weather conditions in most of the states involved.

India’s pioneering role in the successful exploitation of heterosis at the global level on a commercial scale resulted in the release of first hybrid ‘H4’ in 1970 by Late Dr. C.T. Patel in Gujarat. Since then, followed a release of many hybrids (intra-species and interspecific). The studies on heterosis from early 1950s onwards indicated higher level of heterosis in G. herbaceum × G. arboreum than intra herbaceum crosses. The first ever success story of heterosis breeding in tetraploid cotton encouraged breeders to try the same principles in diploid cotton which resulted in the development of hybrids namely G. Cot DH 7, G. Cot DH 9 and DDH 2. These hybrids were based on conventional emasculation and pollinaton. The

10

Thermosensitive Genetic Male Sterility System in Cotton (G. arboreum L.) 63

hand emasculation and pollination (Doak, 1934) was not effective in producing large quantity of economically viable seeds. Despite these methods, higher level of seed set equal to G. hirsutum was not possible due to delicate and small flower structure. To overcome this problem of hybrid seed production, two sources of genetic male sterility (GMS) have been used for seed production.

The two-line systems of hybrid seed production hold promise for breeding specific genotypes bearing response to temperature and photoperiod fluctuations. However, considering slow increase in yield levels the male sterility systems have to make a dent in commercialization for larger benefits. There is certain amount of risk in exploiting heterosis by means of TGMS, if temperature fluctuation occurs at critical stages of flowering. Therefore, knowledge on critical thermo-sensitive stages for fertility alteration is useful to determine the most suitable time of sowing for seed multiplication and hybrid seed production. The present study was therefore undertaken to characterize and stabilize the identified TGMS 1-1 line in G. arboreum cotton for developing two line-hybrids.


The present investigation was undertaken at Central Institute for Cotton Research, Nagpur, India. The material consisted of the plants of identified TGMS line 1-1. These plants and progenies of selected plants were sown for four consecutive years (2007-08 to 2010-11). The line was planted in normal kharif season (June- July) during the first three years and planted in three staggered sowings during the fourth year 2010-11 to screen for temperature sensitivity and find out most suitable period for hybrid seed production.

In field screening, the individual plants were observed daily for pollen sterility/fertility when the flowering was initiated. At flowering stage, during the first year, the plants which showed fertility – sterility reversion were tagged and others removed. The anthers were collected at anthesis from each selected plants. For pollen stainability, anthers were smeared in 1 % acetocarmine solution. Round and dark stained pollen were scored as normal fertile and irregular shaped with empty pollen grain as sterile. Five randomly selected fields within the portion covered by the coverslip were taken for recording of data. Plants with no stained pollen were considered completely male sterile, whereas plants having more than 95 % deeply stained, well filled pollen grains were counted as fertile. The ratio of stained pollen to total pollen counted was expressed as per cent fertility. At the same time, the selected plants were selfed for observing boll setting. Shedding of selfed boll was correlated with the pollen fertility/sterility. From the same plants, seeds were collected boll-wise. Boll to row progenies was raised during successive two years which were thoroughly monitored for alterations till they were found stable with respect to the TGMS trait. The parent plants were further continued during summer as rattoons and their reversion to complete sterility was confirmed.

The flower behaviour during the growing season was correlated with the prevailing weather conditions especially mean minimum temperature and sunshine hours during the period. The sterility/fertility of flowers was confirmed by visual observation of flowers as well as by pollen staining studies under microscope. The flowers showed white anthers during sterility phase and yellow anthers during fertility phase (Fig 1)


Sterile

Partially Fertile

Completely Fertile

Fig. 1: Sterile, Partially Fertile and Complete Fertile Flowers of TGMS Line

The TGMS line was also raised under controlled conditions in the National Phytotron Facility, Indian Agricultural Research Institute, New Delhi. TGMS line along with control variety PA 255 under 13 hour photoperiod with the day/night temperature regime of 300C/250C. The minimum night temperature was lowered step-wise (2-3 0C steps) up to 15 0C. Each of the new temperature regimes was maintained for 8-10 days and newly opening flowers were checked for pollen viability by fluorescein diacetate (FDA) staining and observed under fluorescence microscope.


The field grown TGMS 1-1 line was evaluated for sterility and fertility behaviour during the last four years 2007-08 to 2010-11. The appearance of first flower was recorded in all the plants in the field. The flowers produced at the onset (i.e during last week of August to first week of September depending on the sowing date) were sterile with very small white anthers. The mean minimum temperature during the period was 240C with continuous and good sunshine hours (Table 1 & 2). Mean temperature has been observed to be the primary factor influencing fertility alteration in TGMS lines of rice (Latha et al., 2003). The percentage boll set after selfing was zero in the TGMS line during the initial flowering stage i.e. first week of September. As the temperature reduced towards the end of September and beginning of October, the flowers started turning fertile with yellow anthers. The flowers turned completely fertile with almost full yellow anthers when the mean minimum temperature reduced to 180C during the following months. In rice, the lines with complete pollen sterility under high temperature condition and more than 30 per cent self seed set under low temperature condition are considered as promising TGMS lines for commercial exploitation (Lu et al., 1994). These plants when continued as rattoons beyond February started turning sterile and became completely sterile by the month of April under high temperature and continuous good sunshine hours. TGMS lines causing male sterility at high atmospheric temperature and fertility under low temperature have been reported in rice (Ramakrishna et al., 2006). The pollen sterility was confirmed by visual observation of flowers as well as by pollen staining studies


under microscope. The period in between the completely fertile and completely sterile phase which produced partially fertile/sterile flowers were observed to be the sensitive stage. Thus three stages critical fertility phase, critical sterility phase and sensitive phases were identified in the TGMS line 1-1.

TABLE 1: THE DURATION OF SUNSHINE HOURS AND STERILITY/FERTILITY OBSERVED IN TGMS 1-1

Week/ Month Flower Behaviour Weekly Mean Mini Temp ( 0c) Weakly Mean Sunshine Hours August, 2008 1st week Sterile 24.3 0.64 2nd week Sterile 24.7 2 ( Sunshine was nil during 4

days) 3rd week Sterile 24.5 4.2 4th week Sterile 24.0 7.0 September 2008 1st week Partially fertile 23.8 4.7 2nd week Partially fertile 23.6 3.7 3rd week Partially fertile 24.2 5.0 4th week Partially fertile 22.5 7.5 October, 2008 1st week Partially Fertile (40% ) 23.3 7 2nd week Fertile (70-80 % ) 21.8 7.6 3rd week Completely fertile 18 9 4th week Fertile (80%) 15 9 November, 2008 1st week Fertile (80%) 14.0 9.0 2nd week Fertile (80% ) 15.5 8.5 3rd week Completely Fertile 20.3 6.5 4th week fertile (60-70%) 12.4 9.8

TABLE2: THE DURATION OF SUNSHINE HOURS AND STERILITY/ FERTILITY OBSERVED IN TGMS 1-1

Week/ Month Flower Behaviour Weekly mean Mini Temp ( 0c) Weakly Mean Sunshine Hours August, 2009 1st week Sterile flowers 25.60 5.2 2nd week Partially Fertile 24.80 2.6 3rd week Partially Fertile 24.40 2.6 4th week Partially Fertile 23.90 4.6 September, 2009 1st week Partially Fertile 24.50 4.5 2nd week Partially Fertile 23.95 5.3 3rd week Partially Fertile 23.90 9.6 4th week Sterile flowers 25.00 8.7 October, 2009 1st week Sterile 25.0 4.1 2nd week Partially Fertile 20.6 9.0 3rd week Partially Fertile 21.0 9.1 4th week Completely Fertile 16.0 10.4 November, 2009 1st week Completely Fertile 16.5 10.0 2nd week Completely Fertile 21.0 3.8 3rd week Completely Fertile 17.7 5.0 4th week Fertile 12.5 8.5

For determining critical temperature for inducing male sterility/fertility in TGMS lines of G. arboreum plants were raised under controlled condition under Phytotron conditions at IARI, New Delhi during the year 2008-09. Initially plants were grown at 30 0C day and 26 0C night temperatures with 13 hr photoperiod (Table 4). Under this temperature regime, all the flowers were male sterile in the TGMS line. The night temperatures were lowered step-wise (2 0Csteps) and pollen viability was recorded in the flowers that opened in the next one week. Pollen viability was tested by FDA staining and observed under microscope (Fig. 2). A night temperature of 20 0C was found to lead partial fertility. The results revealed that temperature below 16 0C is necessary for obtaining male fertile plants (Table 4).


Sterile Pollen Grains Partially Fertile Pollen Grains

Normal Fertile Pollen Grains

Fig. 2: Acetocarmine Staining to Determine Sterility and Fertility of Pollen Grains in TGMS Line

TABLE 3: THE WEEKLY MEAN MIN. TEMP ( 0C), WEEKLY MEAN SUNSHINE HOURS AND STERILITY/ FERTILITY OBSERVED IN TGMS 1-1

Week/Month Flower Behaviour Weekly Mean min. Temp. ( 0c)

Weekly Mean Sunshine Hours

August 2010 1st week Partially fertile (6% after pollen staining) 23.0 0 2nd week Partially fertile (4% after pollen staining) 24.0 1.7 (Sunshine nil for five days) 3rd week Partially fertile (10% after pollen staining) 23.0 1.5 (Sunshine nil for five days) 4th week Partially fertile 24.0 2.1 (Sunshine nil for four days) September 2010 1st week Partially fertile (15 % after pollen staining) 24.0 1.7 (Sunshine nil for five days) 2nd week (Second sowing started)

Partially fertile (15 % after pollen staining) 24.0 2.0 (Sunshine nil for five days)

3rd week Partially fertile (15 % after pollen staining) 23.0 1.5 (Sunshine nil for five days) 4th week Partially fertile (8 % after pollen staining) 23.2 7.0 (Sunshine present on all days) October, 2010 1st week Partially fertile (20% fertility after pollen

staining ) 22.9 7.4 ( All Days good sunshine )

2nd week Partially fertile (25% fertility after pollen staining )

22.9 7.2

3rd week Partially fertile 23.8 4.0 (Sunshine nil for 3 days) 4th week fertile (80% fertility after pollen staining ) 19.7 7.0 November, 2010 1st week Fertile (90% fertility after pollen staining) 19.0 7.0 2nd week Fertile 21.0 8.0 3rd week Fertile 20.7 7.0 4th week Fertile (80% fertility after pollen staining) 19.0 8.5

TABLE 4: EFFECT OF NIGHT TEMPERATURE ON POLLEN VIABILITY IN TGMS LINE OF G. ARBOREUM

Temperature Regime % Male Fertile Flower Pollen Viability (%) No. Days Tested 30ºC days/ 26ºC night 0 0 10 30ºC days/ 22ºC night 0 0 7 30ºC days/ 20ºC night 9 20-50 7 30ºC days/ 18ºC night 37 20-50 7 30ºC days/ 16ºC night 41 20-100 7


TABLE 5: STUDY OF TGMS SYSTEM IN DIPLOID COTTON (G. ARBOREUM) UNDER NATURAL FIELD AND PHYTOTRON CONDITIONS

Growth Condition Temperature at Complete Male Sterility Obtained Temperature at Complete Male Fertility Obtained

Artificial (Phytotron) 22 0C and above 16 0C Natural Field 24 0Cand above ( As observed for three consecutive years

(2007, 2008 and 2009) 18 0C

Natural Field (Fourth Year - 2010)

No complete sterility (for early and late sown) even at 240C due to cloudy weather with no sun shine consecutively for several days.

180C

The third sowing date which was in the end of January 2011 started flowering by the end of April

and was at peak flowering by the month of May. The flowers were completely male sterile with unstained and deformed pollen observed under microscope after aceto-carmine staining (Fig. 2). Developmental variation in the TGMs line, soon after microspore release and before dehiscence of anther, it was found that, break down of fertility in the sterile anthers was post-meiotic after the release of tetrad in the developmental stage (Fig. 3). Similar observation has been recorded Reddy and Reddi (1974) in pearl-millet that microspores in sterile lines collapsed soon after their release from the tetrads.

Fig. 3: Microspore tetrad Formation in Sterile and Fertile Flowers of TGMS Line

Simultaneously selfing was performed in the TGMS line as well as normal fertile line. The selfed boll set was absent in the TGMS line till the second week of June where as it was 60-70% in the normal fertile line. The mean minimum temperature was above 240C during the whole month (Table 3 & 5). In rice, the TGMS line T 29 was male sterile when exposed to daily mean temperature of 24.1 0C (Cuong et al., 2004). Also in maize a novel TGMS line exhibiting full sterility during summer has been discovered (Tang et al. 2006). In the present study a period of 35 - 40 days with complete male sterility could be obtained in the third date of sowing unlike other two dates of sowing. The TGMS line developed and characterized was thus found to be beneficial for hybrid seed production in the month of May and for maintainance by selfing during the normal kharif season.


Thus, for two-line system using TGMS line, any fertile line can be used as pollen parent, so the choice of parents in developing heterotic hybrids is greatly broadened. Since there is no need for restorer genes in the male parents of two-line hybrids, this system is ideal for developing arboreum hybrids. Identification of proper locations for seed production of hybrid as well as of the TGMS line itself will play an important role in commercial success of this system.

REFERENCES [1] Cuong, Van Pham., Seiichi, Murayama., Yukio, Ishimine., Yoshinobu, Kawamitsu., Keiji, Motomura and Eiji, Tsuzuki

(2004) Sterility of thermo-sensitive genic male sterile line, heterosis for grain yield and related characters in F1 hybrid rice (Oryza sativa L.). Plant Production Science, 7: 22-29.

[2] Doak, C. C. (1934) A new technique in cotton hybridizing suggested changes in existing methods of emasculation and bagging of cotton flowers. J. Hered. 25: 201-204.

[3] Latha, R. S., Thiagarajan, K. and Thyagarajan, K. (2003) Inheritance of thermo-sensitive genic male sterility trait in rice. J. Genet. Breed. 57: 89-91.

[4] Lu, X. G., Zhang, Z. G., Maruyama, K., Virmani, S. S. (1994). Current status of two line method of hybrid rice breeding In: Virmani S. S., editor. Hybrid rice technology: new developments and future prospects. Manila (Philippines) International Rice Research Institute. p 37-39.

[5] Liu, Y., He, H., Shun, Y., Rao, Z., Pan, X., Huan, Y., Geo, J. and He, X. (1997) Light and temperature ecology of photo-thermo-sensitive genic male sterile rice and its application in plant breeding. In Proc. Int. Symp. On Two line system of heterosis breeding in crops” pp. 49 -58 (China National Hybrid Rice Research and Development Centre, Changsha, China)

[6] Ramakrishna, S., Mallikarjuna, Swamy., Mishra, B., Virakthamath, B. C. and Ahmed M. Illyas. (2006) Characterization of thermosensitive geneitic male sterile lines for temperature sensitivity, morphology and floral biology in rice (Oryza sativa) Asian J. Plant Sciences, 5 : 421 - 428

[7] Tang, J. H. , Fu Z. Y., Hu, Y. M., Li, J. S., Sun, L. L. and Ji, H. Q. (2006) Genetic analyses and mapping of a new thermo-sensitive genic male sterile gene in maize Theor. Appl. Genet., 113: 11-15.

[8] Reddy, B.B. and M.V. Reddi, (1974) Cytohistological studies on certain male sterile lines of pearl millet (Pennisetum typhoides. S. and H). Cytologia, 39: 585-589.

[9] Singh, Vrijendra., Deshmukh, S. R., Deshpande, M. B. and Nimbkar, N. ( 2008 ) Potential use of thermosensitive genetic male sterility for hybrid development in safflower Fourth Int. Safflower Conference, Australia.

[10] Xiaodong, Chen., Dongfa Sun., Rong D. F., Genlou, Sun and Junhua, Peng (2010) Relationship of genetic distance and hybrid performance in hybrids derived from a new photoperiod-thermo sensitive male sterile wheat line 337 S. Euphytica, 175: 365 – 371.

[11] Xia, Liu., Xihong Li., Xin, Zhang and Songwen, Wang. (2010) Genetic analysis and mapping of a thermosensitive genic male sterility gene, tms6(t) in rice (Oryza sativa L.). Genome, 5 3: 119-124.

[12] Yuan, L. P. (1998) Hybrid rice breeding in China. In “Advances in Hybrid Rice Technology” (Ed. SS Virmani; EA. Siddique; K. Muralidharan), pp: 27 -33 International Rice Research Institute, Manila, Philippines

Heterosis for Yield and Yield Attributing Traits in Arboreum Cotton (Gossypium arboreum L.)

S.B. Lalage1, N.D. Deshmukh2, I.S. Halakude3 and J.C. Rajput4

Nirmal Agricultural Research and Development Foundation, Pachora–424201 (MS) 1SR. Scientist (Cotton), Nirmal Agricultural Research and Development Foundation,

Pachora Dist. Jalgaon, India 2Plant Breeder, Nirmal Agricultural Research and Development Foundation,

Pachora Dist. Jalgaon, India 3Research Coordinator, Nirmal Agricultural Research and Development Foundation,

Pachora Dist. Jalgaon, India 4Director of Research, Nirmal Agricultural Research and Development Foundation,

Pachora Dist. Jalgaon, India

Abstract—The studies on heterosis made with 24 specific cross combinations using two diverse genetic male sterile (GMS) lines viz., NCAGA-4 and NCAGA-26 as female parents and 12 contrasting Arboreum strains as male parents at R&D, Farm of Nirmal Agricultural Research and Development, Jalgaon. The experiment was laid out in randomized block design with three replications. The observations were recorded for number of sympodia, number of bolls/plant, average boll weight (g) and seed cotton yield (g/plant) on five randomly selected plants per replicate from each genotype. It indicated that the maximum heterosis for seed cotton yield was observed in NACH-433 (121% for MP and 109.13% for BP) and average boll weight (g) were observed in NACH-433 (55.34% for MP and 53.85% for BP). Thus, the female parent NCAGA-26 can be used for exploitation of heterosis.

INTRODUCTION

Cotton plays a vital role in the economy of the nation being an important raw material for textile industry. Gossypium arboreum being resistant to abiotic and biotic stresses, gets well adapted to the climatic aberrations and also well suited in resource-limited environments. The competitive demand for fibre warrants to improving the productivity of cotton crop in such situation which is difficult to achieve through conventional hybridisation and selection. Heterosis breeding seems to be good approach in this directions. Several studies indicated that in cotton heterosis assisted in gathering the strong genetic information (Kapoor, et al.,., 2002 and Patil, et al.,., 2009). The present investigation is linked to above statement.


The experiment was conducted with two diverse genetic male sterile (GMS) lines, namely, (NCAGA-4 and NCAGA-26) used as female parents and 12 contrasting Arboreum strains NSA-12, NSA-13, NSA-15, NSA-17, NSA-18, NSA-19, NSA-27, NSA-28 NSA-29, NSA-32, NSA-300 and NSA-301 (used as male parents) in randomized block design with three replications. The 12 male parents were crossed with each of the GMS line in a line x tester manner to develop 24 hybrids. All these 38 genotypes (24 hybrid + 12 parents + 2 GMS lines) were grown at experimental farm of R&D Division, Nirmal Agricultural Research and Development Foundation (NARD), Pachora, Dist Jalgaon, India during kharif 2009.

The observations were recorded for number of sympodia per plant, number of bolls/plant, average boll weight (g) and seed cotton yield (g/plant) on five randomly selected plants per replicate from each genotype. The data of all the genotypes were pooled and per cent heterosis over mid parent and better parent was calculated for seed cotton yield and other related traits.


The per cent heterosis over mid parent and better parent for all the traits are given in Table 1. Per cent heterosis of number of sympodia per plant ranged from –9.26 to 9.89 percent for mid parent and -15.69

11


to 4.17 for better parent. Three hybrids namely, NACH-338 NACH-259 and NACH-7 for mid parent and NACH-338, for better parent were superior over all the genotypes. The maximum heterosis effect 9.89 and 4.17 per cent was obtained in hybrid NACH-338 over mid parent and better parent respectively.

Per cent heterosis for the number of bolls/plant ranged from -6.67 to 43.00 per cent for mid parent and -13.27 to 40.40 per cent for better parent. Maximum per cent heterosis was estimated for hybrid NACH-18 (43.00 % for mid percent) and NACH-12 (40.40 % for better parent), respectively. The hybrids NACH-18, NACH-12, NACH-433 and NACH-15 exhibited significant positive per cent heterosis among all the genotypes. Similar heterosis effect for this character was reported by Nanjundan et al., (1992) and Patil et al., (1991), Chavan et al., (1999), Jain (1996) and Nirania et al., (1992).

Maximum per cent heterosis for boll weight (g) was recorded by hybrid NACH-433 (55.34 % and 53.85 % for mid parent and better parent respectively). The per cent heterosis for this character ranged from -19.05 to 55.34 per cent for mid parent and -32.89 to 53.85 per cent for better parent. Fourteen hybrids for mid parent namely NACH-6, NACH-9, NACH-15, NACH-221, NACH-338, NACH-286, NACH-223, NACH-225, NACH-226, NACH-12, NACH-11, NACH-375, NACH-433, NACH-434 and Eleven hybrids for better parent namely NACH-15, NACH-221, NACH-338, NACH-286, NACH-223, NACH-225, NACH-226, NACH-12, NACH-18, NACH-375 and NACH-433 exhibited positive significunt heterosis over remaining genoypes. Heterosis for this character has also been reported earlier by Nanjundan et al., (2004) and Chavan et al., (1999).

For seed cotton yield, the per cent heterosis ranged from 0.60 to 121.92 per cent for mid parent and -12.66 to 109.13 per cent for better parent. Out of 24 hybrids, 18 hybrid for mid parent and 15 hybrid for better parent showed positive significant heterosis. Maximum heterosis was exhibited by hybrid NACH-433 (121.92 per cent for mid parent and 109.13 per cent for better parent) followed by NACH-18 (115.34 per cent for mid parent) and NACH-12 (104.74 per cent for better parent). Kapoor et al., (2002), Patil et al., (2009), Patel (2009) also reported significant positive heterosis for seed cotton yield in cotton hybrids.

It can be concluded that number of bolls per plant and boll weight were main components for good yield. Therefore, selection for these characters might results in the improvement of yield and the promising hybrids like NACH-433, NACH-18 and NACH-12 may be further tested on large plots over different locations and seasons before recommending them for commercial utilization.

TABLE 1: ESTIMATES OF HETEROSIS OVER MID PARENT AND BETTER PARENT FOR SEED COTTON YIELD AND ITS COMPONENT TRAITS IN DESI COTTON HYBRIDS

Mean MP Mean Mean Mean1 NACH-7 NCAGA-4 x NSA-12 25.00 4.17 -1.96 64.00 19.63 ** 16.36 ** 2.70 9.09 8.00 172.90 30.76 ** 28.60 **2 NACH-6 NCAGA-4 x NSA-13 24.00 1.05 -5.88 65.50 20.71 ** 15.93 ** 2.80 15.46 * 12.00 183.55 39.74 ** 38.32 **3 NACH-9 NCAGA-4 x NSA-15 21.50 -8.51 -15.69 * 64.50 21.70 ** 19.44 ** 2.75 14.58 * 10.00 177.40 39.47 ** 36.46 **4 NACH-11 NCAGA-4 x NSA-17 23.00 -5.15 -9.80 60.50 11.52 ** 7.08 2.55 3.03 2.00 154.50 15.02 11.435 NACH-10 NCAGA-4 x NSA-18 24.00 -4.00 -5.88 64.50 17.28 ** 11.21 * 2.65 4.95 3.92 171.30 23.22 ** 15.706 NACH-17 NCAGA-4 x NSA-19 24.00 -5.88 -5.88 56.00 0.45 -5.88 2.60 1.96 0.00 145.80 2.51 -5.607 NACH-23 NCAGA-4 x NSA-27 25.00 -3.85 -5.66 67.50 16.38 ** 5.47 2.75 10.00 10.00 185.55 27.97 ** 15.978 NACH-24 NCAGA-4 x NSA-28 24.00 -4.00 -5.88 61.00 20.20 ** 17.31 ** 2.55 -0.97 -3.77 156.00 19.63 * 19.279 NACH-25 NCAGA-4 x NSA-29 24.50 -2.97 -3.92 61.50 18.84 ** 18.27 ** 2.60 -2.80 -8.77 159.75 15.53 9.0110 NACH-259 NCAGA-4 x NSA-32 25.50 6.25 0.00 59.50 19.60 ** 14.42 ** 2.45 -5.77 -9.26 145.55 12.65 11.9611 NACH-415 NCAGA-4 x NSA-300 24.00 -8.57 -11.11 61.00 12.96 ** 8.93 2.55 0.99 0.00 155.00 14.19 9.2412 NACH-416 NCAGA-4 x NSA-301 24.50 -9.26 -14.04 * 60.50 22.84 ** 16.35 ** 2.55 -19.05 ** -32.89 ** 154.20 0.60 -12.6613 NACH-15 NCAGA-26 x NSA-12 24.00 3.23 0.00 67.00 29.47 ** 21.82 ** 3.90 54.46 ** 50.00 ** 261.50 100.84 ** 94.50 **14 NACH-221 NCAGA-26 x NSA-13 23.00 0.00 -4.17 64.50 22.86 ** 14.16 ** 3.80 53.54 ** 46.15 ** 245.25 89.64 ** 84.82 **15 NACH-338 NCAGA-26 x NSA-15 25.00 9.89 4.17 59.00 15.12 ** 9.26 3.80 55.10 ** 46.15 ** 224.00 78.95 ** 77.85 **16 NACH-286 NCAGA-26 x NSA-17 23.00 -2.13 -4.17 49.00 -6.67 -13.27 ** 3.70 46.53 ** 42.31 ** 181.50 37.19 ** 30.91 **17 NACH-223 NCAGA-26 x NSA-18 22.50 -7.22 -8.16 56.00 5.16 -3.45 3.70 43.69 ** 42.31 ** 207.10 51.17 ** 38.89 **18 NACH-225 NCAGA-26 x NSA-19 24.00 -3.03 -5.88 62.50 15.74 ** 5.04 3.75 44.23 ** 44.23 ** 234.00 66.90 ** 51.51 **19 NACH-226 NCAGA-26 x NSA-27 23.00 -8.97 -13.21 * 59.00 4.89 -7.81 3.80 49.02 ** 46.15 ** 224.00 56.67 ** 40.00 **20 NACH-12 NCAGA-26 x NSA-28 24.50 1.03 0.00 69.50 41.84 ** 40.40 ** 3.85 46.67 ** 45.28 ** 268.80 108.61 ** 104.74 **21 NACH-18 NCAGA-26 x NSA-29 24.50 0.00 -2.00 71.50 43.00 ** 38.83 ** 4.10 50.46 ** 43.86 ** 293.40 115.34 ** 100.20 **22 NACH-375 NCAGA-26 x NSA-32 21.50 -7.53 -10.42 50.50 5.21 4.12 3.40 28.30 ** 25.93 ** 171.85 35.13 ** 33.84 **23 NACH-433 NCAGA-26 x NSA-300 24.50 -3.92 -9.26 74.50 42.58 ** 33.04 ** 4.00 55.34 ** 53.85 ** 297.70 121.92 ** 109.13 **24 NACH-434 NCAGA-26 x NSA-301 26.00 .0.95 -8.77 57.00 20.00 ** 17.53 ** 3.95 23.44 ** 3.95 224.85 48.66 ** 27.36 **

3.34

No. of sympodia/plant Avg. Boll wt (gm)MP BP

24.96

1.783.695.01

0.120.250.34

Seed cotton yield/plant (gm)Sr. No. Hybrid

No. of bolls/ Plant

8.8918.39

1.192.46

Cross

S.Em +CD at 5% CD at 1%

BPMP BP MPBP

Heterosis for Yield and Yield Attributing Traits in Arboreum Cotton (Gossypium arboreum L.) 71

REFERENCES [1] Chavan, M. K., Shekar, V. B., Golhar, S. R., Gite, B. D. and Rajput, N. R. (1999). Heterosis studies in the interspecific

crosses of G. arboreum and G. herbaceum, J. Soils and Crops. 9: 195-197 [2] Jain, S.(1996). Heterosis for fibre characters in intra and interspecific hybrid of cotton. J. Cotton Res. Dev. 10: 147-49. [3] Kapoor, C.J., Singh, M. and Maheshawari, R.V.(2002). Heterosis for yield and yield attributing traits in Desi cotton. J.

Cotton Res. Dev. 16 : 182-183. [4] Nanjundan, J., Sangwan, B. S., Chhabra, B. S. and Kumar, R., (2004). Heterosis for yield and its component traits in Desi

cotton (Gossypium arbourem L.) J. Cotton Res. Dev. 18 (1): 33-35. [5] Nirania, K. S., Singh, I. P., Singh, B. P., Jain, P. P. and Tutga, O. P. (1992). Heterosis and combining ability analysis in

Gossypium arboreum L. J. Cotton Res. Dev. 6 (1): 11-17 [6] Patel, K. G., Patel, R. B., Patel, M. I. and Kumar, V. (2009). Studies on heterosis and combining ability through

introgression in diploid cotton. J. Cotton Res. Dev. 23 (1): 23-26. [7] Patil, F. B., Shinde, Y. M. and Thombre, M. V. (1991). Heterosis in multiple environments for yield components and its

relation with genetic divergence in cotton. Indian J. Genet. 51: 118 - 24. [8] Patil, S. S., Gavit, A. F., Magar, N. M. and Pawar, V. Y.(2009). Heterosis in hybrid of Gossypium arboreum cotton. J.

Cotton Res. Dev. 23: 209-212.

Multi-Level Determination for Heat Tolerance of Cotton Cultivars

Nicola S. Cottee1, Michael P. Bange2, Daniel K.Y. Tan3, J. Tom Cothren4 1Faculty of Agriculture Food and Natural Resources, The University of Sydney,

Sydney, NSW 2006 Australia 2CSIRO Division of Plant Industry, Locked Bag 59, Narrabri, NSW 2390 Australia

3Cotton Catchment Communities Cooperative Research Centre, Locked Bag 1001 Narrabri, NSW 2390 Australia

4Department of Soil and Crop Sciences, Texas A&M University, College Station Texas 77843, USA

E-mail: [email protected]

Abstract—High temperatures (>35oC) are common throughout the cotton-growing season in many regions and may adversely affect the growth and development potential of the crop, ultimately limiting yield. Development of stress screening techniques will enable selection of heat tolerant genotypes for incorporation into future breeding programs. This study assessed the use of the membrane integrity and enzyme viability assays as biochemical screening techniques for determination of genotypic difference in heat tolerance under field conditions. These biochemical screens were evaluated as part of a multi-level approach assessing morphological, physiological, biochemical and molecular determinants of heat tolerance in response to evaluated temperatures.

High yielding Australian cotton cultivars of known and differing yield performance in hot environments were evaluated to ascertain whether biochemical screens could be employed to detect differences in their heat tolerance. Cultivar Sicot 53 was selected as a relatively thermotolerance genotype whilst Sicala 45 was selected as a cultivar with relatively lower heat tolerance. To simulate elevated temperature in the field, clear plastic tents were constructed above the cotton crops in Narrabri, Australia and College Station, USA to determine whether a field based high temperature stress improved the resolution of biochemical screens for heat tolerance and whether differences detected translated to physiological performance.

This study revealed that field-based elevated air temperatures were not sufficient to resolve cultivar differences in cell membrane integrity or enzyme viability under ambient field conditions across the three cotton-growing seasons. However, exposure of leaf tissue to high air temperature using tents resulted in a genotype specific response to heat stress. Implementation of tents increased the resolution of the membrane integrity assay and changed the response of enzyme viability for cultivars Sicot 53 and Sicala 45. Cultivar differences for membrane integrity (P=0.007) and enzyme viability (P<0.001) were consistent in explaining differences for photosynthesis (P=0.046), electron transport rate (P=0.057) and stomatal conductance (P=0.036) which reflected previously determined differences in yield. This highlighted the potential for development of rapid biochemical screening methods for heat tolerance to be used in combination with a multi-level approach also incorporating morphological, physiological and molecular performance indicators to ensure that genotypes selected would contribute to improvements in economic yield.

INTRODUCTION

Laboratory based assays have been developed to rapidly screen large cotton populations for heat tolerance (Azhar et al., 2009; Khan et al., 2008; Rahman et al., 2004). Incorporation of rapid biochemical assays for heat tolerance determination into conventional breeding programs may assist in breeding for increased yield in hot cotton growing environments (Constable et al., 2001; de Ronde and van der Mescht 1997; Ismail and Hall 1999; Rahman et al., 2004; Saadalla et al., 1990; Sullivan 1971). Inclusion of heat tolerance screens into current breeding programme may decrease the intergenerational time and logistic constraints associated with breeding programs focused on long term selection for yield in warm and hot environments.

Reductions in performance at temperatures exceeding the thermal kinetic window (23.5 to 32oC) for cotton (Burke et al., 1988) are commonplace in Australian cotton production regions and may be attributed to decreased plant growth and development, as well as increased fruit shedding (Hodges et al..

12

Multi-Level Determination for Heat Tolerance of Cotton Cultivars 73

1993). At a leaf level, evaluation of processes associated with chronic photosynthetic decline (Reddy et al., 1991) such as membrane leakage and permeability (Sullivan 1971) and decreased stability of photosynthetic (Salvucci and Crafts-Brandner 2004a) and respiratory enzymes (de Ronde and van der Mescht 1997) offer potential for development of rapid and reliable biochemical screens for heat tolerance determination.

However extension of the principals of these screens to in-situ high temperature stress in the field is limited, principally due to the difficulties in creating an effective in-situ heat treatment in a field environment. A recent study by Cottee et al., (2010) indicated that genotypic differences determined using the laboratory-based cell membrane integrity and enzyme viability assays for heat tolerance determination reflected higher order physiological performance and yield under elevated temperature tents in the field. Although biochemical assays have been successfully used to discern heat tolerance in cotton cultivars using different thermal environments (Ismail and Hall 1999) or by staggering planting date (Rahman et al., 2004), it is unknown whether laboratory determined biochemical performance reflects genotypic differences in cell membrane integrity and enzyme viability under in-situ high temperature stress in the field.

In this study, heat tolerance was ascertained for two high yielding Australian cotton cultivars with known field performance under high temperatures using the cell membrane integrity and enzyme viability assays under ambient field conditions and were then validated under elevated temperature tents. Genotypic differences for biochemical performance were then compared with photosynthesis, stomatal conductance and electron transport rate under tents to determine whether elevated temperatures similarly affected leaf level physiological performance.

This paper presents research that indicates that genotypic differences for membrane integrity and enzyme viability are not able to be detected for material grown under ambient field conditions. However, exposure of leaf material to in-situ elevated temperatures under tents increases the resolution of the cell membrane integrity assay and increases the response of dehydrogenase activity in cotton cultivars with a relatively higher (Sicot 53) and lower (Sicala 45) heat tolerance and these biochemical differences were consistent with previously determined performance under field conditions and were reflected in higher order physiological performance under tents.


Genotypes

Normal leaf, non-transgenic, medium maturity and high yielding cultivars of upland cotton (Gossypium hirsutum L.) were established under field conditions. Sicot 53 was selected as a relatively thermotolerant cultivar while Sicala 45 was selected as a cultivar with relatively lower heat tolerance. This selection was based on recent breeding data (not published) in hot and cool environments in experiments conducted by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) breeding program over a number of sites and seasons (cf. Reid et al., 1989)

Experimental Design and Plot Management

Cultivars were grown over three consecutive seasons in a randomized complete block design. Season 1 (sown 14th October 2005) and 3 (sown 18th October 2006) were located at the Australian Cotton Research Institute, Narrabri, Australia (30oS, 150oE). Season 2 (sown 25th April 2006) was located at the Texas Agricultural Experiment Station near College Station, Texas, U.S.A. (30oN, 96oW). Plots were furrow irrigated every 10 to 14 d, according to crop requirements and high input management and pest control were maintained throughout the season. Meteorological data were collected less than 2km from the field sites.


In Situ Heat Stress Treatment

Heat stress treatments were applied in the field to identify whether cultivar differences could be determined using biochemical heat tolerance assays under in-situ high temperature stress in a field environment. In-situ high temperature treatment was imposed by the construction of Solarweave tents above the crop canopy to increase ambient air temperatures (Lopez et al., 2003). Tents were applied between first square and the cessation of vegetative growth for a period of between 4 and 20 days within the 3 seasons. Time of application was dependent on environmental and managerial conditions whereby run 1, 2 and 3 refer to an early, mid and late season tent. Tents were only applied 4 days post irrigation and hence soil moisture was non-limiting during the time of tent application. Mean temperature under the tent was higher than external ambient air temperatures for all tent events (Table 1.). The average daily maximum temperatures were increased by 5.3oC under tents, (pooled for all measurements within the 3 seasons).

TABLE 1: MEAN DAILY MAXIMUM, MEAN AND MINIMUM TEMPERATURE UNDER AMBIENT (CONTROL) AND TENT TEMPERATURE REGIMES IN THE FIELD FOR SEASONS 1 AND 3 IN NARRABRI AND SEASON 2 IN TEXAS. THE MEAN IS TAKEN FROM 3 REPLICATES

Season Run Daily Maximum Temperature Daily Mean Temperature Daily Minimum Temperature Control Tent Control Tent Control Tent

1 1 37.25 43.92 28.61 31.89 22.35 23.06 1 2 33.04 36.77 24.02 25.79 18.00 19.23 2 1 40.08 46.51 31.05 32.64 23.15 22.66 3 1 34.82 37.31 25.30 26.26 16.09 16.46 3 2 37.00 42.68 27.22 29.06 19.02 18.89 3 3 36.29 42.83 25.09 27.72 16.16 16.41

Mean 36.41 41.67 26.88 28.89 19.13 19.45 l.s.d. 2.44 1.1 0.65 F test P value <.001 <.001 n.s.

Biochemical Assays for Heat Tolerance

In-vitro measurements of membrane integrity and enzyme viability were made on leaf material grown under ambient field conditions and under tents. Leaves of cultivars Sicot 53 and Sicala 45 were collected under ambient field conditions or under the tents between 1400 and 1500 h and transported back to the laboratory in paper bags. For each run, leaves for the ambient field and tent treatments were sampled once at the end of the tent measurement period and leaf material was taken from the same row within the same plot for comparison between treatments. Leaf discs with a 10mm diameter were excised from the interveinal portion of the 3rd youngest fully expanded leaf. Discs were triple rinsed to remove exogenous electrolytes.

For the membrane integrity assay, 5 discs were submerged in 10 mL distilled water in 25mL glass vials. One set of leaf discs were held for 2 h at 25oC (REC25) in a thermally controlled water bath. An additional set of leaf discs from the same parent leaf were held for 2 h at 45oC (REC45) in an adjacent water bath. Vials were allowed to cool to room temperature. Initial electrical conductivity (IECt) was determined at each water bath temperature using a low range (0-1990 μS cm-1) ECTestr calibrated conductivity meter (Oakton Instruments, Vernon Hills, IL). Vials were then autoclaved at 121oC and 103 kPa for 15 min and cooled to room temperature. Final electrical conductivity (FECt) was determined for each water bath temperature with the calibrated conductivity meter. Relative electrical conductivity was determined for each water bath temperature where RECt = (IECt/FECt)*100. Relative cellular injury was then calculated where RCI45 = (1-((1-(IEC45/FEC45))/(1-(IEC25/FEC25))))*100 to account for differences incurred during the sampling and water bath incubation period, whereby RCI only shows the injury caused by increased temperature (Sullivan 1971). Increasing RECt and RCI45 indicates decreasing membrane integrity (Sullivan 1971).

For the enzyme viability assay, 2 leaf discs were taken from the same leaf sampled for the cell membrane integrity assay and were submerged in 2 mL distilled water in 14 mL glass vials. One set of leaf discs were held for 2 h at 25oC (Abs25) in a thermally controlled water bath. An additional set of leaf


discs from the same parent leaf were held for 2 h at 40oC (Abs40) in an adjacent water bath. Vials were cooled to 25oC and a buffer solution containing 0.01 M phosphate buffered saline (-0.138 M NaCl; 0.0027 M KCl with TWEEN 20 (0.05% v/v)), pH 7.4 at 25oC) and 0.8% w/v 2,3,5-triphenyltetrazolium chloride (TTC) was prepared and 8 mL added to each vial. Leaf discs were held at -33 kPa for 15 mins to ensure TTC uptake into the leaf and incubated in the dark for 24 h at 25oC. Enzyme viability was determined by spectrophotometric absorbance at 530 nm using 95% ethanol as a reference. Relative absorbance at 530 nm was calculated where RAbs40 = (Abs40/Abs25)*100 to account for differences incurred during the water bath incubation period. High absorbance indicates high enzyme viability whereas low absorbance is indicative of impaired enzyme activity and decreased capacity for reduction of TTC to a red formazan product.

Physiological Measurements

To determine the impact of tents on potential growth, photosynthesis, electron transport rate and stomatal conductance were simultaneously measured using a Li-6400 portable photosynthesis system (Li-Cor Ltd, Lincoln, NE) with a pulse-amplitude modulated (PAM) leaf chamber fluorometer sensor head. Measurements were taken on at least 2 days during the tent measurement period. Measurements were made on the third youngest fully expanded leaf for 3 different plants per plot and four replicates per treatment. All measurements were taken between 1000 and 1300 h. Environmental variables were set to approximately optimal conditions and as such, all differences in physiological data present the consequences of previous exposure to ambient (control) or elevated (tent) temperatures after returning leaves to optimal conditions. The leaf chamber block temperature was maintained at 30oC, light intensity was set at 2000 µmol PAR m-2 s-1, flow rate was adjusted to maintain vapour pressure deficit between 1.5 and 2.5 kPa and relative carbon dioxide concentration was set at 400 µmol CO2 mol-1 using a CO2 mixer.

Data Analysis

To determine cultivar biochemical and physiological performance, under ambient field conditions and under tents, two way ANOVA (cultivar.tent) was conducted for electrical conductivity, relative cellular injury, absorbance at 530 nm, relative absorbance at 530 nm, photosynthesis, electron transport rate and stomatal conductance under ambient field conditions and under tents for seasons 1 and 3 in Narrabri and season 2 in Texas. Treatments were blocked by replicate nested within run, nested within season (season/run/replicate).

Results

Genotypic differences were found for both membrane integrity and the enzyme viability assays under the tents (Table 2). REC45 (Fig. 1b) and RCI45 (Fig. 1c) decreased under tents compared with ambient field conditions (Table 2). REC45 was lower for Sicot 53 for leaf tissue grown under ambient field conditions and this difference was greater under the tents (Fig. 1b) indicating relatively higher membrane integrity compared with Sicala 45. Similarly, RCI45 was slightly lower for Sicot 53 under tents compared with Sicala 45 (Fig. 1c).


Fig. 1: Mean Relative Electrical Conductivity at (a) 25oC (REC25) or (b) 45oC (REC45) in the Water Bath, (c) Relative Cellular Injury at 45oC in the Water Bath (RCI45), Absorbance at 530 nm Measured at 25oC (d) (Abs25) or 40oC (e) Abs40 in the Water Bath and (f) Relative Absorbance at 530 nm Measured at 40oC (RAbs40) in the Water Bath for Cotton Cultivars Sicot 53 and Sicala 45 under Ambient Field Conditions (Control) and under Tents Pooled for all

Measurements in Seasons 1 and 3 in Narrabri and Season 2 in Texas. The Vertical Lines in (b), (c), (e) and (f) Represent the Least Significant Temperature Treatment by Cultivar Interaction at P=0.050

An interaction between cultivar and tent treatment was determined for the enzyme viability assay at 40oC in the water bath (Table 2). For Sicot 53, enzyme viability was higher for leaf material collected under the tents compared with ambient field conditions at high water bath temperatures (Fig. 1e). Conversely enzyme viability was lower for leaf material collected under the tents compared with ambient field conditions for Sicala 45 (Fig. 1e). As such, Abs40 was lower for Sicot 53 under ambient field conditions but higher under tents compared with Sicala 45 (Fig. 1e). These genotype and tent treatment differences were similarly reflected in calculation of RAbs40 (Fig. 1f).

No genotypic differences were determined for leaf tissue grown under ambient field conditions or under the tents and subsequently incubated at control (25oC) water bath temperatures measured using the membrane integrity (REC25) or enzyme viability (Abs25) assays (Table 2). Genotypic differences were found for all physiological measurements taken on leaves under ambient field conditions and under the tents (Table ). Photosynthesis (Fig. 2a) and electron transport rate (Fig. 2b) were decreased while stomatal conductance (Fig. 2c) was increased and under tents compared with ambient field conditions (Table ). The decrease in photosynthesis under tents compared with ambient field conditions was greater for Sicala 45 compared with Sicot 53 (Fig. 2a). Similarly, the decrease in electron transport rate was slightly higher for Sicala 45 compared with Sicot 53 under tents (Fig. 2b). The increase in stomatal conductance under tents compared with ambient field conditions was greater for Sicot 53 compared with Sicala 45 (Fig. 2c). No inherent genotype differences were determined for photosynthesis, electron transport rate or stomatal conductance under ambient (control) field conditions (Fig. 2).

l.s.d. Control Tent

RCI 45

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Sicot 53 Sicala 45

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30

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l.s.d. Control Tent

RAbs

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40

60

80

100

120

140

(a)

(b)

(c)

(d)

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Fig. 2: Mean (a) Photosynthesis (b) Electron Transport Rate or (c) Stomatal Conductance for Cotton Cultivars Sicot 53 and Sicala 45 under Ambient Field Conditions (Control) and under Tents Pooled for all Measurements in Seasons 1 and 3 in Narrabri and Season 2 in Texas. The Vertical Lines in (a),

(b) and (c) Represent the Least Significant Temperature Treatment by Cultivar Interaction at P=0.050.

DISCUSSION

In this study, laboratory assays for membrane integrity and enzyme viability were successfully implemented to resolve differences between genotypes with previously determined heat tolerance under field conditions. No genotypic differences were determined for leaf material collected under ambient field conditions (Fig. 1). However, exposure of plants to in-situ high temperatures under tents resolved genotypic differences for membrane integrity and enzyme viability. Consistent with previously determined relative heat tolerance under field conditions, Sicot 53 outperformed Sicala 45 for cell membrane integrity (P=0.007) and enzyme viability (P<0.001) (Table 2) as well as photosynthesis (P=0.046), electron transport rate (P=0.057) and stomatal conductance (P=0.036) (Table ) when exposed to high temperatures under tents.

Imposition of tents increased daily maximum air temperatures between 6 and 20oC, with a daily maximum average of 5.3oC higher than the control and this increase in temperature was associated with a genotype specific change in membrane integrity and enzyme viability. Exposure to elevated temperature under tents improved the resolution of the membrane integrity assay (Table 2) where Sicot 53 outperformed Sicala 45 for REC45 (Fig. 1b). These cultivar differences were similarly reflected in calculation of RCI45 (Table 2). The improvement in genotypic resolution under tents for the membrane integrity assays indicates that resolution of genotypic differences for biochemical performance are best detected in the presence of stress, a notion similarly supported by Ashraf et al., (1994), Ismail and Hall (1999) and Rahman et al., (2004).

l.s.d. Control Tent

Sto

mat

al c

ondu

ctan

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H20

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s-1

)

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Pho

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sis

(µm

ol C

O2 m

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Ele

ctro

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rt ra

te (µ

mol

e-1

m-2

s-1

)

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220

240

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280

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(c)


TABLE 2: F TEST P VALUES FOR RELATIVE ELECTRICAL CONDUCTIVITY (REC25, REC45), RELATIVE CELLULAR INJURY (RCI45), ABSORBANCE AT 530 NM (ABS25, ABS40) AND RELATIVE ABSORBANCE AT 530 NM (RABS40) FOR COTTON CULTIVARS SICOT 53 AND SICALA 45 GROWN UNDER AMBIENT FIELD CONDITIONS OR UNDER TENTS,

POOLED FOR ALL MEASUREMENTS TAKEN IN SEASONS 1 AND 3 IN NARRABRI AND SEASON 2 IN TEXAS

Biochemical Measurement Cultivar Tent Cultivar. Tent REC25 n.s. n.s. n.s. REC45 n.s. 0.023 0.007 RCI45 n.s. 0.005 0.077 Abs25 n.s. n.s. n.s. Abs40 0.004 n.s. <0.001

RAbs40 0.022 n.s. <0.001 Conversely, the genotypic response for enzyme viability changed under tents compared with ambient

field conditions. Although Abs40 was lower for Sicot 53 compared with Sicala 45 under ambient field conditions, Sicot 53 outperformed Sicala 45 under tents (Fig. 1e). This interaction was reflected for calculation of RAbs40 (Table 2). These results were similar to those reported by de Ronde et al. (1995) who attributed higher absorbance for heat stressed cotton compared with the control to a higher affinity for acclimation to high temperature stress in heat tolerant cotton cultivars. The reversal of genotypic performance under ambient field conditions and under tents indicates that the enzyme viability test for heat tolerance determination should be considered under in-situ high temperature stress, or hot growing regions for which the heat tolerant cultivars are being specifically selected.

To determine whether genotypic differences for biochemical performance translated to higher order physiology, gas exchange, fluorescence and water flux were evaluated under tents. Decreases in photosynthesis and electron transport coupled with increases in stomatal conductance under tents indicate that the temperature stress imposed by tents was sufficient to significantly alter physiological performance (Fig. 2). Sicot 53 was found to outperform Sicala 45 for both biochemical assays (Table 2) and these differences are reflected physiological performance under tents (Table ).

TABLE 3: F TEST P VALUES FOR PHOTOSYNTHESIS, ELECTRON TRANSPORT RATE AND STOMATAL CONDUCTANCE MAIN EFFECTS AND INTERACTIONS FOR COTTON CULTIVARS SICOT 53 AND SICALA 45 UNDER AMBIENT FIELD CONDITIONS (CONTROL) AND UNDER TENTS POOLED FOR ALL MEASUREMENTS TAKEN IN SEASONS 1 AND 3 IN NARRABRI AND SEASON 2 IN TEXAS.

Physiological Measurement Cultivar Tent Cultivar. Tent Photosynthesis n.s. 0.006 0.046

Electron transport rate n.s. <.001 0.057 Stomatal conductance n.s. <.001 0.036

Decreases in net photosynthesis under elevated temperatures may be attributed to limited electron flow through photosynthetic and respiratory pathways (Wise et al., 2004) as a result of compromised membrane permeability (Gupta 2007) and a decline in the activity of rate-limiting enzymes, particularly those associate with photosynthetic and respiratory channels (Bjorkman et al., 1980; Burke et al., 1988; Salvucci and Crafts-Brandner 2004 b). Alternately, it may be proposed that genotype specific decreases in membrane permeability and deactivation of respiratory enzymes found in this study are indicative of an overall decrease in the functionality of a range of proteins and metabolic processes that are decreased with elevated temperature under tents. However, photosynthetic rates still require delivery of carbon dioxide to the photosystem and in this study, it is likely that stomata remained open to facilitate gas exchange and maintain leaf temperature under elevated temperature in the tents, as water was non-limiting (Lu et al., 1994).

CONCLUSION

In this study, genotypic differences determined for the membrane integrity and enzyme viability assays were most reflective of field performance when evaluated under in-situ high temperature stress in the field. Similar to previously determined heat tolerance in the field, Sicot 53 outperformed Sicala 45 under tents for both membrane integrity and enzyme viability and differences found using biochemical screens for heat tolerance helped to explain differences in photosynthesis, electron transport rate and stomatal conductance under tents. Thus, the biochemical assays were successfully implemented to resolve between a cultivar with relatively high heat tolerance and a cultivar with relatively lower heat tolerance under elevated temperatures in the field. The findings of this study indicate that biochemical screens for heat tolerance may be useful for initial screening of large populations but heat tolerance should be confirmed under contrasting thermal environments considering higher order physiological performance before selections are made for incorporation into breeding programmes.


ACKNOWLEDGEMENT

Thanks to Darin Hodgson, Jo Price, Jane Caton, Merry Errington, Warren Conaty, Erica Cuell and Aman Dayal in Narrabri and Texas A&M Aggies Josh Bynum, Ellen Batchelder, Joerdan Kennedy, Justin Scheiner and Matt Nors for technical assistance, particularly constructing and dismantling the tents. This work received partial financial support from the Cotton Catchment Communities Cooperative Research Corporation, the Australian Cotton Research and Development Corporation, The University of Sydney, Texas A&M University and CSIRO Plant Industry.

REFERENCES [1] Ashraf , M., Saeed, M. M. and Qureshi, M. J. (1994). Tolerance to high temperature in cotton (Gossypium hirsutum L.) at

initial growth stages. Environ. and Exp. Botany 34 (3), 275-283. [2] Azhar, F. M., Ali, M. M., Akhtar, M. M., Khan, A. A. and Trethowan, R. (2009). Genetic variability of heat tolerance, and

its effect on yield and fibre quality traits in upland cotton (Gossypium hirsutum L.). Plant Breed. 128, 356-362. [3] Bjorkman, O., Badger, M. R., and Armond, P. A. (1980). Response and adaptation of photosynthesis to high temperatures.

In 'Adaptation of plants to water and high temperature stress.' (Eds NC Turner and PJ Jackson) pp. 233-249. (John Wiley & Sons: New York)

[4] Burke, J. J., Mahan, J. R. and Hatfield, J. L. (1988). Crop-specific thermal kinetic windows in relation to wheat and cotton biomass production. Agron. j. 80 (4), 553-556.

[5] Constable, G. A., Reid, P. E. and Thomson, N. J. (2001). Approaches utilized in breeding and development of cotton cultivars in Australia. In 'Genetic Improvement of Cotton.' (Eds J J.N and S Saha) pp. 1-15. (Science Publishers, Inc: Mississippi State)

[6] Cottee, N. S., Tan, D. K. Y., Bange, M. P., Cothren, J. T. and Campbell, L. C. C. (2010). Multi-level determination of heat tolerance in cotton (Gossypium hirsutum L.) under field conditions. Crop Sci. 50 (6).

[7] De Ronde, J. A. and van der Mescht, A (1997). 2,3,5-Triphenyltetrazolium chloride reduction as a measure of drought tolerance and heat tolerance in cotton. South Afric. J. of Sci. 93, 431-433.

[8] De Ronde, J.A., van der Mescht A, and Cress WA (1995). The biochemical responses of six cotton cultivars to heat stress. South Afric. J. of Sci. 91, 363-366.

[9] Gupta, U. S. (2007). Membrane system. In 'Physiology of Stressed Crops' (Science Publishers: Enfield, NH, USA) 58-88 [10] Hodges, H. F., Reddy, K. R., McKinion, J. M., and Reddy, V. R. (1993). Temperature effects on cotton. Mississippi

Agricultural & Forestry Experiment Station, Mississippi State. [11] Ismail, A. M., and Hall, A. E. (1999). Reproductive-stage heat tolerance, leaf membrane thermostability and plant

morphology in cowpea. Crop Sci. 39, 1762-1968. [12] Khan, A. I., Khan, I. A., and Sadaqat, H. A. (2008). Heat tolerance is variable in cotton (Gossypium hirsutum L.) and can

be exploited for breeding better yielding cultivars under high temperature regimes. Pak. J. of Botany. 40, 2053-2058. [13] Lopez, M., Gutierrez, M. V., El-Dahan, M. A. A., Leidi, E. O. and Gutierrez, J. C. (2003). Genotypic variation in response

to heat stress in Upland cotton. In 'Proceedings of the 3rd World Cotton Conference', 2003, Capetown, South Africa, pp. 104-108

[14] Lu, Z., Radin, J. W., Turcotte, E. L., Percy, R. and Zeiger, E. (1994). High yields in advanced lines of Pima cotton are associated with higher stomatal conductance, reduced leaf area and lower leaf temperature. Physiol. Planta. 92, 266-272.

[15] Rahman, H., Malik, S.A. and Saleem, M. (2004). Heat tolerance of upland cotton during the fruiting stage evaluated using cellular membrane thermostability. Field Crops Res. 85, 149-158.

[16] Reddy, V.R., Baker, D.N., and Hodges, H.F. (1991). Temperature effects on cotton canopy growth, photosynthesis and respiration. Agron. J. 83, 699-704.

[17] Reid, P.E., Thomson, N.J., Lawrence, P.K., Luckett, D.J., McIntyre, G.T. and Williams, E.R. (1989). Regional evaluation of cotton cultivars in eastern Australia, 1974-85. Austr. J. Expe. Agric. 29, 679-689.

[18] Saadalla, M.M., Quick, J.S., and Shanahan, J.F. (1990). Heat tolerance in winter wheat: II. Membrane thermostability and field performance. Crop Sci. 30 (6), 1248-1251.

[19] Salvucci, M.E., Crafts-Brandner, S.J. (2004a). Mechanism for deactivation of Rubisco under moderate heat stress. Physio. Planta. 122, 513-519.

[20] Salvucci, M.E. and Crafts-Brandner, S.J. (2004b). Relationship between the heat tolerance of photosynthesis and the thermal stability of Rubisco activase in plants from contrasting thermal environments. Pl. Physio. 134, 1460-1470.

[21] Sullivan, C.Y. (1971). Mechanisms of heat and drought resistance in grain sorghum and methods of measurement. In 'Sorghum in the Seventies.' (Eds NGP Rao and LR House) pp. 247-284. (Oxford & IBH Publishing Co: New Delhi, India)

[22] Wise, R.R., Olson, A.J., Schrader, S.M., and Sharkey, T.D. (2004). Electron transport is the functional limitation of photosynthesis in field-grown Pima cotton plants at high temperature. Pl. Cell and Environ. 27, 717-724.

Genetic Variability in Single Plant Selections for Improving Drought Tolerance

in Upland Cotton

Suman B. Singh, A.H. Prakash and Amol A. Karpe

Central Institute for Cotton Research, Nagpur, India

Abstract—Drought tolerant is one of the most important environmental stress that limits the plant growth and development and in turn productivity worldwide. Work on development of drought tolerant genotypes was initiated using drought tolerant sources. Screening of 112 single plant selections in two sets of experiment for physiological and biochemical parameters resulted in identification of few single plant selections. Selections showed significant difference for seed cotton yield ranging from 408.86 to 1803.86 kg/ha. The lines were separated based on the differential expression of biochemical factors in control and stress plants. The difference was expressed as per cent increase/decrease over the control. Considering the holistic approach viz., physiological, biochemical and yield per se eight lines namely, DTS 39-09, DTS 62-09, DTS 44-09, DTS 67-09, DTS 155-09, DTS 104-09, DTS 100-09 and DTS 108-09 were found to be tolerant. Selections DTS 67-09 identified as drought tolerant in trial 1 recorded good yield and fibre quality with 26.9 mm 2.5% span length, 23.5 g/tex fibre strength and 4.2 10-6 g/in micronaire while DTS 104-09 in second trial recorded good yield and fibre quality with 27.2 mm 2.5% span length, 18.7 g/tex fibre strength and 4.2 10-6 g/in micronaire. The results suggest that selection of genotypes based on drought susceptibility index was effective in development/identification of drought tolerant genotypes.

INTRODUCTION

Cotton is the most important fibre crop and the basic input to the textile industry. In India, cotton is grown in about 11.0 million ha of which more than 70 per cent area is rainfed. Maharashtra has an estimated area of 3.503 million ha under cotton, predominantly under rainfed cultivation (97%). The rainfed tract of central India receives about 500-1200 mm rainfall annually. Uneven distribution of rainfall with prolong dry spells during critical crop growth phases considerably affects growth and development leading to low yield particularly in shrink-swell soils. Thus a rainfed-cotton cultivar needs to withstand extended period of water stress and able to utilize rain when it occurs. Late maturing cultivars have shown to meet these requirements (Stiller et. al., 2004) and genotype with okra leaf traits have also been successful (Stiller et. al., 2004, Thomson, 1994).

Physiological traits associated with WUE or stress tolerance have not been used extensively in plant breeding. This is due to the difficulties associated with measuring these traits on large number of plants, low heritability and complex relationships between these traits and yield (Hall et. al., 1994). It has been well established that plant accumulates a variety of osmo-protectant solutes as an adaptive mechanism to environmental stress such as salinity (Hayashi et al., 1997), water deficit (Rhodes and Hanson, 1993), temperature extremes (Hayashi et. al., 1997). Osmo-protectant solutes includes (i) sugar and sugar alcohols i.e. polyols (Thomas et. al., 1995).(ii) proline (Aspinall and Paley, 1981) and a number of quaternary ammonium compounds and tertiary sulphonium compounds (Rhodes and Hanson, 1993).

Developing plants with higher levels of natural solute accumulating capacity to increase stress tolerance by selection between cultivars or isogenic lines and / or by genetic engineering of plants to accumulate high levels of polyols (Thomas et. al., 1995) and glycine betaine (Hayashi et. al. 1997) is one way to increase plant tolerance to stress.


In present study genotypes from the 50 germplasm lines screened for water use efficiency (WUE) and grouped into high, medium and low WUE groups. F1 crosses were affected using lines with high water

13

Genetic Variability in Single Plant Selections for Improving Drought Tolerance in Upland Cotton 81

use efficiency and genotypes with broad genetic base. Crosses were evaluated for drought tolerance efficiency (DTE), seed cotton yield and other economic characters. Single plant selections were made in F2 of the crosses which recorded high drought tolerance efficiency. The selections were tested in two sets (set 1 and set 2) of experiment in pots with 49 and 62 single plant selections under simulated drought and non-stressed conditions in pots in different years. Simultaneously these selections were also tested under field conditions in randomized block design with three replications. Five random plants were tagged from each plot for recording observations on number of bolls per plant, boll weight (g) and seed cotton yield (kg/ha).The data was subjected to statistical analysis by adopting standard procedure of Panse and Sukhatme (1985).

Observations on physiological (chlorophyll content and membrane stability) and biochemical parameters (reducing sugars, amino acid and phenols) were recorded during peak flowering stage. Chlorophyll a and b were estimated as per the method out lined by Arnon (1949) and membrane stability index was measured by the method described by Sullivan (1971).


Single plant selections (112 no.) tested in two different sets for experiment (in pots) under simulated drought differed significantly for chlorophyll content, membrane stability, reducing sugars, amino acids and phenols. Selection DTS 83-09 recorded significantly higher seed cotton yield (2073 kg/ha) followed by DTS 36-09 (1827 kg/ha), DTS 75-09 (1795 kg/ha), DTS 88-09 (1751 kg/ha), DTS 85-09 (1714 kg/ha) and DTS 67-09 (1701 kg/ha) under field condition in first set (Table 1). However, under simulated drought (in pots) DTS 39-09, DTS 67-09, DTS 36-09, DTS 82-09, DTS 85-09, DTS 88-09, DTS 62-09 selections showed their superiority towards higher yields. In second set, DTS 119-09 (1803 kg/ha), DTS 102-09 (1775 kg/ha), DTS 104-09 (1750 kg/ha), DTS 116-09 (1694 kg/ha) and DTS 151-09 (1681 kg/ha) recorded significantly higher seed cotton yield under field trial (Table 2) while under stressed condition selections DTS 103-09, DTS 131-09, DTS 155-09, DTS 108-09, DTS 104-09, DTS 107-09 were the better performers. The results are in agreement with the finding of Singh et.al. (2006) and Rajarajeswari(1995).

Among biochemical and physiological parameters, the SPS showed considerable variability for these traits as they were found to increase or decrease with the increase in the stress level. Higher reducing sugars and amino acid content and less of phenols in a particular genotype is considered as drought tolerant. Similarly positive chlorophyll value and negative membrane stability index help in rating a genotype as tolerant or susceptible. The total chlorophyll content varied significantly among the SPS tested but reduction was recorded after stress. DTS 21-09, DTS 44-09, DTS 39-09, DTS 62-09, DTS 67-09, DTS 92-09 and DTS 76-09 did not show any variation for total chlorophyll content however, some of them maintained higher level of chlorophyll under stress (5 to 44 per cent increase) over the control. Similar results with increase level of chlorophyll content and physiological activities in high yielding genotypes were reported by Gadallah (1995) and Krasichkova et. al.(1989). High yielding SPS under field condition namely DTS 88-09, DTS 36-09 and DTS 6-09 had larger effect under stress i.e. -41 to -48 per cent reduction over the non-stressed condition.

CSI (maintenance of higher chlorophyll content under high temperature), a highly desirable characteristic under moisture stress conditions, was significantly higher in selection namely DTS 44-09, DTS 01-09, DTS 15-09, DTS 39-09, DTS 62-09, DTS 66-09, DTS 72-09, DTS 70-09, DTS 36-09, DTS 79-09, DTS 80-09,DTS 24-04, DTS 83-09, DTS 84-09, DTS 86-09, DTS 89-09 and DTS 90-09 under both stressed and non-stressed conditions.

Membrane stability index ranged from 27.1 to 65% and 23.2 to 88.3 per cent under non-stressed and stressed conditions respectively. The electrolyte leakage has been used successfully to measure membrane integrity in plants subjected to a variety of environmental stresses (McKersie and Tomes 1980; Blum and Ebercon 1981, McKersie et. al. 1982; Sapra and Anade 1991, Agarie et. al. 1995). Kuo and collegues (1993) showed that yields of vegetable species with low electrolyte leakage were more stable in different growing conditions.


In general there was an increase in the membrane stability index, amino acids and reducing sugar from non-stress to stress condition. Accumulation of solutes such as sugars, amino acids, organic acids and ions during drought stress have been observed in many crops. One of the most notable changes is the synthesis and accumulation of low molecular weight, osmotically active compounds such as sugar, alcohols, amino acids, organic acids and glycine betaine (Turner 1979, Yancy et. al. 1982, Morgan 1984, Good and Zaplachinski 1994; Bartels and Sunkar 2005. The accumulation of these compounds lead to osmotic adjustments as indicated by an increase in the intra-cellular osmotic potential of the cell (Morgan, 1984).

Based on these physiological and biochemical parameters the selections were grouped / rated as good, moderate and susceptible for individual characters (Table 3). The selections were rated against LRA 5166 as standard (moderately tolerant to moisture stress). The selections which represented good or moderate category for the traits were selected. Few promising selections were identified which showed more than 25% and 90% increase over the check Rajat and LRA 5166. Selection DTS 67-09 (identified as drought tolerant) also recorded good yield (1701 kg/ha) and good fibre quality with 26.9 mm 2.5% span length, 23.5 g/tex fibre strength and 4.2 10-6 g/in micronaire . DTS 25-09, DTS 44-09 and DTS 74-09 cultures which recorded more than 24.4 g/tex fibre strength and S/L ratio of >0.80 as against LRA 5166 which recorded fibre strength of 21.2 g/tex and S/L ratio of 0.75 (Table 4). In the second set, selections were identified having more than 50 % and 100% increase over the check Rajat and LRA 5166. Selection DTS 104-09, identified as drought tolerant, also recorded good yield (1750 kg/ha) and good fibre quality (27.2 mm 2.5% span length, 18.7 g/tex fibre strength and 4.2 10-6 g/in micronaire). DTS 96-09, DTS 143-09 and DTS 106-09 had more than 21.4 g/tex fibre strength and S/L ratio of >0.75 as against LRA 5166 which recorded fibre strength of 16.9 g/tex and S/L ratio of 0.69 (Table 5).

Thus, single plant selections namely DTS 39-09, DTS 44-09, DTS 62-09, DTS 67-09, DTS 100-09, DTS 104-09, DTS 108-09 and DTS 155-09 were identified as tolerant lines through holistic approach of physiological, biochemical and yield per se was analyzed. These entries can be advanced further for detailed studies and promotion for multilocation evaluation trials under stress conditions.

TABLE 1: PERFORMANCE OF TOP TEN SINGLE PLANT SELECTION IN FIELD TRIAL OF SET 1

S. No. SPS SCY (kg/ha)

% Increase over Check B. Wt. (g)

GOT (%)

2.5% SL(mm) FS (g/tex)

Micronaire (10-6 g/in) Rajat LRA 5166

1 DTS 83-09 2073.19 55.11 139.11 3.2 39.4 27.9 21.5 4.3 2 DTS 36-09 1827.04 36.69 110.72 3.7 38.9 25.3 22.4 4.0 3 DTS 75-09 1792.93 34.14 106.79 3.3 38.8 24.9 20.6 4.3 4 DTS 88-09 1751.73 31.06 102.04 4.4 40.5 27.5 18.6 4.1 5 DTS 85-09 1714.23 28.25 97.71 3.1 42.1 31.7 19.1 3.8 6 DTS 67-09 1701.16 27.27 96.20 3.6 42.4 26.9 23.5 4.2 7 DTS 69-09 1690.27 26.46 94.95 3.8 38.2 - - - 8 DTS 6-09 1679.20 25.63 93.67 4.3 37.2 27.3 22.5 4.0 9 DTS 82-09 1671.40 25.05 92.77 3.2 39.7 26.3 20.1 3.5 10 DTS 71-09 1669.34 24.89 92.52 3.4 42.0 - - - Rajat 1336.55 - - 3.3 38.9 - - - LRA 5166 867.010 - - 2.7 39.0 28.0 21.2 4.6 C.V 20.07

TABLE 2: PERFORMANCE OF TOP TEN SPS IN TRIAL II

S. No. SPS SCY (kg/ha) % Increase over Check B. Wt. (g) GOT (%) MHL (mm) Rajat LRA 5166

1 DTS 119-09 1803.36 60.19 141.13 2.8 38.9 22.3 2 DTS 102-09 1775.25 57.69 137.37 2.7 39.8 25.0 3 DTS 104-09 1750.64 55.51 134.08 4.0 40.1 27.2 4 DTS 116-09 1694.99 50.56 126.99 3.1 42.6 19.3 5 DTS 151-09 1681.65 49.38 124.86 4.1 40.6 24.5 6 DTS 150-09 1676.04 48.88 124.11 3.5 41.6 21.5 7 DTS 110-09 1672.76 48.59 123.67 3.4 38.7 24.2 8 DTS 103-09 1666.67 48.05 122.85 3.7 42.7 28.8 9 DTS 131-09 1640.35 45.78 119.33 3.3 38.7 24.2 10 DTS 120-09 1616.39 43.58 116.13 4.0 37.7 26.0 Rajat (c ) 1125.73 - - 3.0 41.8 21.1 LRA 5166 ( c ) 747.86 - - 3.0 42.8 26.3 C.V. 19.28

Genetic Variability in Single Plant Selections for Improving Drought Tolerance in Upland Cotton 83

TABLE 3: EVALUATION FOR DROUGHT TOLERANCE PARAMETERS

Characters Good Moderate Chlorophyll stability index (%)

DTS 21, 44, 39, 62, 67, 92, 76 LRA5166, 72, 73, 74, 75, 47, 42, 38, 81, 82, 14, 83, 5

Membrane stability index (%)

DTS40, LRA5166, 44, 41, 1, 39, 65, 7, 6, 77, 78, 81, 24, 86, 88, 91

23, 6, 64, 66, 67, 36, 70, 73, 92, 38, 79, 83, 84,85, 90, 91

Reducing sugar mg/g DTS6,LRA5166,44,41,39,15,66,70,7,79,24,37,84,88,91 25, 40, 64, 72, 73, 47, 42, 78, 43, 80, 89, 90 Amino acid mg/g DTS 25, 23, 65, 66, 72, 42, 76, 78, 80, 82, 85 44,1,62,63,64,67,92,47,38,76,43,79,24,86,87,88,77 Phenols mg/g DTS 44, 1, 39, 15, 19, 62, 63, 65, 74, 92, 75, 77, 14 26, 21, 40, 23, 6, LRA, 41, 64, 66, 67, 36, 70, 73, 92,

42, 76, 7, 78, 43, 80, 84, 86, 87, 89, 90 Yield stability DTS 25, 23, LRA,5166, 41, 1,39, 15, 19, 62, 63, 65, 66,

67, 36, 70, 72, 43, 79, 24, 82, 14, 84, 85, 87, 88, 90, 91, 726, 21, 40, 6, 44, 47, 42, 76, 78, 81, 86

TABLE 4: TOP TEN SPS WITH GOOD FIBRE QUALITY IN TRIAL I

S. No. SPS SCY (kg/ha) 2.5%SL (mm) Maturity UR Micronaire (10-6 g/in) FS (g/tex) Elongation(%) S/L ratio1 DTS 25-09 756.45 27.3 0.76 48.2 4.2 25.3 6.0 0.93 2 DTS 44-09 1495.75 27.3 0.73 48.6 3.9 24.1 5.4 0.88 3 DTS 74-09 1509.01 25.9 0.84 49.1 4.1 24.4 5.9 0.94 4 DTS 73-09 1399.63 24.1 0.74 52.1 3.7 23.9 6.2 0.99

5 DTS 67-09 1701.16 26.9 0.77 48.9 4.2 23.5 6.0 0.87 6 DTS 87-09 1048.03 27.5 0.82 48.0 4.0 23.5 5.6 0.85 7 DTS 90-09 1475.72 28.7 0.79 49.7 4.4 23.3 5.0 0.81 8 DTS 84-09 1210.46 25.4 0.83 52.4 4.8 23.2 5.4 0.91 9 DTS 91-09 1584.96 28.4 0.72 49.4 3.7 23.2 5.1 0.81 10 DTS 72-09 1325.44 31.9 0.68 45.6 3.6 23.2 5.6 0.72

LRA 5166 867.01 28.0 0.80 47.2 4.6 21.2 5.4 0.75

TABLE 5: PERFORMANCE OF TOP TEN SINGLE PLANT SELECTIONS IN TRIAL I

S. No. SPS SCY (kg/ha) % Increase over Check B. Wt. (g)

GOT (%)

2.5% SL (mm)

UR (%)

FS (g/tex)

Micronaire (10-6 g/in) Rajat LRA5166

1 DTS 43-09 1534.31 31.88 113.26 3.6 35.9 30.0 46 19.2 3.6 2 DTS 83-09 1436.11 23.44 99.61 4.1 36.0 27.2 50 17.5 3.8 3 DTS 90-09 1348.10 15.88 87.38 3.7 37.5 28.0 51 20.4 3.9 4 DTS 79-09 1324.07 13.81 84.04 3.1 37.5 25.5 52 19.3 4.1 5 DTS 86-09 1285.88 10.53 78.73 3.4 38.8 24.5 51 17.6 3.7 6 DTS 66-09 1255.55 7.92 74.51 3.7 35.4 24.4 52 18.2 4.2 7 DTS 77-09 1230.86 5.80 71.08 4.1 36.4 26.3 48 22.1 3.8 8 DTS 69-09 1212.97 4.26 68.59 3.9 39.7 26.3 49 17.9 4.3 9 DTS 62-09 1190.06 2.26 65.41 3.0 35.7 25.4 50 18.6 4.3 10 DTS 76-09 1157.05 - 60.82 3.7 36.7 23.3 49 20.0 3.8

LRA 5166 719.44 3.1 35.3 25.4 50 19.2 3.6 Rajat 1163.34 3.7 34.1 25.3 50 19.2 4.3 C.V. 21.40

REFERENCES [1] Arnon, D. I. (1949) - Copper enzymes in isolated chloroplasts. Polyphenols Oxidase in Beta vulgaris. Plant Physiol. 24: 1-

15. [2] Ashraf, M., Saeed, M. M. and Qureshi, M. J. (1994) - Tolerance to high temperature in cotton at initial growth stage. Env.

Exp. Bot. 343:275-283. [3] Aspinall, D and Paleg, L. D. (1981) - In “The Physiology and Biochemistry of Drought Resistance in Plants” Edited by

L.G. Paleg and D. Aspinall. Academic Press, Sydney. pp. 205-241. [4] Baretls, D. and Sunkar, R. (2005) - Drought and salt tolerance in plants. Crit. Rev. Plant Sci., 24:23-58. [5] Devendra Singh, Singh,S. B. and Ahuja, S. L. (2006) - Screening of cotton genotypes for drought tolerance based on stress

susceptibility index. J. Cotton. Res. Dev. 20:(1) 89-90. [6] Gadalloh, M. A. A. (1995) - Effect of water stress, abscissic acid and proline on cotton plants. J. Arid Envt. 30:(3), 315-325. [7] Good, A. G and Zaplachinski, S. T.(1994) - The effect of drought stress on fresh amino acid accumulation and protein

synthesis in Brassica napus, Physiol. Plant, 90:9-14. [8] Hall, A. E., Richards, R. A., Condon, A. G., Wright, G. C., and Farquhar. G. D. (1994) - Carbon isotope discrimination and

plant breeding. p. 18-113. In. J. Janick (ed.) Plant Breeding Review, Vol. 12. John Wiley and Sons. New York. [9] Hayashi, N., Alia, Mustardy, Deshnium, L., Ida P. M. and Murata, N. (1997) - The Plant J. 2. 133-142.


[10] Krasichkova, G. V., Asoeva, L. M., Giller, Y. U. E. and Sanginov, B. S. (1989) - Photosynthetic system of G. barbadense at the early stages of development. Doklady Vsesovuznoi Ordena. Trudovogo Krasnogo Znameni Akademmi Sel skokhozya istvennykh Nauk. Imen V. I. Lenina. No. 12, 9-11, Institute Fiziologii Bio fiziki. Rastenil, Academy of Sciences, Tadjik SSR. Dushanbe. Tadjik SSR.

[11] Morgan, J. M. (1984) - Osmoregulation and water stress in higher plants. Annu. Rev. Plant Physiol., 35:299-319. [12] Panse, V. G. and Sukhatme, P. V. (1985) - Statistical methods for Agricultural Workers, ICAR, New Delhi. [13] Rajarageshwari, V. (1995) - Evaluation of cotton genotypes for drought tolerance under rainfed conditions. Annals of Plant

Physiology, 9(2): 109-112. [14] Ranney, T. G., Bassuk, N. L. and Whitlow, T. H. (1991) - Osmotic adjustment and solute constituents in leaves and roots of

water stressed cherry (Prunus) trees. J. Am. Soc. Hort. Sci. 1164: 684-688. [15] Rekika, D., Nachit, M. M., Araus, J. L., and Monneveux, P. (1998) - Effects of water deficit on photosynthetic rate and

osmotic adjustment in tetreploid wheats. Photosynthetica 35: 129-138. [16] Rhodes, D. and Hanson, A. D. (1993) - Annu. Rev. of Plant Physiol and Plant Mo. Biol. 44. 357-384. [17] Stiller, W. N., Reid P. E., and Constable, G. A. (2004) - Maturity and leaf shape as traits influencing cotton cultivar

adaptation to dryland conditions. Agron. J. 96: 656-664. [18] Sullivan, C. Y. (1971) - Techniques for measuring plant drought stress. In. K.L. Larson and J.D. Eastin (ed.) Drought

injury and resistance in crops. Crop Sci. Soc. Am. Madison, Wis. [19] Tan, W. X., Blake, T. J. and Boyle, T. J. B. (1992) - Drought tolerance in faster and slower growing black spruce (Picea

mariana) progenies: II osmotic adjustment and changes of soluble carbohydrate and amino acids under osmotic stress. 85:645-651.

[20] Thomson, N. J. (1994) - Commercial utilization of the okra leaf mutant of cotton-the Australian experience. p. 393-401. In G.A.Constable and N.W. Forrester (ed.) Proc. World Cotton Research Conf.-1, 14-17 Feb 1994, Brisbane, A.U. CSIRO, Melbourne, V.I.C.

[21] Thomas, J. C., Sepahi, M. Arendall, B and Bohnert, H. J. (1995) - Plant, Cell Env. 18:801-806. [22] Turner, N.C. (1979) - Drought resistance and adaptation to water deficits in crop plants. In: stress Physiology in crop

plants, Mussell, H. and Staples, R.C. (eds). Wiley-interscience, New York, pp. 181-194. [23] Wang, Z., Quebsdeaux, B., and Stutte, G.W. (1995) - Osmotic adjustment: Effect of water stress on carbohydrate in leaves,

stems and roots of apple. Aust. J. Plant. Physiol. 22:747-754. [24] Yancy, P. H., Clark, M. E., Hand, S. C., Bowlus, R. D. and Somero, G. N. (1982) - Living with water stress, Evolution of

osmolyte systems- Science, 217:1214-1222. [25] Zhang, B. L. and Archbold, D. D. (1993) - Solute accumulation in leaves of a Fragaria chilonsis and a F. virginiana

selection responds to water deficit stress. J. Am. Soc. Hort. Sci. 118:280-285.

Genetic Parameters of Physiological Traits for Salinity Tolerance in Diverse Genotypes of Cotton

(Gossypium hirsutum L. and Gossypium barbadense L.)

Hosseini Gholamhossein1 and Behdarvand Pejman2 1Cotton Research Institute of Iran

2Department of Botany, University of Pune- 411007, India

Abstract—Genetic and physiological parameters of different traits related to salinity tolerance in six cotton (Gossypium hirsutum L. and Gossypium barbadense L.) genotypes and their progenies were estimated using diallel crosses which conducted at Agricultural and Resources Research Center of Mazandaran, Iran and Department of Botany, University of Pune, India during 3 years ending to 2009. Along with nutrition by normal Hogland’s solution in non-saline condition, incremental levels of NaCl to Hogland’s solution in a sand culture was added until electrical conductivity of 24 dSm-1 was attained inducing salinity stress and caused osmotic shock. Combined analysis based on two salinity levels revealed significant salinity-level effects for traits. High ratios of σ2A / (σ2A + σ2D) and high narrow-sense heritability estimates were observed for root length, plant height, Na+, K+, Ca2+, K+/Na+, Ca2+/Na+, root length/shoot height and Tolerance Index (TOL), indicating the more involvement of genes additive effects in their genetic control. High differences of [σ2g / (σ2g + σ2e)] - [2 σ2gca + σ2sca / (σ2g + σ2e)] were observed for K+/Na+ and TOL, indicated non-allelic effects in their genetic control. Negative and high index of SI for Na+ indicated that its mean in a saline environment was more than two times from the mean in a non-saline environment. Low estimates of negative SI index for root length, Ca2+ indicated the effects of a saline environment for these traits were better than the other traits. The results of factor analysis indicated that selection for morphological traits, specifically; that selection based on K+, Ca2+ and K+ / Na+ should be more efficient than other traits. Cluster classification of genotypes by means of principle component analysis method on the basis of value of correlation matrix distinguished genotypes Sindose-80 and Sindose-80 × Siokra from other genotypes in salinity tolerance. Low estimates of the tolerance index (TOL) in the above genotypes are also conforming of their salinity tolerance in early stages of growth.

INTRODUCTION

Cotton is a dual-purpose (fiber and oil) crop. It is moderately salt-tolerant crop with a salinity threshold level 7.7 dSm-1. Its growth and seed yield is severely reduced at high salinity levels. However, inter and intra-specific variation for salt tolerance in cotton is valuable and thus can be exploited through specific selection and breeding for enhancing salt tolerance of the crop. Salinity of agricultural lands and irrigation water is one of the factors of environment, which limits the growth and yield of cotton and other crops in many arid and semi-arid regions of the world (Postel, 1989). The stresses imposed by salinity are mainly due to ion compositions and concentrations in rhizosphere and also in plant tissues (Volkmar et al., 1997). Information on the mechanisms involved in salt tolerance and their genetic control is essential to facilitate selection for characteristics and to design an efficient breeding programme for genetic improvement of salinity tolerance (Ashraf, 1994). Plant breeders have focused on finding new resistant cultivars because of detrimental effects of saline soil and irrigation water to reduce quantitative and qualitative cotton crop. Identifying proper selection criteria for salinity tolerance is also a major problem. In this respect, some selection criteria including Geometric Mean Productivity (Fischer and Murrer, 1978), Stress Tolerance Index (Fernandez 1993) and Tolerance Index (Rosielle and Hamblin, 1981) have been defined. Significant general combining ability (GCA) and specific combining ability (SCA) effects of salinity resistance have been reported in Gossypium hirsutum (Saghir and et al., 2002). The objective of the present study is to determine the important genetic parameters for shoot dry weight (g/ plot), root length (cm), plant height (cm), shoot fresh weight, Ca2+, K+, and Na+ contents (mg g-1),Ca2+/Na+ and K+/Na+,shoot dry weight / shoot fresh weight(SDW/SFW), root length/shoot height (RL/SH) and Geometric Mean Productivity (GMP), Stress Tolerance Index (STI) and Tolerance Index (TOL) for shoot dry weight in order to select a suitable breeding program for cotton breeding line and cultivars.

14



A complete diallel cross of six cotton genotypes (Gossypium hirsutum L. & Gossypium barbadense L.) viz Delinter, Sindose-80, Bulgare-539, Termez-14, B-557, Siokra having diverse genetic origin was conducted over two years to determine the potential for improvement in yield, its components, oil and fiber quality traits by means of genetic analysis, combining ability, heritability and heterotic effects. The detailed studies were based on F1 generations whereas crossed seed in first year were used for F1 generation in the second year. The successful hybrids recognized and distinguished by morphological markers such as flower colour, spot position and its colour in petal, leaf colour and it’s shape (Fig.1,2), fiber colour, seed linter, and also molecular marker (SSR). Successful hybrids also exposed to salinity and non-salinity condition for selecting the resistant genotypes to saline environments. Six diverse cotton (Gossypium hirsutum L. and Gossypium barbadense L.) genotypes were crossed in a diallel fashion, and their 15 F1 progenies along with their parents were evaluated in sand cultures under normal and saline environments in a block design with three replications at the greenhouse during 3 years ending to 2009. Sterilized seeds were germinated in Petri dishes at 22° ± 3°C for 4 days. Eight uniform seedlings were transplanted into plots that separated in two sand boxes filled with washed and sterilized river sand, covered with polythene beads. After the establishment, five plants were maintained for evaluation. Temperatures during the experiment were averaged 33.21/ 10.6°C (day/night) and relative humidity was 31.43-75.04% and the photoperiod was 14 hrs. Plants were given deionized water up to 10 days after transplanting and saline and non-saline (control) grown plants were irrigated thereafter every 2 days with half-strength Hoagland’s nutrient solution (Hoagland and Arnon, 1950) with NaCl (EC = 22 dSm-1) and without it (EC = 0.88 dSm-1 ) and pH = 7. Electrical conductivity of the saline treatment was increased to the desired level by incremental addition of the salt over 10-day period to avoid osmotic shock to the seedlings. Plants in both environments were irrigated until saturated, with the excess solution allowed to drain under sandboxes. The plants in both environments were harvested 45 days after planting at 7-8 leaf stages. The characteristics such as shoot dry weight (SDW) in gr/plot, root length (cm),plant height (cm), shoot fresh weight in gr/plot, Na+, K+, and Ca2+ contents (mg g-1), K+/Na+, Ca2+ /Na+, shoot dry weight / shoot fresh weight(SDW/SFW), root length/shoot height (RL/SH), Geometric Mean Productivity(GMP), Stress Tolerance Index (STI) and Tolerance Index (TOL) for shoot dry weight were determined. The harvested plants thoroughly washed with distilled water then dried in an oven for 72 h at 80 °C to a constant weight. Plant samples were ground by mill and dried in a furnace at 500 °C for 2 hrs for ion extraction. Plant samples were added to 5mL of 2M HCl for digestion, and the digested solutions were filtered and diluted by distilled water. The final volume of each sample was 100mL. Sodium and K+ levels of each sample were measured by flame photometry and Ca2+ was measured by atomic absorption spectrophotometry (Isaac and Kerber, 1971). The selection criteria indices, including Geometric Mean Productivity as GMP = √ (Yp)×(Ys) (Fischer and Murrer, 1978),Stress Tolerance Index as STI = (Yp) × (Ys)/Yp 2 (Rosielle and Hamblin,1981) and Tolerance Index as TOL = Yp – Ys ( Fernandez, 1993 ) were calculated for yield of shoot dry weight in non-saline(Yp) and saline(Ys) environments. Tolerance Index (TOL) was also calculated for Ca2+, K+, Na+, Ca2+/Na+, and K+/Na. Data subjected to analysis of variance and means were compared by using the Least Significant Differences (LSD). Variations in general combining ability (GCA) of the parental lines and specific combining ability (SCA) of crosses for the measured characteristics were partitioned from the total genetic variance using Griffing’s Method II, Model I (Griffing, 1956) . The components of variance ratio as σ2A / (σ2A + σ2D) and high narrow-sense heritability [σ2A/(σ2A+σ2D+σ2e)] and [σ2A/(σ2g+σ2e)] were computed as a (σ2A,σ2D,σ2e) Estimated from diallel analysis) and ab(σ2g,σ2e Estimated from Randomized Complete Block Design) method for each characteristic to determine the relative importance of additive and non-additive gene effects respectively (Baker, 1978). The differences of variance ratios as [σ2g/(σ2g+σ2e)] b - [2σ2gca+σ2sca /(σ2g+σ2e)]ab and [2σ2gca+σ2sca/(2σ2gca+σ2sca+σ2e)] a were computed for each characteristic to determine the non-allelic effects in their genetic control. High-parent hetrosis was calculated as mean deviation of a cross performance from the mean of its superior parent (Mather and Jinks, 1982).

Genetic Parameters of Physiological Traits for Salinity Tolerance in Diverse Genotypes of Cotton 87

X1= Delinter X2 = Sindose-80 X3 = Bulgare-539 X4 = Termez-14 X5= B-557

X6 = Siokra Xij = X♂♀

X1= Delinter X2 = Sindose-80 X3 = Bulgare-539 X4 = Termez-14 X5= B-557

X6 = Siokra Xij = X♂♀


For ion composition, the parents and Siokra with 1.66 g/plot had superior mean for shoot dry weight, Delinter with 10.90 cm had superior mean for root length, Termez-14 with 25.74 cm had superior mean for plant height, Termez-14 with 10.81 g/plot had superior mean for shoot fresh weight, Sindose-80 with 15.68 mg g-1 had superior mean for Na+, Bulgare-539 with 24.67 mg g-1 had superior mean for K+, Delinter with 47.74 mg g-1 had superior mean for Ca2+.

TABLE 1: ANALYSIS OF VARIANCE FOR SHOOT DRY WEIGHT, ROOT LENGTH, PLANT HEIGHT, SHOOT FRESH WEIGHT, SHOOT DRY WEIGHT NA+, K+, CA2+, IN A SALINE ENVIRONMENT (MEAN OF THE SQUARES)

S.O.V D.F

Shoo

t D

ry

Wei

ght

(SD

W)

Roo

t L

engt

h (R

L)

Plan

t H

eigh

t (P

H)

Shoo

t Fr

esh

Wei

ght

(SFW

) Na+ K+ Ca2+ GMP

(SDW) STI

(SDW)TOL

(SDW)

Crosses 35 0.187** 11.32** 8.21** 6.11** 21.46** 39.58** 23.63 0.082** 0.33** 0.15**GCA 5 0.28** 25.19** 15.99** 8.76** 47.77** 98.33** 62.18 0.132** 0.45** 0.46**SCA 30 0.183** 5.99** 5.96** 5.45** 13.19** 21.15* 10.88 0.056** 0.26 0.24**Error 70 0.044 1.015 0.966** 0.711 1.99 1.256 0 .98 0.011 0.055 0.014 σ2A/(σ2A + σ2D) 0.41 0.66 0.49 0.36 0.65 0.69 0.69 0.45 0.28 0.70 Narrow-sense heritability a 0.28 0.45 0.43 0.28 0.48 0.54 0.54 0.33 0.25 0.71 Broad-sense heritability a 0.88 0.92 0.86 0.87 0.83 0.99 0.76 0.79 0.85 0.94 C.V (%) 11.25 10.15 9.55 10.62 8.66 5.69 5.62 8.41 17.10 25.05 Narrow-sense heritability ab 0.25 0.36 0.36 0.28 0.34 0.36 0.39 0.24 0.19 0.51 Broad-sense heritability ab 0.66 0.64 0.69 0.63 0.65 0.83 0.73 0.69 0.66 0.75 Broad-sense heritability b 0.76 0.79 0.82 0.76 0.74 0.94 0.79 0.72 0.69 0.84 BSH b-BSH ab 0.10 0.15 0.13 0.13 0.09 0.11 0.06 0.03 0.03 0.09 *, ** Significant at P= 0.05and P= 0.01 respectively; A and D as defined in the text refer to additive and dominance genetic effects respectively. And also a, b and ab as defined in the text refer to estimation of parameters with diallel assumption,without diallel assumption(RCBD method) andσ2A, σ 2D with diallel assumption and σ2P without diallel assumption respectively.

Significant variations in general combining ability and specific combining ability estimates were observed for shoot dry weight, root length, plant height, shoot fresh weight, Na+, K+, and Ca2+ contents and indices of Geometric Mean Productivity (GMP), Stress Tolerance Index (STI), Tolerance Index (TOL) for shoot dry weight (Table 1) indicates the importance of both additive and non-additive genetic effects for these characteristics. High ratios of σ2A/(σ2A+σ2D) and high narrow-sense heritability estimates of root length, plant height, Na+, K+, Ca2 and Tolerance Index (TOL), indicated the more involvement of genes additive effects in their genetic control. Therefore, the efficiency of selection based on these characters is expected to be high but, shoot dry weight, shoot fresh weight and indices of Geometric Mean Productivity (GMP), Stress Tolerance Index (STI) were controlled pre-dominantly by non-additive genetic effects (Table 1). When gca effects are not pre-dominant in self-pollinated crops, the major portion of the variability, is due to additive × additive genetic effects or divergence among progenies in the same parental array and therefore, should be delayed to later generation. The high differences of variance ratios [σ2g / (σ2g+σ2e)] b - [2σ2gca+σ2sca /(σ2g+σ2e)] ab were observed for those all characteristics that had high narrow-sense heritability, indicating correlation between narrow-sense heritability and non-allelic effects in their genetic control. This is resulted from interaction of many locus of gene additive action in the quantitative characteristics that produce non-allelic effects. Sairam and Tyagi (2004) also reported that Salinity stress response is multigenic, as a number of processes involved in the tolerance mechanism are affected, such as various compatible solutes/osmolytes, polyamines, reactive oxygen species and antioxidant defense mechanism, ion transport and compartmentalization of injurious ions. Various genes/cDNAs encoding proteins involved in the above mentioned processes have been identified and isolated in plants.


REFERENCES [1] Ashraf, M. (1994). Breeding for salinity tolerance in plants. Critical Revi.3: 17–42. [2] Ashraf, M. and Saghir, A. (2000). Genetic effects for yield components and fibre characteristics in upland cotton

(gossypium hirsutum L.) cultivated under salinized (NaCl) conditions. Agron. J. 20:917-926. [3] Baker, R. J. (1978). Issues in diallel analysis. Crop Sci.18: 533-536 [4] Fernandez, G. C. J. (1993). Effective selection criteria for assessing plant stress tolerance. In Adaptation of food Crops to

Temperature and Water Stress. Kuo.C.G.,Ed., AVRDC: Shanhua, Taiwan. 257-270. [5] Fischer, R. A. and Murrer, R. (1978). Drought resistance in spring wheat cultivars .I. Grain yield response

.Aust.J.Agric.Res.29:897-912. [6] Griffing, B. (1956). Concept of General and Specific Combining Ability in Relation to Diallel System. .Aust.J.Bio.Sci.

9:463-493 [7] Hayman, B.I. (1954). The Theory and Analysis of Diallel Crosses. Genetics 39:789-809 [8] Hoagland, D. R. and Arnon, D. I. (1950). The water – culture method for growing plants without soil. Cali. Agric. Exp. Stn.

Cric.307,32 pp. [9] Isaac, R. A. and Kerber, J.D. (1971). Atomic absorption and flame photometry: techniques and uses in soil, plant and water

analysis. In Instrumental Methods for Analysis of Soil and Plant Tissue, Walsh,L.M.,Ed., Soil Sci. Soc. Am. Madison, WI:17-37.

[10] Postel, S. (1989). Water for agriculture: Facing the limits. Worldwatch paper 93.Worldwatch Institute. Washington DC. [11] Rosielle, A. A. and Hamblin, J. (1981).Theoretical aspects of selection for yield in stress and non-stress environments. Crop

Sci.21: 943-946. [12] Saghir, A., Khan, N. O., Igbal, M. Z., Hussain, A. and Hassan, M . (2002). Salt tolerance of cotton (Gossypium hirsutum L.)

Asian j. Pl. Sci. 1, 6:715-719. [13] Sairam, R. K., Tyagi, A. (2004). Physiology and molecular biology of salinity stress tolerance in plants .Curr. Sci. 86,

3:407-421. [14] Volkamar, K. M., Hu, Y. and Steppuhn, H. (1998). Physiological response of plants to salinity: a review. Can. J. Pl. Sci. 78:

19-27.

Marker-Assisted Selection for Improving Drought Resistance in Cotton

Yehoshua Saranga1, Avishag Levi1 and Andrew H. Paterson2 1The Robert H. Smith Faculty of Agriculture, Food and Environment,

The Hebrew University of Jerusalem, P.O. Box 12, Rehovot 76100, Israel 2Plant Genome Mapping Laboratory, University of Georgia, Athens, GA 30602, USA

Abstract—Marker-assisted selection (MAS) is gaining an increasing recognition as an efficient approach for improving simply inherited traits, however, there are hardly any examples of successful MAS for complex polygenic traits, such as yield and drought resistance. Quantitative trait loci (QTLs) for yield and drought-adaptive physiological traits (osmotic potential, carbon isotope ratio - an indicator of water use efficiency, and leaf chlorophyll content), were exchanged via MAS between elite cultivars of the two cotton species, Gossypium barbadense and G. hirsutum. The resulting near isogenic lines (NILs) were examined in three field trials to test the effect of the introgressed QTL alleles on cotton productivity under drought conditions and physiological traits. A considerable number of NILs exhibited the expected phenotypes in term of greater osmotic adjustment, higher carbon isotope ratio, and higher chlorophyll content. Moreover, a few NILs exhibited modifications in non-targeted traits such as greater photosynthetic capacity under severe drought, modified leaf morphology, and considerable changes in metabolic and mineral profiles. Finally, NILs introgressed with QTL alleles associated with high yield rarely exhibited a yield advantage over the recurrent parent, consistently with other introgression studies, suggesting that the well balanced genetic and physiological systems of the recurrent parents may be interrupted by these introgressions. We conclude that MAS is a useful approach to enhance drought-adaptive traits in cotton, but complimentary recombination and selection are required to combine these traits with high yield potential.

INTRODUCTION

About one-third of the world's arable land suffers from chronically inadequate water availability for agriculture, and in virtually all agricultural regions, crop yields are periodically reduced by drought (Boyer, 1982). Developing drought resistant crop plants is vital to meeting increasing demand for agricultural products during an environmental shift to greater aridity (Parry et al., 2005). The development of drought-tolerant crops by traditional breeding has been hampered by the low heritability of traits such as yield, particularly under drought, and by large ‘genotype x environment’ interactions. Modern genomic techniques have aided tremendously in identifying quantitative trait loci (QTLs) and diagnostic DNA markers in a wide range of crops and paved the way towards more efficient breeding approaches.

Cotton (Gossypium spp.) with two pre-dominant cultivated species, G. hirsutum L. and G. barbadense L. (denoted hereafter as GH and GB respectively), is the world’s leading fibre crop and also an important oilseed. Cotton is an herbaceous warm-season crop and a major consumer of water. Whether irrigated or not, cotton is often exposed to drought, which adversely affects both yield and lint quality. In this regard, concerted efforts are required to improve drought resistance of cotton. Both GH and GB cottons are tetraploid comprised of ‘A’ and ‘D’ sub-genomes that diverged from a common ancestor about 4-11 million years ago and rejoined in a common nucleus about 1-2 million years ago (Wendel, 1989). Modern cotton cultivars are outcome of intensive selection to produce large amounts of specific types of fibers. This selection has unintentionally narrowed the genetic variability for drought resistance (Rosenow et al., 1983). The availability of two domesticated closely-related cotton species that have evolved independently and retained different genes or alleles for various traits provide an opportunity to restore some of the desirable alleles "left behind" during domestication, by introgression between the two domesticated species.

A long term project aimed at improving cotton adaptation to water-limited condition are briefly reviewed in this paper.

15



Analysis of F2 and F3 generations of an inter-specific cotton population (GH var Siv'on x GB var F-177) indicated a total of 79 QTLs for ten measures of plant productivity and physiological variables (Saranga et al., 2001, 2004; Paterson et al., 2002). Productivity of cotton in well-watered versus water-limited conditions was largely accounted for by different QTLs, indicating that adaptation to both conditions can be combined in the same genotype (Saranga et al., 2001; Paterson et al., 2002). QTL likelihood intervals for high seed cotton yield and low leaf osmotic potential corresponded in three of four possible genomic regions (two involving QTLs specific to water-limited conditions), implicating osmotic potential as a major component of improved cotton productivity under arid conditions (Saranga et al., 2004). These results provided the first evidence that there appears to exist not only a phenotypic correlation but also a partly common genetic basis of OA and productivity (Saranga et al., 2001). Two of these three loci mapped to homeologous (corresponding) locations on the two sub-genomes of tetraploid cotton (chromosomes 6 and 25), suggesting that a particularly important role of one or more ancestral genes in that region may have been retained since the A-D genome divergence and polyploid formation. The finding that the GH allele was favourable at some loci and the GB allele at other loci suggested that recombination of favourable alleles may form novel inter-specific genotypes that are better adapted to arid conditions than either of the parental species.

Selected genomic regions containing QTLs for yield and drought related physiological traits (osmotic potential, carbon isotope ratio - an indicator of water use efficiency, and leaf chlorophyll content), were exchanged via marker assisted selection (MAS) by backcrossing the source of the favourable allele to the alternative parent (GH var Siv'on or GB var F-177). The resulting near isogenic lines (NILs) were examined in three field trials to test the effect of the introgressed QTL alleles on cotton productivity under drought conditions and the underlying physiological traits (Levi et al., 2009a). Many NILs exhibited the expected phenotypes including lower osmotic potential or greater OA (5 out of 9), higher carbon isotope ratio (4 of 6) or higher chlorophyll content (2 of 3). A few NILs exhibited modifications in non-targeted traits such as leaf size, leaf pubescence, and stomatal density. Two NILs that were subjected to gas-exchange study exhibited improved photosynthetic variables and one of them showed a stable net rate of CO2 assimilation across a wide range of leaf water potentials with a notable advantage over its recurrent parent under severe drought (Levi et al., 2009b). Increased levels of several solutes (alanine, aspartic acid, citric acid, malic acid, glycerol, myoinositol, threonic acid, potassium, magnesium and calcium) were found under drought conditions in one or more NILs as compared with their recurrent parents, which could contribute to their superior capacity to cope with drought (Levi et al., 2011). Finally, NILs introgressed with QTL alleles associated with high yield in our mapping study rarely exhibited a yield advantage over the recurrent parent.

CONCLUSION

Yield is known as a low-heritability complex trait, influenced by multiple gene networks and epistatic interactions among genetic elements, as well as between genetic and environmental variables (Levi et al 2009a). Breeding for yield under stress conditions is even more complex due to the difficulty to define and apply a precise set of environmental condition relevant to the range of naturally occurring stress scenarios. This emphasizes the power of genetic mapping, allowing the dissection of complex traits and distinguishing common heredity from casual associations (Paterson et al. 1988), which cannot be achieved by conventional approaches. Targeting specific genomic regions and characterizing their effects can enable the reconstruction of favourable loci into elite cultivars.

Marker-assisted selection (MAS) is gaining an increasing recognition as an efficient approach for improving simply inherited traits; however, there are hardly any examples of successful MAS for complex polygenic traits, such as yield and drought resistance. In the current study, cotton NILs exhibited an improvement in drought related traits, compared with the recipient parent. From a physiological point of view, such changes that can be considered as enhanced drought tolerance. However, NILs containing putatively favourable alleles for yield did not exhibit a clear advantage. Elite

Marker-Assisted Selection for Improving Drought Resistance in Cotton 91

cotton cultivars, such as the recipient parents used in our study, are the outcome of intense selection over many generations among huge number of individual genotypes. The well balanced genetic and physiological systems of such elite cultivars may be interrupted by introgressions of large QTL regions or undetected non-targeted introgression. This possibly is a major reason for the poor success of MAS for improved yield in previous studies (Cattivelli et al. 2008) as well as in the current study. It is established that maximal selection efficiency for quantitative traits may be obtained by a combination of molecular and classical-phenotypic approaches. The successful introgression of QTLs for drought related traits in this study may serve as a basis for future breeding, however, complimentary dissection of the introgressed regions and conventional breeding are required to combine the advantageous effect of the QTL(s) with high yield potential.

REFERENCES [1] Boyer J.S. (1982). Plant productivity and environment. Science 218, 443-448. [2] Cattivelli L., Rizza, F., Badeck, F. W., Mazzucotelli, E., Mastrangelo, A. M., Fracia, E., Mare, C., Tondelli, A., Stanca,

A.M. (2008) Drought tolerance improvement in crop plants: An integrated view from breeding to genomics. Field Crop Res 105: 1-14.

[3] Levi, A., Paterson, A. H., Barak, V., Yakir, D., Wang, B., Chee, P. W. and Saranga, Y.(2009a). Field Evaluation of Cotton Near-Isogenic Lines Introgressed with QTLs for Productivity and Drought Related Traits. Molecular Breeding 23:179-195.

[4] Levi, A., Ovnat, L., Paterson, A. H., Saranga, Y. (2009b). Photosynthesis of cotton near-isogenic lines introgressed with QTLs for productivity and drought related traits. Plant Science 177:88-96.

[5] Levi A., Paterson, A.H., Cakmak, I., and Saranga, Y. (2011). Metabolite and mineral analyses of cotton near-isogenic lines introgressed with QTLs for productivity and drought related traits. Physiol, Plant. 141:265-275.

[6] Parry M.A.J., Flexas, J., Medrano, H. (2005). Prospects for crop production under drought: research priorities and future directions. Ann. Appl. Biol., 147, 211-226.

[7] Paterson, A.H., Lander, E.S. Hewitt, J.D., Peterson, S., Lincoln, S.E. and Tanksley, S.D. (1988). Resolution of quantitative traits into Mendelian factors by using a complete linkage map of restriction fragment length polymorphisms. Nature.335: 721-726.

[8] Paterson, A. H., Saranga, Y., Menz, M., Jiang, C., Wright, R. (2002). QTL Analysis of Genotype x Environment Interactions Affecting Cotton Fiber Quality. Theor. Appl. Genet., 106:384-396.

[9] Rosenow, D.T., Quisenberry, J.E., Wendt, C.W., Clark, L.E. (1983). Drought tolerant sorghum and cotton germplasm. Agricultural Water Management, 7:207-222.

[10] Saranga Y., Menz, M., Jiang, C., Wright, R., Yakir, D., Paterson, A.H. (2001). Genomic dissection of genotype x environment interactions conferring adaptation of cotton to arid conditions. Genome Res., 11:1988-1995.

[11] Saranga Y., Jiang, C., Wright, R., Yakir, D., and Paterson, A.H. (2004). Genetic dissection of cotton physiological responses to arid conditions and their inter-relationships with productivity. Plant Cell Environ., 27: 263-277.

[12] Wendel, J. (1989). New World tetraploid cottons contain Old World cytoplasm. Proc. Natl. Acad. Sci. USA 86: 4132-4136.

Tak FA84-4: New Jassid Tolerant Cotton Variety

P. Seburuang1,W. Sirichumpan2,P. Nakapan3,S. Thaitad1,S. Lapbunjob1

A. Traisiri1,N.T. Khumla1,S. Areerak1,S.A. Juttupornpong4,N. Panlai5,A. Kasivivat6,P. Sangsoda7,R. Chuekittisak8, B. Kumseub9,

P. Pulcha7andK. Khockakang7

1Nakhon Sawan Field Crops Research Center, Tak Fa, Nakhon Sawan–60190 2Khon Kaen Field Crops Research Center, Mueang, Khon Kaen–40000

3Phitsanulok Agriculture Research and Development Center, Wang Thong, Phitsanulok–65130 4Suphan Buri Agriculture Research and Development Center, U Thong, Suphan Buri–72160

5Lop Buri Agriculture Research and Development Center, Khok Toom, Mueang, Lop Buri–15210 6Phetchabun Field Crops Research Center, Mueang, Phetchabun Khon Kaen–67000,

7Loei Plant and Production Technical Service Center, Post Box 1, Mueang, Loei–42000 8Sukhothai Plant and Production Technical Service Center, Si Samrong, Sukhothai–64120

9Nakhon Ratchasima Agriculture Research and Development Center, Si Khiew, Nakhon Ratchasima–30340


Abstract—Cotton damage from cotton jassid (Amrasca biguttula Ishida) becomes very serious problem, especially in a dry period EL Nino, because of 50-100% reduction in cotton yield. Farmers overcome this serious damage by increasing insecticide dose, resulting in more toxic residual effect to human health and environment. In order to reduce more systemic insecticide used for jassid control, jassid tolerant hairy leaf cotton variety improvement was conducted at Nakhon Sawan Field Crops Research Center in 1997. The hairy leaf IRMA1243, exhibiting jassid tolerance, was crossed with smooth leaf and leaf roll resistant Tak Fa 2, which has high yield and good fiber quality cotton variety. Thereafter, plants were selected in bulk in F2-F4 generations, followed by plant-to-row or pure line selection in F5-F6 generations for hairy leaf cotton lines with jassid tolerance, leaf roll disease resistance and high yield under non systemic-insecticide application and artificial leaf roll disease inoculation. Uniform 14 lines with good plant type were selected for yield potential evaluation in 2003-2008. The promising hairy leaf line, Tak Fa 84-4 was out-standing in jassid tolerance, high yield, good fiber quality and leaf roll disease resistance.

INTRODUCTION

In the past 30 years, recommended cotton varieties from Department of Agriculture (DOA) had smooth leaf, more susceptible to cotton jassid (Amrasca biguttula Ishida) than hairy leaf cotton (Boonramphan, 1999). The damage from cotton jassid was more during a dry period when leaves were almost completely destroyed, resulting in reduction in photosynthesis, yield and fiber quality (Cowland, 1947). Most cotton farmers overcome this serious damage by increasing systemic insecticide application, resulting in more toxic residual effect to human health and environment. Some cotton farmers grow local hairy leaf cotton for less insecticide spraying, especially systemic insecticide. However, they get less income from selling their seed cotton due to quality (low ginning out turn or fiber percentage, short and coarse/high micronaire fiber or lint). Besides, their local cotton yields rather low within 5-6 growing period as it is rather late maturing. In order to produce a good hairy leaf cotton variety with good yield and quality, resistance to important leaf roll disease and tolerance to the jassid for less insecticide use especially systemic insecticide use for cotton jassid control, good jassid tolerant hairy leaf cotton variety improvement began at Nakhon Sawan Field Crops Research Center (NSFCRC) in 1997.


Crossing and Selection

Hairy leaf IRMA 1243, exhibiting jassid tolerance, was crossed with smooth leaf and leaf roll resistant Tak Fa 2, which has high yield and good fiber quality cotton variety. Thereafter, selection for good hairy

16

Tak FA84-4: New Jassid Tolerant Cotton Variety 93

leaf cotton lines with cotton jassid tolerance, leaf roll disease resistance and high yield under non systemic insecticide application and artificial leaf roll disease inoculation. Good resistant/tolerant plants were selected in bulk in F2-F4 generations, followed by plant-to-row or pure line selection in F5-F6 generations. Uniform promising rows/lines with good plant type were selected for yield potential evaluation (preliminary trial, standard trial, regional trial and farm trial) in 2003 – 2008. Seed cotton harvest took place four times with intervals of 7-10 days, beginning at 120 days after emergence.

Evaluation on Reaction to Leaf Roll Disease and Jassid

Leaf roll disease evaluation, in comparison with Tak Fa 2 and Deltapine Smooth Leaf (DPSL) that is very susceptible, was conducted in the green house of NSFCRC in 2007. Reaction to jassid trial was conducted at NSFCRC in 2006 under insecticide application once a week. The other trial was conduct again in 2009 under insecticide application once a week in week1th-week6th followed by synthetic pyrethroid application only, which did not have effect on jassid in week7th –week14th.


Cotton Yield and Cotton Fiber Evaluation

Mean seed cotton yield data from preliminary trial, standard trial, regional trial and farm trial evaluation are shown in Table 1. Tak Fa 84-4 yielded 1,625 kg per hectare of seed cotton, which was in the same level of Tak Fa 2. Data on fiber quality are shown in Table 2, suggesting superiority of Tak Fa 84-4.

TABLE 1: MEAN DATA ON SEED COTTON YIELD (KG/HA) OF TAK FA 84– 4 VARIETY, COMPARED TO TAK FA2 VARIETY IN 2003–2008 TRIALS.

Variety PT2/ (2003) ST3/ (2006) RT4/ (2007) FT5/ (2008) Mean6/ Relative to Tak Fa 2 Tak Fa 84 –4 1,938 1,675 a 1,519 a 1,713 a 1,625 98 Tak Fa 2 - 1,644 a 1,606 a 1,731 a 1,663 100 CV (%) 15.3 16.0 17.3 11.4 - - No. of locations1/ (2) (3) (6) (6) (15)

Remarks: Means within the same column followed by a common letter are not significantly different at 0.05 probability level by DMRT.

1/Number in parenthesis is the number of locations. 2/Preliminary trial 3/Standard trial 4/Regional trial 5/Farm trial 6/Averaged from PT, ST, RT and FT in 2003–2008

TABLE 2: MEAN DATA ON GINNING OUT TURN OR GOT (FIBER OR LINT) PERCENTAGE AND FIBER QUALITY OF TAK FA 84–4 VARIETY, COMPARED TO TAK FA 2 VARIETY IN 2006–2008.

Variety Got (%) Fiber Length (Inch)

Fiber Bundle Strength (g./tex)

Micronaire (Fiber Fineness)

Fiber Uniformity (%)

ST (3 locations) Tak Fa 84–4 37.6 1.24 22.9 3.8 54 Tak Fa 2 36.4 1.20 20.8 3.7 52 RT (6 locations) Tak Fa 84–4 38.1 1.21 24.4 3.9 57 Tak Fa 2 36.6 1.17 22.1 3.8 54 FT (3 locations) Tak Fa 84 – 4 38.4 1.22 25.5 3.8 56 Tak Fa 2 37.2 1.20 21.6 4.1 54 Mean1/ Tak Fa 84 – 4 38.0 1.23 24.6 3.9 56 Tak Fa 2 36.7 1.19 21.7 3.9 53

1/Averaged from 3 locations of ST (standard trial), 6 locations of RT (regional trial) and 3 locations of FT (farm trial) in 2006 – 2008

Source: Sebunruang et al. (2009)


Reaction to Jassid

Mean number of jassids/10 cotton plants of Tak Fa 84-4 was lower than that of Tak Fa 2 in 2006 and 2009.(Table 3), this should be due to more hairiness as Tak Fa 84-4 had higher number of hairs on cotton leaf surface as well as on cotton leaf vein (61.6 and 55.9/ 0.20 cm2, respectively).

TABLE 3: MEAN NUMBER OF JASSIDS/ 10 COTTON PLANTS AND NUMBER OF HAIRS ON COTTON LEAF SURFACE AND COTTON LEAF VEIN/0.20 CM2 (NAKHON SAWAN FIELD CROPS RESEARCH CENTER, 2006 AND 2009)

Variety Number of Jassids Per 10 Plants Number of Hairs on Leaf Surface Per 0.20 cm2

Number of Hairs on Leaf Vein per 0.20 cm2 2006 2009

Tak Fa 84–4 97 a 556 a 61.6 a 55.9 a Tak Fa 2 195 b 760 b 12.9 b 16.2 b CV (%) 22.1 14.9 63.8 53.3 Means within the same column followed by a common latter are not significantly different at 0.05 probability level by

DMRT.

Source: Traisiri et al. (2006) Traisiri et al. (2009)

Leaf Roll Disease Reaction

Tak Fa 84-4 cotton variety was considerably resistant to leaf roll disease in the same level as Tak Fa 2 (Table 4). It should be very useful for cotton integrated pest control in which less insecticide application would be needed, comparing to Tak Fa 2 and other smooth leaf cotton variety such as Deltapine Smooth Leaf cotton variety that was very susceptible to leaf roll disease and failed to be commercially grown.

TABLE 4: REACTION TO LEAF ROLL DISEASE UNDER ARTIFICIAL INOCULATION IN 2007 OF TAK FA 84–4, TAK FA 2 AND DELTAPINE SMOOTH LEAF COTTON VARIETIES

Variety Leaf roll Disease Infected Plants (%) Disease Reaction1

Tak Fa 84–4 0 Resistant Tak Fa 2 3.3 Resistant Deltapine Smooth Leaf 93.3 Susceptible

1/Disease reaction is based on 3 levels as following: 0 – 10 % Resistant 11 – 40 % Moderately resistance 41 – 100 % Susceptible Source: Lapbunjob et al. (2007)

From overall results and discussion it can be concluded that Tak Fa 84-4 cotton variety had good adaptation in cotton growing area in the same high level of yield as Tak Fa 2. Due to hairiness of Tak Fa 84-4, growing this variety under less insecticide spraying will result in less reduction of cotton yield and damage from cotton jassid. Moreover, Tak Fa 84-4, with good fiber quality, was resistant to leaf roll disease; therefore, it is very useful for cotton farmers to grow under less pesticide use for controlling jassid and aphid that was the leaf roll disease vector.

REFERENCES [1] Boonramphan, P. (1999)-Cotton variety improvement for cotton jassid damage resistance. Project of Cotton variety

improvement for hight yield and good fiber quality. Kasetsart University. 10 p. (in Thai) [2] Cowland, J.W. (1947)-The cotton jassid (Empoasca libyca Berg.) in the Anglo-Egyptian Sudan and experiments on its

control. Bull. Entom. Res. 38 (2): 99-115. [3] Lapbunjob, S., P., Sebunruang and Thaitad, S. (2007)-Leaf roll disease of cotton lines evaluation,p 15. In: Annual report

2007. Nakhon Sawan Field Crops Research Center. Office of Agriculture Research and Development, Region 5, Department of Agriculture. (in Thai).

[4] Sebunruang, P., S.Thaitad, P.Sangsoda, P.Pulcha, N.Panlai, R. Chuekittisak, S. Juttupornpong and Kasivivat, A. (2009)-Farm trial: fiber quality cotton variety, p 13-14. In: Annual report 2009. Nakhon Sawan Field Crops Research Center, Field Crops Research Institute, Department of Agriculture. (in Thai)

[5] Traisiri A., Sebunruang, P., Khumla, N. and Lapbunjob, S. (2006)-Study on distribution of cotton insect pest, p. 37. In: Annual report 2006. Nakhon Sawan Field Crops Research Center, Field Crops Research Institute, Department of Agriculture. (in Thai)

[6] Traisiri A., Sebunruang, P., Lapbunjob, S., Khumla, N. and Thaitad. S. (2009)-Reaction of cotton lines to aphid. (Bemisia tabaci Gennadius.), p. 20-21. In: Annual report 2009. Nakhon Sawan Field Crops Research Center, Field Crops Research Institute, Department of Agriculture. (in Thai).

High Boll Weight and High Ginning Outturn— The Major Tools for Breaking Yield Barriers

in Gossypium arboreum

Punit Mohan1, S. Manickam2, S.K. Verma3, D. Pathak4, A.S. Singh5 and Tarun Kumar Das6

1Principal Scientist, Central Institute for Cotton research, Nagpur-440010, India 2Principal Scientist, Central Institute for Cotton Research, Regional Station, Coimbatore, India

3Senior Scientist, Central Institute for Cotton Research, Regional Station, Sirsa, India 4Assistant Plant Breeder, PAU, Ludhiana, India

5Programme Coordinator, KVK, Tura, India 6Subject matter specialist, Agri. Extension, KVK, Tura, India

Abstract—The high boll weight, high ginning outturn and optimum boll numbers are the major tools for breaking yield barriers in cotton. Therefore, a exploratory and expedition survey of the tribal area of West Garo Hills of North Eastern Hill Region, Meghalaya was conducted in 2000- 2010. The 59 germplasm lines including perennials of Gossypium race cernuum were collected from where there was no introduction of improved cotton varieties and commercial hybrids.The collected germplasm accessions were characterized by deep palmate leaf lobes, long petiole (20 cm), elongated acute and acrescent capsule with high boll weight (7.5g) and trilocular ovary, length of bursted locule loaded with seed cotton (upto 15.5 cm), high locule retentivity and resistance to high wind velocity with minimum locule shedding. They also possessed high ginning outturn (upto 51%), short staple (21.8 mm) fibre bundle strength (19.7 g/tex) and coarse fibre (micronaire 8.0).The above germplasm accessions are important source for genetic improvement of arboreum cottons in terms of locule retention capacity, boll weight and ginning outturn.

INTRODUCTION

Gossypium arboreum L., commonly known as tree cotton or desi cotton is native to India is under cultivation from time immemorial. Arboreum cottons have wide adaptability and are relatively tolerant to biotic and abiotic stresses (Singh and Punit Mohan, 2005). In any successful varietal improvement programme, the availability of adequate variability in basic genetic stocks is most essential and their utilization in breeding programme for building up improved strains are very necessary. Hence, the collection, conservation, evaluation, documentation and utilization of diverse germplasm material assume special significance.

The boll weight and ginning outturn are the basic features of breeding importance in arboreum cotton. Present investigation was therefore undertaken to study boll weight, ginning outturn and fibre technological properties of cerunnm race for improvement of yield, boll weight and ginning outturn of ‘desi’ cotton.


National germplasm exploration and expedition programme of West Garo Hills, Meghalaya, was jointly carried out by the Central Institute for Cotton Research, Nagpur and National Bureau of Plant Genetic Resources, New Delhi in 2000 and 2010. The 59 morphologically variant germplasm lines were collected and evaluated for morphological characters and fibre technological properties. The important characters of selected accessions are presented in Table 1.


The germplasm accessions collected had specific morphological characters viz., long petiole, deeply palmate leaves, cordate base, central lobe once or twice toothed near the sinus, long broad bracts,

17


elongated- ovate acute, acrescent capsule/boll, white and yellow petals, yellow and creamy pollens, tri-locular ovary, high boll weight (5 - 7.5 g), high locule retentivity, locules with 12-20 seeds free from each other and firmly bound through interlacing of their wool. They also possessed high ginning outturn (upto 51%), short staple (17-21.8 mm) and coarse fibre (micronaire upto 8) (Table 1).

High boll weight was recorded in the germplasm accessions GHA-11, GHA-6, GHA-3, GHA-18, GHA-23, 30826 and 30838 respectively. The ginning out-turn ranged from 38.0 to 51.0 % (Table 1), however earlier studies (Singh and Nandeshwar 1983; Singh and Raut, 1983; Punit Mohan et al., 1992) have reported higher ginning outturn (GOT) with high seed density/ boll in selected genotypes of cernuum race.

Bolls per plant is one of the important components of yield and is positively correlated with it. All the available reports indicated a significant positive correlation between boll number and yield (Shinde and Deshmukh, 1985; Aher et al., 1989 and Duhoon, 1989). Boll number was negatively correlated with boll weight. Therefore, simultaneous improvement of boll number and boll weight may be difficult. (Butany et al.,1966; Bhatt et al., 1967; Singh et al., 1968 and Singh et al., 1979).

The improvement of genetic make-up of cotton plant for assured yield contributing characters are boll number, boll weight, and ginning outturn. Extensive genetical investigations of the above three important yield contributing characters have been carried out by several workers. The findings reported by them have been summarised in Table 2.

Amount of lint obtained from the seed cotton and staple length are the important criteria that determine the genetic potential of a cultivar. These two components are correlated with the density i.e. development of fibre per unit area on seed coat. The ginning outturn is another important component of lint yield but it is again a polygenic character.

The ginning outturn of arboreum cottons in India ranges from 22 to 52 per cent. Comilla cotton belonging to race cernuum ginns upto 49 per cent or even more (Anonymus, 1956 a; Barooch and De, 1950). The race bengalense and the race indicum types occupy the second and third position, respectively. In bengalense cottons those possessing white flowers and narrow central leaf lobes like Roseum, N. Roseum 6 and 231 Rosea, shows higher ginning (36 per cent to 43 per cent). Therefore, cernuum and Roseum cottons have been used in hybridization programme, wherever necessary, for improving the ginning character of arboreum cottons of different tracts . The variability potential in Gossypium arboreum race cernuum offers immense possibilities in breeding for improvement in boll weight, fibre strength and ginning outturn of desi cotton.

LOCULE RETENTIVITY

Shedding of seed cotton locules from the fully opened mature bolls is a serious problem in arboreum cottons. (Singh and Punit Mohan 2004). Most of the released varieties of this species suffer from locule shedding after boll bursting. As a result the seed cotton loaded locules falls on the ground, get mixed with leaf bits and soil particles resulting in the deterioration of the cotton quality. This species warrants immediate picking after boll bursting. The high locule retentivity was observed in race cernuum than race bengalense and indicum (Singh and Punit Mohan 2004). Locule retentive cultivars help in reducing the pre-harvest seed cotton loss due to adverse weather in the form of high wind, rain and hailstorm. Therefore, race cernuum can be utilized in the future breeding programmes for the development of locule retentive cultivars of Arboreum.

DISEASE RESISTANT

The Grey mildew disease of cotton especially G. arboreum caused by the fungus Ramularia areola Atk (Ramularia gossypii) has been reported as a disease of great economic importance in India and other cotton-growing areas in the world. In all 1592 accessions of Gossypium arboreum were screened against the grey mildew disease (Ramularia areola, synonym Ramularia gossypii), six germplasm lines resistant

High Boll Weight and High Ginning Outturn—The Major Tools for Breaking Yield Barriers in Gossypium arboretum 97

to grey mildew disease have been identified namely G 135-49, 30805, 30814, 30826, 30838 and 30856, belonging to G. arboreum race cernuum and can be utilized in development if varieties/ donor lines resistant / tolerant to grey mildew disease.

Morpho- anatomical investigations of resistant lines were carried out which indicates host immunity and greater variability in anatomical features viz., thick smooth cuticle, interlocked epidermal cells, high degree of lamina thickness in comparison to commercial susceptible G. arboreum cultivars viz., AKH 4 and AKA 8401 (Punit Mohan et al., 1997). The variability in foliar anatomical features have been summerised in Table 4. The race cernuum is an ecotype representing the final product of localised selection tendencies among perennial cottons in North-East India as reported by Simlote (1956).

The results presented in Table 1 shows that significant variability for boll weight, ginning percentage, fibre properties and their extent of association with several economic traits have been observed. However, their mode of inheritance need to be studied as it will help in better selection of parental genotypes and their effective manipulation in breeding programme.

TABLE 1: HIGH GINNING OUTTURN AND HIGH BOLL WEIGHT GERMPLASM ACCESSIONS OF GOSSYPIUM ARBOREUM

Sr. No.

Name Boll wt. (g)

Bursted Locule Length

(cm)

Ginning Outturn

(%)

2.5% Staple Length (mm)

UniformiyRatio (%)

Fineness Micronaire

10-6 g/in

Bundle Strength Tenacity (g/tex) at

3.2 mm Gauge

Elongation (%)

1. GHA-1 6.5 14.0 40.1 18.9 52 7.9 15.3 5.7 2. GHA-2 6.3 14.0 40.0 18.2 51 8.0 14.8 5.4 3. GHA-3 7.2 13.5 42.3 18.6 51 8.0 14.8 4.9 4. GHA-4 6.8 12.3 38.5 19.0 51 8.0 15.4 5.1 5. GHA-5 6.8 13.2 40.2 17.9 52 8.0 14.6 4.9 6. GHA-6 7.5 13.5 48.5 19.4 52 8.0 15.4 4.8 7. GHA-7 7.0 14.5 39.5 18.0 51 8.0 14.7 5.3 8. GHA-8 7.2 14.0 39.0 19.6 51 8.0 15.1 5.1 9. GHA-9 6.8 13.3 40.1 19.9 52 7.5 14.8 4.6

10. GHA-10 6.0 13.0 42.0 18.1 54 8.0 14.4 5.3 11. GHA-11 7.5 14.2 41.0 18.9 51 7.9 15.3 5.2 12. GHA-12 7.3 15.0 48.0 18.2 53 8.0 14.4 5.2 13. GHA-13 6.9 14.2 39.5 18.6 53 8.0 14.8 5.2 14. GHA-14 6.0 14.0 40.2 18.2 53 7.9 14.8 5.2 15. GHA-15 5.8 12.4 38.0 18.9 55 7.5 14.8 5.0 16. GHA-16 6.9 13.7 38.3 17.6 51 7.8 14.8 5.5 17. GHA-17 6.3 13.7 44.0 18.0 52 7.5 15.2 5.3 18. GHA-18 7.3 15.3 40.1 17.8 51 7.9 15.0 5.4 19. GHA-19 7.0 14.0 49.3 17.6 52 7.8 15.4 5.5 20. GHA-20 6.3 13.2 40.3 18.5 51 7.3 16.0 5.0 21. GHA-21 5.5 12.8 38.7 18.0 51 7.5 15.4 5.5 22. GHA-22 5.0 13.3 38.0 17.6 52 7.8 14.5 5.1 23. GHA-23 7.3 14.9 40.5 17.9 51 7.8 14.9 5.3 24. G 135-49 5.9 13.0 39.6 21.8 50 7.5 19.7 5.0 25. 30805 6.4 13.0 43.1 20.2 50 7.9 17.9 4.4 26. 30814 6.1 13.0 48.7 17.5 52 7.3 16.4 5.0 27. 30826 7.3 15.3 51.0 18.5 49 7.0 17.0 5.1 28. 30838 7.1 15.5 48.1 20.3 50 7.5 16.4 4.9 29. 30856 6.3 14.3 46.1 17.0 48 7.5 16.0 5.1

Range 5.0-7.5 12.3-15.5 38.0-51.0 17.0-21.8 48-55 7.0-8.0 14.4-19.7 4.4-5.7


TABLE 2: GENE ACTION AND TRAITS

Character Gene Action References Boll diameter and boll shape Polygenic Control Patel and Patel (1927) Boll shape and size Multiple gene

Control Balls (1908), Kearney (1923) Kokuev (1935)

Boll size Multiple gene control

Ramiah and Bholanath (1947)

Length and breadth of bolls Multiple gene Control

Afzal (1930)

Variability and correlations for boll attributes

Multiple gene control

Singh (1988)

Ginning Outturn Multiple gene Control

Mc Lendon (1912), Kottur (1923),Patel and Patel (1927)O’Kelly and Hull (1930)

TABLE 3: GENETIC SOURCES FOR HIGH GINNING OUTTURN AND HIGH BOLL WEIGHT (GOSSYPIUM ARBOREUM)

1. Khasia Hills Cotton G. Arboreum Race Cernuum

White Petals, Ginning Outturn 50 %, Fibre Length 18-22mm, Boll Weight 6 to 7 g.

2. Jaintia Hills Cotton G. arboreum race cernuum

Yellow petals, ginning outturn 52 % coarsests cotton of Assam, Lint white creamy colour.

3. Haflong Hills Cotton

G. arboreum race bengalense

Vernacular name- Khum-Mah, Khum-sab, patsen-grows between 1500 to 2000 feet above sea level. All these are short linted, fairly soft cotton of creamy, white colour with ginning percentage of 37-40%.

4. Lushia Hills Cotton G. arboreum race bengalense

Consists of three local varieties -Lafang: yellow flower, short lint, inning outtrurn 37%, halo length -19mm.Lapui- white flower and coarser, ginning outturn 37% and halo length -22mm.Lauk- Yellow flower, short linted, rusty brown colour.

5. Mikar Hills Cotton G. arboreum race cernuum

Two local known varieties viz. Borkapa and Sorukapa- yellow flower.

6. Naga Hills Cotton G. arboreum race cernuum

White flower, Ginning outturn 40-45 %, coarse fibre and boll weight 5 to 6 g.

7. Abor Hill Cotton G. arboreum race cernuum

Yellow flowered, fairly fine, short stapled, maximum halo length 20-24 mm., monopodial habit, ginning outturn 35-40 % and boll weight 6 g.

TABLE 4: FOLIAR ANATOMICAL FEATURES OF IMMUNE AND SUSCEPTIBLE TREE COTTON (GOSSYPIUM ARBOREUM L.) IN RELATION TO GREY MILDEW DISEASE (RAMULARIA AREOLA ATK)

Germplasm Accession

Cuticle Thickness

(µ) *

Lamina Thickness

(µ)*

Thickness Covered by

Palisade Parenchyma(µ) *

Thickness Covered by

Spongy Parenchyma(µ) *

No. of Epidermal

Cell *

No. of Stomata*

‘Bangladesh’ 5.166 115.62 46.90 39.52 19.31 71.19 ‘G 135-49’ 4.936 113.16 51.82 39.52 19.23 67.50 ‘30805’ 4.166 113.16 41.98 39.52 19.45 69.31 ‘30814’ 4.920 113.16 41.98 39.52 19.38 69.28 ‘30826’ 4.920 113.16 41.98 39.52 19.55 71.53 ‘30838’ 4.920 110.70 41.98 39.52 21.74 71.46 ‘30856’ 3.690 113.16 41.98 39.52 19.55 71.81 ‘AKH 4’ 2.460 108.24 37.06 39.52 14.77 89.44 ‘G 27’ 2.460 105.75 37.48 39.52 17.53 103.35 Range 3.690 110.70 41.98 39.52 19.23 67.50 (immune) 5.166 115.62 51.82 39.52 21.74 71.81 Range(susceptible) 2.460- 2.460 105.75-108.24 37.06-37.48 39.52-39.52 14.77-17.53 89.44-

103.35 *per microscopic field

REFERENCES [1] Afzal, M. (1930) - Studies in inheritance of Cotton- Mem. Dept. Agric India., Bot., 17 : 75-115. [2] Aher, R.P., Sanap, M. M. and Thete, R,Y.(1989) - Genetic parameters and correlation coefficient studies in Deshi Varieties

of Cotton - J. Maharashtra Agri. Univ., 14 (1), 63-64. [3] Anonymous, (1956) – A guide to Indian cottons (Revised) - I.C.C.C., Bombay-74.

High Boll Weight and High Ginning Outturn—The Major Tools for Breaking Yield Barriers in Gossypium arboretum 99

[4] Balls, W. L. (1908) – Mendelian Studies of Egyptian Cotton. J. agric. Sci, 2: 346- 379. [5] Barooch, S. R. and II, B., (1950) – Hill Cotton in Assam - I.C.G.R.,4 : 65- 69. [6] Bhatt, M. G., Singh, R. B. And Mor, B. R. (1967) - Genetic variability in upland cotton (G. hirsutum L.) II Analysis of yield

and its components. Indian J. agric. Sci., 37, 555 - 559. [7] Butany, W.T., Munshi Singh and Mehra, R. B. (1966) - Interrelationships between some characters in hirsutum Cotton.

Indian J. Genet. and Pl. Breeding, 26,262-268. [8] Duhoon, S. S. (1989) - variability, correlations and path analysis of nine characters in Gossypium arboreum Cotton. J.

Indian Soc. Cotton. Improv., 14, 39-44. [9] Kearney, T. H. (1923) - Segregation and Correlation of Characters in an upland Egyptian Cotton hybrid. U.S. Dept. Agric.

Bull., 1164-68. [10] Kokuev, V. I. (1935) - Inheritance of Certain agronomic and morphological characters in cotton. A Sredoz N. I. Kh. I.

Tashkent, 80: 65-80. [11] Kottur, G.L. (1923) - Studies on inheritance in cotton .I. History of a Cross between Gossypium herbaceum and

G.neglectum. Mem. Dept.Agric. Indian. Bot., 12: 71-133. [12] Mc Lendon, C. A. (1912) - Mendelian inheritance in cotton hybrids - Georgia sta. Bull., 99: 141 -228. [13] O’Kelly, J.F. and Hull. W. W. (1930) – Cotton inheritance studies. Lint percentage -Tech. Bull. Miss, Agric. Expt. Sta.,

18:15. [14] Patel, M. L. And Patel, S.J. (1927) – Studies in Gujarat Cottons. Part IV Hybrids between Broach Desi and Goghari

varieties of Gossypium herbaceum - Mem. Dept Agri. Indian Bot., 14: 131-176. [15] Punit Mohan, Bhat. M.G., Singh, V. V. and Singh, P (1992) - variability for biomass and harvest index in Asiatic

(G.arboreum L.) and American (G. hirsutum L.) cottons. Adv. Plant Sci. 5: 100 – 105. [16] Punit Mohan., Mukewar, P.M., Sheo Raj and Singh, V.V. (1997) - Anatomy of Gossypuim arboreum lines immune to grey

mildew disease, - J. Cotton Res. & Dev. 11: 191-195. [17] Punit Mohan., Mukewar, P.M., Singh, V.V. and Kairon, M. S. (2000), - Perpetual immunity of arboreum cotton to grey

mildew. - SAIC, News Letter, 10:8. [18] Ramiah, K and Bholanath (1947) – Studies on the cotton boll with special reference to G. arboreum - 3rd - Conf. Cotton.

Gr. Prop. India. I.C.C.C., Bombay, 100-106. [19] Shinde, V. K. and Deshmukh, M. D. (1985)-Genetic variability for yield and characters association in desi cotton - J.

Maharashtra Agri. Univ, 10, 21-22. [20] Simlote K.M. (1956) – Cotton improvement in India - Simlote Institute of Plant Industry, Indore, 201 P. [21] Singh R. B., Gupta, M.P., Mor, B. R. and Jain, D. K. (1968) - Variability and correlation studies on yield and quality

characters in hirsutum cotton - Indian J. Genet. and Pl. Breeding ., 28(2), 216-222. [22] Singh, B. N., Singh, H. G. and Singh, U.P. (1979) - Path analysis of yield and fibre components in upland Cotton – Indian J.

agric. Sci., 49,7 63-765. [23] Singh, Munshi and Raut, R.N. (1983) – Genetic research on cotton and Jute – In: Genetical Research in India, 1983, pp.154

– 171, Pal B.P.(Ed) ICAR, New Delhi. [24] Singh, P. and Nandeshwar, S.B.(1983) – Variability in Gossypium arboreum Linn. Race Cernuum in Garo Hills of India.

Indian J. agric. Sci., 53(7) : 511-13. [25] Singh, P. and Punit Mohan (2004) Locule retentive cotton in India CINA-316. SAIC News Letter. 14: 6. [26] Singh, P and Punit Mohan (2005) Progress and prospects of R &D in diploid desi Cotton in India. J. Indian soc. Cotton

Improv. 30: 75-84. [27] Singh, V. V. (1988) – Variability and correlations for boll attributes in upland Cotton (Gossypium hirsutum) germplasm.

Indian J. agric Sci., 58: 309-10 [28] Singh, V. V and Punit Mohan (1999) - Role of Cotton Genetic Resources as a Major Tool for breaking yield barrier in

cotton J. Indian Soc. Cotton Improv. 24:155-163.

Development of Naturally Coloured Gossypium hirsutum Cotton Genotypes Suitable for Textile

Industry through Genetic Improvement

Manjula S. Maralappanavar, Vikas V. Kulkarni, Somshekhar, C. Madhura, S.S. Patil, K. Narayanan, K.J. Sanapapamma and Jyoti V. Vastrad

Agriculture Research Station, UAS, Dharwad–580007, Karanataka, India

Abstract—Broad use of natural coloured cottons is not effective yet due to their lower fiber qualities in comparison to conventional white cottons and limited range of natural colours. The low yielding, short fibered coloured cottons were not suitable for machine spinning; therefore they failed to face the rapid industrial turnover. Off late attention is diverted to study the possibility for using these eco-cottons commercially but few systematic studies and reports are available on the breeding programmes and meagre information on the fiber quality of naturally colored cottons. We report breeding efforts made to improve the naturally coloured G. hirsutum cotton genotypes with respect to yield and fiber quality through intra-specific, inter-specific and three way crosses between coloured and superior white genotypes followed by selections independently in three populations. Stable genotypes with uniform colour and high yield potential and improved fiber qualities were developed. Eight of the 32 advanced coloured genotypes in three populations tested under three replicated trials were superior to white linted check, Sahana (2138 kg/ha) for seed cotton yield. Three of these, dark brown (DDB-12 with 2986 kg/ha seed cotton yield), medium brown (DMB-225 with 2934 kg/ha) and green (DGC-78 with 1381 kg/ha) were potential for seed cotton yield and quality in the respective colour. The genotype DDB-12 had 21.6 mm fiber length and 18.6 g/tex strength; DMB-225(medium brown) had 22.9mm and 20.4 g/tex while green linted DCG-78 had 25.8mm and 22.2g/tex, span length and strength respectively. These genotypes performed consistently over three years of testing for yield and fiber quality. Yarn and fabrics were manufactured which were suitable for mill spinning and eco-fabrics of commercially acceptable range could be produced.

The simultaneous development of medium, dark brown and green shades along with white cotton will help in the creation of variability in the textile industry. Efforts need to be done to further improve the fibre properties which are being done using the stable color cotton lines developed in the present study for crossing with superior white cultivars for introgression and selection. Biotechnological approaches have been initiated to diversify the lint colour.

INTRODUCTION

The vast majority of cotton grown commercially in the world has white lint. However, there are genotypes / species which produce naturally coloured cotton and most of the wild species of cotton have coloured lint or fuzz. Though historical evidence like the fossils obtained from the excavations at Huca Preita in Northern coastal Peru indicated the usage and cultivation of colour cottons with lint colour from tan to red shades before 2500 B.C., only some of which exist today. It seems others have been lost, as they have never been described in the botanical literature. The ability of the white cotton to take up any colour to produce a large range of shades and colours in fabrics has lead to the popularization of white cotton.

In the recent past the thinking over of the other side of industrial revolution has made man realize that there is an urgent need to protect the environment. This eco- awareness has led to the revival of colour linted cottons, which can do away the processes of dyeing and processing. These colour cottons have once again crawled out with the efforts of an American Scientist, Sally Fox who began to improve colour cotton since 1982 and has developed naturally Colour Cotton Corporation that markets colour cotton fabrics (Fox, 1987). Naturally pigmented cottons not only are economical but more eco- friendly as they can avoid the use of carcinogenic dye chemicals in the fabric and also minimize the affluent of the dyeing industries, which pollute the land and water resources. Previous studies along with the advantage of inherent colour have also shown the flame resistance of brown cotton (Kimmel and Day, 2001; Williams, 1994) and colour change (darkening instead of fading) occurring with certain laundering

18

Development of Naturally Coloured Gossypium hirsutum Cotton Genotypes Suitable for Textile Industry 101

methods (Oktem et al, 2003; Vanzandt, 1994). It is also reported that naturally coloured cottons bring medical remedy for over 50 different somatic and psychosomatic disorders of man (Vreerland, 1993). The study demonstrates that naturally pigmented cottons have excellent sun - protection properties (high UV protection factor (UPF values), which are far superior to conventional bleached or unbleached cotton (Gwendolyn and Patricia, 2005) (green cotton UPF = 30 to 50 +; tan UPF= 20 to 45; brown UPF = 40 to 50+; bleached conventional UPF = 4; unbleached conventional UPF = 8).

On one hand, the knowledge of all these desirable features of the naturally pigmented cottons, there is no second thought for the adaptation of these cottons; on the other hand history shows that though they co-existed with white cotton they were left behind in the mid way. The low yielding, short fibered coloured cottons were not suitable for machine spinning; therefore they failed to face the rapid industrial turnover. Off late attention is diverted to study the possibility for using these eco-cottons commercially but few systematic studies and reports are available on the breeding programmes and still meagre information on the fiber quality of naturally coloured cottons(Święch and Frydrych 1998,1999; Święch et al., 1999).

We present a complete study done at UAS, Dharwad encompassing breeding to improve the naturally coloured G. hirsutum cotton with respect to yield and fiber quality to make these cottons commercially viable to both the farmer and textile industry. Among the four cultivated species of cotton, colour lint is reported in G. arboreum among diploid and in G. hirsutum in tetraploid cottons. White G. barbadense that are inherently superior sources of fibre quality and white G. hirsutum cottons are a source for both yield and fibre quality have been used for improvement of color cotton.


The dark brown selection DDBS-98, white released varieties, Abadhitha of G. hirsutum and Suvin of G. barbadense with characters as given Table 1 were used in the crossing programme to develop 3 populations as detailed in figure 1. The green genotype used in the crossing was very low yielding and had unstable colour expression.

In all the selection cycles from 2000–01 to 2005–06 individual plants were selected in field after peak boll bursting based on morphological observation on lint color, yield per plant and fibre length. Individual plants were sown in plant to progeny rows and again individual plants were selected. In advanced generations, during 2006 – 07 progeny row selections were effected.

Population I consisted of eighteen colour cotton genotypes from the cross DDBS 98 (Dark brown Hirsutum) x Abadhita (white Hirsutum) and one green from (Green Hirsutum x Abadhitha); population II, had ten genotypes from DDBS-98 (Dark brown Hirsutum) x Suvin (white Barbadense) and population III had seven genotypes from three way crosses [three selections from [(colour Hirsutum x white Hirsutum) x White barbadense] and 4 selections from [(colour Hirsutum x white Barbadense) x White hirsutum]. These stable genotypes were sown under three independent trials along with colour parent DDBS – 98 and white commercial check, Sahana. The trials were laid in three replications with two rows per genotype and spacing of 90 x 20 cm. under rainfed condition at ARS, Dharwad Farm. Recommended agro-management were followed.

The seed cotton yield was analyzed in RBD trial. Observations on boll weight were taken as average of twenty bolls per genotype. The ginning out turn (GOT) was calculated (using 300g seed cotton yield to get seed and lint weight) using the standard formula , GOT =[(Lint weight / Seed cotton weight) x 100] and seed index (SI) was weight of 100 seeds and lint index (LI) was calculated using the formula, LI= [(SI x GOT) / (100 – GOT)].

The fibre quality was analyzed at Central Institute of Research on Cotton Technology (CIRCOT), Regional laboratory at Dharwad, using HVI machine.


The genotype, DMB–225 which had significantly higher yield based on progeny row results of the year 2006-07 was grown on an area of one acre under isolation in 2007-08 with a spacing of 90 x 20cm following the same package of practices as in commercial white hirsutum varieties and the lint was tested for its suitability for commercial yarn and fabric production.


Population I was developed from intra-specific crosses, among the eighteen improved brown linted genotypes and one green genotype, DG-78 were tested along with white variety Sahana and dark brown parent DDSG-98. All the test entries were superior for both yield and fiber properties compared to original dark brown parent DDSG-98. Also some of the genotypes were numerically superior to even the white commercial cultivar Sahana for seed cotton yield and boll weight, but inferior with respect to lint index and GOT. Three genotypes DDB-12 (2986 kg/ha) with dark brown, DMB –225 (2934 kg/ha) with medium brown and DDB-210 (2834 kg/ha) with dark brown color were significantly superior for seed cotton yield than Sahana (2138 kg/ha) (Table 2 and Fig. 2).

Most of the selected genotypes were better for fibre quality than original parent DDBS-98 but were not on par with white check Sahana. Among the high yielding genotypes, medium brown coloured selection DMB-225 had better fiber length of 22.9 span length (2.5 %) and 20.4 g/tex strength and micronaire of 4.0 (Table 3). As it was very difficult to get stable green colour plants, in each generation individual plants selected on basis of uniform green shade and fiber length were bulked and advanced to next generation to repeat the same. The green genotype DG-78 thus developed was highly stable for green colour although its yield was not comparable to improved brown selections. It had good fiber quality of 25.8mm span length and 22.2 g/tex strength (Table 3).

In the population II, consisting of stable lines from inter-specific cross between dark brown G. hirsutum and white G. barbadense, among ten genotypes only one cream coloured selection, DCR-110 was numerically superior to white check, (Sahana) for seed cotton yield, lint index and GOT and even on par for fiber quality. Most of these selections were of medium brown lint. The genotypes DMB – 105 had very good fiber properties as 26.2mm 2.5% span length and 21.5 g/tex tenacity (Table 4 and 5).

In the third population derived from three way crosses using both white hirsutum and barbadense, only 7 selections could be advanced to replicated trial as most of them had very light colour. Though none of them was better than Sahana but were better than coloured parent. The highest yielding genotypes among colour selections in this population were dark brown, DDB-5 which had 22.8mm span length and one more medium brown type DMB-3 had the highest strength of 20.6g/tex. The cream colored genotypes DC-12 and DC-5 had fiber length of 24mm (Table 6 and 7).

Across all the populations using different approaches, intra-specific, inter-specific and three way cross followed by selections, it was observed that the segregants in inter-specific approach using G.barbadense had very good fiber quality in the early generation but as selections were made for darker shades in the advanced generations the fiber quality and the yield were reduced and those selections with good quality had light shades. In studies with white G. hirsutum cotton improvement by utilizing the G. barbadense for superior fiber quality similar observations of the reduction in fiber quality in the selections of advanced generations have been observed. However in the intra-specific population using G. hirsutum, there was significant increase in the yield and thus through this approach it was possible to improve seed cotton yield and boll weight along with moderate improvement of fiber quality parameters. The color in fiber lint is governed by major gene, multiple alleles and modifiers (Khan et al., 2009 and Waghmare and Koranne., 2000). and the expression of colour depends on the modifiers which may be present in the same species of G.hirsutum. It is observed that G. hirsutum colour genotypes can be improved by intra-specific hybridization followed by selection approach that is by using the white superior G.hirsutum genotypes. Once genotypes with dark brown colour with high yield and medium/ light brown genotypes with good fiber quality parameters are available in the G.hirsutum species, these can be intermated to combine color, yield and fiber quality into single genotype.

Development of Naturally Coloured Gossypium hirsutum Cotton Genotypes Suitable for Textile Industry 103

The result indicated the progress in the improvement of naturally coloured cottons to make them commercially viable. Among all the genotypes put together, DDB-12 (dark brown), DMB – 225 (medium brown) and DCR – 110 (cream) were best in that shade of brown. The green genotype DCG-78 had good fiber traits. The genotypes, DDB-12, DMB-225 and DCG-78 were grown in larger plots over three years and tested for their productivity and suitability for yarn and fabric manufacture. Dark and medium brown genotypes were found to be on par with white linted variety, Sahana with respect to yield and suitable for various fabric productions (Fig.2 & 3). The green genotype DCG – 78 though had comparatively less yield potential but it necessiated to promote this genotype as it had superior fiber quality traits. The simultaneous development of medium and dark brown and green shades along with white cotton will help in the creation of variability required for the textile industry. These three genotypes were presented in the Zonal Research and Extension Committee Meeting of the university during 2009-10 and have been approved for commercial cultivation of these genotypes under contract farming under the technical supervision of the university (Proceedings of Rabi/Summer 2010-11).

Efforts need to be done to further improve the fibre properties which are being done using the stable colour cotton lines developed in the present study for crossing with superior white cultivars for introgression and selection. Also there is a necessity to diversify the lint colour which is attempted through biotechnological approaches. The Flavonoid 3’-5’ hydroxylase gene from petunia and snapdragon which is the enzyme responsible for turning the pathway of pigmentation towards blue shades has been cloned. The transformation of these genes in the improved genotypes is initiated. The expression of these genes in lint may help in creation of a shade not naturally available.

REFERENCES [1] Apodaca, J.K., (1990). Naturally coloured cotton: A new niche in the Texas Natural Fibers. BBR Working Paper Series

1990 – 2 Bureau of Business Research, University of Texas at Austin. [2] Fox, S. (1987). Naturally Coloured Cotton: Spin-off. December, 48-50. [3] Gwendolyn, H. and Patricia, C. C. (2005). The ultraviolet protection factor of naturally pigmented cotton. The Journal of

Cotton Science, 9, 47-55. [4] Khan A. A., Azhar F. M., Khan I. A., Riaz A. H. and Athar M. (2009). Genetic basis of variation for lint colour, yield and

quality in cotton (Gossypium hirsutum L.) Plant Biosystems. (143) pp 517-524. [5] Kimmel, L.B. and Day, M.P., (2001).New life for an old fiber: attributes and advantages of naturally coloured cotton.

American Association of Textiles and Colour Cotton Review 1(10), 32-36. [6] Oktem, T.A., Gurel and Akdemir, H., (2003). The characteristic attributes and performance of naturally coloured cotton.

American Association of Textiles and Colour Cotton Review, 3(5), 24-27. [7] Proceedings of Rabi/Summer 2010-11. Combined Zonal Research and Extension Advisory Council and Zonal Research and

Extension Formulation Comitee Meeting (Zone- I & II, III & IV), DATED 02-04 September, 2010, UAS, Dharwad. [8] Stephens, S.G., (1975). A re-examination of the cotton remains from Huaca Prieta, NorthCoastal Peru. American Antiquity

40(4), 406-418. [9] Święch T. and Frydrych I., (1998). Naturally colored cotton as an element of humanoecology, Architektura Tekstyliów (1):

20-22. [10] Święch T. and Frydrych I., (1999). Naturally colored cottons: Properties of fibres and yarns. Fibres andTextiles in Eastern

Europe, (4), 25-29. [11] Święch T., Frydrych I. and Balcar G., (1999).The assessment of naturally colored cotton properties. Bulletin of Gdynia

Cotton Association, (3), 12-26. [12] Vanzandt, M.J., (1994). Development of fabric from fox fibre naturally coloured cotton and evaluation of flame-resistant

characteristics. Ph.D. Dissertation, Texas Technical University, Lubbock, TX. [13] Vreerland, J.M., (1993). Naturally coloured and organically grown cottons.Anthropological and Historical perspective.

Proceedings of Beltwide Cotton Conferences, 1533-1536. [14] Williams, B., Fox (1994). Fibre naturally coloured cotton, green and brown (coyote) resistance to changes in colour. Ph.D.

Dissertation, Texas Technical University, Lubbock, TX. [15] Waghmare V. N., Koranne K. D. (2000). Inheritance of lint colour in Desi cotton (Gossypium arboreum L.) Indian Journal

of Genetics and Plant Breeding (60).

Divergent Selection for Yield and Earliness in Cotton (Gossypium hirsutum L)

P. Michalakopoulos, C. Goulas, A. Katsiotis and S. Rangasamy

Organization of Agricultural Vocational Education Training and Empl, Agricultural University of Athens, Greece

INTRODUCTION

Knowledge of the nature and the size of genetic influences on the breeding material are necessary so that a breeding procedure could be decided upon, as the genetic behavior of each trait may vary, depending on the genetic material and the environment. Therefore, the gene action of quantitative traits must be studied before the beginning of a breeding program.

The existence of genetic variability and the definition of its nature (additive, non-additive, etc.) are necessary for the decision upon the most effective breeding methodology, regarding the creation of the desired variety. The first and, by far, simplest approach is that of divergent selection (high vs low yield or desired vs undesired genotypes, in general). Its planning permits information retrieval regarding the existence of genetic variability and the heredity mode of the specific trait. Furthermore, it provides information on the response to the selection as well as on indirect changes in traits indirectly selected (Falconer and Mackay, 1996). Divergent selection has been mainly implemented in corn (Chesang-Chumo, 1993; Masole, 1993; Martin et al., 2004; Pressoir and Berthaud, 2004; Chimenti et al., 2006; Uribelarrea et al., 2007; Hallauer et al., 2010) and in other crops, such as in wheat (Hucl, 1995; Al Hakimi et al., 1998), alfalfa (Chloupek, 1999; Lamb et al., 1999; Klos and Brummer, 2000) and cotton (Verhalen et al., 1975; Radin et al., 1994; Ulloa et al., 2000). The objectives of this study were: (i) to determine the effect of divergent selection for yield and earliness in diverse segregating populations derived from six crosses and (ii) to examine the potential use of specific genetic material in planning and implementing a breeding program for yield and its components and earliness of upland cotton.


The genetic material used consisted of seven commercial varieties; five cultivated in Greece and two in India. The experiments were conducted during five cultivation periods. In year 2003, crosses were performed using as a common parent one of the varieties cultivated in Greece. During year 2004, the F1 hybrids were backcrossed to their parental progenitors.

During the 2005 cultivation period, divergent selection in the F2 generation and for all six crosses was performed for yield and earliness (Falconer, 1960). One hundred individual plants, using a grid mass selection scheme, were analyzed (10 grids and 10 plants per grid) as described (Gardner, 1961). The distance among the lines was 97cm and among the plants on the line 25cm, meaning four plants per square-meter. The parents of each cross were alternately sown as testers on the two lines of each grid. The earliness and the yield in seed cotton were registered for every individual plant (F2 and the respective P1 and P2 parents). For earliness, the day-span from the sowing until the opening of the first ball (DBO) was used. The yield of, the seed cotton (weight) was expressed in grams.

In each grid of the ten F2 plants per cross divergent selection was performed (selection ratio 10%) for the following traits; a) one high-yielding plant (HY) and one low-yielding plant (LY), b) one earlier plant (HE) with the later one (LE), c) one earlier plant among those yielding more than 85% of the average of witnesses (YHE) and the later one among those yielding more than 85% of the average of the witnesses (YLE). Thus, balanced mixtures of the ten selected plants, HY-LY, HE-LE, YHE-YLE, were created for each one of the six crosses.

19

Divergent Selection for Yield and Earliness in Cotton (Gossypium hirsutum L) 105

The six (6) F3 selected populations (HY-LY, HE-LE, YHE-YLE) of each cross (36, in total) were analyzed during the 2006 cultivation period. The experimental design used was the Randomized Complete Blocks (RCB) with four replications. An experimental block of one, five-meter long, line was used. The distance among the lines was 97cm, while the final density after sparsing was 12 to 14 plants per meter. Earliness (DBO) and seed yield were registered. Random F4 seed sample was taken from each selected population and it was used for analysis during the 2007 cultivation period, according to the same procedure described for the F3 selected populations.

STATISTIC ANALYSIS

For each one of the six crosses the variance of one hundred plants was estimated for all the traits, estimating the total phenotypic variance as σp

2 = σg2

+ σe2. The variance of the thirty plants per parent (P1

and P2) was also estimated. The average variance of the plants of P1 and P2 parents (30+30) was an estimation of σe

2. Criterion F was made for the evaluation of variances P1 and P2, as well as for F2 vs. P1, P2 and (P1+P2)/2. Therefore, estimation of σp

2 = σg2 + σe

2 and of H2 heredity coefficient was made feasible. Furthermore, the genetic variability coefficient (GCV) and the selection differential for divergent selection (high-low), and the expected selection progress R = S x H2 for yield and earliness were estimated.

The data concerning the selection effectiveness were analyzed with the conventional RCB Anova (Steel and Torrie, 1980). The distinction of average rates was made with the least important difference (Fisher’s protected LSD) for every trait. The statistic model was fixed and made possible the estimation of the genetic variance σg

2 among the six genotypes according to the mean rate of each genotype (plot mean basis).


In year 2005, F2 yield was practically around parental mean rate, as expected from a qualitative trait like yield. The genetic variability among F2 plants ranged from 36.59% in GR1 x GR5 to 42.16% in GR1 x IN1 in bigger amounts in relation to the genetic variability among parental plants in all crosses. The data of the divergent selection revealed substantial differentiation between high-yielding and low-yielding plants, implying indication of existence of genetic variability potential use for effective selection for yield. The heredity coefficient was satisfactorily high ranging from 0.38 to 0.60 (Table 1).

TABLE 1: DATA OF SELECTION FOR YIELD (G / PLANT) IN DIVERGENT SELECTION IN 2005

Cross Means CV% σG2 h2 Selection Differential

Parents F2 Parents F2 - + 1. GR1 x GR2 111.27 113.29 26.07 – 25.03 40.04 1242.05 0.60 58 78

118 - 104.53 136 2. GR1 x GR3 111.90 118.23 30.32 – 31.21 40.68 1128.27 0.49 61 88

116.53 - 107.27 149 3. GR1 x GR4 105.93 98.81 21.45 – 36.28 38.56 556.70 0.38 51 61

118.80 - 93.07 112 4. GR1 x IN1 106.95 102.29 27.41 – 29.54 42.16 938.90 0.50 54 83

114.90 - 99 137 5. GR1 x GR5 112.03 113.04 27.07 – 25.32 36.59 846.22 0.49 53 79

113.63 - 110.43 132 6. GR1 x IN2 110.23 107.36 27.94 – 26.27 41.28 1073.40 0.55 57 75

103.03 - 117.43 132 As for earliness, the data indicated the existence of genetic variability and the heredity coefficient

ranging from 0.54 to 0.83, implying indication of effective selection potential. The data of divergent selection allowed for the differentiation among early and late plants from 14 to 19 days, implying potential for selection regarding earliness (Table 2).


TABLE 2: DATA OF SELECTION FOR EARLINESS (DBO) IN DIVERGENT SELECTION IN 2005

Cross Means σP2 (CV%) σG

2 h2 Selection Differential Parents F2 Parents F2s - +

1. GR1 x GR2 113.5 115.6 2.88 - 2.87 5.1 24.08 0.69 7 9 104.6 - 122.4 16

2. GR1 x GR3 114.7 113.6 2.86 - 2.59 4.68 18.52 0.66 7 9 107.4 - 122 16

3. GR1 x GR4 106.3 109.9 2.46 - 3.18 5.07 22.00 0.71 5 10 107.1 - 105.4 15

4. GR1 x IN1 115.7 114.5 3.97 - 4.10 5.60 24.82 0.60 8 11 108.7 - 122.7 19

5. GR1 x GR5 112.7 112.5 3.88 - 2.78 4.90 16.41 0.54 6 8 106.8 - 118.7 14

6. GR1 x IN2 106.8 112.1 1.84 - 2.39 5.07 26.90 0.83 6 10 101 - 112.7 16

The combined selection for yield and earliness (Table 3) revealed potential for genotype selection combining satisfactory yield – ranging from 45% to 72% - with respective earliness from five to seven days compared to the selection for earliness alone, being from eight to eleven days. The combination between earliness and yield appears to be possible while the combination between yield and maturity seems to be impossible for the specific genetic material and under the specific circumstances (as shown in the first cross).

TABLE 3: DATA OF SELECTION FOR YIELD (GR) AND EARLINESS (DBO) IN DIVERGENT SELECTION IN 2005

Cross Means Means Selection Differential Parents F2 Yield Earliness Yield Earliness Yield / Early Yield / Late

1. GR1 x GR2 114.2 113.5 113.3 115.6 165 109 148/ 121 118 - 110.4 104.6 - 122.4

2. GR1 x GR3 118.5 114.7 118.23 113.6 168/ 107 147/ 119 128.7 - 108.3 107.4 - 122

3. GR1 x GR4 107.8 106.3 98.81 109.9 150/ 105 133/ 114 116 - 99.7 107.1 - 105.4

4. GR1 x IN1 104.5 115.7 102.29 114.5 163/ 107 120/ 120 113.6 - 95.4 108.7 - 122.7

5. GR1 x GR5 114.8 112.7 113 112.5 148/ 107 148/ 117 115.6 - 113.9 106.8 - 118.7

6. GR1 x IN2 107.8 106.8 107.4 112.1 142/ 107 133/ 117 100.4 - 115.1 101 - 112.7

SELECTION EFFECTIVENESS

Yield

The productive behaviour (yield) of the F3 genotypes and the check for the year 2006 is shown in Table 4, whereas variance analysis and estimation of the genetic parameters for yield during the same year are shown in Tables 5 and 6, respectively. The results indicated that, genotypes differed in five out of the six crosses on 99% significance level and on 90% in the sixth cross. The CV% variance coefficient ranged from 2.78 to 8.07% while the heredity coefficient gave values of 0.25 for the GR1 x GR2 and higher (0.41 to 0.57) for the rest of the crosses. Finally, the genetic variance coefficient ranged on low levels from 3.17 to 6.59 %.

The genotypes which had been selected as high-yielding (HY) in year 2005, were differentiated from the low-yielding ones (LY) in the GR1 x GR2, GR1 x GR5 and GR1 x IN2 crosses (Table 4). The genotypes combining high-yield and earliness (YHE) were differentiated from the ones combining high-yield and maturity (YLE) in two crosses; in the GR1 x GR4 cross, where the late genotype was the highest-yielding one, as expected, and in the GR1 x GR4 cross, with the opposite result, however; the earlier genotype was higher-yielding than the late one. As far as earliness alone is concerned, the earlier genotypes (HE) were differentiated from the later ones (LE) in two crosses (GR1 x GR3 and GR1 x GR4), with the latter out-yielding the first ones, as expected.


TABLE 4: MEANS FOR YIELD (G PLOT -1) OF F3 GENOTYPES IN 2006

Cross Source GR1 x GR2 GR1 x GR3 GR1 x GR4 GR1 x IN1 GR1 x GR5 GR1 x IN2

HE 2059bc 2110d 1894c 1966abc 2032bc 1963d HY 2158ab 2456a 2226ab 1868bcd 2179a 2188a LE 2060bc 2443a 2166b 2137a 1999c 1996cd LY 1946c 2374ab 2159b 1835cd 2010bc 2066bc

YHE 2329a 2362abc 2176b 1748cd 2178a 2151a YLE 2200ab 2188cd 2336a 1757cd 1974c 2109ab

Check 2051bc 2198bcd 2223ab 2056ab 2029bc 2109ab LSD 208 186 156 221 109 84

The behaviour of the F4 genotypes and the check, variance analysis and the genetic parameters, respectively, as for yield in the subsequent 2007 year, are presented (Table 7, 8 and 9). The genotypes differed in all six crosses on 99% significance level. The CV % variance coefficient ranged from 2.51 to 3.83% while the heredity coefficient gave significantly higher values, ranging from 0.73 to 0.90 for all crosses. The genetic variance coefficient ranged again on low levels from 4.86 to 8.57%.

TABLE 5: ANALYSIS OF VARIANCE FOR YIELD (G PLOT -1) IN 2006

Cross GR1 x GR2 GR1 x GR3 GR1 x GR4 GR1 x IN1 GR1 x GR5 GR1 x IN2

ΜS Genotypes. 47208 60635.4 57782.2 84253 23182.8 20622.4 ΜS Error. 20361 16240.6 11426.2 22974 5578 3323.8 CV% 6.76 5.56 4.91 8.07 3.62 2.78 Ftest + ** ** ** ** **

**p = 0.01, * p = 0.05, + p = 0.10

TABLE 6: ESTIMATIONS OF GENETIC PARAMETERS FOR YIELD (G PLOT -1) IN 2006

Cross GR1 x GR2 GR1 x GR3 GR1 x GR4 GR1 x IN1 GR1 x GR5 GR1 x IN2 σG

2 6711.7 11098.7 11589 15319.7 4401.2 4324.6 σP

2 27072.7 27339.3 23015.2 38293.7 9979.2 7648.4 h2 0.25 0.41 0.50 0.40 0.44 0.57 GCV% 3.88 4.59 4.94 6.59 3.21 3.17

TABLE 7: MEANS FOR YIELD (G PLOT -1) OF F4 GENOTYPES IN 2007

Cross Source GR1 x GR2 GR1 x GR3 GR1 x GR4 GR1 x IN1 GR1 x GR5 GR1 x IN2 HE 1847c 1748c 2057b 1822abc 1777e 1747cd HY 2094a 1730cd 1855d 1736c 1948c 1857b LE 1701d 1696cd 1818d 1899a 1836de 1947a LY 1828c 1581f 1631e 1911a 1987bc 1826bc YHE 1804c 2006a 1929c 1779bc 2064ab 1946a YLE 1847c 1681de 1842d 1529e 1914cd 1740d Check 1935b 1868b 2088b 1861ab 1830de 1842b LSD 79 64 72 98 85 81

Progeny means followed by a different letter are significantly different at the P = 0.05.

TABLE 8: ANALYSIS OF VARIANCE FOR YIELD (G PLOT -1) IN 2007

Cross GR1 x GR2 GR1 x GR3 GR1 x GR4 GR1 x IN1 GR1 x GR5 GR1 x IN2 ΜS Genotypes. 56491.8 69687.9 111498 75805.9 54687.6 35547.5 ΜS Error. 2914.2 1927.4 2442 4493.7 3419.3 3055.3 CV% 2.86 2.51 2.57 3.83 3.00 2.98 Ftest ** ** ** ** ** **

**p = 0.01, * p = 0.05, + p = 0.10.


TABLE 9: ESTIMATIONS OF GENETIC PARAMETERS FOR YIELD (G PLOT -1) IN 2007


2 13394.4 16940.1 27264 17828 12817.1 8123 σP

2 16308.6 18867.5 29706 22321.7 16236.4 11178.3 h2 0.82 0.90 0.92 0.80 0.79 0.73 GCV% 6.13 7.43 8.57 7.62 5.82 4.86

Progeny means followed by a different letter are significantly different at the P = 0.05.

The genotypes which were selected as high-yielding (HY) in year 2005 were differentiated from the low-yielding ones (LY) in year 2007 in four out of the six crosses. However, only in one of them (GR1 x GR2) was the equivalent differentiation noticed in year 2006. In the other two crosses (GR1 x GR5 and GR1 x IN2), with differentiation in year 2006, no difference was noticed for yield in year 2007. The genotypes combining high yield and earliness (YHE) were differentiated from those combining high yield and maturity (YLE) in five out of the six crosses (except for the GR1 x GR2). Therefore, the differentiation noticed in year 2006 in the GR1 x GR4 and GR1 x GR5 crosses was maintained for the next generation in year 2007. It is noticeable that the early genotype (YHE) out-yielded the late one (YLE) in all six crosses. As far as earliness alone is concerned, the early genotypes (HE) were differentiated from the later ones (LE) in three out of the six crosses (GR1 x GR2, GR1 x GR4 and GR1 x IN2), with the second maintaining the differentiation presented in year 2006. Furthermore, in the first two crosses the early genotype (HE) out-yielded the later one (LE) while in the third cross, the opposite trend was observed.

Earliness

The earliness behaviour of the F3 genotypes and the check, variance analysis and the genetic parameters were reported in Table 10,11 and 12 for year 2006 respectively. The genotypes differed in five out of the six crosses on 99% significance level, and on the sixth cross on 90% significance level. The CV% variance coefficient ranged on very good levels in all crosses from 1.17 to 2.06%, while the heredity coefficient gave high values from 0.71 for the GR1 x GR4 to 0.91 for the GR1 x IN2 cross. Finally, the variance genetic coefficient was on low levels, ranging from 3.21 to 4.86%.

TABLE 10: MEANS FOR EARLINESS (DBO) OF F3 GENOTYPES IN 2006

Cross Source GR1 x GR2 GR1 x GR3 GR1 x GR4 GR1 x IN1 GR1 x GR5 GR1 x IN2 HE 105c 104cd 98e 108cd 106de 117a HY 117a 108b 104bc 109c 114b 111b LE 120a 114a 109a 114b 118a 111b LY 108bc 102d 102cd 105d 106de 107c YHE 107c 106bc 99de 109c 104e 107c YLE 117a 112a 107ab 118a 115b 106cd Check 108bc 106bc 102cd 113b 111c 105d LSD 3 3 3 3 3 2

Progeny means followed by a different letter are significantly different at the P = 0.05. TABLE 11: ANALYSIS OF VARIANCE FOR EARLINESS (DBO) IN 2006

Cross GR1 x GR2 GR1 x GR3 GR1 x GR4 GR1 x IN1 GR1 x GR5 GR1 x IN2 ΜS Genotypes. 121.42 53.76 47.82 60.69 99.75 66.40 ΜS Error. 5 4.66 4.47 5.07 3.60 1.64 CV% 2.01 2.02 2.06 2.04 1.71 1.17 Ftest + ** ** ** ** **

**p = 0.01,* p = 0.05, + p = 0.10.


TABLE 12: ESTIMATIONS OF GENETIC PARAMETERS FOR EARLINESS (DBO) IN 2006


2 29.11 12.27 10.84 13.91 24.04 16.19 σP

2 34.10 16.94 15.31 18.98 27.64 17.83 h2 0.85 0.72 0.71 0.73 0.87 0.91 GCV% 4.86 3.28 3.21 3.38 4.43 3.66

TABLE 13: MEANS FOR EARLINESS (DBO) OF F4 GENOTYPES IN 2007

Cross Source GR1 x GR2 GR1 x GR3 GR1 x GR4 GR1 x IN1 GR1 x GR5 GR1 x IN2 HE 112bc 110def 106cd 112de 112de 110g HY 122a 113cd 109bc 114cd 119ab 114cd LE 122a 117a 113a 120ab 121a 114de LY 113bc 107g 107bcd 110e 111de 112ef YHE 113bc 112cde 105d 115cd 110e 112efg YLE 120a 115ab 110b 121a 118bc 119b Check 115b 114bc 113α 116bc 116c 111fg LSD 3 2 3 4 2 2

Progeny means followed by a different letter are significantly different at the P = 0.05. TABLE 14: ANALYSIS OF VARIANCE FOR EARLINESS (DBO) IN 2007

Cross GR1 x GR2 GR1 x GR3 GR1 x GR4 GR1 x IN1 GR1 x GR5 GR1 x IN2 ΜS Genotypes. 72.65 33.76 23.11 50.13 71.13 57.57 ΜS Error. 5.63 2.88 4.78 6.29 2.87 1.72 CV% 2.05 1.52 2.02 2.18 1.47 1.15 Ftest ** ** ** ** ** **

**p = 0.01, * p = 0.05, + p = 0.10.

TABLE 15: ESTIMATIONS OF GENETIC PARAMETERS FOR EARLINESS (DBO) IN 2007


2 16.75 7.72 4.58 10.96 17.06 13.96 σP

2 22.39 10.60 9.36 17.25 19.93 15.68 h2 0.75 0.73 0.49 0.64 0.86 0.89 GCV% 3.53 2.48 1.98 2.88 3.58 3.27

The genotypes selected as early (HE) in year 2005 were differentiated from the later ones (LE) in all six crosses in year 2006, with the early genotypes remaining early and the late ones remaining late. This differentiation ranged from six days for the GR1 x IN2 to fifteen days for the GR1 x GR2 cross. The genotypes combining high yield and earliness (YHE) were differentiated from those combining high yield and maturity (YLE) in five out of the six crosses, with the first (YHE) being earlier than the second ones (YLE) from six (GR1 x GR3) to eleven (GR1 x GR5) days. The high- (HY) and low- (LY) yielding genotypes differed in earliness in five out of the six crosses, with the high-yielding ones being later, as expected.

The same holds true for the behavior of the seven genotypes (F4) for earliness in year 2007 (Table 13). The genotypes differed in all six crosses on 99% significance level while the CV% variance coefficient was on very good levels in all crosses, ranging from 1.15 to 2.18% (Table 14). The heredity coefficient gave values from 0.49 for the GR1 x GR4 to 0.89 for the GR1 x IN2 cross and the variance genetic coefficient ranged from 1.98 to 3.58% (Table 15).

Early genotypes (HE) were differentiated from later ones (LE) in all crosses in year 2007 as well, with the HE remaining early and the LE late. This differentiation occurred from four for the GR1 x IN2 to ten days for the GR1 x GR2 cross. Likewise, the genotypes combining high yield and earliness (YHE) were differentiated from those combining high yield and maturity (YLE) in all six crosses, with the first (YHE) being earlier than the latter (YLE) from three (GR1 x GR3) to eight (GR1 x GR5) days. High-(HY) and low-yielding (LY) genotypes different in earliness in five out of the six crosses, with the high-yielding ones being later in year 2007 as well.


To sum up, in divergent selection, regarding yield, differentiation between high (HY) and low (LY) was noticed for three out of the six crosses in both years 2006 an 2007 (F3 and F4 genotypes, respectively). However, only one of the three crosses maintained this differentiation for both years. The genotypes combining yield and earliness (YHE and YLE) were differentiated in two crosses in year 2006 and in our in year 2007.

As for earliness, the differentiation between early and late genotypes was absolute for all six crosses during both cultivation periods. In addition, differentiation was noticed between HY and LY genotypes in the same five out of the six crosses in both years of analysis, with the first being later than the latter, as expected. The behavior of the YHE and YLE genotypes was differentiated in five in year 2006 and in six crosses in 2007, with the YHE genotypes being earlier than the YLE ones.

Selection for earliness and yield appears to be possible while selecting for yield and late maturity seems to be impossible with this specific genetic material and under these specific circumstances.

REFERENCES [1] Hakimi, Al., Monneveaux, A., P. and Nachit, M.M. (1998). Direct and indirect selection for drought tolerance in alien

tetraploid wheat x durum wheat crosses. Euphytica 100: 287-294(8). [2] Chesang-Chumo, J. (1993). Direct and correlated responses to divergent selection for rind penetrometer resistance in

MoSCSSS maize synthetic (Zea mays L.). Ph.D. thesis. Univ. of Missouri, Columbia. [3] Chimenti, A. C., Marcantonio, M. and Hall A.J. (2006). Divergent selection for osmotic adjustment results in improved

drought tolerance in maize (Zea mays L.) in both early growth and flowering phases. Field Crops Research 95:305-315. [4] Chloupek, O. (1999). Effect of divergent selection for root size in field-grown alfalfa. Can. J. Plant Sci. 79:93–95. [5] Falconer, D.S. and Mackay, T. F. C. (1996). Introduction to quantitative genetics. 4th ed. Longman Group Limited, Harlow,

Essex, U.K. [6] Hallauer, A. R., Ross, A. J. and Lee, M. (2010). Long-Term Divergent Selection for Ear Length in Maize, in Plant Breeding

Reviews: Long-term Selection: Crops, Animals, and Bacteria, Volume 24, Part 2 (ed J. Janick), John Wiley & Sons, Inc., Oxford, UK.

[7] Hucl, P. (1995). Divergent selection for sprouting resistance in spring wheat. Plant Breed. 114: 199–204. [8] Klos L. E. K., and Brummer, E. C. (2000). Response of Six Alfalfa Populations to Selection under Laboratory Conditions

for Germination and Seedling Vigor at Low Temperatures, Crop Sci. 40:959–964. [9] Lamb, J. F. S., Barnes D. K. and Henjum K. I. (1999). Gain from Two Cycles of Divergent Selection for Root Morphology

in Alfalfa. Crop Sci. 39: 1026–1035. [10] Martin, A. S., Darrah L. L., and Hibbard B. E. (2004). Divergent selection for rind penetrometer resistance and its effects

on European corn borer damage and stalk traits in corn. Crop Sci. 44:711–717. [11] Masole, H. (1993). Evaluation of high and low divergent rind penetrometer resistance selection at three plant densities in

maize. M.Sc. thesis. Univ. of Missouri, Columbia. [12] Pressoir, G., and Berthaud, J. (2004). Population structure and strong divergent selection shape phenotypic diversification in

maize landraces. Heredity. 92: 95–101. [13] Radin, J. W., Lu. Z. M., Percy, R. G., and Zeiger, E. (1994). Genetic variation for stomatal conductance in Pima cotton and

its relation to improvements of heat adaptation. Proc. Natl. Acad. Sci. USA 91: 7217–7221. [14] Ulloa M., Cantrell R. G., Richard P. G., Zeiger E. and Lu. Z. (2000). QTL Analysis of stomatal conductance and

relationship to lint yield in an interspecific cotton. J. Cotton Sci. 4:10-18. [15] Uribelarrea, M., Moose, S. P. and Frederick, E. Below. (2007). Divergent selection for grain protein affects nitrogen use in

maize hybrids. Field Crops Research 100 (1): 82-90. [16] Verhalen, L. M., Baker, J. L. and McNew, R. W. (1975). Gardner’s Grid System and Plant Selection Efficiency in

Cotton. Crop Sci.15: 588-591.

Development of Recombinant Inbred Lines for Fibre Quality Traits in Gossypium hirsutum L

Jagmail Singh1, Babita Chaudhary2, Preeti Srivastva3, Sapna Tiwari4 and Mukesh Kumar Sharma5

1Principal Scientist, 3Research Associate, 4Senior Research Fellow, 5Technical Officer T5, Division of Genetics, IARI, N. Delhi–110012

2Senior Scientist, Sunnhemp Research Station, (CRIJAF), Pratapgarh (UP)

INTRODUCTION

Cotton is an important commercial crop and plays a key role in Indian economy. It is a major fibre crop contributing nearly 75% to the natural fibre production. During 2010 the area under cotton was about 11 million ha with an expected production of 330 to 335 lakh bales. Cotton is grown in tropical and sub-tropical regions of 80 countries. China, India, USA, Pakistan, Brazil, Uzbekistan, Turkey, Greece, Turkmenistan and Syria are top 10 cotton producing countries of the world. India ranked first in area under cotton and second in total production after China.

Since the launching of All India Coordinated Cotton Improvement Project in 1967, considerable success has been achieved in developing improved cultivars with high yield potential and superior fibre quality. Cultivars with spinning counts ranging from 6s to 120s counts have been developed. The research programmes was largely centred on improving fibre length and fineness but fibre strength attracted relatively less attention. Development of G. hirsutum varieties like ‘G-67’ and ‘MCU 5’ was a major mile-stone in improvement of yield and fibre quality. G. barbadense varieties ‘Sujatha’ and ‘Suvin’ could be spun at 100s counts and 120s counts, respectively. Development of inter-specific and intra-specific tetraploid hybrids like H-4, H-6, H-8, H-10, JKHy-1, JKHy-2, DHH-11, PKVHy-2, NHH-44, Savita, etc (intra- specific) and Varalaxmi, DCH-32, NHB-12, HB 224, DHB 105, TCHB 213, Sruthi, etc (inter-specific) also played significant role in increasing production of superior quality cotton. The adoption of modern high speed ring/open-end spinning system by textile industry has increased demand for high fibre strength cottons. Most of the presently developed varieties have low fibre strength of 18 to 20 g/tex. The genetic variation available for the improvement, especially for fibre strength in Gossypium hirsutum cotton that accounts for 90% of total production is limited. Research was therefore initiated at Indian Agricultural Research Institute, New Delhi to develop recombinant inbred lines for fibre quality traits, especially fibre strength and to study the genetic variation in segregating generations and the feasibility to develop superior lines combining high yield with high fibre strength.


Research work was initiated at Indian Agricultural Research Institute, New Delhi to develop strains having high seed cotton yield and fibre strength that resulted in the development of the strain P 56-4 for high fibre strength (Singh and Kaushik 2006; Singh et al., 2007). The mean fibre strength of ‘Pusa 56-4’ was found to be 27.8 g/tex against 23.1 g/tex of local check ‘Pusa 8-6’ during 5-year period from 2003 to 2007 (Table 1). Likewise, its mean 2.5% span length was 28.4 mm and micronaire 3.9 associated with fibre uniformity (53.5%), good elongation (6.2%) and low short fibre index (5.0%). During the same period the mean 2.5% span length of local check ‘Pusa 8-6’ was 28.2 mm, mean micronaire value 4.6, mean uniformity ratio 51.7%, mean fibre elongation 5.8% and mean short fibre index 6.1%. Variety ‘RS 2013’ developed by Agricultural Research Station, Sriganganagar was released for commercial cultivation in Rajasthan state. It belongs to medium staple category with fibre length of about 25 mm and fibre strength of about 19 g/tex. Besides evaluation at IARI, New Delhi, Pusa 56-4 and RS 2013 were also evaluated for some fibre quality traits at Central Institute for Cotton Research (CICR), Nagpur and

20


University of Agricultural Sciences (UAS), Dharwad during 2006. Pusa 56-4 showed 27.7 g/tex mean fibre strength, 28.7 mm 2.5% span length, 3.8 micronaire value and 6.3% fibre elongation. The variety RS 2013 showed 22.1 g/tex fibre strength, 25.4 mm 2.5% span length, 4.4 micronaire value and 6.1% elongation (Table 2). ‘Pusa 56-4’ and RS 2013 were therefore selected as contrasting parents for developing recombinant inbred lines for fibre quality traits i.e. fibre strength.

TABLE 1: EVALUATION OF PUSA 56-4 VS LOCAL CHECK PUSA 8-6 FOR FIBRE QUALITY TRAITS FROM 2003 TO 2007

Year Strain/ Variety


Fibre Strength (g/ tex)

Micronaire Value

Uniformity Ratio (%)

Fibre Elongation

(%)

Short Fibre

Index (%)2003 Pusa 56-4 28.6 29.4 3.7 53.0 6.1 6.8

Pusa 8-6 28.0 24.2 4.7 52.1 5.5 7.8 2004 Pusa 56-4 28.5 26.7 3.8 52.1 6.0 8.0

Pusa 8-6 28.0 23.3 4.7 52.7 4.8 11.7 2005 Pusa 56-4 27.9 26.9 4.0 52.3 6.3 3.2

Pusa 8-6 27.5 22.1 4.7 49.9 6.2 3.5 2006 Pusa 56-4 29.7 28.6 4.0 56.0 6.4 3.5

Pusa 8-6 29.6 22.9 4.6 51.5 6.3 3.5 2007 Pusa 56-4 27.7 27.5 4.0 55.6 6.2 3.5

Pusa 8-6 27.9 23.0 4.5 52.1 6.3 4.2 Mean Pusa 56-4 28.4 27.8 3.9 53.5 6.2 5.0

Pusa 8-6 28.2 23.1 4.6 51.7 5.8 6.1

TABLE 2: PERFORMANCE OF PUSA 56-4 AND RS 2013 FOR IMPORTANT FIBRE QUALITY TRAITS AT DELHI, NAGPUR AND DHARWAD DURING 2006

(a) Fibre Strength (g/tex) IARI, N. Delhi CICR, Nagpur UAS Dharwad Mean

Pusa 56-4 28.4 28.9 25.9 27.7 RS 2013 19.9 24.8 21.7 22.1

(b) 2.5% Span length (mm) Pusa 56-4 28.5 29.0 28.6 28.7 RS 2013 25.7 25.7 24.9 25.4

(c) Micronaire value Pusa 56-4 4.1 3.8 3.6 3.8 RS 2013 4.5 4.5 4.2 4.4

(d) Fibre Elongation (%) Pusa 56-4 6.3 6.4 6.1 6.3 RS 2013 5.7 6.4 6.3 6.1

Strain ‘Pusa 56-4’ was crossed with variety ‘RS 2013’ in 2004 to obtain F1 generation. It was advanced to F2 generation during 2005 and was evaluated during 2006. Two hundred and ninety seven single plants from F2 generation were phenotyped for fibre strength and other fibre quality traits. Data were also recorded on seed cotton yield and important yield components. These single plants were advanced to F3, F4 and F5 generations through selfing, following single seed descent method and were evaluated for fibre quality traits in F3 generation (2007–08), F4 generation (2008–09) and F5 generation (2009-10). Data were also recorded on seed cotton yield and important yield components.


Data on mean, range and standard deviation related to fibre quality traits, seed cotton yield and important yield components in F 2, F 3, F 4, and F5 generations are given in Table 3.

Fibre Quality Traits

The data indicated wide variation for several fibre quality traits in 4th generations, especially in F 2. The 2.5% span length ranged from 22.7 to 30.6 mm in F 2 ; 22.6 to 30.6 mm in F 3, 23.5 to 31.9 mm in F 4 and 21.0 to 31.8 mm in F5 .The mean 2.5% span length was 26.8 mm in F 2, 26.6 mm in F 3, 27.6 mm in F 4 and 26.4 mm in F5. The fibre strength ranged from 18.1 to 33.1 /tex in F2 ; 18.8 to 27.9 g/tex in F 3, 20.0 to 30.7 g/tex in F 4 and 18.0 to 27.9 g/tex in F5 generation. The mean fibre strength in F2 , F3, F4 and F5 generations was 26.6, 23.1, 25.1 and 23.7g/tex, respectively. The micronaire value varied from 3.6 to 4.9

Development of Recombinant Inbred Lines for Fibre Quality Traits in Gossypium hirsutum L 113

in F2 , 3.2 to 5.7 in F3, 2.8 to 5.4 in F4 and 2.7 to 5.2 in F5, with the respective mean of 4.2, 4.4, 3.9 and 4.1. The fibre uniformity ranged from 47.6 to 61.3% in F2, 46.6 to 58.5% in F3, 45.8 to 60.2% in F4 and 45.8 to 58.4% in F5. The mean fibre uniformity ratio was 55.8%, 52.4%, 53% and 52% in F2, F3, F4 and F5 generations, respectively. There was not much variation for fibre elongation and fibre maturity. The mean fibre elongation per cent was 6.3, 6.1, 6.1 5.2, respectively in the 4th generations, which ranged from 5.4 to 6.7% in F2 , 5.5 to 6.6% in F 3, 5.5 to 6.9% in F4 and 4.8 to 5.7% in F5 . All the plants in the 4 generations showed good fibre maturity ranging from 0.8 to 0.9. The short fibre content was found to be 3.5% to 8.8% in F 2, 3.5 to 11.2% in F 3, 3.5 to 8.6% in F4 and 3.5 to 9.5% in F5, with mean of 3.8%, 4.8%, 4.1% and 4.0%, respectively in the 4 generations.

TABLE 3: PERFORMANCE OF THE CROSS PUSA 56-4 AND RS 2013 FOR IMPORTANT FIBRE QUALITY TRAITS AND SEED COTTON YIELD IN F2, F3, F4 AND F5 GENERATIONS AT IARI, N. DELHI

Trait Generation Mean SD Minimum Maximum2.5% span length (mm) F2 26.8 1.5 22.7 30.6 F3 26.6 1.6 22.6 30.6 F4 27.6 1.7 23.5 31.9 F5 26.4 1.7 21.0 31.8Fibre strength (g/tex) F2 26.6 2.3 18.1 33.1 F3 23.1 1.6 18.8 27.9 F4 25.1 2.0 20.0 30.7 F5 23.7 1.8 18.0 27.9Micronaire value F2 4.2 0.3 3.6 4.9 F3 4.4 0.5 3.2 5.7 F4 3.9 0.5 2.8 5.4 F5 4.1 0.5 2.7 5.2Fibre uniformity (%) F2 55.8 2.3 47.6 61.3 F3 52.4 2.5 46.6 58.5 F4 53.0 2.6 45.8 60.2 F5 52.0 2.4 45.8 58.4Fibre elongation (%) F2 6.3 0.2 5.4 6.7 F3 6.1 0.2 5.5 6.6 F4 6.1 0.2 5.5 6.9 F5 5.2 0.2 4.8 5.7Fibre maturity F2 0.9 0.0 0.8 0.9 F3 0.8 0.0 0.8 0.9 F4 0.8 0.0 0.8 0.9 F5 0.8 0.0 0.8 0.9Short fibre index (%) F2 3.8 0.7 3.5 8.8 F3 4.8 1.6 3.5 11.2 F4 4.1 1.1 3.5 8.6 F5 4.0 1.0 3.5 9.5Yield / plant (g) F2 43.2 31.0 22.0 196.3 F3 75.9 33.1 25.2 193.1 F4 163.4 95.7 21.5 581.4 F5 147.7 69.8 27.4 342.8Boll weight (g) F2 3.5 0.7 2.0 5.1 F3 3.4 0.6 2.1 5.7 F4 3.9 0.7 2.1 5.8 F5 3.6 0.7 1.9 5.6Ginning outturn (%) F2 30.6 3.3 25.6 41.4 F3 31.7 2.4 25.6 39.3 F4 32.6 2.4 26.0 40.4 F5 33.4 2.7 26.5 44.7Seed index (g) F2 9.3 1.5 4.0 13.5 F3 8.1 1.0 5.6 11.6 F4 8.9 1.3 3.0 12.2 F5 8.2 1.2 5.4 12.8Lint index (g) F2 3.9 0.7 2.1 5.8 F3 3.8 0.5 2.5 6.0 F4 4.3 0.6 2.9 6.4 F5 4.0 1.0 3.5 9.5


Yield and Yield Components

Wide variation was also observed for seed cotton yield per plant in all the 4 generations, i.e. F2 through F5. It ranged from 22.0 to 196.3 g in F2, 25.2 to 193.1 g in F3, 21.5 to 581.4 g in F4 and 27.4 to 342.8g in F5 generation. The mean seed cotton yield was 43.2 g in F2, 75.9 g in F3, 163.4 g in F4 and 147.7g in F5. The boll weight was found to vary from 2.0 to 5.1 g in F2, 2.1 to 5.7 g in F3, 2.1 to 5.8 g in F4 and1.9 to 5.6g in F5 generation, the mean in the 4 generations being 3.5g, 3.4g, 3.9g and 3.6g, respectively. The ginning outturn also showed wide variability, ranging from 25.6 to 41.4% in F2, 25.6 to 39.3% in F3, 26.0 to 40.4% in F4 and 26.5 to 44.7% in F5. The mean ginning outturn in the 4 generations was 30.6% in F2, 31.7% in F3, 32.6% in F4 and 33.4% in F5. Good variation was also observed for seed index and lint index in all the 4 generations.

The distribution for fibre strength in F2 generation was little skewed as 76.5% plants out of 297 showed high fibre strength (above 25 g/ tex). Furthermore, 21 plants (7.0%) in F2 showed above 28 g/tex fibre strength which was higher than that of the better parent, suggesting transgressive segregation for the trait. The range observed for fibre strength in F 3, F 4 and F5 generations was relatively less as compared to F 2 generation. Transgressive segregation for fibre strength was observed as 2.7% plants showed higher fibre strength than the better parent. Transgressive segregation was also observed for 2.5% span length with 18.7% plants in F2 showing higher fibre length than 28.4 mm of better parent ‘Pusa 56-4’. Only 1.3% plants in F2 showed lower micronaire value (finer fibre) as compared to 3.9 micronaire value of better parent ‘Pusa 56-4’ and 6.3% plants showed higher short fibre index than better parent ‘Pusa 56-4’. The boll weight was found to be higher than 4.5 g of ‘Pusa 56-4’ in 21% plants. Transgressive segregation was also observed for low as well as high ginning percentage. The variation and transgressive segregation observed for fibre length and strength and other traits has practical implication for combining high yield and superior fibre quality in G. hirsutum cottons. Percy et al. (2006) also reported transgressive segregation for high and low lint percentage, with about 5% of lines exceeding high ginning outturn parent. Similarly, about 25% lines exceeded the height of the taller parent. They further reported that 20% lines possessed fibre strength equivalent to high fibre strength parent while 4% exceeded high strength parent. Fibre length and uniformity were reported to be normally distributed, while 14% lines showed transgressive segregation for lower micronaire value. They also opined shifted distribution among recombinant inbred lines towards smaller boll size. Reinisch et al., (1994) reported strongly distorted segregation of molecular markers in early generations while Jiang et al., (2000) reported skewed transmission in advanced generations of inter-specific hybrids. The transgressive segregation was also observed for several important traits in our study.

As many as 93 plants out of 297 evaluated in F 4 generation showed above 26.0 g/tex fibre strength during 2008–09. The fibre strength of these 93 plants ranged from 26.1 to 30.7 g/tex, 2.5% span length from 25.1 mm to 31.9 mm and micronaire value from 2.9 to 4.7. Although the overall seed cotton yield among these 93 plants varied from 32.3g to 459.2 g/plant, nonetheless 30 plants showed per plant yield of above 200 g/plant. Thus, the F4 plants derived from the cross ‘Pusa 56-4’ × ‘RS 2013’ showed valuable genetic variation for simultaneous improvement of yield and fibre quality in G. hirsutum cottons, suggesting the feasibility of combining high yield and superior fibre quality.

REFERENCES [1] Jiang, C., Wright, R. J., El-Zik, K. M. and Paterson, A. H. (2000). QTL analysis of leaf morphology in tetraploid

Gossypium. Theoretical and Applied Genetics. 100: 409–18. [2] Percy, R. G., Cantrell, R. G. and Zhang, Jinfa. (2006). Genetic variation for agronomic and fibre properties in an

introgressed recombinant inbred population of cotton. Crop Science. 46: 1311–7. [3] Reinisch, M. J., Dong, J., Brubaker, C. L., Stelly, D. M., Wendel, J. F. and Paterson, A. H. (1994). A diallel RFLP map of

cotton, Gossypium hirsutum × Gossypium barbadense: chromosome organization and evolution in disomic polyploidy genome. Genetics. 138: 829–47.

[4] Singh, J. and Kaushik. S. K. (2006). High fibre strength strains of American cotton suitable for rotor spinning. ICAR News. 12 (2): 15–6.

[5] Singh, J., Kaushik, S. K. and Chaudhary, Babita. (2007). Seed cotton yield and fibre quality analysis in American cotton. Journal of the Indian Society for Cotton Improvement. 32 (3): 188–92.

Elite Cotton Varieties in the Zimbawean Private Sector Research Programme

Mandiveyi Jeremiah Kudzayi

Seed Cotton Breeder, Quton Seed Company (Pvt) Ltd, Box 192, Kadoma, Zimbabwe

Abstract—In the 2009-2010 cropping season, seven elite cotton varieties from Quton’s (Quton Seed Company) Medium Staple Breeding Programme were planted across 10 sites to evaluate field and fiber characteristics. The yield data indicated that the entry 675-02-1 performed better than others with the average seed cotton yield of 2.33 t/ha under dryland conditions. Entry 675-02-1 has medium bolls with very good seed cotton retention and early maturity. Two hundred and sixty four lint samples from the first picking were collected and sent to the Cotton Company of Zimbawe (Cottco) Laboratory for fiber analysis in terms of fiber length, strength, elongation, maturity and micronaire (HVI). The latest maturing entry B81-05-1, had the longest fibers associated with strong fiber and a good micronaire. This variety also had the highest ginning outturn and the heaviest bolls in this season. Another elite line MS98-01-68, produced the second best fiber strength value of 31.8 g/tex. Strong fibers can be span at higher speeds and meets demands of modern spinning technologies. Earlier maturing varieties were generally better yielding mainly due to an end of season drought spell that affected late maturing varieties.

INTRODUCTION

Quton Seed Company (Pvt.) Ltd. (Quton), a subsidiary of Seed Co-Group is the only cotton planting seed company operating in Zimbabwe. It has a breeding unit within the Department of Research and Specialist Services based in Kadoma, Zimbabwe. This Department has a strong breeding programme that has yielded significant results by releasing cotton varieties such as QM 301, a high quality medium staple variety that meets all stakeholders requirements. The major aim of the cotton variety development programme of Quton is production of medium-staple (Gossypium hirsutum) varieties suitable for open-end spinning for Zimbabwe and the region.

Currently, one public and one private Research Institutes are involved in cotton research in Zimbabwe. The main focus on cotton breeding programs is to develop cotton varieties which produces high yields of seed cotton and lint of a suitable quality under the wide range of growing conditions in Zimbabwe (Cotton Outlook 2001 Special Edition). Research works are also carried out for fiber quality, disease and pest resistance, drought tolerance and early maturity. Development of medium-staple cotton varieties suitable for modern spinning methods is the main target of cotton research in the private sector represented by Quton Seed Company. Quton Seed Company’s breeding work is mainly divided into two separate programs that are sub-divided into three maturity groups (Late, Medium and Early Maturity). The general objectives of each program and current successes are outlined below.

The Medium Staple (MS) Program

This concentrates on breeding of improved cotton varieties in the medium staple range (2.5% Span Length between 28mm and 32mm) for the main cotton- growing areas of Zimbabwe and other regional countries. The objectives include wide adaptability, resistance for jassid, bacterial blight, verticillium wilt, and improvements in plant habit, earliness, ginning percentage, yield potential and fiber quality. The present Quton variety for this program is Albar Plus QM 301.

Commercially Released Private Sector Varieties

Quton’s produced the first non-government bred cotton variety called Albar Plus QM 301 in the history of cotton production in Zimbabwe in September 2006. This variety was selected as a single plant at Cotton Training Centre during the 2000-2001 season out of F3 generation of a population created by crossing a number of West African and local varieties.

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Albar Plus QM 301 is a late maturing and indeterminate cotton variety with a potential yield between 1500 and over 4000 kg/ha. It has some improvements in verticillium wilt and bacterial blight tolerance. However, its leaf pubescence has space and therefore is less tolerant to jassid attack. The fibre quality of Albar Plus QM 301 is significantly better particularly in terms of fiber length and strength. The lint colour is white with a reflectance value of 78,5. QM 301 has the following fiber parameters: 2.5% span length 28.5mm, fiber strength 31.2 g/tex, fiber elongation 7.7%, micronaire 4.4.

Albar Plus QM 301 was released as a new variety with improved fiber quality as an alternative to SZ 9314 in both the middleveld and lowveld.

The Long Staple (LS) Programme

The long staple programme on the other hand is a relatively small program whose main objective is the development of long staple (up to 34mm) cotton varieties. Current production of the long staple variety is insignificant since farmers shun the low yield potential of the variety under dryland conditions. The general aim of the programme is thus to produce high quality cultivars, which also meet the needs of producers in terms of reliable yield performance. Quton has a couple of elite lines under evaluation but none have been registered for commercial production yet.

Experimental Procedure

Cotton variety assessment trials were conducted in summer 2009-2010 cropping season at two on-station sites and 10 off-station sites in major cotton-growing areas of Zimbabwe. Seven most advanced varieties from the Quton breeding programme were evaluated against the current commercial variety, SZ 9314 (bred by Cotton Research Institute, a government owned breeding unit based in Kadoma). These cotton varieties were planted and evaluated for field characteristics (yield, ginning %, boll weight, earliness) and fiber characteristics (2.5% span length, strength, elongation, maturity and micronaire). Acid delinted seeds were planted to ensure good germination. Five seeds were planted per hill and thinned to one plant per station within the first three weeks of crop emergence.

All trials were in dryland areas and were sown between mid- November and mid-December. Trials were laid out in Randomised Complete Blocks with eight treatments replicated thrice at eight locations (Anfield, Bindura, Bluegrass, Dande, Kadoma, Muzarabani, Raffingora, and Shamva). Gross plot size ranged between 17.1 square metres and 22.8 square metres depending on site. Prior to sowing, compound L (5:18:10) at 250 kg/ha had been banded adjacent to sowing furrows. At all sites trials were sown at a standard spacing of 1.0 m x 0.30 m giving a plant population of 33 333 plants per hectare. Top dressings of ammonium nitrate (34.5%N) were done 8 weeks after crop emergence at the rate of 100 kg/ha. At all sites hand-hoeing and/ or mechanized cultivation were used to control weeds. At Kadoma and Bindura, herbicides Codal Gold 412.5 DC was applied pre-emergence, at the rate of 4.0 litres per hectare. Scouting and spraying, wherever possible, followed methods and recommendations laid down in the relevant sections of the Cotton Handbook. Where trials were conducted on farmer’s fields, scouting and spraying were left to the grower to use his own discretion, but chemicals were provided by Quton.

Harvesting was spread over a period from early March to late July across all sites. The number of picks taken varied from a minimum of two at some sites to a maximum of three. For all trials, boll samples were collected at the first pick stage and were used as the ginning sample. The boll samples were standardized by taking 100 fully open undamaged bolls per plot. The first two plants on either side of the plot were excluded. Ninety gram lint samples were taken from the ginning of each plot’s seed cotton. The lint samples were sent to The Cotton Company of Zimbabwe (Cottco) for fiber testing using HVI Spectrum from Ulster Technologies, USA. Most of the areas that hosted our trials received normal to above normal rainfall with a poor distribution thereby affecting mainly the late-planted trials. There was a prolonged mid-season drought spanning between January and March. The crops that were established early yielded quite well compared to late-planted trials.

Elite Cotton Varieties in the Zimbawean Private Sector Research Programme 117


Field Characteristics

Seed cotton yields from individual sites are presented in Table 1. The variety 675-02-1 was outstanding in overall performance across both high and low input cotton-growing areas with a 14% yield advantage over the main control variety SZ 9314 (Table 1). This variety will benefit farmers due to its superior earliness if introduced into commercial production. At one of the sites, 675-02-1 produced some tight locs. Although MS99-03-176 produced a very satisfactory average seed cotton yield of 2300 kg/ha, its productivity was poor under low input conditions (the predominant conditions in which Zimbabwean cotton is grown). The latest maturing entry, B81-05-1 with an earliness index of 54% (Table 2) produced the heaviest boll and the highest ginning percentage compared to all test varieties. Although the variety MS99-01-68 has smaller bolls than SZ 9314 and QM 301, it is superior to both in yield and earliness. MS98-01-176 produced better seed cotton and lint yield than QM 301 because of and late maturity than controls (Table 2).

TABLE 1: SEED COTTON YIELD (KG PER HA) OF MS VARIETY

Treatment Variety Raffingora Seedco Bluegrass Bluegrass Bluegrass Bindura 1 Bindura 2 Shamva Anfield Mean (High) (High) (Low) (Low) (Low) (High) (Low) (High) (High) 1 675-02-1 2659 3058 1378 1410 1728 3037 1799 3648 2290 2334 2 679-02-1 2813 2539 1420 1237 1310 2976 1685 3788 2316 2232 3 772-03-6 3097 2954 1359 1185 1517 3051 1297 3453 2569 2276 4 B81-05-1 2715 2399 1682 1542 1504 2440 1229 3267 2901 2187 5 MS98-01-68 2946 2817 1662 1308 1506 2819 1562 3343 2350 2257 6 MS99-03-176 2930 2996 1338 1304 1457 2911 1646 3665 2456 2300 MEANS 2860 2794 1473 1331 1504 2872 1536 3527 2480 2264 CHECKS(1) : 8 SZ 9314 2379 2335 1472 1250 1481 2685 1164 3489 2214 2052 CHECKS(2) : 7 QM 301 2482 2796 1568 1304 1378 2684 1460 3458 2136 2141 OVERALL: MEANS 2753 2737 1485 1318 1485 2825 1480 3514 2404 2222 STD ERR 241.1 158.9 11906 154.1 143.8 133.5 172.9 100.3 201.1 1468.0 5% LSD 731.2 482 362.8 467.5 436.2 405 524.3 304.4 609.9 480.4 C.V. 15.2 10.1 14 20.3 16.8 8.2 20.2 4.9 14.5 13.8

*Trials at 11 site having net plots size between 17.1 and 22.8 sq. m under RBD with three replications

TABLE 2: FIELD CHARACTERISTICS OF MS VARIETY ASSESSMENT TRIALS AT NINE SITES, 2009-2010 SEASON.

Variety Total Seed Ginning Lint Yield Boll Weight Seed Earliness Plant Population Cotton (kg/ha) % (kg/ha) (g) Weight % Height (cm) (000s) 675-02-1 2334 40.79 953 5.93 11.32 72 132 33.65 679-02-1 2231 39.37 900 5.92 10.93 68 130 33.17 772-03-6 2276 40.72 921 6.23 11.53 66 131 33.92 B81-05-1 2187 42.19 926 6.82 12.94 53 129 33.32 MS98-01-68 2257 41.94 942 5.96 11.33 71 135 33.28 MS98-03-176 2300 41.20 947 5.97 10.91 64 133 33.26 SITES 9 9 9 9 9 9 9 9 MEANS 2264 41.03 931 6.14 11.49 66 132 33.43 CHECKS(1): SZ 9314 2052 41.48 844 6.20 11.66 65 129 33.39 MEANS 2052 41.48 844 6.20 11.66 65 129 33.39 CHECKS(2): QM 301 2141 42.80 916 5.84 10.55 70 128 33.44 MEANS 2141 42.80 916 5.84 10.55 70 128 33.44 OVERALL: MEANS 2222 41.31 919 6.11 11.40 66 131 33.43

Fiber Characteristics

Fiber strength is now the most important fiber parameter in both rotor and friction spinning. The fiber strength data from 11 trials (Table 3) show that most entries produced stronger fibers than the controls.


The entry with the best fiber strength value (32.12 g/tex), B81-05-1 also had the highest fiber length value of 31.61 mm (2.5% span length). The fiber strength values of three best lines (675-02-1, B81-05-1 and MS98-01-68) are inherently superior (Table 3) across both high and low potential areas, while the variety 772-03-6 consistently gave poor strength values across all sites. Another entry, 675-02-1 with very good field characteristics had a fiber length value equal to QM 301 but its fiber strength was better than QM 301 by 2.5%. Although 679-02-1 inherently has the shortest fiber, it produced a good fiber strength value of 31.5 g/tex. B81-05-1 is high grade cotton with long and strong fiber (Table 4).

TABLE 3: FIBER STENGTH VALUES OF MS VARIETY

Variety Raffingora Seedco Seedco Bluegrass 1

Bluegrass 2

Bluegrass 3

Bindura 1

Bindura 2

Shamva Anfield Anfield Mean

High High Low Low Low low High low High High Low 675-02-1 31.80 33.43 29.77 30.47 30.57 32.10 32.87 34.10 31.13 29.30 31.23 31.52 679-02-1 31.40 32.23 32.03 29.07 32.43 31.20 32.57 33.47 30.73 31.30 30.07 31.50 772-03-6 31.07 31.77 30.03 29.10 29.07 31.67 30.67 33.43 29.43 29.47 30.50 30.56 B81-05-1 31.03 35.93 30.80 29.23 32.40 33.57 32.23 34.10 32.53 30.47 31.03 32.12 MS98-01-68 29.50 33.77 30.67 31.43 30.20 32.00 33.73 35.50 31.50 30.83 30.37 31.77 MS99-03-176 32.00 33.23 31.27 28.60 31.27 31.87 31.03 32.80 29.73 29.80 31.80 31.22 MEANS 31.13 33.39 30.76 29.65 30.99 32.07 32.18 33.90 30.84 30.20 30.83 31.45 CHECKS(1) : SZ 9314 30.80 33.60 28.70 30.23 29.30 30.77 31.77 33.50 28.13 31.20 30.20 30.75 CHECKS(2) : QM 301 31.23 31.67 30.53 29.50 30.53 30.50 31.63 34.40 28.53 28.90 30.67 30.74 OVERALL: MEANS 31.1 33.5 30.5 29.7 30.7 31.7 32.1 33.9 30.2 30.1 30.7 31.3 STD DEV 1.7 2.6 1.6 1.7 1.6 1.6 1.6 1.5 1.5 1.6 1 1.6 C.V. 5.6 7.8 5.3 5.6 5.3 5 5 4.3 5.1 5.2 3.4 5.2

*Assessment Trials across eleven site during 2009-10 season having 17.1 and 22.8 sq. m plot size under RBD with three replications.

TABLE 4: FIBER CHARACTERISTICS OF MS VARIETY

Variety Length (mm) Strength Elongation Uniformity Micronaire Maturity 675-02-1 29.96 31.52 5.86 84.80 4.13 0.88 679-02-1 29.64 31.50 6.04 84.34 4.18 0.88 772-03-6 30.21 30.56 5.96 84.56 4.09 0.87 B81-05-1 31.61 32.12 5.78 85.27 4.03 0.88 MS98-01-68 30.61 31.77 5.91 85.01 4.08 0.88 MS98-03-176 31.01 31.22 5.89 84.91 4.03 0.87 MEANS 30.51 31.45 5.91 85 4.09 0.88 CHECKS(1): SZ 9314 29.66 30.75 6.18 84.41 4.23 0.88 CHECKS(2): QM 301 30.00 30.74 6.26 84.86 4.04 0.87 OVERALL: MEANS 30.34 31.27 5.99 85 4.10 0.88

*Assessment Trials across eleven sites during 2009-2010 season

Fiber elongation values were average for the most promising entries and were less than 7%. The micronaire, uniformity and maturity values were within acceptable ranges. The three varieties (B81-05-1, MS98-01-68 and MS99-03-176) combined major gains in both fiber length and fiber strength parameters.

Pests

Major pests observed across the ten sites were termites, jassids (leaf hoppers), aphids, bollworms (red, Heliothis), cotton strainers, and leaf eaters (mainly elegant grasshoppers and semi loppers). Pest menace was high and an average of 10,6 sprays were applied during the season with an average of 7,1 against bollworms, 4.0 against aphids, 1.8 against red spider mite and 1.0 against jassids. At some trial sites, insect damage caused serious plant population losses.

Elite Cotton Varieties in the Zimbawean Private Sector Research Programme 119

All the varieties were assessed for jassid resistance using a method to build up high jassid numbers in an unsprayed block. Reasonable levels of jassid resistance are essential for varieties grown in the smallholder sector. Jassid build up was poor and was also compounded by the mid-season drought. No meaningful data was obtained this season and thus no scores are presented in the field data.

CONCLUSION

Zimbabwe mainly grows cotton for lint exports to overseas markets. The competitiveness of its lint that is traded based on quality parameters. The MS breeding program has made huge gains in the improvement of fiber quality parameters especially fiber length and strength particularly against the main commercial and government owned variety, (SZ 9314). The field data of Quton’s elite lines also shows that the MS breeding program has diverse varieties in different maturity groups surpassing the yield potential of SZ 9314.

REFERENCES [1] Cotton Outlook, 2001 Special Edition, International Cotton Advisory Committee, 60th Plenary Meeting, Victoria Falls,

Zimbabwe. [2] Cotton Handbook of Zimbabwe. [3] Cotton Research Institute Annual Report, 1983-1984, Department of Research and Specialist services, Government Printer,

Harare, 1985. [4] The ICAC Recorder, International Cotton Advisory Committee, Technical Information Section, Volume. XX No.

1 March 2002

Development of Biotic Stress Resistance Transgenic Diploid Cotton Utilizing Agrobacterium

and Shoot Apical Meristem Cells

Sukhadeo Nandeshwar, Pranjib Chakraborty, Kanchan Singh, Mithila Meshram, Bipinchandra Kalbande

Division of Crop Improvement, Central Institute for Cotton Research, Nagpur-MS. India

INTRODUCTION

Cotton is a global crop with world hectarage of 32.4 m and production of 87.4m bales. It is one of the major source of fibre, cattle feed and edible oils. The productivity of cotton is adversely affected by biotic and abiotic stresses. Major concern world over has been to protect it from bollworm (Helicoverpa armigera) a single pest capable of causing damage to the extent of 40% besides infestation of fungal pathogens.

In past two decades, extensive research efforts have been made for transformation, regeneration and genetic enhancement of cotton, especially G. hirsutum. Gene conferring agronomic advantages has been introduced through Agrobacterium and particle gun and the plants were regenerated through callus based somatic embryogenesis (Firoozabady et. al., 1987; Umbeck et al., 1987; Perlak et al., 1990; Finer and Mc Mullen 1990; Bayley et. al., 1992; Thomas et al., 1995; Rajshekharan et al., 1996; Zhao et al. 2006). All these workers however mostly employed Coker (G. hirsutum) sister lines and their derivatives for transformation. Shoot tip meristem and apex culture offers unique advantage to regenerate plants directly from inoculated shoots on simple MS medium. The procedure has been used to regenerate and transform many cultivars of cotton (Gould et al., 1991a; Gould and Megallanes-Cedeno 1998; Zapata et al., 2002, Kategari et al., 2007 and Nandeshwar et al., 2009) has reported successful transformation in diploid cotton G. arboreum by transferring cry IAc gene. This protocol has also been used in crop plant like maize (Gould et al., 1991) and pine (Gould et al., 2002). It has also been observed that the incidence of genetic mutation and somaclonal variation were low in plant regeneration from shoot tip explants (Gould and Megallanes-Cedeno 1998). Recently new transformation methods have been reported which minimizes the steps of in vitro regeneration and transformation which also increases transformation frequency.

Diploid cotton is widely cultivated in at least six states in India covering approximately 7% of the cotton-growing area. The importance of diploid cotton especially G. arboreum is increasing owing to the development of long staple and high yielding varieties combined with its inherent tolerance to number of diseases such as leaf curl, new wilt etc. and drought. However plants are often badly damaged by bollworm and grey mildew. In this study we describe two efficient and simple protocols of transformation and development of transgenic diploid cotton by using cry IAc and chitinase genes respectively.


Plant Material

Seeds of G. arboreum cv RG 8 and PA255- popular commercial varieties were selected for transformation. Seeds were delinted with concentrated sulphuric acid followed by treatment with lime water and several rinses with running tap water. They were sun-dried and stored for further use. Seed sterilization was carried out with doubled distilled water added with few drops of teepol. Seeds were rinsed several times in this solution and washed 3-4 times with doubled distilled water. Seeds were then

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Development of Biotic Stress Resistance Transgenic Diploid Cotton Utilizing Agrobacterium 121

transferred in the solution of bavistin (1 % w/v) and agitated on orbital shaker at 90 rpm for 20 min, followed by 3-4 washes with autoclaved distilled water. Seeds were treated with 0.1% solution of mercuric chloride for 7 min followed by continuous washes with autoclaved doubled distilled water till the traces of mercuric chloride are completely removed and were collected in petri plates and inoculated in conical flask containing half strength MS medium from germination.

Bacterial Culture

An Agrobacterium tumefaciens strain EHA 105 carrying the binary vector pBinBt3 was used. The vector was obtained from the National Research centre on Plant Biotechnology, New Delhi, India. The plasmid harboured the cry IAc gene and the nptII gene each driven by CaMv 35s promoter. With regard to chitinase gene, binary plasmid pBin-AR was used as a vector for transformation. The plasmid harboured the chitinase gene isolated from cotton G.hirsutum and nptII (Chakraborty personal communication).The bacterial culture was maintained on YEM medium containing 50mg/L Kanamycin. For inoculation of explants, a single colony of bacterial cells was grown overnight in liquid YEM broth at 28 0 c.

Transformation and Co-cultivation

Seven days old geminated seedling (fig.1.a) were used for isolation of shoot tip explants. Both the cotyledonary leaves were gently removed from the seedling with the help of sterile forceps and an oblique excision was made at the base of the shoot tips just below the cotyledonary leaf as described by Nandeshwar et al., (2002). All extraneous tissue surrounding the meristem dome was removed for efficient Agrobacterium infection.

Shoot tip explants were inoculated with an overnight grown culture of Agrobacterium for 60 minutes (fig.1.b). The infected explants were collected in petri-plate overlaid with sterile filter paper and co-cultivated for 4 days separately on simple MS medium. Following co- cultivation, explants were transferred to the same medium for 2 weeks containing 500mg/L carbenicillin. Subsequently, explants were subjected to screening on kanamycin medium (50mg/L). To promote shoot elongation, shoots (or explants with developing shoots) were transferred to MS medium supplemented with 50mg/l kanamycin, 0.1mg/L kinetin, and 0.1 mg/l gibberellic acid (fig.1.c) or 2mg/L BA and 1 mg/L kinetin and 50 mg/L kanamycin for regeneration of shoot directly or multiple shoot formation (fig.1.d). Shoot (desired from direct shoot regeneration or multiple shoot induction) were separated and transferred in MS medium containing 15g/L glucose and NAA (0.1 mg/L). Rooted plants were established (fig.1.e) in glass house for further analysis. The To plants were first tested for gene amplification by PCR and positive plants were selfed to collect T1 seeds for raising T1 plant progenies.

For in-planta transformation method, surface sterilized seeds were sown directly in earthen pot containing sand:soil mixture. Seven days healthy seedlings were selected and they were vertically bisected along the line of cotyledonary leaf attachment. Twenty four hours grown 200 µL of Agrobacterium culture pre-mixed with modified 100 µL vir induction medium diluted with MS broth was applied at the bisected exposed portion of the apical meristem. The plants were covered with polythene bags for 10 days. The matured To plants (fig.3) were tested for the presence of gene by PCR. The PCR positive plants were selfed and T1 progenies on boll basis was harvested.

Molecular Analysis of Gene Integration

Extraction of genomic DNA was extracted following protocol developed in our lab (Chakra borty et al., 2007). Young leaves of putative transgenic cotton plants were frozen in liquid nitrogen and ground in a pre-cooled mortar. Ground tissue (0.5g) was extracted in 15 ml extraction buffer (100mM Tris HCl pH 8, 20 mM EDTA, 1.4 M NaCl, 2% CTAB and 0.5M glucose) in a 50 ml centrifuge tube storing remaining powder at -70 ̊ C for later use. The mixture was homogenised and incubated at 60 ̊C for 30 min with occasional shaking. The DNA was extracted once each in equal volume of phenol: chloroform: isoamylalcohol, (25:24:1) and chloroform:isoamyl alcohol (24:1) each time producing an emulsion by


gently inverting the tube few times and transferring the upper aqueous layer to a fresh tube following centrifugation at 6000g for 8 min. at 4 ̊ C. The DNA was precipitated with 0.1 volume of 3M sodium acetate (pH 5.2) and 1 volume of isopropanol at room temperature. Following precipitation, the DNA was spooled gently with the help of bent Pasteur pipette after allowing the tube to stand at – 20 ̊C for 30 min. Following spooling of DNA, the remaining solution was centrifuged at 14000 rpm for 5 min. The spooled and the pelleted DNA was rinsed with 70% alcohol, dried briefly and dissolved in 200µl of sterile distilled water. Purity of DNA was checked by obtaining absorbance ratios at A260/280 and A260.230. Concentration of DNA in the sample was calculated by the value of absorbance at A260.

Detection of Cry IAc and Chitinase Gene by PCR

Presence of the transgene was ascertained by polymerase chain reaction (PCR) amplification of 1 kb fragment of cry IAc gene using a set of primers cry IAc F (5’ CCCAGAAGTTGAACTTGGTGG 3’) and cryIAc R (5’ CCGATATTGAAGGGTCTTCTGTAC). The PCR was performed in 50 µl reaction volumes. Each reaction consisted of 2µl of 100ng/µl template, 5µl of 10xPCR buffer, 0.5µl of 25mM dNTPs, 1.5 µl of 15mM MgCl2, 1µl each of 10µM reverse and forward primer, 0.25µl of 5U/µl Taq DNA polymerase (MBI Fermentas, USA), and 38.7 µl sterile distilled water. The PCR protocol was standardized with the initial denaturation at 94 ̊ C for 4 ̊ C followed by 39 cycles consisting of denaturation at 94 ̊C for 45 sec. primer, annealing at 60̊ C for 30 sec, and primer extension at 72 ̊C for 1 min and a final extension at 72 ̊C for 5 min. Negative controls were maintained for non-specific amplification, if any.

Presence of Chitinase gene was confirmed using the same method as followed for CryIAc gene by using gene specific primers Chitinase F (5’ GGGGTACCATGAGCTTTCTTCAGGCCTT3’) and Chitinase R (5’ GGGGTACCGCACGTTTACTGATTTCATTT 3’).The PCR protocol was modified for Chitinase with initial denaturation at 95 ̊ C for 5 minutes followed by 10 cycles of denaturation at 95 ̊C for 45 sec. primer annealing at 55 ̊ C for 30 sec and primer extension at 72 ̊C for 60 sec. Next twenty cycles consisting of denaturation at 95 ̊C for 60 sec annealing at 58 ̊ C for 30 sec and primer extension at 72 ̊C for 60 sec. Final extension was done at 72 ̊C for 5 min.

Detection OF Transgene BY Southern Hybridization

Genomic DNA was extracted from transgenic cotton plant by the above-described method. The total DNA (10 μg) was subjected to digestion with EcoRI restriction enzyme. Following electrophoresis, the DNA was stained with ethidium bromide and examined under UV light. The digested DNA fragments were transferred on positively charged nylon membrane (Biodyne B, Pall Gelman, USA) by alkaline transfer using 0.4N NaOH, as transfer solution (Sambrook et al., 1989). The cry1Ac gene fragment (1 kb) present in plasmid pGemT-cryAc-1 (PCR amplified cry1Acgene fragment cloned in 3.0 kb plasmid pGEM-T marketed by Promega, USA) was used as DNA probe for Southern hybridization. The fragment was excised from pGemTcryAc-1 and pGEM-T chitinase (4.0 kb) with PstI and SacII and purified using gel extraction kit (Qiagen, Germany) as per manufacturer’s protocol. Probe was labelled with digoxigenin DNA labelling and detection kit (Roche, Germany) following manufacturer’s protocol. Southern blot containing the genomic DNA was hybridized to DIG labelled cry1Ac probe and Chitinase probe at 68°C for 24 h in hybridization oven. The hybridized probes were immuno-detected on the nylon membrane in a visual reaction catalyzed by anti-DIG-AP conjugate in the presence of chromogenic substrate NBT/BCIP, following manufacturers protocol.

Expression of Cry I Ac Gene

Two discs were excised from terminal leaf of the putative transformants and crushed in 0.5 mL extraction buffer in a 1.5-mL eppendorf tube with the help of micro-pestle. Qualitative expression of CryIAc protein in Bt-transgenic plants was ascertained by appearance of a purple band on Bt-express immune detection strips, while quantification of insecticidal protein in the sample was done using Bt Quant ELISA kit (Kranthi et al., 2005). In general, the plants found positive for expression of Bt protein in qualitative


assay were further analyzed for quantitative expression by enzyme-linked imunosorbent assay (ELISA). Both assay kits were developed in this institute, while it is commercialized and marketed in India by Innovative Biosciences Pvt., Nagpur, India.

RESULTS

Out of 3772 explants co-cultivated with Agrobacterium containing Cry 1Ac gene12 plants were established. The transformation frequency was 3.6%. It was observed that during first and second cycles of passage, large number of explants survived on kanamycin selection medium but during subsequent passages, drastic reduction in the survival of explants was observed (data not shown). The shoots emerging from the surviving explants though robust, nevertheless, slow growing during initial stages. These were transferred immediately to fresh MS medium supplemented with 0.1 mg/L kinetin and 500 mg/L carbenicillin. The shoot apices after third cycle of selection were transferred to regeneration medium. The regeneration was carried out by direct shoot organogenesis and induction of multiple shoots. In a later case, the meristematic cells (in the axils of cotyledonary node) proliferated within 20 days. The proliferation was accompanied by lateral expansion of the explants accompanied by degeneration of primary shoot. Within 4–6 weeks, a huge mass containing large number of shoot buds differentiated (Fig. 1). The average number of shoots produced per explants was 10–12 shoots. The shoot growth in both the processes of regeneration was slow. The kanamycin-resistant shoots were excised and transferred on rooting medium after 3 months. In all, 64 independent, putatively transformed shoots were selected out of 3772 explants used in co-cultivation. Finally only six putatively transformed shoots were survived at T0 generation. The rooted plants were liquid-hardened and established in the clay pots containing sand and soil mixture (1:1) in glass house.

With regard to in-planta transformation, 78 seedling were raised in earthen pots and their shoot tips were bisected vertically and applied with Agrobacterium suspension premixed with vir induction medium. Of the 78 seedlings, 50 seedlings survived and reached to maturity and 17 plants were PCR positive. At flowering, all the PCR positive plants were selfed and seeds were collected to rise T1 generation.

Molecular Characterization of Transformed Plants

Successful transformation was ascertained through PCR amplification of 1 kb DNA fragment of cry1Ac gene in transgenic plant (fig.2.a). The fragment was not amplified with the gene-specific primer in negative control. Southern hybridization of genomic DNA of transgenic plant was done by using a 1 kb DNA fragment of cry1Ac gene as probe. The probe hybridized with genomic DNA fragments of 2.4 and 2.0 kb in Bt-RG8-16, while it hybridized with a single genomic DNA fragment in case of Bt-RG8-16 (fig.2.b), showing them to be the product of two independent transformation events.

In case of Chitinase, out of 50 plants which were survived after transformation 17 were found to be PCR positive. In all the PCR positive plants there was amplification of 1.3 kb gene fragment (fig.4.a). Sothern hybridization of genomic DNA of transgenic plants was confirmed by using 1.3 kb DNA fragment of Chitinase as probe (fig.4.b).

Gene Expression Analysis

The progenies of PCR positive self pollinated T0 plants were evaluated for expression of insecticidal Cry IAc protein. The concentration of Bt protein evaluated by Bt ELISA in putatively transgenic plant ranged from 0.24 to 4.36 µg/g fresh weight. The quantitative expression of Bt protein was evaluated for 117 out of a population of 238 plants at 60 and 120 days of the plant growth. Only 35 plants expressed Bt protein of 3µg/g fresh weight and above, while 47 plants exhibited expression between 1 and 3 µg/g fresh weight.

Transgenic plants containing Chitinase gene, gene expression analysis was carried out in T1 progenies by fungal spore inoculation method followed by Chitinase activity assay


DISCUSSION

Efficient transformation system is essential for genetic manipulation and improvement of cotton through genetic engineering. The cotton is highly recalcitrant to regeneration by somatic embryogenesis due to number of impediment including genotype specificity (Trolinder and Goodin1987). However, cotton belonging to Coker series of G. hirsutum in general has been found amenable to regeneration by somatic embryogenesis (Firoozabady et al., 1987; Umbeck et al., 1987; Perlak et al., 1990). Besides Coker, genotype Acala of G. hirsutum has also been used successfully for genetic transformation (Rajasekaran et al., 2001). Successful transfer of regenerative trait from such transformed genotypes to recalcitrant elite cultivar by back-crossing often leads to introgression of undesirable characters (Kumar et al., 1998). Therefore in the absence of regeneration by somatic embryogenesis, transformation using shoot apices has been the best choice for gene transfer. Gould and Magallanes-Cedeno(1998) and Zapata et al., (1999) have developed a method to directly transform elite genotypes of cotton by shoot-tip culture. The meristem-based method has been successfully used in Agrobacterium-mediated transformation of petunia (Ullian et al., 1988), pea (Hussey et al., 1989), corn (Gould et al., 1991b), banana (May et al. ,1995), and rice (Park et al., 1996). Trolinder et al., (2006) used chilled apical shoot tips to develop transgenic plants.

A new method was also developed using a tissue culture independent in-planta protocol which was standardized to develop transform plants. Such protocols have also been used earlier in crops like buckwheat (Kojima et al., 2000), mulberry (Ping et al., 2005), kenaf (Kojima et al., 2004), soybean (Chee et al., 1989) and rice (Supertana et al., 2005). In all these methods, Agro bacterium is targeted to the wounded apical meristem of the differentiated seed embryo.

In shoot tip-based method seven-day-old in-vitro germinated seedlings were used as source of explants. The explants are processed so as that maximum number of meristematic cells get exposed to Agrobacterium, harboring cry1Ac gene during co-cultivation. Healthy seedlings, removal of excess tissue, and incorporation of acetosyringone in the medium during agro-infection, besides temperature, were the key factors for successful transformation. Acetosyringone pre-induction of Agrobacterium and/or inclusion of acetosyringone in the co-cultivation medium can enhance transformation (Veluthambi et al., 1989; Sunilkumar et al., 1999). Satyavathi et al., (2002) reported high transformation efficiency above 60% in three Indian varieties, using embryo axis as explants, while Kategari et al., (2007) obtained transformation frequency of only 0.2% in Bikaneri Narma, using embryo axis.

Selection of explants on kanamycin medium is an important initial step in the development of transgenic plants in meristem-based method of gene transfer. Maintenance and restoration of meristematic activity of shoot apical meristem is also essential for successful transformation. This can be accomplished by adding low level of kinetin in the medium. Incorporation of tolerable levels of kanamycin during initial stages of selection allowed proliferation of greater number of shoots. After considerable elongation of shoots, level of kanamycin was enhanced to 50 mg/L during subsequent passages for proper selection of putative transform ants. Rooting was induced in kanamycin-free MS medium as the antibiotic impeded the development of normal roots. The transgenic plants regenerated through the procedure described by us were phenotypically normal. The plants were obtained within 6 months, compared to those regenerated by embryogenesis based transformation system, which takes 1 year or more to obtain fertile plants.

In-planta transformation method offered a simple and unique procedure for gene transfer. In that meristem cells were exposed through vertical bisection. These cells were targeted to Agrobacterium containing Chitinase gene. The shoot formed from such cells may either be chimeric or completely transgenic depending on the type of the cells which have been transformed. The transgenic nature of the plants was confirmed in T0 and T1 plant progenies. It has been observed that compared to somatic embryogenesis and shoot tip-based organogenic method which usually takes longer longer time to obtain promising transformants. The present in-planta transformation and shoot tip-based organogenic protocol are simple, less time consuming and potentially useful approach for crops which are recalcitrant to regeneration. Transformation of the vertical bisected seedling obviates essential tissue culture

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Cloning and Characterization of Cellulose Synthase Genes from Arabidopsis thaliana

Balasubramani G., Amudha J., Sahare S. and Kranthi K.R.

Central Institute for Cotton Research, P.B. No. 2. Shankar Nagar P.O. Nagpur, India E-mail: [email protected]

SUMMARY

Cellulose allied genes viz., Rsw1 and AthA from Arabidopsis, which brings about rapid conversion of carbon to UDP glucose to facilitate the synthesis of cellulose and / or callose as energy-efficient process. The full length sequence of AthA and Rsw-1 genes were amplified from A. thaliana. The amplified product was characterized as 5.3kb and 6.kb for AthA and Rsw-1 respectively. The amplicons were cloned into pJET 1.2/blunt vector and transformed into E. coli (DH5 Alpha). The clones were confirmed by restriction analysis and PCR. The positive clones were subjected to nucleotide sequence analysis. Since the sequence was colossal we used primer walking method to obtain full length sequence information and then aligned with help of bioinformatics tool BLAST-Align. The results yielded the full length sequence of AthA and rsw-1 and BLAST analysis showed that homology the AthA gene has 99% with CesA2 (AthA) gene and the sequence was submitted to GenBank (Acc. No. FJ687279). In addition to these any successful fiber specific expression and localization demands delineation of promoters that would facilitate expression of gene in secondary wall synthesis (16-40DPA) phase. Thus, fiber specific promoter was isolated from cotton. Inverse primers were designed to amplify upstream regulatory region in G. hirsutum cultivar, which yielded ~1.8kb amplicons. The amplicon was cloned and sequenced by primer walking and homology results showed the similarity with CesA4 promoter region. The nucleotide sequence was annotated and submitted to GenBank (Accession No. HM142347). This loom for enhancing high fibre strength coupled with other desirable traits genotypes through transgenic approach to meet the requirement of modern textile industry.

INTRODUCTION

Cotton fibers provide humankind’s most important renewable textile fiber. Approximately 100 million families rely on cotton production as a major source of their income and 150 countries either import or export cotton lint (Chen et al. 2007). The rapid increase of the world’s population and the severe decrease in arable land raise serious concerns about our continued ability to meet global demands for cotton. It is even more challenging to improve both yield and fiber quality simultaneously. The yield of cotton fibers known as cotton lint, is usually negatively associated with fiber quality (Meredith, 1984). With the modernization of textile industry and high speed spinning technology strong and long fiber is in high demand. Mills using open-end rotor and friction spinning have given improved fiber strength as highest priority. Plant cell shape is a key determinant in plant morphogenesis and is in turn strongly influenced by the organization of the cell wall. Within the cell wall, cellulose microfibrils constitute the major load bearing structures, and their oriented deposition confers differential extensibility to the wall (Carpita and Gibeaut, 1993; McCann and Roberts, 1994). Presumably under the influence of the microtubular cytoskeleton, microfibrils in the primary wall of growing cells are deposited perpendicularly to the prospective elongation axis (Wyatt and Carpita, 1993; Wymer and Lloyd, 1996). Biologically, cotton fiber is an excellent model system for the study of plant cell elongation and cell wall and cellulose biosynthesis (Kim and Triplett, 2001). The >90% cellulose content in the secondary wall and the >2.25 cm fiber length of domesticated cotton fiber are key characters that have made this unusual seed epidermal hair especially useful to humans for over 7 000 years (Ryser 1985; Dillehay et al. 2007).

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The fiber is composed of nearly pure cellulose, which is also the largest component of plant biomass. They differentiate over a period of 45–60 days, beginning with expansion of individual cells above the plane of the ovule outer integument near the day of flower opening. Cellulose, a paracrystalline form of H-bonded - (1, 4)-Glc chains (McCann and Roberts, 1991; Carpita and Gibeaut, 1993), is thought to be synthesized by membrane-bound complexes. Cellulose synthase genes have been eventually discovered genetically in bacteria, and divergent homologs in plants have been identified (Saxena and Brown, 2000). Cellulose biosynthesis in plants has gained ground during recent past. The isolation of plant cDNA clones encoding cotton homologs of the bacterial cellulose synthase catalytic subunit is a significant achievement, which promises the elucidation of cellulose biosynthesis. Two cDNA clones of the bacterial celA genes that encode the catalytic subunit of cellulose synthase are GhCesA-1 and GhCesA2 that are highly expressed at the onset of secondary wall when the rate of cellulose synthesis in vivo raises over 1000 fold. GhCesA-1 and GhCesA-2 genes have been believed to possess four conserved sub domains critical for catalysis and / or binding of substrate UDP glucose new insights into biochemistry of cellulose biosynthesis and identifying of different subunits of GhCesA-1 and GhCesA-2 complex are likely to stem from Arabidopsis cellulose biosynthetic mutants such as radial swelling1 (rsw1) and their homologues of cotton.

Recent investigation by Betancur et al (2010) reported that 10 member cellulose synthase (CesA) gene family in Arabidopsis provides a useful reference point for comparing cell wall biosynthetic processes between cotton fibers and Arabidopsis shoot trichomes (Somerville 2006). Although their precise role in the biochemical pathway of cellulose synthesis is still undefined, the cellulose synthases are UDP-glucose: 1, 4-ß-D-glucosyltransferase enzymes in the glycosyltransferase family-2. In Arabidopsis, members of a triplet of CesA isoforms (AtCesA1, 3, 6, or a 6-like protein) have non-redundant roles in primary wall cellulose synthesis (Persson et al. 2007; Desprez et al. 2007), whereas members of another triplet (AtCesA4, 7, 8) have non-redundant roles in secondary wall cellulose synthesis in xylem cells (Taylor et al. 2003) For convenience, the six clades that Arabidopsis CesAs form with their orthologs from other seed plants have been designated P1 (Primary1), P2, and P3 (defined by AtCesA1, 3, and 6, respectively) and S1 (Secondary1), S2, and S3 (defined by AtCesA 4, 7, and 8, respectively) (Haigler and Roberts 2009). The remainder of the ten Arabidopsis CesA genes appear to be relatively recently derived within P1 (AtCesA10) and P3 (AtCesA2, 5, and 9) in the crucifer lineage. The Arabidopsis members of P3 are functionally interchangeable (Persson et al. 2007; Desprez et al. 2007) and AtCesA10 has limited expression (Doblin et al. 2002). Based on available evidence, the division of function between these traditionally defined primary- and secondary wall CesAs is broadly conserved in other angiosperms even if the number of CesA genes has increased (Tanaka et al. 2003; Djerbi et al. 2005; Kumar et al. 2009). Other genes/proteins may be required for both primary and secondary wall cellulose biosynthesis, e.g. an endo-glucanase–Korrigan, or alternatively may parallel the CesA family in having isoforms specialized for primary or secondary wall biosynthesis (Somerville 2006). In the present investigation full length sequence of AthA and Rsw-1 genes were amplified, characterized and cloned from A. thaliana. We also successfully cloned and characterized fiber specific promoter belonging to CesA4 gene family of cotton.


Plant Material

Arabidopsis thaliana (Thale cress), Columbia plants were established initially in pots containing an autoclaved 1:1:2 mix of peat: soil: sand, (v/v) and later raised at in vitro condition using Murashige and Skoog (1962) medium containing 0.75% (w/v) agar. Plants were cultured in a photoperiod of 16 hr light and 8 hr dark cycle. After 12 days of growth seedlings were taken aseptically for DNA isolation.

Cloning and Characterization of Cellulose Synthase Genes from Arabidopsis thaliana 131

Genomic DNA Isolation

Total genomic DNA was isolated by Dellapotta et al. (1983) method using fresh healthy young leaves of A. thaliana. The DNA was purified with Plant DNA purification kit (Sigma). The genomic DNA was checked quantitatively and qualitatively by Qubit Fluorometer and agarose gel electrophoresis respectively.

Primer and PCR Amplification

Amplification of the target genes was carried out using forward and reverses primer designed with software FastPCR. The forward sequence 5’- ATTGTCGATTCGGTTTATTTCGT-3 and reverse sequence 5’- ACAAAGAAGGTGTAAAACAACAC -3’ was synthesized by MWG, Bangalore. The purified genomic DNA was used for target gene amplification. PCR was performed in 20 μl reaction mixture containing 1.0 μl of 100 ng DNA, 4.0 μl 5 × fusion buffers (HF), 1.0 μl of 10 mM dNTPs, 1.0 μl of 100 nM of each forward and reverse primer, and 0.2 μl of 1U Pfu DNA polymerase for larger DNA fragment (>10kb). PCR program was standardized using TProfessional Gradient Thermal cycler (BIOMETRA®). The following PCR conditions of 98°C for 30 seconds, followed by 35 cycles of 98°C for 10 seconds, 57.8°C for 30 seconds, 72°C for 2 min and 10 min of final extension at 72°C were used. The amplified products were electrophoresed on 1.5% w/v agarose gel and documented.

Cloning of Amplicons

The amplicons were cloned into pJET 1.2/blunt vector and transformed to host bacteria (DH5α). The transformed bacteria were screened in the selection media containing IPTG (isopropyl beta-D-thiogalactopyranoside) with x-gal (5-bromo-4-chloro-3-indolyl-beta-D-galactopyranoside) as per the supplier protocol. The positive bacterial colony was selected for sequence analysis. The white colony was demonstrated as recombinant bacteria.

Amplification of Promoter

A detailed understanding of the key steps in the fiber development process provides opportunities to improve fiber quality either by molecular breeding or by genetic engineering technology. The second technology uses extremely important tools such as cloning the targeted nucleotide sequences, making desirable gene cassette and transfer to the targeted cells etc. For expressing a new character (gene) in cotton fibers there is great need of a module (promoter) in expression cassette (transgene construct) which will specifically express the character in cotton fiber cells. Therefore simultaneously, the upstream region of fiber gene was isolated and the sequence information confirmed that the fiber specific region belonging to CesA4 gene family.

Genomic DNA Isolation

DNA isolation was carried out using 20DPA boll of G. hirsutum cultivars LRA -5166, following Paterson et al (1993) method and purified as mentioned above.

Primer and PCR Amplification

The cellulose synthase gene was used to design primer sequence to amplify upstream region i.e. regulatory sequence by inverse primers. The primers were designed using FastPCR s/w. The forward sequence 5’-GCTATGTGGTAGGGACAATCTGGTC-3’ and reverse sequence 5’-CTCAATACCTTTGTGTCTTGTTGTG-3’ was synthesized by MWG, Bangalore. The genomic DNA was restricted with stringent reaction of Hind-III restriction digestion and allowed for circularization of DNA using ligase reaction. The ligated reaction was used for amplification of upstream region. Gradient PCR (Biometra) was performed with reaction mixture components (dNTPs, MgCl, Taq polymerase, forward and reverse 2 primers, ddH2O) and genomic DNA. The amplified product was characterized and


the expected size amplicon was eluted and reamplified with primers. Then the amplicon was eluted from the gel using Roche® agarose gel extraction kit and further subjected to cloning and transformation using kit. The transformed single colony was sub-cultured and pure recombinant bacteria were subjected to sequence analysis. After sequencing the nucleotide were BLAST searched for sequence homology and annotated sequence was submitted to GenBank.


Cotton fibers are a type of trichome and researchers have frequently looked for analogies with vegetative trichomes, especially those in the model plant Arabidopsis. An alternative model cell type for investigating the function of genes expressed in cotton fiber would be particularly useful given the substantial time and resources required for stable cotton transformation. The term trichome denotes a filamentous outgrowth such as a plant epidermal hair. ‘Trichome’ now refers to outgrowths of the plant epidermis exclusive of cells of sub-epidermal origin; mainly leaf and stem (shoot) trichomes, cotton seed hairs (fiber), and root hairs. These morphologically diverse cells and multicellular structures have been shaped by natural selection for a wide range of functions, including water absorption, thermoregulation, UV protection, both repellent and attractant components of defence, and seed dispersal (Evert 2006). The seed epidermal trichomes that presently dominate world cotton commerce were derived through domestication of wild cotton species with ancestral fibers that probably evolved to aid seed dispersal and/or germination (Wendel et al. 2009).

In the present investigation, the cellulose synthase genes and fiber specific promoter were cloned and sequence information was established. Expressive gene specific primers were designed and amplified directly from the total genomic DNA of Arabidopsis thaliana. The full length sequence of AthA and Rsw-1 genes were isolated from Arabidopsis thaliana by using high fidelity Pfu polymerase. The amplified product was characterized as 5.3kb and 6.kb for AthA and Rsw-1 respectively (Fig-1). The amplicons were cloned into pJET 1.2/blunt vector and transformed to host bacteria (DH5α) and positive colony was selected after 24hrs of culture (Fig-2). The clones were confirmed by restriction analysis and PCR. The positive clones were subjected to sequence analysis. Since the sequence was colossal nature, primer walking method was used to obtain full length sequence information and then Aligned with help of bioinformatics tool (BLAST-Align). The sequence information showed that the AthA has homology of 99% with CesA2 (AthA) gene and the sequence was submitted to GenBank (Acc. No. FJ687279). The other cellulose biosynthetic gene such as radial swelling1 Rsw-1 gene specific primers amplified the full length sequence and the homology analysis showed similarity with rsw1 gene and the sequence was annotated and submitted to Gen Bank.

Fig. 1: PCR Amplified Amplicons Were Resolved in Agarose Gel Showing 6.0kb and 5.3kb Fragments. Lane 1: 1kb Ladder, 2: RSW-1 Amplicon and 3: AthA Amplicon


Fig. 2: The Amplicons Were Cloned Into pJET 1.2/blunt Vector and Transformed to Host Bacteria (DH5α). White Colonies are Transformed E.coli

Fig. 3: PCR Amplified Amplicons from LRA 5166 Cotton Cultivar was Resolved in Agarose Gel Showing 1.8kb Fragments. Lane 1: Cesa Amplicon, 2: 1kb ladder

Concurrently, to express these cellulose biosynthetic genes in tissue specific, cotton fiber specific promoter was isolated. Inverse primers were designed to amplify upstream region of G. hirsutum cultivars. Well characterized single amplicon of PCR product was selected. The size was found ~1.8kb amplicon (Fig-3). The amplicon was cloned and sequenced by primer walking and homology results showed the similarity with CesA4 promoter region. The nucleotide sequence was annotated and submitted to GenBank (Accession No. HM 142347).

Assessing the function of individual CESA genes will require the identification of the null-mutant phenotypes and of the gene expression profiles for each gene (Delmer, 1999). Beeckman et al., 2002 reported four of 10 CESA genes, CESA1, CESA2, CESA3, and CESA9 are significantly expressed in the Arabidopsis embryo. They further identified two new mutations in the RADIALLY SWOLLEN1 (RSW1/CESA1) gene of Arabidopsis that obstruct organized growth in both shoot and root and interfere with cell division and cell expansion already in embryogenesis. In our study we identified similar full length sequence of RSW1/CESA1 gene. In the embryo, CESA1, CESA2, CESA3, and CESA9 are expressed in largely overlapping domains and may act cooperatively in higher order complexes. The embryonic phenotype of the presumed rsw1 null mutant indicates that the RSW1 (CESA1) product has a critical, nonredundant function, but is nevertheless not strictly required for primary cell wall formation as reported by Beeckman et al., (2002).

In all species, cellulose synthase catalytic subunits, encoded by CesA genes, share a common structure that includes several putative transmembrane helices, and a cytoplasmic loop containing four conserved regions (U1 through U4) predicted to be involved in substrate binding and catalysis (Delmer


1999). CesA–CesA interactions (Taylor et al. 2000, 2003; Kurek et al. 2002; Gardiner et al. 2003) have revealed that CesA proteins also play a role in maintaining the association of the particles that compose terminal complexes (Doblin et al. 2002).Divergence in both terminal complex organization and CesA gene sequence among groups of organisms in which both have been characterized also indicates that terminal complex organization, and thus microfibril dimensions, are influenced by CesA structure. However, the evolutionary relationships among these organisms, which include seed plants (Delmer 1999). Although seed plants are thought to have only rosette terminal complexes, those species that have been examined have numerous CesA genes.

In A. thaliana, analysis of mutant phenotypes and gene expression have revealed that some of the 10 members of the CesA gene family serve distinct functions in primary and secondary cell wall synthesis(Taylor et al. 1999; Fagard et al. 2000; Holland et al. 2000; Scheible et al. 2001). However, some groups of AtCesAs appear to have identical expression patterns and genetic complementation and co-precipitation experiments have indicated that up to three distinct CesA subunits are required for assembly of a functional rosette (Taylor et al. 2000, 2003; Scheible et al. 2001; Burn et al.2002; Desprez et al. 2002; Doblin et al. 2002;Gardiner et al. 2003). Expression analysis revealed similar patterns in other seed plant species (Tanaka et al. 2003; Burton et al. 2004; Liang and Joshi 2004). Furthermore, CesA are members of a larger gene superfamily that includes the CesA-like (Csl) genes, some of which may function in the synthesis of non-cellulosic cell wall polymers (Richmond and Somerville 2001;Dhugga et al.,2004). Thus, the differences between CesAs specialized for primary and secondary cell wall deposition could relate to the ways in which they interact with each other or the cellular structures that control terminal complex localization or movement.

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Cotton Transgenic with DRE-binding Transcription Factor Gene (DREB1A) and Zinc Finger Gene (ZF1)

Confers Enhanced Tolerance to Drought

Amudha J., G. Balasubramani, A.H. Prakash, Shweta C. K.C. Bansal and K.R. Kranthi

Central Institute for Cotton Research, Post Bag No. 2, Shankar Nagar–440 010, Maharashtra, India


Abstract—Drought tolerant transgenics were developed in elite genotypes LRA 5166 and LRK 516 with Prd29: AtDREB 1A and PLEA1:Bc ZF1 gene constructs through Agrobacterium mediated transformation. Embryonic axes were excised from 48 hr grown cottonseeds used as explants and the shoots were screened in the MS medium with 50 µg/ml kanamycin. The regenerated shoots were transformed in the MS medium containing auxin 1mg/l and cytokinin 1mg/l. The transgenics were confirmed for the presence of the gene by PCR using specific primers for DREB 1A, ZF1, npt II and the copy number by Southern analysis. RT-PCR study was carried by isolating mRNA from transgenic plants and cDNA was synthesized and amplified with npt II primer and DREB 1A gene specific primer produced the 700 bp and 540 bp fragments. To plants were hardened in the polyhouse. The transgenics subjected for drought tolerance, physiological and biochemical studies viz., PEG (polyethylene glycol), proline, reducing sugar, amino acid, protein and phenols at regular interval.

INTRODUCTION

Environmental abiotic stresses such as drought are major limiting factors that influence plant growth and crop production. Abiotic stress mediated gene expression has been shown to be regulated by different transcription factors of which, Dehydration responsive element binding (DREB 1A) protein plays a key role. The transcription factors DREB1A are important in the ABA-independent drought tolerant pathways that induce the expression of stress response genes. DREB transcription factors bind to dehydration responsive element (DRE/CRT) of genes at promoter region. DRE contains one sequence A/GCCGAC which was identified as cis acting promoter element which regulates the expression of downstream genes. It is involved in the transcriptional regulation of a dynamic network of genes controlling various biological processes, including abiotic and biotic stress responses and finally enhances plant stress tolerance.

Responses to abiotic stress require the production of important metabolic proteins such as those involved in synthesis of osmoprotectants and of regulatory proteins operating in the signal transduction pathways, such as kinases or TFs. Given that most of these responses imply control of gene expression, TFs play a critical role in the abiotic stress response (Chaves and Oliveira, 2004). TFs are proteins with a DNA domain that binds to the cis-acting elements present in the promoter of a target gene. They induce (activators) or repress (repressors) the activity of the RNA polymerase, thus regulating gene expression. Transcription factors play critical roles in the regulation of cellular and physical changes in response to environmental stresses in plants. The C-repeat binding factor/dehydration responsive element binding factor (CBF/DR0EB), NAM, ATAF, and CUC (NAC) transcription factor, zinc finger protein and other transcription factors have been described as important regulators in plant responses to environmental stresses. TFs can be grouped into families according to their DNA binding domain (Riechmann et al., 2000). A group of genes controlled by a certain type of TF is known as a regulon. In the plant response to abiotic stresses, at least four different regulons can be identified (1) the CBF/DREB regulon; (2) the NAC (NAM, ATAF and CUC) and ZF-HD (zinc-finger homeodomain) regulon; (3) the AREB/ABF (ABA-responsive element-binding protein/ ABA-binding factor) regulon; and (4) the MYC (myelocytomatosis oncogene)/MYB (myeloblastosis oncogene) regulon. The first two regulons are ABA

24

Cotton Transgenic with DRE-binding Transcription Factor Gene (DREB1A) and Zinc Finger Gene (ZF1) 137

independent, and the last two are ABA dependent. It is explained below how these regulon’s are controlled and how TFs may be involved in the regulation of photosynthesis as a response to abiotic stress. The C2H2-type zinc finger proteins have a variety of roles in plant reproductive development and abiotic stress responses (Ciftci-Yilmaz et al., 2008; Huang et al., 2007). Although their functions in stress responses are still largely unknown, a number of stress-responsive C2H2 zinc finger proteins have been identified in various plant species (Huang et al., 2007). In our study we have gene constructs with two regulons, the CBF/DREB and ZF-HD (zinc-finger homeodomain regulon).

The CBF/DREB regulon is mainly involved in cold stress response. It is conserved throughout the plant kingdom, including in plants that do not cold-acclimate (e.g. cotton, tomato and rice) (Dubouzet et al., 2003). In 1994, Yamaguchi-Shinozaki and Shinozaki identified a novel cis-acting element that, in addition to the ABA-responsive element (ABRE), is also present in the promoter of the RESPONSIVE TO DEHYDRATION 29A (RD29A), a gene induced by drought, high salinity and cold. This new element was named C-repeat/dehydration-responsive element (CRT/DRE) and characterized as ABA independent. The core motif of this cis-acting element is CCGAC and the TFs that bind to it were named CRT-binding factors or DRE-binding proteins 1 (CBF/DREB 1) (Gilmour et al., 1998; Liu et al., 1998). CBF/DREB 1 gene expression is quickly and transiently induced by cold stress, and in turn CBF/DREB1 TFs activate the expression of several other genes (e.g. encoding proteins involved in production of osmoprotectants and antioxidants). The over-expression of CBF/DREB1 genes in Arabidopsis resulted in plants with improved survival rates when exposed to salt, drought and low temperatures (Jaglo-Ottosen et al., 1998; Kasuga et al., 1999). This improved tolerance was correlated with both altered relative abundance of transcripts encoding proteins associated with stress adaptation and increased sugar contents (Gilmour et al., 2004). When CBF/DREB1 genes from Arabidopsis were over-expressed in other plants, the result was similar to that in Arabidopsis (Hsieh et al., 2002a; Pellegrineschi et al., 2004), revealing a conserved signaling and response mechanism even between dicots and monocots.

Various studies have demonstrated that improved stress tolerance by over-expression of CBF/DREB1 genes is associated with sustained photochemical efficiency and photosynthetic capacity as compared with wild-type plants (Hsieh et al., 2002b; Savitch et al., 2005; Oh et al., 2007). To overcome growth retardation, CBF/DREB1 genes have been expressed in transgenic plants under the control of a stress-inducible promoter, RD29A (Kasuga et al., 2004). These plants have also shown enhanced abiotic stress tolerance without totally compromising the yield (Pino et al., 2007). However, it seems that the use of the Arabidopsis RD29A promoter is more efficient in driving the expression of CBF/DREB1 genes in dicots rather than in monocots, or at least in rice (Ito et al., 2006).

DREB1A and Drought Tolerance

Water deficit stress that known as drought stress has many physiological effects on the plants; include reduction in vegetative growth, leaf expansion and transpiration. As a secondary effect, ABA concentration has increased and stomata close to prevent the transpirational water loss that results in limited photosynthesis due to decline in Rubisco activity (Bota et al., 2004). On the other hand, decline in intracellular CO2 levels results in the generation of ROS components that they may lead to photo-oxidation and finally they can cause extensive peroxidation and de-esterification of membrane lipids, as well as lead to protein denaturation and mutation of nucleic acids (Bowler et al., 1992).

On the cellular level, removal of water from the membrane disrupts the normal bilayer structure and results in membrane damage, displacement of membrane proteins and reduced activity ion transporters or may even complete denaturation of enzymes and cytosolic and organelle proteins, that those can cause disruption of cellular metabolism. Plant tend to protection of the membranes as well as macromolecules by synthesis of large number of osmolyte’s compounds such as proline, glutamate, glycine-betaine, carnitine, mannitol, sorbitol, fructans, polyols, trehalose, sucrose, oligosaccharides and inorganic ions like K+ (Ramanjulu and Bartels, 2002). The primary function of compatible solutes is to maintain cell turgor and thus the driving gradient for water uptake. Some studies indicate that compatible solutes can also act as free-radical scavengers or chemical chaperones by directly stabilizing membranes and/or proteins (Diamant et al., 2001, Garg et al., 2002).


Analyses of the expression of dehydration-inducible genes have shown that at least four independent signaling pathways function in the induction of stress-inducible genes in response to dehydration: two are ABA dependent (Uno et al., 2001; Velasco et al., 1998) and two are ABA independent (Savoure et al., 1997). Dehydration responsive element (DRE) or C-repeat (CRT), a cis-acting element, plays an important role in regulating gene expression in response to stress in an ABA independent manner (Yamaguchi-Shinozaki et al., 2002). DRE/CRT exists in many dehydration responsive genes and DREB1A, as a DRE/CRT-binding transcription factor, can up-regulate them. Consequently, over-expression of DREB1A gene will significantly introduce expression of dehydration responsive genes and it can results in high tolerance to drought stress in transgenic plants.


Seeds of cotton variety LRA 5166 and LRK 516 were obtained from the gene bank, Central Institute for Cotton Research, Nagpur.

Bacterial Strain and Vector

Agrobacterium mediated transformation with pCambia 2300 - Prd29: DREB1a: nos and pBinAR – PLEA 1: BcZF1 : nos gene constructs were used for transformation (Fig 1 & 2). Both the constructs has npt II gene as selection marker in the T-DNA driven by Cauliflower mosaic virus (35S CaMV) promoter and NOS-terminator in the vector system. Bacterial culture was maintained on YEMA medium (1.0% w/v Yeast extract, 1.0%w/v Mannitol, 0.1%w/v Sodium chloride, 0.2% w/v Magnesium sulphate, pH-7.0) containing 50mg/l kanamycin and 25mg/l rifampicin. For inoculation, one single colony was grown overnight on liquid YEMA at 28ºC with appropriate antibiotics.

Transformation of Cotton Plants

Cotton variety LRA 5166 and LRK 516 seedlings were raised aseptically on half- Murashige and Skoog (MS) medium. The embryonic axes were excised and trimmed from both the sides and used for co-cultivation with A.tumefaciens. The explants were co-cultivated in the half-MS liquid medium with actively growing culture of A.tumefaciens at 1.0 OD and 100mM acetosyringone. After overnight co-cultivation, shoots were decontaminated in the half MS medium containing cefotaxime 250 mg/l. The explants were then transferred to selection medium containing kinetin 0.1mg/l, BAP 0.1mg/1 and kanamycin 50mg/l. The kanamycin resistant shoots were sub-cultured in a media containing 0.1 mg/l BAP for root induction. Rooted plants were rinsed well and transferred to pots containing peat, soil and sand in 1:1:1 ratio. Plants were covered with plastic bags and then to a pot with soil for hardening for 15 days before transferring to the greenhouse under natural condition. T1 plants were raised in the green house.

Screening for Transformed Plants using PCR

Genomic DNA was isolated by the method of Paterson et al.,(1993) from the young leaves of T0 plants grown in the Polyhouse. The template DNA was used for PCR amplification with the DREB 1A gene specific primer (5’-3’) F-AAG AAG TTT CGT GAG ACT CG and R- CTTCTGCCATATTAGCCAAC, ZF1 gene specific primer (5’-3’) F- ATG GTT GCT ATT TCA GAG ATC and R- TAA CCT TCT GGA CAA ACA ACT and npt II specific primer F-GAGGCTAATTCGGCTATGACTG and R- ATCGGGAGAGGCGATACCGTA was carried out to check the presence of the transgene. PCR was performed in 20μl (total volume) reaction mixture containing 1.0 µl of 100ng DNA, 2.0 µl 10X reaction buffer, 2.0 µl of 10mM dNTP’s, 1.0 µl of 100nM of each forward and reverse primer, 3.0 µl of 25mM MgCl2 and 0.5 µl of 1U of Taq DNA polymerase. The following PCR conditions of 94ºC for 5min, then 35 cycles of 94ºC for 30sec, 56ºC for 1min, 72ºC for 1 min and 5 min of final extension at 72ºC was maintained in a thermo cycler (BIOMETRA). The amplified products were resolved on 1.5 % w/v agarose gel and documented.


RT-PCR

The mRNA was isolated using mRNA capture kit (Roche, Germany) from young leaves of T0 plants. The mRNA was used for cDNA synthesis by Transcriptor high fidelity c DNA kit (Roche, Germany).

SOUTHERN HYBRIDIZATION OF TRANSFORMED PLANTS

To confirm the gene integration Southern blotting method was used in the transgenic plants (T0 plants). Genomic DNA was isolated from the leaves of the T0 plants. For Southern hybridization 10μg of total genomic DNA from the putative transgenics was digested with Bam HI and resolved on 0.8% agarose. The probe was labeled with non- radioactive DIG labeling kit (Roche, Germany).

RNA DOT BLOT ANALYSIS

The independent events of T1 plants were grown in the poly house for best event selection and gene expression analysis under drought stress condition. RNA was isolated from the young leaves of the independent transgenic events and blotted on the nitrocellulose membrane and with the specific DREB 1A and ZF 1 probe.

PHYSIOLOGICAL STUDIES

Transgenic events of LRA 5166 and LRK 516 with DREB 1A and BcZF1 resp. were subjected for drought tolerance physiological studies. Moisture was withheld after 75 days after transplanting and plants started growing under receding moisture. The reducing sugars, amino acids and proline (Bates et al., 1973) were quantified at regular interval using standard procedures. The leaf discs from non-stressed plants of both transformed and non-transformed were placed on PEG medium with varying degrees of stress (0, 0.4, 0.6, and 0.8 MPa). The biochemical changes induced due to stress was quantified at 0, 7 & 15 days after inoculation.


Plant Transformation and Regeneration

Cotyledons of 2-3 day old were trimmed and embryonic axes measuring about 5-10 mm was used for co-cultivation. After co-cultivation for overnight the explants were decontaminated with Carbenicillin 50ug/50 ml. The explants were inoculated and selected in MS medium with kanamycin 50 mg/l as selection marker which allows only the transformants to grow. The shoot induction was observed after 10 -15 days in the MS medium. The putatively transformed shoots were sub-cultured twice in the shooting medium and then transferred to rooting medium after shoots attained a height of 5-6 cm. Rooted plants were rinsed well and transferred to pots containing peat, soil and sand in 1:1:1 ratio . The number of embryonic axes used for the experiment and the transformation frequency was given in the table 1. T1 plants are grown in the green house under controlled condition.

TABLE 1: TRANSFORMATION FREQUENCY OF THE PUTATIVE TRANSFORMANTS

Genotypes Gene Construct Number of Explants Used

Putative Transformants

PCR Positive for npt II

Transformation Frequency (%)

LRA 5166 At DREB 1A 450 45 4 0.88 LRA 5166 PLEA1:BcZF1 650 50 6 0.92 LRK 516 At DREB 1A 545 46 4 0.73 LRK 516 PLEA1:BcZF1 550 46 5 0.90


PCR Analysis of the Transgenic Plants

The PCR analysis with the npt II gene and DREB 1A, ZF 1A gene specific primers was carried out with the genomic DNA as template of individual plants (Fig 3&4). The independent transgenic events positive for npt II gene and DREB 1A gene is given in the Table 2.

TABLE 2: TOTAL NUMBER OF TRANSGENICS EVENTS POSITIVE FOR AT DREB 1A AND BCZF1 GENE.

Sr. No Variety Gene Construct No. of To Plants Survived in Kanamycin

Medium

No. of npt II Positive Putative

Transformants

No. of Specific Positive

1 LRK 516 At DREB 1A 42 38 15 2 LRA 5166 At DREB 1A 17 13 11 3 LRK 516 PLEA1:BcZF1 10 4 3 4 LRA 5166 PLEA1:BcZF1 8 6 5

Southern Hybridization by Non-radioactive Labeling Method

Southern hybridization was carried out in the PCR positive T0 transgenics by using Roche DIG labeling kit. Genomic DNA was isolated from the transgenic plants and they were restricted with the BamHI enzyme. The restricted DNA was resolved on 0.8% agarose gel electrophoresis and then blotted on to nitrocellulose membrane. The DREB 1A gene was amplified from the gene construct with the specific primer and eluted after purification and the probe DNA was labeled with the dig labeling kit. DNA samples of the independent transgenic plants of cotton was digested with BamHI and hybridized with DREB 1A gene and ZF 1 gene probe has shown the integration of single copy gene ( Fig 5 & 6 ).

RNA Dot Blot Analysis

The independent events of T1 plants were grown in the poly house for best event selection and gene expression analysis under drought stress condition. RNA was isolated from the young leaves of the independent transgenic events and blotted on the nitrocellulose membrane and hybridized with the specific DREB 1A and ZF 1 probe using Roche DIG labeling kit. The dot blot assay result has shown positive in the T1 transgenic plants (Fig 7).

RT-PCR Study

The mRNA from transgenic plants were isolated and cDNA was synthesized using the transcriptor high fidelity cDNA synthesis Roche kit .The cDNA of the transgenic plants were used for amplification with npt II primer and DREB 1A gene specific primer. The amplified product was checked by agarose gel electrophoresis.

PHYSIOLOGICAL STUDIES

Transgenic events of LRA 5166 and LRK 516 with DREB 1A and BcZF1 resp. were subjected for drought tolerance physiological studies. Sixteen transgenic plants of LRA 5166 and LRK 516 with DREB 1A and BcZF1 raised in pots along with one control plant of LRA 5166. The plants were grown under optimum growth conditions till flowering. Moisture was withheld after 75 days after planting and plants started growing under receding moisture. All physiological and biochemical constituents were quantified at regular interval. The leaves of both non-transformed and transformed plant started to droop within seven days after stress induction. The transformed plants would show recovery during night and leaves were turgid in early part of the day. This helped the plant to recover and grow normally. The leaf water potential also was maintained at higher level due to accumulation of solutes, which was not observed in case of control plants.


Over Expression of DREB 1A Improved Drought Tolerance of Transgenic Plants

T1 transgenic plants at the vegetative stage were deprived of water for 15 days exhibited increased tolerance to drought stress, compared to control plants. To evaluate physiological changes in two-month-old transgenic plants deprived of water for 15 days, soluble sugar contents in the leaves of wild type and different transgenic lines were compared. Under control conditions, the soluble sugar contents in leaves were similar for wild type and different transgenic plants, that is, around 2.56 mg/g FW. However, following drought treatment, the soluble sugar levels in transgenic plants increased after 5 days, and reached 3.64 to 7.01 mg/g FW at 20 days, whereas those in control plants at the same developmental stage reached only 3.803 g/g FW at 20 days. The amino acid content in transgenic plants after drought treatment increased after 5 days, and ranged between 0.344 to 0.985 mg/g FW at 20 days, whereas those in control plants at the same developmental stage reached only 0.750 mg/g FW at 20 days. After drought treatment, the phenol levels in transgenic plants increased after 5 days, and ranged between 1.879 to 3.498 mg/g FW at 20 days, whereas those in control plants at the same developmental stage reached only 2.355 mg/g FW at 20 days. The statistical analysis showed that soluble sugar, phenol and amino acids contents of transgenic plants were significantly higher than those of the control plants at 5, 10, 15 and 20 days (P\0.05)(Table 3).

Analysis of Stress Tolerance and Physiological Changes in Transgenic Cotton by PEG Treatments

In this method of screening, the leaf discs from non-stressed plants of both transformed and non-transformed were placed on PEG medium with varying degrees of stress (0, 0.4, 0.6, and 0.8 MPa). The biochemical changes induced due to stress was quantified at 0, 7 & 15 days after inoculation. The data showed that there was an inherent tolerance developed in transgenic plants due to DERB 1A and BcZF1 genes (Fig 8). The control plants showed a immediate burst in synthesis of reducing sugars, amino acids and proline but declined by seven days, while the transformed plants showed a gradual increase in solute accumulation and maintained high even after 7 days. The non-transformed discs produced very high phenolic’s which led to death of the tissues with stress. Over expression of DREB 1A and BcZF1 improved drought tolerance in transgenic cotton and after stress alleviation the solute content reached normal and was similar to control plants.

All three common abiotic stresses, drought, low temperature and high salinity, cause an accumulation of compatible solutes and antioxidants, such as sugars, proline (Hasegawa et al. 2000; Fukutaku and Yamada 1984). There are some overlaps in the regulation pathways of gene expression between different environmental stresses (Rabbani et al. 2003). Because of the various adverse effects of abiotic stresses on plant growth and productivity, it is very important to improve stress tolerance of the crop plants to maintain growth and productivity and increase crop yield under stress conditions. Although the tolerance of plants to abiotic stresses is well known to be a multigenic trait; plant improvement using genes that play a role in the abiotic stress response is frequently insufficient to improve stress tolerance significantly. To overcome this, transcription factors that regulate several stress-responsive genes (e.g. the DREB1s family), often have been used to manipulate plants in order to have a broader response and maintain the function and structure of cellular components (Saibo et al. 2009).

Under drought temperature conditions, many plants produce osmolytes such as free proline and various soluble sugars, which may function as osmoprotectants in stress-tolerant plants (Ishitani et al. 1996; Igarashi et al. 1997; Taji et al. 2002). Overexpression of CBF3/DREB1A in transgenic Arabidopsis plants produced a higher level of free proline than in control plants under stress conditions. (Gilmour et al. 1998), and over expression of OsDREB1A in transgenic rice plants was associated with increased soluble sugars levels compared with wild-type plants under drought, high salt and low temperature conditions (Ito et al. 2006). In our study, rd29A:: DREB 1A transgenic plants accumulated higher levels of soluble sugar than wild-type plants under drought stress conditions, suggesting that


overexpression of DREB activated the expression of downstream genes involved in sugar biosynthesis, which in turn, enhanced tolerance to drought stress in transgenic plants. Overexpression of the DREB1A gene in transgenic Arabidopsis and rice plants activated the expression of many stress-inducible genes and improved drought, high salt and freezing tolerance (Liu et al. 1998; Kasuga et al.1999, Dubouzet et al. 2003). Likewise, 35S::DREB1A transgenic cotton plants in our study showed increased tolerance to drought stress.

In plants, the EAR (ERF-associated amphiphilic repression)-motif was first identified in the C-terminal region of class II AP2/ERFs and Cys2/His2-type zinc-finger proteins (Ohta et al. 2001). Zinc finger proteins as members of transcriptional factors were further grouped into the subfamilies of TFIIIA, WRKY, Dof, LIM, and RING finger. In plants zinc finger proteins are involved in growth, development and responses to environmental stresses. bZIP proteins contain a region of basic amino acids followed by a region containing at least three to four repeats of Leu or another hydrophobic amino acid. The hydrophobic region mediates homo dimer formation, whereas the basic region is involved in DNA binding. Several zinc finger proteins containing DLN-box/EAR-motifs were revealed to have transcriptional repression activities by transient analyses in plants, such as petunia ZPT2-3 (Sakamoto et al., 2004), Arabidopsis STZ/ZAT10 and AZF2 (Sugano et al., 2003). The DLN-box/EAR-motif is not the only determinant of transcriptional repression activity of C2H2-type zinc fingers. Other unknown domains may also have an impact on the transcriptional activation/repression activity. Alternatively, the transcriptional repression activity of C2H2 zinc finger proteins may require post-translational modifications that are only performed in plants. Overexpression of a petunia zinc finger protein gene, ZPT2-3, in transgenic petunias increased the plants’ tolerance to drought stress (Sugano et al., 2003).

When plants suffer from drought stress, the ABA signal transduction pathway is activated and ZFP accumulates quickly. ZFP promotes the accumulation of free proline by activating the expression levels of pyrroline-5-carboxylatesynthetase and proline transporter genes, and enhances the ROS-scavenging ability in plant cells by activating the ROS-scavenging enzymes. Our data suggest that ZFP contribute to the drought tolerance of transgenic plants by regulating their proline levels and ROS-scavenging abilities with enhanced tolerance to abiotic stress. In the present study, all the transgenic lines grew normally, suggesting that DREB genes from a monocotyledon plant might not affect the growth and development of a dicotyledonous (Chen et al. 2003). Nevertheless, the basis of underlying abnormal growth and development of transgenic plants with DREB genes might be very complicated and possibly related to a range of factors, such as gene structure, uncertain insertion sites of the exogenous genes, and instability of gene expression caused by copy numbers (Finnegan and McElroy, 1994).

DREB1A is a transcription factor that induced by abiotic stress, strongly up-regulates many downstream genes; result in adaptation of plants to stress conditions and exercise specific tolerance mechanisms. Many studies indicated that over-expression of DREB1A in crop plants can result in high tolerance to abiotic stress and thereby increased efficiency of plants production. Taken together suggest we used gene transfer by DREB 1A and ZF1 strategy to prevent of large and widespread yield reductions under stress conditions and obtain more products in agronomic development. However DREB1A has a key role in tolerance to abiotic stress such as drought, salinity, heat and low temperature stresses. Given that the molecular control mechanisms of abiotic stress tolerance are similar and DREB1A effected on majority of them, therefore it is possible that over-expression of DREB1A gene leads to tolerance in transgenic plants. It is hoped in the future that these efforts will help to prevent global-scale environmental damage that is resultant from these stress.

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Fig. 5: Southern Analysis of DREB 1A Transgenic Plants. Genomic DNA (10ug) Was Digested with Bam HI and Hybridized with DREB 1A Gene Probe Labeled with Dig - Labeling Kit.

Lane 1: 100bp Ladder, Lane 2-5: DNA samples of the independent transgenic plants of cotton. Fig. 6: Southern Analysis of ZFP 1 Transgenics. Genomic DNA (10ug) was Digested with Bam HI and Hybridized

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Study of Heterosis in Inter Varietal Crosses of Asiatic Cotton (Gossypium herbaceum L)

N.N. Patel, D.U. Patel, D.H. Patel, K.G. Patel, S.K. Chandran and V. Kumar

Main Cotton Research Station, Navsari Agricultural University, Athwa Farm, Surat-395007, India

Abstract—The present investigation was carried out using line x tester analysis consisting of four line and ten pollinator parents to have information on extent of heterosis for seed cotton yield and yield components in Asiatic cotton (G. herbaceum). High parent heterosis was observed for seed cotton yield ranging from –23.31 to 29.25 whereas standard heterosis against check G.Cot.DH-9 ranged from –45.07 to 18.21. Three hybrids G.Cot-23 x GBhv-191, G.Cot-23 x GBhv-178, G.Cot-23 x GBhv-215 exhibited significant and positive heterosis for seed cotton yield over standard check. Seven cross combinations namely G.Cot-23 x GBhv-191, G.Cot-23 x GBhv-178, G.Cot-23 x GBhv-215, Jaydhar x GShv-820/91, G.Cot-17 x GShv-384/92, G.Cot-17 x GShv-820/91 and G.Cot-17 x GBhv-201 showed heterobeltiosis in desired direction for seed cotton yield. The magnitude of heterobeltiosis and standard heterosis was high for seed cotton yield, boll weight and ginning percentage, medium for plant height and number of bolls per plant and low for 2.5 % span length. The result indicated that, in general high heterotic hybrids was involved at least one good donor parent for seed cotton yield and its components. The hybrids, G.Cot-23 x GBhv-191, G.Cot-23 x GBhv-178, G.Cot-23 x GBhv-215 expected to provide better segregants in subsequent generation as these crosses are associated with parents having significant and positive gca effects for majority of the characters.

INTRODUCTION

Considerable progress has been made for commercial exploitation of hybrid vigour in Hirsutum, but it is not so for Herbaceum. The desi or diploid cotton varieties are still preferred in the low rainfall areas because of their resistance to disease and pest, drought tolerance and suitability under rainfed conditions. These aroused the interest for developing superior hybrids in Asiatic cotton. The choice of appropriate breeding procedure for the development of high yielding varieties in intra-specific hybrids of desi-cotton depends on the nature and magnitude of genetic variation present in the material with respect to yield and its component traits through line x tester mating design.


The seed of 40 F1 hybrids developed from line x testers mating design by crossing 4 lines/females and 10 testers/males was sown in randomized block design with three replications at Regional Cotton Breeding Research Station, Navsari Agricultural university, Bharuch during kharif 2001-02. Each plot consisted of single row of 5.4 m. length spaced at 120cm apart with plant-to-plant spacing 45 cm. The hybrids were grown along with parent and standard check (G.Cot-DH-9). The recommended dose of fertilizer was applied. The insects and pests were controlled with proper insecticides. The data for seed cotton yield and its components viz; boll weight, number of bolls per plant, plant height, number of monopodia, ginning percentage and 2.5 % span length were recorded from five competitive plants in each replication. The heterosis over better parent and hybrid check G.Cot-DH-9 was estimated using standard procedure. (Panse and Sukhatme (1978) and Singh and Choudhari (1979).


The analysis of variance (Table1) indicated that differences among genotypes were statistically significant for all the characters, indicating considerable amount of variability. Heterosis over better parent and standard hybrid variety are presented in Table 2. The heterobetiosis and standard heterosis over seed cotton yield ranged from –23.31 to 29.25 and –45.07 to 18.21 per cent respectively. Only three crosses (hybrids) viz.,G.Cot.23 x GBhv-191 (18.21), G.Cot.23 x GBhv-178 (14.37) and G.Cot.23 x GBhv-215 (12.67 per cent)exhibited significant heterosis over standard check for seed cotton yield. Similar results were also reported by Tuteja et al., (2004), Preetha and Raveendaran (2008) and Rajamani

25


et al., (2009). For boll weight 15 and 22 hybrids expressed significant positive heterosis over better parent and standard check respectively. The highest positive heterosis was observed by the cross G.Cot-23 x GShv-531/92 (32.37 %) over standard check for boll weight. Similarly, for number of bolls per plant the hybrids Digvijay x GBhv-178 and Jaydhar x GShv-820/91 recorded significant positive heterosis of 17.50 and 13.49 % over better parent and standard check respectively. For ginning percentage, the hybrid G.Cot-17 x GShv-613/97 (27.31%) recorded maximum standard heterosis. The significant positive heterosis (23.14%) was exhibited by the hybrid G.Cot-17 x GBhv-201 over better parent and 14.61 % heterosis was recorded by the hybrid Digvijay x GShv-695/93 over standard check for plant height (Tuteja and Singh 2001, Kapoor et al., 2002). None of the hybrid had positive heterosis for 2.5% span length over long staple standard hybrid check (Patel et al., (2000).

TABLE 1: ANALYSIS OF VARIANCE (MEAN SQUARE) FOR EXPERIMENTAL DESIGN FOR DIFFERENT CHARACTERS IN COTTON

Source of Variation

d.f. Seed Cotton Yield

Per Plant

Boll Weight

(g)

Number of Bolls Per

Plant

Ginning Percentage

Plant Height (cm)

2.5 % span Length (mm)

Replications 2 177.85 0.01 19.71 1.36 25.78 0.24 Treatments 54 1868.80 0.32 172.59 18.38 1423.26 4.17 Parents 13 959.97** 0.32** 109.88** 14.53** 1182.65** 3.02** Females 3 2928.92** 0.91** 173.35** 42.16** 1769.68** 2.94** Males 9 407.78** 0.11** 50.78** 5.38** 1062.55** 2.95** Females vs Males 1 22.88 0.43** 451.35** 14.01** 502.45** 3.87* Hybrids 39 1928.65** 0.31** 176.27** 19.02* 1511.66** 1.99** Parents vs Hybrids 1 11451.0** 0.77** 703.91** 2.45 982.25** 0.05 Control vs Rest 1 1767.22 0.26 313.11 59.13 1544.60 108.44 Error 108 57.87 0.002 13.70 1.28 30.09 0.66 S.Em. + 4.39 0.03 2.14 0.65 3.17 0.47

*Significant at 5% ** Significant at 1%

TABLE 2: ESTIMATES OF HETEROSIS IN PERCENTAGE OVER BETTER PARENT (BP) AND STANDARD CHECK (SC) G.COT.DH-9 FOR DIFFERENT CHARACTERS

Hybrids Seed Cotton Yield Per Plant Boll Weight No. of Bolls Per Plant BP BP BP SC BP SC

Digvijay x GShv-384/92 8.23 -15.97** 6.13** -4.15* 5.71 -7.98* Digvijay x GShv-695/93 2.76 -26.39** 1.64 2.90 -6.30 -26.08** Digvijay x GShv-820/91 4.26 -20.96** -5.59** -6.64** 7.01 -14.64** Digvijay x GShv-613/97 7.71 -24.53** 7.10** -4.15* 0.00 -19.60** Digvijay x GShv-531/92 1.38 -25.86** 1.62 4.15* 4.27 -17.74** Digvijay x GBhv-178 13.31** -6.39 4.27* 1.24 17.50** 0.09 Digvijay x GBhv-191 -9.81* -20.99** -2.07 4.98** -4.34 -21.82** Digvijay x GBhv-198 6.60 -10.88** -5.43** 5.81** -0.56 -21.56** Digvijay x GBhv-201 16.95** -15.48** -1.28 6.64** -7.09 -26.70** Digvijay x GBhv-215 -14.75** -25.48** -8.68** 1.66 -8.11 -26.62** G.Cot-17 x GShv-384/92 22.96** 2.00 9.35** 6.64** 6.61 -2.74 G.Cot-17x GShv-695/93 -13.34** -28.03** 4.10* 5.39** -15.66** -23.07** G.Cot-17 x GShv-820/91 21.31** 0.75 3.91* 2.90 3.60 -5.49 G.Cot-17 x GShv-613/97 2.52 -14.91** 9.63** 7.05** -8.27 -16.31** G.Cot-17 x GShv-531/92 11.32** -7.61* 11.35** 14.11** -2.82 -11.35** G.Cot-17 x GBhv-178 14.80** -4.72 13.31** 10.79** 4.57 -4.60 G.Cot-17 x GBhv-191 -1.74 -13.92** 2.33 9.54** -9.73* -17.65** G.Cot-17 x GBhv-198 16.11** -2.93 -2.96 8.71** -0.10 -8.86* G.Cot-17 x GBhv-201 21.26** 0.64 -0.77 7.47** 8.27 -1.23 G.Cot-17 x GBhv-215 13.62** -0.68 -9.68** 0.83 7.20 -2.21 G.Cot-23 x GShv-384/92 -1.22 -1.33 -13.18** 5.81** 7.24 -6.66 G.Cot-23x GShv-695/93 -17.67** -17.77** -3.18* 17.84** -12.93** -28.29** G.Cot-23 x GShv-820/91 0.30 0.19 5.68** 28.63** 3.34 -14.91** G.Cot-23 x GShv-613/97 0.15 0.03 -2.27 19.09** 4.20 -14.18** G.Cot-23 x GShv-531/92 6.05 5.93 8.86** 32.37** -0.32 -17.91** G.Cot-23 x GBhv-178 14.51** 14.37** 4.32** 26.97** 8.33 -7.71

Table 2 (Contd.)…

Study of Heterosis in Inter Varietal Crosses of Asiatic Cotton (Gossypium herbaceum L) 151

…Table 2 Contd. G.Cot-23 x GBhv-191 18.35** 18.21** 6.36** 29.46** 16.92** -3.72G.Cot-23 x GBhv-198 -3.20 -3.31 1.36 23.24** 2.69 -15.44**G.Cot-23 x GBhv-201 4.95 4.82 3.64* 26.14** 5.60 -13.04**G.Cot-23 x GBhv-215 12.80** 12.67** 6.36** 29.46** 7.65 -11.35**Jaydhar x GShv-384/92 -10.29** -30.35** -8.28** -17.43** -9.88* -8.52*Jaydhar x GShv-695/93 -23.31** -45.07** -13.39** -12.45** -30.94** -29.89**Jaydhar x GShv-820/91 29.25** -2.01 -8.38** -9.13** 11.80** 13.49**Jaydhar x GShv-613/97 -7.33 -35.07** 3.40 -7.47** -26.31** -25.19**Jaydhar x GShv-531/92 5.12 -23.13** -6.49** -3.73* -17.57** -16.32**Jaydhar x GBhv-178 -13.95** -28.91** -10.26** -12.86** -13.81** -12.51**Jaydhar x GBhv-191 -16.59** -26.93** -21.71** -16.18** -7.17 -5.76Jaydhar x GBhv-198 14.51** -4.26 -15.31** -4.98** 0.96 2.49Jaydhar x GBhv-201 15.79** -16.31** -17.90** -11.20** 0.87 2.39Jaydhar x GBhv-215 8.53* -5.13 -10.92** -0.83 4.63 6.21S.Em + 4.39 4.39 0.03 0.03 2.14 2.14CD at 5 % 12.17 12.17 0.08 0.08 5.92 5.92CD at 1 % 15.99 15.99 0.11 0.11 7.80 7.80

Hybrids Ginning Percentage Plant Height 2.5 % Span Length (mm)BP SC BP SC BP SC

Digvijay x GShv-384/92 -0.87 16.62** 7.49** -7.22** 1.28 -19.74**Digvijay x GShv-695/93 -0.09 17.53** 6.90** 14.61** -3.46 -24.38**Digvijay x GShv-820/91 -12.09** 4.39 18.94** -18.70** -1.47 -16.69**Digvijay x GShv-613/97 -1.56 15.79** -9.26** -6.59* -1.58 -22.89**Digvijay x GShv-531/92 -4.42 12.43** -16.03** -15.78** -0.70 -19.74**Digvijay x GBhv-178 -8.48** 7.63** 8.19** 8.51** 0.55 -18.05**Digvijay x GBhv-191 3.64 21.91** 4.79 5.04 2.68 -17.94**Digvijay x GBhv-198 -0.78 16.71** 8.96** 9.28** 0.00 -16.69**Digvijay x GBhv-201 -9.61** 8.24** -1.36 -1.06 3.58 -18.28**Digvijay x GBhv-215 6.58** 25.35** 4.81 5.11* 1.35 -15.44**G.Cot-17 x GShv-384/92 -0.41 22.21** -2.46 -5.27* 1.28 -19.74**G.Cot-17x GShv-695/93 -3.40 18.54** -28.49** -23.33** 0.00 -21.43**G.Cot-17 x GShv-820/91 3.07 26.48** -19.54** -31.58** -3.60 -18.49**G.Cot-17 x GShv-613/97 3.73 27.31** -31.76** -29.75** -6.61* -26.62**G.Cot-17 x GShv-531/92 -0.08 22.61** -21.47** -22.02** -0.56 -19.64**G.Cot-17 x GBhv-178 -0.75 21.81** -13.14** -21.51** -6.23* -23.57**G.Cot-17 x GBhv-191 -4.65* 17.01** -2.81 -24.51** -1.27 -21.09**G.Cot-17 x GBhv-198 -6.80** 14.35** -1.31 -23.73** -6.91* -22.45**G.Cot-17 x GBhv-201 -2.16 20.07** 23.14** -3.50 3.15 -18.63**G.Cot-17 x GBhv-215 -5.56* 15.88** -18.31** -29.34** -8.80** -23.91**G.Cot-23 x GShv-384/92 -5.34* 17.32** -12.20** -14.74** -1.39 -19.84**G.Cot-23x GShv-695/93 2.47 27.00** -9.95** -3.48 -2.78 -20.99**G.Cot-23 x GShv-820/91 -12.33** 8.67** -4.47 -9.29** -4.41 -19.17**G.Cot-23 x GShv-613/97 -6.08** 16.40** -23.71** --25.48** -0.56 -19.17**G.Cot-23 x GShv-531/92 -9.78** 11.82** -24.65** -25.17** -1.81 -20.18**G.Cot-23 x GBhv-178 -6.82** 15.49** 1.35 -3.77 -5.54* -23.02**G.Cot-23 x GBhv-191 -7.07** 15.18** 15.08** 9.26** 3.75 -15.68**G.Cot-23 x GBhv-198 -12.65** 8.24** -16.80** -21.01** -4.20 -20.18**G.Cot-23 x GBhv-201 -3.20 19.98** -6.07* -10.82** -2.64 -20.86**G.Cot-23 x GBhv-215 -5.01* 17.72** -25.98** -29.73** -1.76 -18.05**Jaydhar x GShv-384/92 -1.96 7.14* -28.11** -30.19** 3.13 -18.28**Jaydhar x GShv-695/93 -8.25** -0.30 -19.42** -13.62** 3.95 -22.79**Jaydhar x GShv-820/91 -9.26** 7.76** -15.01** -27.74** -3.20 -18.15**Jaydhar x GShv-613/97 -1.02 8.24** -28.02** -25.91** 1.20 -23.70**Jaydhar x GShv-531/92 -2.55 9.16** -30.68** -31.17** -2.37 -21.09**Jaydhar x GBhv-178 -9.30** 1.34 -2.89 -12.26** -7.06* -24.24**Jaydhar x GBhv-191 -9.09** 1.83 -2.30 -24.12** -5.23 -24.24**Jaydhar x GBhv-198 -5.56* 3.78 7.55* -16.89** -11.25** -26.07**Jaydhar x GBhv-201 -17.09** -0.70 -6.11 -26.42** -2.00 -22.69**Jaydhar x GBhv-215 0.19 8.37** -2.07 -15.29** -6.50* -22.01**S.Em + 0.65 0.65 3.17 3.17 0.47 0.47CD at 5 % 1.80 1.80 8.77 8.77 1.30 1.30CD at 1 % 2.37 2.37 11.51 11.51 1.71 1.71


Identification of superior heterotic hybrids are mostly done on the per se performance. The performance of hybrids indicated that high seed cotton yielding hybrids also performed well in at least one or more yield attributing characters. Among females (G.Cot-23) and among males (GBhv-191 and GBhv-215) appeared promising for seed cotton yield as well as for most of the yield components. The hybrid G.Cot-23 x GBhv-191 expressing highest positive heterobeltiosis and standard heterosis for seed cotton yield also had significant heterosis for yield component namely boll weight, ginning percentage and number of bolls per plant. The results are in agreement with the report of Bhatade et al., (1979); Waldia et al., (1979); Khadi et al., (1992).It will be a boon to the breeder to screen such parental combination to exploit them for a successful heterotic breeding.

From the above discussion it is interesting to note that generally high heterotic hybrids involved at least one good donor parent for seed cotton yield or its components. Therefore, the hybrid G.Cot-23 x GBhv-191, G.Cot-23 x GBhv-178 and G.Cot-23 x GBhv-215 expected to provide better segregants in subsequent generation.

REFERENCES [1] Bhatade, S.S., Shobhane, M.R. and Unchegaonkar, P.K. (1979). Studies on heterosis in inter-varietal crosses of Desi

(Gossypium arboreum L.) cotton. J. Indian. Soc. Cotton Improve., 4 (1) : 28-36. [2] Kapoor, C.J.; Singh, M. and Maheshwari, R.V. (2002). Heterosis for yield and yield attributing traits in desi cotton. J.

Cotton Res. Dev.,16(2) : 182-183. [3] Khadi, B.M.; Janagoudar, B.S.; Katageri, I.S. and Eshanna, M.R. (1992). Desi hybrids cotton for rainfed conditions. J.

Cotton Res. Dev., 6(2): 105-110. [4] Panse, V.G. and Sukhatme, P.V. (1978). “Statistical methods for Agricultural workers”. I.C.A.R., New Delhi. [5] Patel, J.C.; Patel, U.G.; Patel D.H.; Patel, R.H. and Patel, M.V. (2000). Performance of intra hirsutum and asiatic hybrids

based on male sterility system. Indian J. Genet., 60: 111-115. [6] Preetha, S. and Raveendran T. S. (2008). Combining ability and heterosis for yield and fibre quality traits in line x tester

crosses of upland cotton. International J. Plant Breed. Genet., 2(2): 64-74. [7] Rajamani, S., Rao C. M. and Naik R. K. (2009). Heterosis for yield and fibre properties in upland cotton (G. hirsutum L.).

J. Cotton Res. Dev., 23(1): 43-45. [8] Tuteja, O.P., and Singh, D.P. (2001). Heterosis for yield and its components in desi cotton hybrids based on GMS system

under varied environments. Indian J. Genet., 61 (3) : 291-292. [9] Tuteja, O.P.,Verma S.K. and Ahuja, S.L.(2004). Estimation of heterosis for seed cotton yield and its component characters

in Gossypium hirsutum L. J. Cotton Res. Devlop.18 : 38-41. [10] Singh, R.K. and Choudhary, B. D. (1979). Biometrical methods in quantitative genetic analysis (Revised ed.1979). Kalyani

Publisher,New Delhi, pp.191-200. [11] Waldia, R.S., Mor, B.R. and Lather, B.S.P. (1979). Heterosis and combining ability in desi (G. arboreum L) cotton. J.

Indian Soc. Cotton Improve., 8 (1) : 36-037.

Assessment of Genetic Diversity for Improved Fibre Quality Traits in G. barbadense Accessions

to Widen Cotton Gene Pool

Amala Balu P., D. Kavithamani and S. Rajarathinam

Department of Cotton, Centre for Plant Breeding and Genetics Tamil Nadu Agricultural University, Coimbatore–641003

Abstract—The knowledge on the presence of genetic diversity and breeding potential of Gossypium spp., accessions are vital source for the genetic improvement of cotton fibre quality and productivity. Hence G. barbadense germplasm is known existing source for availability of substantial variation of fibre quality traits. The objective of this study was to assess the genetic diversity and relationship among the G. barbadense accessions using multivariate Mahalanobis D2 statistics. Fifty five G. barbadense accessions and one G. hirsutum (for forming different clusters) accession were utilized in this study. Grouping of accessions into different clusters was independent of the geographical origin of accessions. G. hirsutum accession formed a separate cluster from the G. barbadense accessions. The analysis of variance showed highly significant differences among genotypes for all the characters studied. Cluster I was largest consisting of 36 accessions followed by cluster V with five accessions. The composition of clusters indicated the existence of relationship between genetic diversity and geographical distribution. The inter cluster distances were maximum when compared to intra cluster distances, which indicated wide genetic diversity among the genotypes of different groups than those of same cluster. The results inferred that there is need to broaden the genetic base of individual clusters by introducing different alleles from the germplasm accessions of other clusters. Seed cotton yield, GOT, boll weight, bundle strength, S/L ratio were the major characters contributing towards divergence.

Keywords: Genetic divergence, Gossypium barbadense, inter cluster, intra cluster multivariate analysis.

INTRODUCTION

A better knowledge about the genetic diversity of cotton is warranted for exploitation of existing variability. It also plays an important role in the manifestation of heterosis. Hybrids between genotypes of diverse origin display a greater heterosis than those hybrids involving closely related parents. Multivariate analysis employing Mahalanobis’s D2 analysis has been extensively used as a quantitative measure to identify diverse genotypes. Present investigation was carried out to estimate the nature and magnitude of genetic diversity.


The study was conducted in the department of cotton, Tamil Nadu Agricultural University, Coimbatore during winter 2010. Fifty five Gossypium barbadense cotton genotypes obtained from Central Institute for cotton Research (Regional station) Coimbatore along with on G.hirsutum genotype were planted in randomized block design with three replications. Uniform spacing of 90 cm x 45 cm and all the recommended field operations were carried out. In each replication five competitive plants were randomly selected and observations were recorded for 14 characters viz., days to 50 per cent flowering, no. of bolls /plant, boll weight, lint and seed index, ginning out turn, seed cotton yield / plant, lint yield / plant. 2.5 per cent span length, bundle strength, micronaire value and fibre strength / length ratio. The genetic divergence was worked out by using Mahalanobiss D2 statistic as described by Rao (1952). Based on the D2 value, evaluated genotypes were grouped into different clusters by employing Tocher’s method as outlined by Rao (1952).

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RESULT AND DISCUSSION

The analysis of variance showed highly significant differences among genotypes for all the characters studied and infers existence of considerable genetic diversity among genotypes. Hence, further analysis was carried out for relative magnitude of D2 values for all the characters and all the genotypes were grouped into ten clusters (Table 1).

TABLE 1: GENOTYPES INCLUDED IN DIFFERENT CLUSTERS

Cluster Number Genotypes No. of Genotypes I

NDGB7, NDGB12, NDGB22, NDGB29,NDGB32, NDGB33, NDGB35, NDGB41, NDGB43, NDGB44, NDGB45, NDGB46, NDGB48, NDGB49, NDGB60, NDGB62, NDGB64, NDGB67, NDGB68, NDGB74, NDGB76, NDGB77, NDGB78, NDGB79, NDGB80, NDGB81, NDGB87, NDGB88, NDGB89, NDGB90, NDGB92, NDGB93,ICB1,ICB3,ICB61and ICB73

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II ICB124 and ICB238 2 III ICB104 and ICB165 2 IV ICB172 and ICB180 2 V ICB85,ICB87,ICB128,ICB 137and ICB164 5 VI ICB169,ICB 171 and ICB207 3 VII ICB 235 and CCB1 2 VIII ICB173 and ICB 242 2 IX SUVIN 1 X MCU 13 1

Among the clusters obtained the maximum number of germplasm accessions (36) were included in cluster I followed by cluster V (5) and cluster VI (3), while clusters, II,III,IV,VII and VIII included two genotypes each and the lowest in cluster IX (1) and X (1). Genotypes from diverse eco-geographical regions of the country were grouped in the cluster I. Thus, the grouping of genotypes into different clusters was at random and no relationship between the genetic divergence and geographical origin of the genotypes was observed. Generally geographical diversity has been considered as a measure of genetic diversity. However, this is an inferential criterion and it may not be so effective in quantifying or differentiating various populations. The present pattern of grouping of genotypes indicated that the genetic diversity was not fully related to the geographical diversity. These results are in agreement with the earlier studies viz., Single and Bains (1968), Singh and Gill (1984), Sumathi and Nadarajan (1994), Amudha et al. (1997), Pushpam et al., (2004), and Gopinath et al., (2009). Hence, it indicated that the geographic diversity though important, might not to be the only factor in determining genetic divergence. It may be the outcome if several other factors such as genetic drift, natural selection forces and diverse environmental conditions within the country. Therefore, choice of the parents for hybridization should be decided on the basis of genetic diversity rather than geographical diversity.

TABLE 2: AVERAGE INTRA (DIAGONAL) AND INTER (OFF- DIAGONAL) CLUSTER DISTANCES BASED ON D2 VALUES

Clusters I II III IV V VI VII VIII IX X I 42.00 59.55 42.30 79.88 57.20 119.76 122.16 41.29 133.04 150.34 II 5.01 21.46 21.52 67.78 42.02 67.81 54.32 93.22 147.81 III 20.64 34.32 56.74 66.67 95.87 44.60 124.53 127.14 IV 20.71 83.14 38.23 121.53 74.99 143.91 189.39 V 48.85 135.46 136.77 49.12 165.42 228.36 VI 63.34 130.48 112.76 140.69 191.71 VII 36.91 106.28 53.95 146.98 VIII 41.99 120.08 173.15 IX 0.00 122.39 X 0.00

In the present study, inter cluster distances were found to be greater than intra cluster distances, revealing considerable amount of genetic diversity among genotypes (Table 2). The highest intra cluster distance was observed in cluster VI (63.34) followed by cluster V (48.85), cluster I (42.00) cluster VIII (41.99), cluster VII (36.91), cluster IV (20.71), cluster III (20.64) and cluster II (5.01) where as the highest inter cluster distance was observed in between the clusters X and V(228.36) followed by cluster

Assessment of Genetic Diversity for Improved Fibre Quality Traits in G. barbadense Accessions 155

X and VI(191.71), cluster X and IV(189.39), cluster X and VIII (173.15) cluster IX and V (165.42), cluster X and I (150.34), cluster X and II (147.81), cluster X and VII (146.98), cluster IX and IV (143.91), cluster IX and cluster VI (140.69) and the lowest in between cluster III and II (21.46).

Maximum genetic divergence between the clusters indicates that the hybridization between the genotypes of distant clusters would produce potential and meaningful hybrids and desirable segregants also. Use of genetically distance genotypes as parents to get the most promising breeding material had also been suggested by Singh and Singh (1984), Sambamurthy et al., (1995), Pushpam et al., (2004) and Gopinath et al., (2009). However, Arunachalam and Bandopadhyay (1984), Alther and Singh (2003) and Kulkarni et al.,(2011) experimentally proved that more number if heterotic combinations with higher level of heterosis were from the parents grouped into moderate divergent groups like clusters IX and III. The results obtained from clustering pattern are in agreement with hypothesis of moderate divergence for the best heterotic combinations.

Divergence reflecting in the material was also evidenced by an appreciable amount of desirable variation among cluster means for different characters (Table 3). The component of cluster means for seed cotton yield / plant was the highest for cluster X (1587 kg/ha) followed by cluster V (1164kg/ha) and the lowest for cluster IX (656 kg/ha). A minimum day to 50 per cent flowering was observed for cluster X (60 days) followed by cluster I (71 days) a maximum mean value for cluster II and IV (75 days). For plant height, the highest cluster mean was recorded in cluster VI (209 cm) followed by cluster IV (203 cm) and the lowest in cluster IX (118cm).

TABLE 3: COMPONENTS OF INTRA CLUSTER D2 OF COTTON

Cluster Different plant characters 1 2 3 4 5 6 7 8 9 10 11 12 13 14

I 71 128.42 14 19 3.86 5.48 10.56 34.17 987.23 338 32.17 27.52 4.36 0.81 II 75 175.66 19 24 4.09 6.07 11.88 33.80 1034.00 350 34.10 30.33 4.10 0.86 III 72 162.41 16 18 4.23 6.79 12.02 36.07 958.75 349 33.17 28.88 4.40 0.82 IV 75 203.16 17 28 4.10 6.05 11.53 34.35 813.00 280 30.47 27.98 4.63 0.89 V 75 128.56 13 17 3.92 6.01 11.11 35.01 1163.80 404 32.72 30.83 4.19 0.89 VI 74 209.00 19 30 3.52 5.10 9.83 34.07 811.50 279 33.20 29.87 4.15 0.88 VII 74 130.16 23 28 4.32 6.18 12.29 33.43 738.50 246 36.90 28.98 3.95 0.76 VIII 74 123.08 15 21 3.76 5.05 10.35 32.61 735.25 245 33.25 28.83 4.55 0.82 IX 73 118.17 24 31 3.20 4.93 11.30 30.40 656.00 200 31.80 35.40 3.45 0.94 X 60 119.50 21 31 4.35 5.55 9.50 36.95 1587.00 586 30.00 22.55 4.25 0.75

1- Days to 50 per cent flowering; 2- Plant height (cm); 3- Symbodia/plant; 4- Bolls/plant; 5- Boll weight (g); 6. Lint index; 7- Seed index; 8- Ginning Outturn; 9- Seed Cotton Yield (kg/ha); 10- Lint yield(kg/ha); 11- 2.5 per cent span length (mm); 12- Bundle strength (g/tex); 13- Micronaire value; 14- Strength/Length ratio.

For sympodia /plant, cluster IX (24) exhibited the highest cluster mean, while cluster V (13) had minimum cluster mean. The highest cluster mean for number of bolls / plant was exhibited by cluster IX and X (31) and the lowest was recorded by cluster V (17). The cluster X had the highest cluster mean for boll weight (4.35g) followed by cluster VII (4.32g) and the lowest cluster IX (3.20g). For lint index, cluster III (6.79) registered the highest mean value and cluster IX recorded the lowest (4.93) cluster mean. The highest cluster mean for seed index was exhibited by cluster VII (12.29) and the lowest in cluster (9.50). For ginning outturn cluster X (36.95) exhibited the highest cluster mean, while cluster IX (30.40) has minimum cluster mean. The highest cluster mean for lint yield was exhibited by cluster X (586 kg/ha) followed by cluster V (404 kg/ha) and the lowest in cluster IX (200 kg/ha).

For 2.5 per cent span length, cluster VII possessed the highest cluster mean of 36.90mm followed by cluster II (34.10mm) and the lowest was registered by cluster X (30.00 mm). For fibre strength, the highest cluster mean was exhibited by cluster IX (35.40 g / tex), followed by cluster II (30.33 g / tex) and lowest was in cluster X (22.55g/tex). The highest cluster mean for Micronarie value was exhibited by cluster VIII (4.55) and lowest was recorded by cluster IX (3.45). For strength / length ratio, the maximum


cluster mean was registered by cluster IX (0.94) and minimum ratio was recorded by cluster X (0.75). Strength / length ratio (32.40%), seed cotton yield (11.80%), sympodia / plant (9.09), ginning outturn (8.57%) and boll weight (7.53%) collectively contributed 69.39% towards the total divergence (Table 4) and the other characters that influenced the divergence were having minimum value (30.09 percent).

TABLE 4: CONTRIBUTION OF DIFFERENT CHARACTERS TO GENETIC DIVERSITY S. No. Characters Percent Contribution

1 S/L ratio 32.4 2 Seed cotton yield 11.80 3 Sympodia / plant 9.09 4 Ginning outturn 8.57 5 Boll weight 7.53 6 2.5 per cent span length 4.74 7 Bundle strength 4.74 8 Bolls / plant 4.03 9 Micronaire value 2.92 10 Days to 50 per cent flowering 2.47 11 Lint index 2.21 12 Lint yield 2.21 13 Plant height 0.97 14 Seed index 0.48

The better genotypes selected for all the characters under consideration were presented in table 5. Among these, NDGB 41 included in cluster I possessed the highest seed cotton yield (1806 kg/ha). Similarly, genotype MCU 13 of cluster X showed minimum days to 50 per cent flowering. In case of G.barbadense genotypes NDGB 32, NDGB 67 and NDGB 68 of cluster I had a minimum period of 68 days required for 50 per cent flowering. For plant height the highest mean value of 216.33 cm was recorded by ICB 171 of cluster VI. The genotype NDGB 64 of cluster I exhibited the highest mean value for number of symbodia / plant (14). The highest mean performance for number of bolls / plant was recorded by ICB 169 (35 bolls) of cluster VI. For considering boll weight, the highest mean boll weight of 4.69 g was registered by ICB 3 of cluster I. Likewise, the highest mean value for lint index and seed index were showed by ICB 104 (7.18) of cluster III and NDGB 64 (14.35) of cluster I. The highest mean value for ginning out turn of 39.40 per cent was recorded by ICB 87 of cluster V. For considering lint yield NDGB 41 (cluster I) had showed highest mean value of 619 kg/ha. However, the genotype CCB 1 of cluster VII was found superior for 2.5 per cent span length (38.55 mm) and genotype suvin of cluster IX for fibre strength (35.40 g/tex). The genotype NDGB 44 of cluster I for highest micronaire value (4.9) and ICB 85 of cluster V for strength/ length ratio (0.98) were also observed.

TABLE 5: DESIRABLE GENOTYPES FOR THE IMPORTANT TRAITS OF COTTON

S. No Characters I II III IV V VI VII VIII IX X 1. 50 % flowering NDGB 67 ICB 238 ICB 165 ICB 180 ICB 85 ICB 171 ICB 235 ICB 173 Suvin - 2. Plant height NDGB 78 ICB 124 ICB 104 ICB 180 ICB 128 ICB 171 ICB 235 ICB 173 Suvin MCU 133. Symbodia NDGB 64 ICB 238 ICB 104 ICB 180 ICB 164 ICB 207 ICB 235 ICB 242 Suvin MCU 134. Bolls NDGB 41 ICB 238 ICB 165 ICB 172 ICB 137 ICB 169 ICB 235 ICB 242 Suvin MCU 135. Boll weight ICB 3 ICB 238 ICB 104 ICB 180 ICB 87 ICB 207 ICB 235 ICB 242 - MCU 136. Lint index NDGB 64 ICB 238 ICB 104 ICB 180 ICB 87 ICB 207 CCB 1 ICB 242 - MCU 137. Seed index NDGB 64 ICB 238 ICB 104 ICB 180 ICB 85 ICB 207 ICB 235 ICB 242 Suvin MCU 138. GOT % NDGB 48 ICB 238 ICB 165 ICB 180 ICB 87 ICB 207 CCB 1 ICB 242 - MCU 139. Seed cotton

yield NDGB 41 ICB 124 ICB 104 ICB 242 ICB 85 ICB 207 ICB 235 ICB 242 - MCU 13

10 Lint yield NDGB 41 ICB 124 ICB 104 ICB 172 ICB 85 ICB 207 ICB 235 ICB 242 - MCU 1311. 2.5% length NDGB 80 ICB 124 ICB 165 ICB 180 ICB 128 ICB 207 CCB 1 ICB 173 Suvin - 12. Strength ICB 61 ICB 124 ICB 165 ICB 180 ICB 85 ICB 171 ICB 235 ICB 173 Suvin - 13. Micro value NDGB 44 ICB 124 ICB 104 ICB 172 ICB 85 ICB 207 CCB 1 ICB 242 - MCU 1314. S/L ratio NDGB 62 ICB 238 ICB 165 ICB 180 ICB 85 ICB 171 ICB 235 ICB 242 Suvin MCU 13

Based on the present study of genetic divergence and its component analysis, it can be concluded that inter crossing among the genotypes of genetically diverse clusters showing superior mean performance may be helpful for obtaining desirable segregants with higher yield and better fibre quality. The genotypes, NDGB 41, NDGB 64 and ICB 3 of cluster I; ICB 104 of cluster III; ICB 180 of cluster IV and

Assessment of Genetic Diversity for Improved Fibre Quality Traits in G. barbadense Accessions 157

ICB 85, ICB 137 of cluster V expressed superiority for more than two characters. They may be utilized as parents in hybridization programme for obtaining desirable combinations. It is also evident that cross combinations between the genotypes falling in cluster X and V; X and VI; and IV may be most compatible considering the high inter- cluster distances among them for getting inter specific hybrids(G.hirsutum X G. barbadence). Incase of G. barbadence accessions, cluster IX and V; IX and VI; VII and V; VI and V for getting desirable combinations based on the high inter cluster distances among them.

Intra cluster distances, inter cluster distances, cluster mean for all the characters studied and cluster wise performance of all the genotypes suggest that the genotypes selected for improvement of yield and quality components were NDGB 41, ICB 85, NDGB 67, MCU 13, ICB 137, ICB 235, CCB1, NDGB 80 and ICB 128. The hybridization programme with the selected genotypes by considering inter cluster distances may produce high magnitude of heterosis or desirable segregants, which would be meaningful for improvement in yield and fibre quality traits.

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methods of clustering. J.Indian Soc.Cotton Improv.28:158-63. [2] Amudha, K., Raveendran, T.S. and Krishnadoss, D. 1997. Genetic diversity in coloured linted cotton varieties. Madras

agric. J. 84: 334-37. [3] Arunachalam,V. and Bandopadhyay, A. 1984.Limits to genetic divergence for occurrence of heterosis: Experimental

evidence from crop plants. Indian J.Genet. Plant Breeding 44: 548 -54. [4] Kulkarni, A.A., H.C.Nanda and Patil, S.G. 2011. Studies on genetic divergence in upland cotton (Gossypium hirsutum L.).

J. Indian Res. Dev.25 (1): 9-13. [5] Pushpam, R., Raveendran, T.S., Devasena, N. and Ravikesavan, R. 2004. Studies on genetic diversity in upland cotton

(Gossypium hirsutum L.). J.Indian Soc. Cotton Impro.29:80 -85. [6] Rao, C.R. 1952. Advanced Statistical Methods in Biometrical Research. John Wiley and Sond, New York. [7] Sambamurthy, J.S.V., Reddy, M.D. and Reddy, K.H.G.1995. Studies on the nature of genetic divergence in upland cotton

(Gossyoium hirsutum L.). Annals Agric.Rec.16: 307-210. [8] Singh, R.B. and Gill, S.S. 1984. Genetic diversity in upland cotton under different environment. Indian J. Genet. 44: 506-

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Genet. 28: 262–68. [10] Singh, V.V. and Singh, A.K.1984. Studies on genetic diversity in upland cotton. J. Indian Soc. Cotton Improv. 9: 41-45. [11] Sumathi, P. and Nadarajan, N.1994. Genetic divergence in upland cotton (Gossypium hirsutum L.) J. Indian Soc. Cototn

Improc. 3: 36- 42.

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World Cotton Research Conference - 5 .Session_1