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ACKNOWLEDGEMENTS

The Maize Technologists Association of India thankfully acknowledges the following scientists who spared their valuabletime for reviewing/editing the manuscripts during the year 2013.

Dr. A.K.Singh DMR, New Delhi

Dr. Bhupender Kumar DMR, New Delhi

Dr. C.M. Parihar DMR, New Delhi

Dr. K.S. Hooda DMR, New Delhi

Dr. Meena Shekhar DMR, New Delhi

Dr. Nirupma Singh DMR, New Delhi

Dr. Ramesh Kumar DMR, New Delhi

Dr. Shiva Dhar IARI, New Delhi

Dr. S.L. Jat DMR, New Delhi

Dr. Vinay Mahajan DMR, New Delhi

Dr. V.K. Yadav DMR, New Delhi

Dr. Y.V. Singh IARI, New Delhi

Mr. Yatish DMR, New Delhi

MAIZE JOURNALAn International Journal of Maize Research and Related IndustriesPublished by:Maize Technologists Association of IndiaDirectorate of Maize ResearchPusa Campus, New Delhi - 110 012

Volume 2, Number (1 and 2) , April and Ocotober 2013

Review Paper1. M.K. KHOKHAR, K.S. HOODA, S.S. SHARMA, VIMLA SINGH AND ANITA SAINI. Fusarium stalk rot:

a major threat to maize production in India

Research Papers7 S.S. SINHA, R.B. DUBEY AND LAKSHYA DEEP. Heterosis and combining ability for quality traits in

early maturing single cross hybrids of maize ( Zea mays L.)

14 K. SUMALINI AND G. MANJULATHA. Genetic divergence studies in maize germplasm (Zea mays L.)

19 SWETA DOSAD AND N.K. SINGH. Stability and adaptability of kernel carotenoids in maize

25 J.M. PATEL.Genotypic variability for morphological traits among land races in maize (Zea mays L.)

28 MRUTHUNJAYA C. WALI, UDAY KUMAR KAGE, H.L. NADAF, C.P. MANSUR AND S.I. HARLAPUR.Genetic diversity studies in newly derived inbred lines of maize (Zea mays L.)

33 DILIP SINGH, A.K. SINGH C.M. PARIHAR, S.L. JAT AND ASHOK KUMAR. Weed management inquality protein maize (Zea may L.) under rainfed conditions of southern Rajasthan

36 G. MANJULATHA. Evaluation of zinc fortified fertilizer in maize (Zea mays L.)

41 M. SHANTI, R. BALAJI NAIK, T. SHASHIKALA AND CH. CHIRANJEEVI. Forage production potential ofvarious maize cultivars grown for baby corn

45 K.H. PATEL, S.K. SINGH, A.S. BHANVADIA, P.M. PATEL AND S.M. KHANORKAR. Effect of tiedridging on soil moisture conservation and yield of maize under rainfed condition

49 R.V. HAJARI, J.B. PATEL, K.H. PATEL AND S.K. SINGH. Response of summer maize (Zea mays) toirrigation schedules and zinc levels under middle Gujarat conditions

53 V. SOBHANA AND ASHOK KUMAR. Effect of plant population and nutrient levels on periodical growthand yield of baby corn hybrids

57 P. LAKSHMI SOUJANYA, J.C. SEKHAR AND P. KUMAR. Maize grain losses due to Sitophilus oryzaeL. and Sitotroga cerealella (Oliv.) infestation during storage

Short Communications

60 V. BHARATHI, K. KANAKADURGA, R. SUDHAKAR AND L. KISHAN REDDY.Farmers participatoryresearch on chemical control of turcicum leaf blight disease in maize

63 V.K. YADAV, TUHINA VIJAY, P. SUPRIYA AND KP. SINGH. Constraints in scientific maize cultivation

66 Landmark Papers of Maize Research in 2013

67 Authors Guidelines

[April & October 2013] 1

Fusarium stalk rot: a major threat to maize production in India

M.K. KHOKHAR1, K.S. HOODA1, S.S. SHARMA, VIMLA SINGH1

AND ANITA SAINI2

Department of Plant Pathology, Rajasthan College of Agriculture,Maharana Pratap University of Agriculture and Technology, Udaipur-313001 (Rajasthan)

ABSTRACT

Fusarium is considered as a devastating fungal menace of the most prevalent fungus on maize, particularly inUSA, Europe, Africa, Asia and Australia. It causes Fusarium stalk rot on plants, which is considered as major threatto production of maize, accompanied by small losses to total wipeout of the crop. This disease is more prevalent inarea where water stress occurs after flowering stage of the crop. Owing to its soil borne infection pathway, fungicidalcontrol of Fusarium stalk rot is not effective. A number of quantitative trait loci have been identified which will helpto expedite breeding program against Fusarium stalk rot. Moreover, various chemical and biological control methodshave been developed, but major emphasis is on development of maize cultivars with genetic resistance to Fusariumstalk rot for environment friendly control of the disease.

Sustainable maize cultivation is continuouslychallenged by diseases that cause quantitative andqualitative losses in yield. Apart from abiotic stresses anumber of fungal, viral and bacterial pathogens havebeen reported causing different diseases in maize (Payakand Sharma, 1980). Fusarium Stalk Rot (FSR), RajasthanDowny mildew, Maydis leaf blight, Banded leaf andsheath blight, Curvularia leaf spot, Brown stripe Downymildew and Turcicum leaf blight are major diseases ofmaize. Among these diseases of maize Fusarium stalkrot of maize is caused by Fusarium verticillioides(Saccardo) Nirenberg (= Fusarium moniliforme(Sheldon), was first reported from United States ofAmerica by Pammel in 1914 as a serious root and stalkdiseases. Later Valleau (1920) indicated that Fusariummoniliforme was a primary cause of root rot and stalk rotof maize. Subsequently this disease has also beenreported from several countries like Canada (Conner,1941), U.K. (Butler, 1947), Hungary (Podhradszky, 1956),North America (Kucharek and Kommedahl, 1966), Russia(Ivaschenko, 1989) and China (Wu et al., 1973). In IndiaFusarium stalk rot was first reported from Mount Abu,Rajasthan (Arya and Jain, 1964). Fusarium stalk rot wasobserved in the plant age group of 55 to 65 days whichcoincides with tasselling and silking and immediatelyfollowed grain formation stage. At these stages the stemreserves are depleted and most of the carbohydrates are

Corresponding author Email: [email protected] of Maize Research, Pusa Campus, New Delhi-110012 2G.V.M.G.C. Sonipat (Haryana)

translocated to developing sinks and stalks arepredisposed to the fungi (Desai et al., 1992).

DistributionStalk rot is one of the most devastating soil-borne

diseases of maize, occurring in all continents of the world,including USA (Koehler, 1960), Europe (Ledencan et al.,2003), Africa (Chambers, 1988), Asia (Lal and Singh, 1984),and Australia (Francis and Burgess, 1975). In India, thedisease is prevalent in most of the maize growing areas,particularly in rainfed areas viz., Jammu and Kashmir,Punjab, Haryana, Delhi, Rajasthan, Madhya Pradesh,Uttar Pradesh, Bihar, West Bengal, Andhra Pradesh, TamilNadu and Karnataka, where water stress occurs afterflowering stage of the crop (Singh et al., 2012).

Impact of diseaseThe stalk rot usually occurs after flowering stage

and prior to physiological maturity, which reduces yieldsin two ways: (i) affected plants die prematurely, thereby,producing lightweight ears having poorly filled kernelsand (ii) plants with stalk rot easily lodge, which makesharvesting difficult, and ears are left in the field duringharvesting (Singh et al., 2012). Stalk rot reduces maizeyield directly by affecting the physiological activity ofthe plants and finally results in lodging, which is themain cause of economic losses (Ledencan et al., 2003).

Lal et al., (1998) reported that incidence of Post FloweringStalk Rot complex (Charcoal rot, Fusarium stalk rot, Latewilt) varying from 5 to 40 per cent at different parts ofthe country. The annual loss due to maize diseases inIndia was estimated to the tune of 13.2 to 39.5% (Payak

Maize Journal 2 (1&2): 1-6 (April & October 2013)

2 [Vol. 2. No. 1 & 2]

and Sharma 1985). The disease was reported to cause areduction of 18.7% in cob weight and 11.2% in 1000-grain weight in the infected plants (Cook, 1978). Thedisease incidence ranged from 10 to 42% in Karnataka(Harlapur et al., 2002). Hooker and Britton (1962)estimated the reduction in grain weight by 5-20 per centwhereas, the estimated loss due to FSR has been reportedas 38% in total yield (AICRP, 2009).

Associated pathogensAs different species of pathogens have been

isolated from diseased maize stalks in different parts ofthe world, therefore, it appeared to be a complex disease(Chambers, 1987). Among the variety of pathogens,Fusarium is considered as a devastating fungal menaceof the most prevalent fungus on maize. Reports ofsurveys conducted in African countries showedFusarium as the most prevalent fungus on maize (BabaMoussa, 1998). Doko et al., (1996) reported Fusariumverticillioides as the most frequently isolated fungusfrom maize and maize-based commodities in France, Spainand Italy. Likewise, Orsi et al., (2000) found Fusariumverticillioides as the predominant species on maize inBrazil. Dorn et al., (2009) surveyed the prevalence ofFusarium species and its impact between the north andthe south regions of Switzerland and between kernel andstem piece samples. Several species of Fusarium havebeen reported to cause stalk rots like, Fusariumsubglutinans (Fusarium semitectum), Fusariumavenaceum , Fusarium sulphurcum , Fusariumacuminatum, Fusarium roseum, Fusarium merismoides,Fusarium nivale and Fusarium solani (Rintelen, 1965,Kommedahal et al., 1972, Nur Ain Izzati et al., 2011). InIndia, so far only Fusarium moniliforme and Fusariumsemitectum are reported to be widespread in WesternUttar Pradesh, Punjab and Rajasthan (Lal and Diwivedi,1982).

Macrocondia of the pathogen, Fusariummaniliforme. are hyaline, curved near the tips, three tofive septate and 2.5-5 X 15-60 µm. Micro conidia areabundant single celled, 2-3 X 5-12 µm and borne in chains.Conidiophores are unbranched with branchedmanophialids (Leslie & and Summerell, 2006).

SymptomsThe disease becomes apparent when the crop enters

senescence phase and severity increases during grainfilling stage. The stalk rot symptoms are observed duringpost flowering and pre-harvest stage (Lal and Singh,1984). The rotting extends from infected roots to the stalkand causes premature drying, stalk breakage and eardropping, thus significantly reducing maize yields(Colbert et al., 1987). The disease causes internal decayand discoloration of stalk tissues, directly reducing yield

by blocking translocation of water and nutrients, thusresulting in death and lodging of the plant (Dodd, 1980).Symptom development depends on several stress factors,including an excess or lack of moisture, heavy andcontinuous cloudiness, high plant density, foliardiseases, and corn borer infestation (Parry et al., 1995).

Factors affecting development of Fusarium stalk rotTemperature may be one factor that determines the

extent of invasion of the stalk rot fungi of maize (Williamsand Munkvold, 2008). Fusarium verticillioides is morecommon in regions with hot and dry growing conditions(Doohan et al., 2003), especially before or duringpollination (Pascal et. al., 2002). Reid et al., (2002)observed that hot and dry conditions, especially at maizesilking stage predisposes the plants to infection byFusarium moniliforme and Fusarium proliferatum.Williams and Munkvold (2008) reported the role of hightemperatures in promoting systemic infection of maizeby Fusarium verticil l ioides , but plant-to-seedtransmission may be limited by other environmentalfactors that interact with temperature during thereproductive stages.

Higher temperature reduces the time between wiltingand lodging because heat increases the metabolic rateof fungi. After flowering, a major shift in carbohydrateflow towards the ear reduces the availability to thetissues resulting in senescence of root cells. Hence,insufficient water is moved to the leaves to meet thedemands of transpiration causing the wilting of plants.This causes premature death that always precedes stalkrot. Dead rind tissues are invaded by other fungi likeFusarium, Diplodia, Gibbrella, Colletotrichum,Macrophomina etc. Cellulase and pectinases enzymesfrom these fungi further weaken the stalk tissues (Dodd,1980).

The water stress at flowering and high soiltemperature help in increasing of the magnitude of thestalk rot symptoms at post flowering stage of maize crop(Smith and McLaren, 1997). The PFSR is more severeunder moisture stress condition after flowering (Kumarand Shekhar, 2005). Schneider et al., (1983) observed thatpre-tasselling moisture stage resulted in higher stalk rotincidence compared to moisture stress at post pollinationand grain filling stages. Mews et al., (1988) opined thatpre-tassel moisture stress reduced the stalk rot duringlater season by reduced photosynthetic sink becausethe plants are subjected to the highest moisture stressand did not produce any grains.

Soil texture affected the incidence of Fusariummoniliforme on maize when it was grown alone orintercropped with cowpeas and soybeans. Diseaseincidence was greater in sandy soil than in loam or clay

KHOKHAR ET AL


soils (Mohamed, 1991). The influence of climatic factorson Fusarium caused complications as they can causedisease complex infections and there are numerousreports on how species differentially respond to differentenvironmental variations, particularly temperature andhumidity (Doohan et al., 1998).

In general, stalk rot incidence and severity increasewith increased fertility. There is evidence that potassiumfertilizers reduces the severity of stalk rot and thatnitrogen fertilizers, especially if in excess compared withpotash, increases the severity of stalk rot (Abney andFoley 1971). A balanced and continuous nitrogen supplyhelps to explain the reduction of stalk rot with the use ofnitrification inhibitors such as 2-chloro-6-(trichloromethyl) pyridine (nitrapyridin) when mixed withanhydrous ammonia (White et al.,1978). Potassium isinvolved in stomatal functions as well as metabolicpathways. When plants are deficient in potassium, thephotosynthesis rate is lower and may result in pithsenescence. Hence, maintaining a sufficient supply ofpotassium to prevent lodging needs more attention inmaize hybrids. The response to phosphorous varies withthe season, cultivar and the pathogen while, higher levelof phosphorous does not decrease stalk rot severityhowever, it seems to afford some protection against thestalk rot (Thayer and Williams, 1960).

Disease cycleThe fungus, Fusarium moniliforme survives on

crop residue in the soil or on the soil surface (Nyvall andKommedahl, 1970). Under favorable condition, it mayinfect roots as well as stalk (Lipps and Deep, 1991).Fusarium moniliforme may be present throughout thelife cycle of the plant, originating from infected seed(Headrick and Pataky, 1990).

Genetics of resistance to FSROwing to its soil borne infection pathway, fungicidal

control of Fusarium stalk rot is not effective.Alternatively, discovery and utilization of resistancegenes to improve maize tolerance to stalk rot is a costeffective and environment friendly approach to reducethe grain yield loss. Resistance to post flowering stalkrot disease involves several physiological,morphological and functional traits. Maize stalk strengthis determined by two main factors, the mechanicalstructure of the stalk and abiotic stress factor (Singh etal., 2012). The degree of stalk rot infection dependsgreatly on environmental factors, the genotype andenvironment interaction (GxE) and the resistance of thegiven maize genotype to the pathogens (Szoke et al.,2007). Ledencan et al., (2003) have showed the resistanceof maize inbreds and their hybrids to natural and artificial

stalk infection with Fusarium spp. and compared theresponse of inbreds and their test cross hybrids to thepathogen. Inbreds and hybrids differed significantly inresistance and infection types and disease scores ofhybrids were generally lower than that of inbreds.

A large body of efforts is being diverted towarddevelopment of biotechnological tools for identificationand tagging of genes conferring resistance to PFSR. Theidentification of quantitative trait loci (QTL) forresistance to PFSR is considered as an efficient tool indevelopment of disease resistant maize hybrids. A majorgene for Fusarium stalk rot resistance has been reportedon chromosome 6 (Yang et al., 2004). Studies have alsoindicated that resistance to stalk rot is quantitativelyinherited and controlled by multiple genes with additiveeffects. Pe et al., (1993) identified five resistancequantitative trait loci (QTL) to Fusarium stalk rot, locatedon chromosome 1, 3, 4, 5, and 10. Yang et al., (2010)detected two loci QTLS qrfg1 and qrfg 2, conferringresistance to Fusarium stalk rot. Report from Egyptindicated that resistance to Fusarium stalk rot wascontrolled by two genes and was dominant in expression.These two genes were located in the short arm ofchromosome 7 and long arm of 10. Resistance toFusarium stalk rot in inbred 61 C was also attributed totwo genes. Source of resistance against Fusarium stalkrot of maize identified were CM 103, CM 119, CM 125, CI21 E, CML 31, 77, 79, 85, 90 and CML 381 (Kumar andShekhar, 2005).

Disease managementSince the stalk rot of maize is a complex disease

involving more than one organism, it is very difficult tomanage the disease with single control measure. Hence,efforts are needed to explore the feasibili ty ofcombination of various control measures for integratedmanagement of stalk rots (Kulkarni and Anahosur, 2011).Trivedi et al. (2002) evaluated systemic and non systemicfungicides viz., bavistin, dithane M-45, blitox 50, hexacap-75, TMTD, topsin-M, and apron-35SD against Fusariumpallidoroseum causing post flowering stalk rot of maizein vitro at different concentration viz. 100, 250, 500, and1000 ppm. All the fungicides completely inhibited thegrowth at 500 and 1000 ppm, though Topsin-M recordedthe highest growth inhibition (70% and 98%) at lowconcentrations i.e. 100 and 250 ppm, respectively.Chandra et al. (2008) evaluated two fungicides viz.,tebuconazole and thiabendazole for their ability to inhibitthe growth of toxigenic Fusarium verticillioides andfound that tebuconazole 5% aqueous solutioneffectively reduced ear rot disease and fumonisinsaccumulation to a maximum extent compared to otherfungicides.

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Bioagents are useful for the effective managementof soil borne pathogen propagules like chlamydosporesof Fusarium species. The isolation and identification ofeffective bio control agents against PFSR is urgentlyrequired for use in integrated disease management. Fordecades, various Trichoderma species had shownantagonistic activities against many pathogens, both invitro and in vivo (Howell, 2003). Successful growthsuppression of Fusarium verticillioides (in vitro) andits subsequent significant exclusion from internodes ofmaize (Zea mays) stem in the field (in vivo) by strains ofTrichoderma pseudokoningii had been reported bySobowale et al., (2005). Shekhar and Kumar (2010)reported the native isolate of Trichoderma harzianumresulted in good plant health and reduced post-floweringstalk rot of maize. Patil et al., (2003) reported the seedtreatment with Trichoderma harzianum (4g/kg seed)along with soil application of castor or neem cake (250kg/ha), 15 days prior to sowing gave an effective controlto stalk rot disease and gave better cost benefit ratio.

Integrated Disease ManagementIntegration of biological and chemical control seems

to be a promising way of controlling many pathogenswith minimum interference in the biological equilibriumin soil (Papavizas, 1973). Since soil is highly complexand biologically active substrate through which thefungicide act against fungi, fungitoxicants often giveviable success in controlling seedling disease of cropsin diverse agro-climatic regions of the world (Khan etal., 2008). The use of fungicides and tolerant genotypeshas been reported to be effective method to manage stalkrot of maize which holds some promise.

Reported that application of farm yard manure andneemcake along with Trichoderma harzianum 15-20 daysbefore sowing with two additional irrigation at tassellingand silking stage reduced the diseased from 70.08 to13.24 per cent (Kulkarni and Anahosur 2011) . Thori etal., (2011) reported that maximum germination (90%) withminimum mortality (0.0 and 2.5%) at 35 and 70 DAS andleast percent disease index (PDI) of 23.2% was recordedby integration of Trichoderma viride (drenching), withbavistin seed treatment, followed by tebuconazole (ST)+ Trichoderma viride (drenching). Among the individualtreatments, seed treatment with bavistin andTrichoderma viride drenching showed good effects andresulted in 75% germination with 3.3% and 7.1% mortalityafter 35 and 70 day after sowing followed by 72.5% intebuconazole seed treatment. Integration of plantresistance with these components was useful forreducing the losses caused by PFSR pathogen.

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Rintelen, J. (1965). Fusarium culmorum and Fusarium Artenals Erreger einer Stengelfaule an reifenden Maispflanzen.Z.Pflanzenkr (Pflanzenpathol) Pflanzenschutz. 72:89-91.

Schneider, R. W. and Pendery W. E. (1983). Stalk rot of corn:mechanism of predisposition by in early season water stress.Phytopathology 73: 863-71

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Singh, N., Rajendran A., Meena S. and Mittal, G. (2012).Biochemical response and host-pathogen relation of stalkrot fungi in early stages of maize (Zea mays L.) AfricanJournal of Biotechnology. 11(82): 14837-14843.

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KHOKHAR ET AL


Heterosis and combining ability for quality traits in early maturing singlecross hybrids of maize ( Zea mays L.)

S. S. SINHA, R. B. DUBEY AND LAKSHYA DEEP

Department of Plant Breeding and Genetics, Rajasthan College of Agriculture,Maharana Pratap University of Agriculture and Technology, Udaipur 313001

ABSTRACT

A set of 15 diverse yellow seeded inbred lines were crossed with three testers viz., ‘CM-111’, ‘CM-137’ and ‘CM-138’ in line x tester mating design and developed 45 Single Cross Hybrids of maize. These 45 hybrids and 18 parentallines along with three standard checks viz., ‘Mahi Kanchan’, ‘Navjot’ and ‘PEHM-2’ were grown in randomized blockdesign with three replications. Data were recorded on oil content, starch content, protein content and grain yield perplant. Heterosis over mid parent, better parent and standard check was observed in various hybrids for all the traits.Both additive and non-additive gene effects were present in the material under study. However, the ratio of additiveand non-additive genetic variance revealed that there was preponderance of non-additive gene action in the expressionof all the traits under study. Among the parents, the inbred lines L6 and L12 were found as good general combinersfor oil content; while inbred line L11was found as good general combiner for starch and protein content. The hybridsL5 x T3 and L6 x T3 were exhibited highest standard heterosis and per se performance for oil and protein contentrespectively. In general, close association between sca effects and standard heterosis was observed among the besthybrids identified on the basis of sca effects for oil content, starch content, protein content and grain yield per plant

Key words: Combining ability, Heterosis, Quality traits, Zea mays L.

Maize is one of the prominent cereals at global leveldue to multiple uses ranging from human and animal feedto several industrial applications. In India, limited effortshave been carried out to exploit the potential of maizefor quality traits like high oil, protein and starch contentin maize grains. Available high oil species/strains in USAhave about 18-20 percent oil on whole kernel basis(Jugenheimer, 1961). Most of the oil is present in thegerm of seed (Earle et al., 1946). Germ of ordinary corncarries about 30 percent oil whereas the germs of highoil strains have been reported to contain as much as 50percent oil. There is a positive correlation between oilcontent in germ oil and size of germ. Strains having highoil content have a larger germ and reduced endospermsize. Concentrated research on this aspect will providehybrids that are nutritionally superior and industriallyimportant with respect to high protein, oil and starchcontent. The present investigation was therefore,undertaken to assess the heterosis and combining abilityfor quality traits so as to identify the best combiner linesand suitable heterotic single cross hybrids with respectto oil, starch and protein content.

MATERIALS AND METHODS

Fifteen diverse early maturing yellow seeded inbredlines (Table 1) of maize were crossed with three testersviz., ‘CM-111’, ‘CM-137’ and ‘CM-138’ in line x testermating design to generate 45 single cross hybrids ofmaize. These 45 hybrids, 18 parents along with threestandard checks viz., ‘Mahi Kanchan’, ‘Navjot’ and‘PEHM-2’ were grown in randomized block design withthree replications, in a single row plot of 5 m lengthhaving 60 cm x 25 cm crop geometry. Data were recordedon quality traits viz., oil content, starch content, proteincontent and grain yield per plant on ten randomlyselected competitive plants. The total oil content of dryseeds was determined by Soxhlet Method (A.O.A.C.,1965), starch content by Anthrone reagent Method(Morris 1948) and protein content was estimated byMicro-Kjeldhal’s method (Kjeldhal, 1883). Heterosis overmid-parent (MP) heterobeltiosis or better parent (BP) andstandard- check (SC) were calculated as per standardprocedure (Meredith and Bridge, 1972) and combiningability analysis was carried out as per procedure givenby (Kempthrone, 1957).

Corresponding author Email: [email protected]


8 [Vol. 2. No. 1 & 2]

Table 1. Inbred lines used as parents

Code Pedigree Source population/pool Origin Seed Colour

L1 G18SEQC2-F141-2-2-1-1-1-2-#-#-2-1 DMR*, Hyderabad DMR* YellowL2 G18SEQC2-F141-2-2-1-1-1-2-#-#-2-2 DMR*, Hyderabad DMR* YellowL3 POB DIPLODIA C4-1 DMR*, Hyderabad DMR* YellowL4 POB DIPLODIA C4-2 DMR*, Hyderabad DMR* YellowL5 POB DIPLODIA C4-3 DMR*, Hyderabad DMR* YellowL6 POB DIPLODIA C4-4 DMR*, Hyderabad DMR* YellowL7 CML 50POB78AC-8078-2-4-1-ff-#-#-X-1-1 DMR*, Hyderabad CIMMYT YellowL8 CML53POOL23C20MH268-1-2-B-3-1-ff-#-#-X-1-2 DMR*, Hyderabad CIMMYT YellowL9 SINTOBCOTSR-3-1-2-3-2-BBB-####-BBB-1 DMR*, Hyderabad DMR* YellowL10 P24C5HC227-1-2-1-1-1-1-###-BB-f-BBB-X-1 DMR*, Hyderabad DMR* YellowL11 (24F26*24F34)-1-2-2-3-BBB-3B-#-BBBBB-X-5-1 DMR*, Hyderabad DMR* YellowL12 SAMTSR-23-3-2-3-5-BBBB-#*4-BBB-1 DMR*, Hyderabad DMR* YellowL13 P5 G15C22MH131#-1-3-4-1-1-B-BB-1 DMR*, Hyderabad DMR* YellowL14 S3 X AC-1-2 DMR*, Hyderabad DMR* YellowL15 S3 X AC-1-3 DMR*, Hyderabad DMR* Yellow

TestersT 1 CM-111 DMR*, Hyderabad DMR* YellowT 2 CM-137 DMR*, Hyderabad DMR* YellowT 3 CM-138 DMR*, Hyderabad DMR* Yellow

*Winter Nursery, Directorate of Maize Research, Amberpet Farm, Hyderabad

Table 2. Analysis of variance for quality traits and yield in maize.

Source of variation d.f. Mean square

Oil Content Starch Content Protein Content Grain yieldper plant

Replication 2 0.036** 0.008 0.392 71.847**Genotypes 62 1.252** 21.439** 6.504** 410.38**Parents 17 0.997** 26.439** 1.521** 3666.67**Crosses 44 1.373** 19.286** 4.026** 190.81**Parents v/s crosses 1 0.262** 31.140** 200.25** 10815**Error 124 0.001 0.015 0.276 8.351

*, ** Significant at 5% and 1% respectively

RESULTS AND DISCUSSION

Analysis of variance for experimental design (Table 2)revealed the presence of significant amount of variabilityamong parents and crosses for all the traits. Further,Analysis of variance for combining ability revealed thatmean square due to lines, testers and lines x testers weresignificant for all the traits. The ratio of was 62sca/62gcawas greater than one for all the traits. This indicated thepreponderance of non-additive variance in the expressionof traits under study (Table 3). Similar results were alsoreported by earlier workers (Back et al., 1990; Kumar et al.,1999 and Dadheech and Joshi, 2007).

Oil contentMid-parent heterosis and heterobeltiosis are important

parameters as they provide information about presence of

dominance and over-dominance type of gene action in theexpression of various traits. The significant relativeheterosis for oil content was exhibited by 19 hybrids with arange varying from 1.33 (L11 x T1) to 42.46 % (L5 x T3).Thehighest positive significant relative heterosis for oil contentwas expressed by the hybrid L5 x T3 (42.46 %). Thepresence of relative heterosis for oil content indicated thatthe genes with positive effect were dominant. The positivesignificant heterobeltiosis was observed in 12 hybrids. Thehighest positive significant heterobeltiosis was depictedby hybrid L5 x T3 (29.56 %). The presence of heterobeltiosisindicated that over-dominance played an important role inthe expression of oil content. The positive significantheterosis over better parent for oil content was also reportedby earlier workers (Kumar et al., 2003 and Dubey et al.,2009).The positive significant economic heterosis was

SINHA ET AL


Table 3. Analysis of variance (mean squares) of combing ability for various traits in maize

Source d.f. Oil content Starch content Protein content Grain yield per plant

Replication 2 0.036349** 0.008676 0.39201 71.847**

Cross 44 1.3725** 19.286** 4.0262** 190.81** Line 14 0.86699** 23.197** 4.9366** 224.06** Tester 2 3.7096** 42.578** 6.0225** 696.94** Line x Tester 25 1.4583** 15.667** 3.4285** 138.03**

Error 88 0.001859 0.00885 0.30712 9.3513

ó2L -0.0657 0.83663 0.16757 9.5593

ó2T 0.050029 0.59802 0.057645 12.42

ó2gca -0.0043699 0.1843 0.030442 2.6878

ó2sca 0.48548 5.2194 1.0405 42.892

ó2sca/ ó

2gca 111.096 28.32 34.179 15.957

*, ** Significant at 5% and 1% respectively

expressed by 12 hybrids with a range of 1.97 (L3 xT3) to28.05 % (L5 x T3). The highest positive significant economicheterosis for oil content was exhibited by hybrid L5 x T3(28.05 %). The positive significant economic heterosis foroil content was also reported by various workers viz., (Deviand Pradhan, 2004). The highest positive significant for allthe three types of heterosis were exhibited by hybrids viz.,L5 x T3, L12 x T2, L1 x T3, L6 x T3 and, L12 x T3 (Table 4).Perusal of sca effects revealed that significant positivevalues were exhibited by 18 hybrids with a range varyingfrom 0.05 (L12 x T3) to 1.34 (L1 x T3). Among the above 11hybrids which showed all types of heterosis, except L3 xT3 and L6 x T3 all of them exhibited significant positive scaeffects. Further, hybrids L13 x T1 and L1 x T3 also exhibitedrelative heterosis, heterobeltiosis and economic heterosisfor grain yield/plant along with showing high mean valuesfor both oil content and grain yield. Hybrid L13 x T1 was acombination of good x poor parents for both oil contentand grain yield/plant while L1 x T3 was a combination ofpoor x good parents for oil content and good x good parentsfor grain yield/plant. Hybrid L13 x T1 also showedsignificant sca effects for grain yield/plant.

Starch contentHybrid L11 x T2 was the best performer (67.74 %) for

starch content. Significant relative heterosis was exhibitedby 29 hybrids with a range of 0.50 (L13 x T2) to 14.61 % (L8x T1). Hybrid L1 x T2 (11.42 %) depicted the highest valueamong 21 hybrids showing positive significantheterobeltiosis (Table 5). Significant positive value ofeconomic heterosis was observed in 11 hybrids with a rangeof 0.32 (L7 xT1) to 5.41 % (L11 x T2). 9 hybrids viz., L7 x T1,L8 x T1, L1 x T2, L7 x T2, L10 x T2, L11 x T2, L14 x T2, L10 xT3 and L11 x T3 exhibited all the three types of heterosis forstarch content. General combining ability effects (Table 8)revealed that all of these hybrids involved at least onegood combiner parent. Estimates of sca effects showedthat except L7 x T1, all of them exhibited positive and

significant values. Among these hybrids, L7 x T2 and L10 xT3 also showed all the three types of heterosis, significantpositive sca effects along with high and highest meanvalues, respectively for grain yield/plant. Hybrid L7 x T2was a combination of good x average parents for grain yield/plant and good x good parents for starch content while L10x T3 was a combination of good x poor parents for starchcontent and good x good parents for grain yield/plant.

Protein contentHighest protein content was recorded in hybrid L6 x

T3 (11.84%). Significant relative heterosis was exhibited by42 hybrids with a range of 9.93 (L2 x T1) to 61.73 % (L13 xT3). Hybrid L13 x T3 (61.73 %) depicted the highest valueamong 37 hybrids showing positive significantheterobeltiosis (Table 6). Significant positive value ofeconomic heterosis was observed in 30 hybrids with a rangeof 9.84 (L4 xT1, L15 xT1, L8 xT2, L15 xT2 and L8 xT3) to31.90 % (L6 x T3). Overall 30 hybrids showed relativeheterosis, heterobeltiosis and economic heterosis forprotein content. Out of these 30 hybrids, 11 hybridsexhibited significant sca effects for protein content namely,L3 xT1, L5 xT1, L9 xT1, L10 xT1, L1 xT2, L5 xT2, L12 xT2, L14xT2, L6 xT3, L11 xT3 and L13 xT3. Among above hybrids,L1 xT2, L12 xT2, L6 xT3, L11 xT3 and L13 xT3 also exhibitedrelative heterosis and heterobeltiosis for grain yield/plantalong with high mean values for protein content and grainyield/plant. Except L1 xT2 and L12 xT2, remaining threehybrids involved at least one good combiner parent forboth protein content and grain yield/plant.

Grain yield/plantThe best yielding hybrid was L10 xT3 (80.67 g/plant).

Relative heterosis for grain yield/plant with a range varyingfrom 7.20 (L8 x T2) to 95.58 % (L7 x T3) was found in 37hybrids. Significant positive heterobeltiosis was observedin 29 hybrids depicting the range of 13.87 (L13 x T3) to72.86 % (L10 x T3). Regarding economic heterosis, 6 hybrids

HETEROSIS AND COMBINING ABILITY OF SINGLE CROSS HYBRIDS OF MAIZE

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* Si

gnifi

cant

at 5

% a

nd 1

% re

spec

tivel

y; x

-indi

cate

no

hete

rosi

s or

no

valu

e

Tabl

e 6.

Sup

erio

r hyb

rids

iden

tifie

d on

the

basi

s of

rela

tive

hete

rosi

s, h

eter

obel

tiosi

s an

d ec

onom

ic h

eter

osis

for g

rain

yie

ld/p

lant

with

rela

tions

hip

betw

een

oil,

star

ch a

nd p

rote

in c

onte

nt in

mai

ze

Hyb

rid/p

aren

t/che

ck

Het

eros

is %

P

er s

e

Prot

ein

Oil

cont

ent

Star

chG

rain

yie

ld/

Prot

ein

cont

ent

Oil

cont

ent

Star

ch c

onte

ntG

rain

yie

ld/p

lant

cont

ent

cont

ent

plan

t(%

)(%

) (%

)(g

)

Rela

tive

hete

rosi

sL7

x T

395

.58*

*-8

.07*

*9.

47**

60.8

8**

73.6

74.

7363

.00

11.3

5L7

x T

287

.04*

*-3

4.88

**13

.93*

*41

.31*

*77

.00

3.32

66.4

310

.15

L10

x T3

84.0

3**

-8.7

0**

4.52

**35

.39*

80.6

73.

8664

.54

10.1

5L2

x T

377

.29*

*-1

6.25

**-6

.21*

*19

.91*

*67

.67

3.75

57.0

18.

33L6

x T

372

.50*

*19

.47*

*-5

.65*

*56

.41*

*69

.00

4.83

57.4

911

.84

Het

erob

eltio

sis

L10

x T3

72.8

6**

X0.

49**

21.8

5**

80.6

73.

8664

.54

10.1

5L7

x T

357

.86*

*X

6.30

**52

.42*

*73

.67

4.73

63.0

011

.35

L1 x

T3

50.7

1**

24.3

2**

6.47

**42

.60*

*70

.33

5.79

64.3

410

.15

L6 x

T3

47.8

6**

19.4

7**

-5.6

5**

56.4

1**

69.0

04.

8357

.49

11.8

4L2

x T

345

.00*

*X

X15

.21*

*67

.67

3.75

57.0

18.

33Ec

onom

ic h

eter

osis

L10

x T3

24.1

0**

X0.

43**

13.0

7**

80.6

73.

8664

.54

10.1

5L7

x T

218

.46*

*X

3.37

**13

.11*

*77

.00

3.32

66.4

310

.15

L7 x

T3

13.3

3**

3.58

**X

26.4

4**

73.6

74.

7363

.00

11.3

5L1

x T

38.

21**

0.12

13.1

1**

8.21

*70

.33

5.79

64.3

410

.15

L13

x T1

8.21

**4.

67**

X2.

0870

.33

4.78

62.7

19.

16

*, *

* Si

gnifi

cant

at 5

% a

nd 1

% re

spec

tivel

y; x

-indi

cate

no

hete

rosi

s or

no

valu

e


12 [Vol. 2. No. 1 & 2]

Table 8. Estimates of gca effects for various traits in inbred lines of maize

Line/tester Oil content Starch Content Protein Content Grain yield/plant

L1 -0.03* 2.25** -0.10 5.13**L2 -0.09** -2.39** -1.70** -2.32*L3 0.20** -1.13** -0.78** -5.65**L4 -0.09** 0.12** -0.65** 5.90**L5 0.35** 0.06 -0.29 -6.87**L6 0.38** -1.97** 0.29 3.57**L7 -0.32 2.02** 0.87** 4.90**L8 0.10** -0.09** -0.14 -0.65L9 0.36** -1.84** 0.11 2.79**L10 -0.16** 0.70** 0.88** 4.01**L11 -0.32** 2.68** 0.53** -4.32**L12 0.38** -0.87** 0.23 -0.10L13 0.21** -1.42** 0.21 5.90**L14 -0.41** 0.50** 1.25** -3.65**L15 -0.55** 1.40** -0.28 -8.65**T 1 -0.03** 0.07** 0.02 -4.01**T 2 -0.27** 0.94** -0.38** 0.15

T 3 0.30 -1.00 0.36** 3.86**

*, ** Significant at 5% and 1% level, respectively

SINHA ET AL

Table 7. Superior hybrids identified on the basis of relative heterosis, heterobeltiosis and economic heterosis for grain yield/plant withrelationship between oil, starch and protein content in maize

Hybrid/parent/check Heterosis % Per se

Grain yield/ Oil Starch Protein Grain yield/ Oil Starch Proteinplant content content content plant (g) content (%) content (%) content (%)

Relative heterosis

L7 x T3 95.58** -8.07** 9.47** 60.88** 73.67 4.73 63.00 11.35L7 x T2 87.04** -34.88** 13.93** 41.31** 77.00 3.32 66.43 10.15L10 x T3 84.03** -8.70** 4.52** 35.39* 80.67 3.86 64.54 10.15L2 x T3 77.29** -16.25** -6.21** 19.91** 67.67 3.75 57.01 8.33L6 x T3 72.50** 19.47** -5.65** 56.41** 69.00 4.83 57.49 11.84

Heterobeltiosis

L10 x T3 72.86** X 0.49** 21.85** 80.67 3.86 64.54 10.15L7 x T3 57.86** X 6.30** 52.42** 73.67 4.73 63.00 11.35L1 x T3 50.71** 24.32** 6.47** 42.60** 70.33 5.79 64.34 10.15L6 x T3 47.86** 19.47** -5.65** 56.41** 69.00 4.83 57.49 11.84L2 x T3 45.00** X X 15.21** 67.67 3.75 57.01 8.33

Economic heterosis

L10 x T3 24.10** X 0.43** 13.07** 80.67 3.86 64.54 10.15L7 x T2 18.46** X 3.37** 13.11** 77.00 3.32 66.43 10.15L7 x T3 13.33** 3.58** X 26.44** 73.67 4.73 63.00 11.35L1 x T3 8.21** 0.12 13.11** 8.21* 70.33 5.79 64.34 10.15L13 x T1 8.21** 4.67** X 2.08 70.33 4.78 62.71 9.16

*, ** Significant at 5% and 1% respectively; x-indicate no heterosis or no value


ble

9. H

ybri

ds s

how

ing

high

er s

ca (

best

fiv

e) e

ffec

ts f

or o

il, s

tarc

h an

d pr

otei

n co

nten

t w

ith e

cono

mic

het

eros

is a

nd p

er s

e pe

rfor

man

ce

O

il co

nten

t

S

tarc

h C

onte

nt P

rote

in c

onte

nt

G

rain

yie

ld/p

lant

Hyb

rid

sca

Eco

.H

ybri

dsc

aE

co.

Hyb

rid

sca

Eco

.H

ybri

dsc

asE

co.

effe

ctH

et.

Per

seef

fect

Het

.Pe

r se

effe

ctH

et.

Per

seef

fect

Het

.Pe

r se

(g)

L 1 x

T 31.

34**

26.9

5**

5.79

L 1 x

T 13.

19**

2.35

**65

.78

L 1 x

T 21.

94**

26.4

4**

11.3

5L 10

xT 3

11.2

5**

24.1

0**

80.6

7

L 12 x

T 21.

03**

16.5

8**

5.32

L 12 x

T 12.

76**

0.48

**64

.57

L 12 x

T 21.

20**

21.9

8**

10.9

5L 7

x T 2

10.4

1**

18.4

6**

77.0

0

L 5 x

T 31.

01**

28.0

5**

5.84

L 5 x

T 22.

75**

3.94

**66

.79

L 5 x

T 31.

31**

31.9

0**

11.8

4L 14

xT 1

9.79

**-

63.6

7

L 2 x

T 20.

90**

3.58

**4.

73L 2

x T 1

2.58

**-

62.8

7L 2

x T 1

0.93

**30

.49*

*11

.71

L 3 x

T 28.

63**

-64

.67

L 11 x

T 10.

75**

0.44

4.58

L 11 x

T 12.

39**

-62

.87

L 11 x

T 10.

82**

16.3

4**

10.4

4L 13

xT 1

6.90

**8.

21**

70.3

3

*

Sign

ifica

nt a

t 5%

lev

el.

** S

igni

fican

t at

1%

lev

el


showed significant positive values over the best check‘Mahi Kanchan’ with a range of 7.69 (L4 x T1) to 72.86 %(L10 x T3) (Table 7). Among these six hybrids exhibitingeconomic heterosis, 4 hybrids namely, L4 x T1, L13 x T1, L7x T2 and L10 x T3 showed significant positive sca effectsand involved at least one good combiner parent.

On overall basis, Hybrid L1 x T3 [G-18 SEQC 2-F141-2-2-1-1-1-2-#-#-2-1 x CM-138] could be identified as the bestperforming hybrid as it not only exhibited significantpositive heterobeltiosis for all the traits but also showedsignificant and positive values of economic heterosis andsca effects for oil and protein content along with showingeconomic heterosis for grain yield/plant.

ACKNOWLEDGEMENTS

The authors are grateful to the Directorate of MaizeResearch, ICAR New Delhi, Director, Directorate ofResearch Maharana Pratap University of Agriculture &Technology, Udaipur, and Project Incharge AICRP on Maize,Rajasthan College of Agriculture, Maharana PratapUniversity of Agriculture & Technology, Udaipur,(Rajasthan) for providing all facilities to conduct theexperiment.

REFERENCES

A.O.A.C. (1965). Official methods for oil analysis for associationof Official Agricultural Chemists 10th Ed. Washington, D.C.

Dadheech,Amit and Joshi,V.N. (2007).Heterosis and combiningability for quality and yield in early maturing single crosshybrids of maize (Zea mays L.). Indian J. Agric. Res. 41(3):210-214.

Devi, T.R. and Pradhan, H.S. (2004).Combining ability andheterosis studies in high oil maize (Zea mays L.) genotypes.Indian J. Genet. 64: 323-324.

Dubey, R.B., Joshi, V.N. and Manish, Verma. (2009). Heterosisfor nutritional quality and yield in conventional and non-conventional hybrid of maize (Zea mays L.) Indian J. Genet.69(2) : 109-114.

Earle, F.R., Curtis, J.J. and Hubbard, J.E. (1946). Composition ofthe component parts of the corn kernel. Cereal Chem.23 (5):504-511.

Jugenheimer, R.W. (1961). Breeding for oil and protein contentin maize. Euphytica 10(2):152-156.

Kempthrone, O. (1957). An Introduction of Genetics Statistics,John Wiley and Sons Inc., New York.

Kjeldhal, J. Z. (1883).A new method for the determination ofnitrogen in organic bodies. Analytical Chemistry 22: 366.

Meredith, W.R. and Bridge, R.R. (1972). Heterosis and geneaction in cotton Gossypium hirsutum. Crop Sci. 21: 304-310.

Morris, D.L. (1948). Quantitative determination of carbohydratewith Derwood’s anthrone reagent. Science 107: 254-255.

14 [Vol. 2. No. 1 & 2]

Genetic divergence studies in maize germplasm ( Zea mays L.)

K. SUMALINI AND G. MANJULATHA

Agricultural Research Station, ANGRAU, Karimnagar 505 001

ABSTRACT

The genetic divergence among 249 germplasm lines of maize was assessed by D2 statistics based on nine parametersat Agricultural Research Station, Karimnagar. The germplasm lines were grouped into eleven clusters. Clusters I andII were the largest clusters with 73 and 79 genotypes, respectively. The highest inter cluster distance was observedbetween cluster X and XI followed by cluster V and XI indicating more variability in the genetic makeup of inbredsincluded in these clusters. Cluster V showed highest mean values for grain yield/plant and ear length. Cluster XI hadthe lowest mean values for plant height and ear height and these two characters showed maximum contributiontowards total divergence among different characters. Based on inter cluster distances, inter crossing among thegenotypes belonging to cluster V, IX, X and XI has the chance of getting high yielding hybrids with higher heterosis.

Key words: Cluster analysis, Genetic diversity, Maize

Hybrid maize has high yield potential than those ofsynthetics and composites (Pandey and Gardner, 1992;Vasal et al., 1995). In any crop improvement programme,assessment of genetic diversity is an essential pre-requisite for identifying potential parents forhybridization. Several studies on maize have shown thatcrosses between inbred lines from diverse stocks tendto be more productive than crosses of inbred lines fromthe same variety (Vasal, 1998). Saxena et al. (1998) alsoreported that manifestation of heterosis usually dependson the genetic divergence of the two parental lines. D2

statistics is a useful multivariate statistical tool foreffective discrimination among various genotypes on thebasis of genetic diversity (Murthy and Arunachalam,1966). The present investigation was undertaken with aview to estimate the nature and magnitude of geneticdiversity in maize germplasm and to identify divergentparents from distantly related clusters for futurehybridization.


The germplasm of about 249 diverse maize inbredlines was tested in a simple lattice design with tworeplications at Karimnagar during rabi 2011-12. Out of249 germplasm lines, 145 lines belong to CIMMYT,Hyderabad, 45 lines to Winter Nursery Centre, Directorateof Maize Research, Hyderabad, 33 inbred lines toKarimnagar and 22 drought tolerant lines to CIMMYT,

Mexico and are being maintained since 1996 at ARS,Karimnagar. Each genotype was grown in a single row of4 m length, spaced 75 cm apart with a 20 cm distancebetween plants within the row. One plant was kept perhill after thinning. Fertilizers were applied @ 120: 60: 60kg/ha of N, P2O5 and K2O, respectively. The otherintercultural operations were done timely to raise thecrop uniformly.

For plant height, ear height, ear length, ear girth,kernel rows/ear, kernels/ row, 100 kernels weight andgrain yield/plant observations were recorded on tenrandomly selected plants in each entry of replication.While the data relating to days to 50 percent silkemergence was recorded on whole plot basis. The meandata was analysed for genetic divergence usingMahalanobis D2 statistics (1936) and clustering ofgenotypes was done according to Tocher’s method asdescribed by Rao (1952).


The analysis of variance revealed highly significantdifferences among the genotypes for all the charactersindicating the existence of genetic variability among theexperimental material. Maximum coefficient of variationwas found in grain yield/plant, kernels/row and 100kernel weight. Hence, there is a scope for selecting highyield potential lines (Table 1). The D2 values ranged from0.00 to 40.13 and principal component scores alsoindicated a high degree of genetic diversity among the




genotypes. The germplasm lines of maize evaluated fordivergence was grouped into eleven clusters (Table 2).Cluster II was the largest having 79 germplasm linesindicating overall genetic similarity among themfollowed by the cluster I and cluster V comprising 73and 28 genotypes, respectively. The lowest singlegenotype was included in clusters IV, VII and IX.Clustering pattern of inbred lines under this study revealsthat the inbred lines showed considerable geneticdiversity among themselves by occupying elevendifferent clusters. Chen FaBo et al. (2007) confirmedthe findings.

The inter and intra cluster distance (D = sqrt D2)values were worked out from divergence analysis (Table3). The intra cluster distances were lower than the inter-cluster distances indicating heterogeneous andhomogeneous nature between and within groups,respectively. The maximum intra-cluster distance (D=

3.80) was observed in cluster X followed by cluster VIII(3.65) and cluster VI (3.57). The clusters IV, VII and IXhad only a single genotype and hence, minimum intracluster distance was observed.

The crosses involving parents from most divergentclusters are expected to manifest maximum heterosis andgenerate wide variability in genetic architecture. Thiswas further supported by an appreciable variationobserved for cluster means (Table 4).

The highest inter cluster distance (D=6.33) wasobserved between cluster X and XI followed by clusterV and XI (D=6.03), cluster IV and XI (5.64), cluster IXand X (D=5.61), cluster VI and X (5.41), cluster VIIand XI (5.40), cluster V and IX (5.29), cluster I and XI(5.28), suggesting more variability in genetic makeup ofthe genotypes included in the clusters X and XI. ClusterXI contains five drought tolerant genotypes with broad

Table 1. Mean, standard error and co-efficient of variation (CV%) of yield and yield contributing characters of maize germplasm

Characters MSS Standard error CV (%) F- test

Grain yield/plant (g) 52.32 6.115 16.53 **Days to 50% silk emergence 61.80 0.610 1.40 **Plant height (cm) 152.32 1.551 1.44 **Ear height (cm) 66.10 1.046 2.24 **Ear length (cm) 13.42 0.743 7.83 **Ear girth (cm) 12.27 0.366 4.22 **Kernel rows/ear 13.06 0.844 9.13 **Kernels/row 22.61 1.962 12.27 **100 kernels weight (g) 21.32 1.977 13.11 **

** Significant at 1% level of probability.

Table 2. Grouping of 249 germplasm lines of maize into clusters

Cluster Total no. of genotypes Sl. No. of the genotypes

Cluster I 73 5,6,10,12,14,16,17,18,23,25,26,27,45,50,52,53,57,59,65,67,72,76,87,90,93,97,114,115,116,117,118,119,120,121,124,125,128,131,132,134,136,139,140,141,142,144,145,148,149,151,152,154,157,158,162, 168,172,173,174,178,183,189,191,192,199,200,201,209,243,244,246,247,248.

Cluster II 79 11,19,21,24,28,30,31,32,33,34,36,37,38,39,40,41,42,44,46,47,48,49,51,55,58,60,61,62,63,64,66,69,70,71,73,74,75,77,78,79,80,89,92,95,100,107,126,146,150,155,159, 160,161,163,165,1 6 6 , 1 6 9 , 1 7 5 , 1 7 6 , 1 7 9 , 1 8 0 , 1 8 1 , 1 8 2 , 1 8 6 , 1 8 7 , 1 9 3 , 1 9 4 , 1 9 6 , 1 9 7 , 1 9 8 , 2 0 3 , 2 1 6 , 2 2 3 ,230,231,235,236,237,241.

Cluster III 26 1,3,13,15,20,68,88,91,94,101,102,103,147,164,184,208,217,218,221,228,229,232,238,239,240,242.

Cluster IV 1 110.Cluster V 28 7,8,9,35,54,56,82,84,85,86,98,104,108,109,112,113,122,123,133,137,138,156,170,172,185,

190,206,249.Cluster VI 22 2,22,29,106,127,129,130,135,153,177,188,195,202,204,205,211,212,214,215,220,224,245.Cluster VII 1 213.Cluster VIII 8 43,81,96,99,143,227,233,234.Cluster IX 1 167.Cluster X 5 4,83,105,111,207Cluster XI 5 210,219,222,225,226.

GENETIC DIVERGENCE STUDIES IN MAIZE

16 [Vol. 2. No. 1 & 2]Ta

ble

3. A

vera

ge i

nter

and

int

ra c

lust

er D

2 an

d D

val

ues

in m

aize

Clu

ster

sI

IIII

IIV

VV

IV

IIV

III

IXX

XI

I7.

90 (

2.81

)*14

.51

(3.8

1)12

.74

(3.5

7)9.

88 (

3.14

)12

.44

(3.5

3)16

.83

(4.1

0)9.

11(3

.02)

13.4

2 (3

.66)

19.8

4 (4

.45)

17.1

4 (4

.14)

27.8

4 (5

.28)

II8.

96 (

2.99

)13

.24

(3.6

4)19

.43

(4.4

1)22

.51

(4.7

4)12

.11

(3.4

8)15

.89

(3.9

9)12

.28

(3.5

0)11

.96

(3.4

6)27

.28

(5.2

2)18

.40

(4.2

9)

III

8.92

(2.

99)

13.9

8 (3

.74)

19.3

0 (4

.39)

16.1

9 (4

.02)

16.0

2 (4

.00)

14.5

1 (3

.81)

13.2

2 (3

.64)

22.1

2 (4

.70)

21.6

8 (4

.66)

IV0.

00 (

0.00

)9.

82 (

3.13

)21

.60

(4.6

5)12

.17

(3.4

9)17

.36

(4.1

7)23

.34

(4.8

3)12

.53

(3.5

4)31

.78

(5.6

4)

V9.

39 (

3.06

)24

.40

(4.9

4)13

.24

(3.6

4)19

.71

(4.4

4)27

.94

(5.2

9)13

.04

(3.6

1)36

.37

(6.0

3)

VI

12.7

3 (3

.57)

16.2

4 (4

.03)

16.0

1 (4

.00)

15.8

6 (3

.98)

29.2

4 (5

.41)

18.9

8 (4

.36)

VII

0.00

(0.

00)

15.5

3 (3

.94)

23.3

6 (4

.83)

18.5

7 (4

.31)

29.1

8 (5

.40)

VII

I13

.34

(3.6

5)16

.02

(4.0

0)24

.39

(4.9

4)23

.97

(4.9

0)

IX0.

00 (

0.00

)31

.48

(5.6

1)13

.12

(3.6

2)

X14

.45

(3.8

0)40

.13

(6.3

3)

XI

9.75

(3.

12)

*Fig

es i

n pa

rent

hesi

s in

dica

te D

val

ues.

Dia

gona

l va

lues

ind

icat

e in

tra-

clus

ter

dist

ance

s.

Tabl

e 4.

Clu

ster

mea

ns f

or n

ine

char

acte

rs in

mai

ze g

erm

plas

m

Cha

ract

ers

Clu

ster

sN

o.of

tim

esPe

rcen

tage

of

appe

arin

g fi

rst

cont

ribu

tion

to

III

III

IVV

VI

VII

VII

IIX

XX

Iin

ran

king

war

ds t

otal

dive

rgen

ce

Gra

in y

ield

/52

.61

46.1

547

.77

59.0

070

.71

58.2

051

.00

44.6

339

.00

51.6

055

.20

436

1.41

plan

t (g

)

Day

s to

50%

61.3

259

.99

69.5

867

.50

61.1

659

.52

57.5

059

.00

68.5

066

.10

68.9

059

8919

.40

silk

em

erge

nce

Plan

t he

ight

(cm

)16

6.42

133.

4714

6.42

178.

5018

8.38

139.

4317

8.00

141.

8111

1.50

197.

5099

.00

1654

653

.59

Ear

hei

ght

(cm

)71

.91

58.9

564

.85

79.5

084

.88

50.0

763

.50

69.8

858

.00

89.5

036

.00

6901

22.3

5

Ear

len

gth

(cm

)13

.44

12.8

913

.49

14.7

514

.80

13.7

010

.25

11.8

814

.25

14.4

513

.75

223

0.72

Ear

gir

th (

cm)

12.2

511

.91

11.9

614

.75

13.2

512

.56

12.5

011

.94

12.2

512

.35

12.8

053

11.

72

Ker

nel

row

s/ea

r12

.92

12.7

313

.69

16.0

013

.61

13.2

714

.00

12.5

014

.00

12.8

013

.40

780.

25

Ker

nels

/row

22.4

021

.65

23.1

516

.50

25.4

523

.77

16.5

019

.88

29.0

021

.80

23.4

086

0.28

100

kern

els

22.1

020

.48

18.1

528

.00

23.8

221

.75

24.0

020

.88

13.0

022

.60

22.9

086

0.28

wei

ght

(g)

SUMALINI AND MANJULATHA


Table 5. Latent vectors for nine principal component characters of maize germplasm lines

Characters Vectors 1 Vectors 2 Vectors 3

Grain yield/plant (g) 0.0563 0.1212 0.0394

Days to 50% silk emergence -0.0080 -0.9031 0.2657

Plant height (cm) 0.8472 0.1218 0.4898

Ear height (cm) 0.5225 -0.1881 -0.7964

Ear length (cm) 0.0172 -0.0347 0.1716

Ear girth (cm) -0.0497 0.2644 0.0108

Kernel rows/ear 0.0543 -0.0410 -0.0914

Kernels/row 0.0103 0.1708 0.1211

100 kernels weight (g) 0.0134 0.1325 0.0331

genetic variability. The genotypes belonging to theclusters separated by high statistical distance could beused in hybridization programme for obtaining a widespectrum of variation among the segregates. In thiscontext, genotypes from clusters V, IX, X and XI shouldbe selected as parents in hybridization programme foryield improvement in genotypes of maize. These findingsare in conformity with the findings of Ganesan et al.(2010). Therefore, it is suggested that the most diverseclusters may be used as parents in hybridizationprogramme to develop high yielding hybrids.

Mean values of grain yield/plant (70.71 g) and earlength (14.8 cm) were highest in cluster V, ear girth

(14.75 cm), kernel rows/ear (16) and 100 kernel weight(28 g) were highest in cluster IV, plant height (197.5 cm)and ear height (89.5 cm) were highest in cluster X, kernels/row (29) was highest in cluster IX and lowest mean valuesfor days to 50% silking (57.5 days) was observed incluster VII. A wide range of variations for severalcharacters among single as well as multigenotypic clusterwas observed.

The results on the contribution of individualcharacters towards the total divergence (Table 4)suggested that the percent contribution was the highestfrom plant height (53.59) followed by ear height (22.35)and days to 50% silk emergence (19.4). The present

Fig.1.Scatter diagram of maize germplasm.

GENETIC DIVERGENCE STUDIES IN MAIZE

18 [Vol. 2. No. 1 & 2]

results are in agreement with those of Marker andKrupakar (2009) who also identified plant height andear height characters as the principle componentscontributing maximum to the total variation in maize.

The principal component analysis revealed that inmajor vector I, the important characters responsible forgenetic divergence in the major axis of differentiationwere grain yield/plant, plant height, ear height, earlength, kernel rows/ear, kernels/row and 100 kernelweight (Table 5). In vector II, which was the second axisof differentiation, the characters grain yield/plant, plantheight, ear girth, kernels/row and 100 kernel weight wereimportant. In vector III, which was the third axis ofdifferentiation, all the characters except ear height andkernel rows/ear were important. The role of grain yield/plant, plant height, kernels/row and 100 kernel weightfor all the three vectors was positive across three axiswhich is an indication of the important components ofgenetic divergence in the germplasm.

Group constellation was also independently derivedby principal component analysis to verify groupingobtained through D2 statistic in a three dimensional chart(Z1-Z3). Therefore, scores obtained for the first twocomponents were plotted against two main axis and thensuperimposed in 3D pattern (Fig. 1). This clusteringpattern confirmed the results obtained by D2 analysis.

More the genetically diverse parents used inhybridization programme, greater will be the chancesof obtaining high heterotic hybrids and broad spectrumof favourable genetic variability in segregatinggenerations (Arunachalam,1981). It has been observedthat the most productive hybrids may come from highyielding parents with a high genetic diversity.

In maize, the traits viz., kernel rows/ear, kernels/rowand 100 kernel weight were the key component traits

associated with high grain yield. Therefore, based onhigh grain yield and large inter-cluster distances, it isadvisable to attempt crossing among the genotypes fromcluster V, VI, X and XI, which would exhibit high heterosisand likely to produce new recombinants with desiredcharacters in maize.

REFERENCES

Arunachalam, V. (1981). Genetic distance in plant breeding.Indian J. Genetics 41: 226-236.

Chen FaBo, Yang KeCheng, Rong TingZhao and Pan GuangTang.(2007). Analysis of genetic diversity of maize hybrids in theregional tests of Sichuan and Southwest China. ActaAgronomica Sinica 33(6): 991-998.

Ganesan, K.N., Nallathambi, G., Senthil, T.N. and Tamilarasi, P.M.(2010). Genetic Divergence Analysis In Indigenous MaizeGermplasms (Zea Mays L.). Electronic J. Plant Breeding 1(4):1241-1243.

Marker, S. and Krupakar, A. (2009). Genetic divergence in exoticmaize germplasm (Zea mays L.). ARPN J. Agrl. Biol. Sci. 4:44-47.

Murty, B.R. and Arunachalam, V. (1966). The nature of divergencein relation to breeding system in crop plants. Indian J. Genetics26A: 188-198.

Pandey, S. and Gardner, C.O. (1992). Recurrent selection forpopulation variety, and hybrid improvement in tropical maize.Adv. Agron. 48: 1-87.

Rao, C.R. (1952). Advanced Statistical Methods in BiometricalResearch. John Wiley and Sons, New York. 390 pp.

Saxena, V.K., Mathi, N.S., Singh, N.N. and Vasal, S.K. (1998).Heterosis in maize: Grouping and patterns. Proc. of 7th AsianRegional Maize Workshop. Los Banos, Philippines. February23-27, 124-133, pp.

Vasal, S.K., Dhilon, B.S. and Zhang, S.H. (1995). Improvement inselfed and random mated generations of our subtropical maizepopulations through S3 recurrent selection. Euphytica 83: 1-8.

Vasal, S.K. (1998). Hybrid maize technology: Challenges andexpanding possibilities for research in the next century. Proc.of 7th Asian Regional Maize Workshop. Los Banos, Philippines.February 23-27, 58-62 pp.

SUMALINI AND MANJULATHA


Stability and adaptability of kernel carotenoids in maize

SWETA DOSAD AND N. K. SINGH

Department of Genetics and Plant BreedingG. B. Pant University of Agriculture and Technology, Pantnagar 263145

ABSTRACT

Significant genetic variance was rewarded among the 34 maize genotypes for grain yield and kernel carotenoids.None of the genotypes were found to possess general stability criteria either for the kernal caritonides (KC) or grainyield. However, ‘PML-1’, ‘PML-6’, ‘PML-17’, ‘PML-27’, ‘PML-31’ were identified to be promising for both the traitsand may serve as potential donor particularly for improvement of carotenoids in maize hybrids or composites. Relationbetween KC and grain yield was found to be non-significant with very low coefficient of determination. Similarly,kernel colour was found to be associated non-significantly with KC with low coefficient of determination.

Key words: Grain yield, Kernel carotenoids, Maize, Stability

Maize (Zea mays L.) is the crop with highest geneticyield potential among cereals. Besides its diverse usesright from food and feed to industrial products such asethanol, and adaptability to diverse ecological niches, itis the only carotenogenic crop among the major cereals.Presence of provitamin ‘A’ carotenoid in maize kernelmakes this crop suitable for biofortification to supplementvitamin ‘A’ deficiency. In fact, biofortification is a methodwhere breeders target to increase essential nutrient levelsin staple foods by using specific strategies in programsof plant improvement and genetic transformation (Nestelet al. 2006, Oaim et al. 2007).

Hybrids in maize are attractive due to high yieldpotential, tolerance to biotic and abiotic stresses anduniform maturity and harvest. However, most of thepromising cultivars of maize had low and narrow rangeof kernel carotenoids (KC), whereas, wide range ofvariability for KC (5.5 to 66µg/g) has been reported indiverse maize germplasm (Harjes et al. 2008; Berardoet al., 2009). The high concentration of KC in maizegermplasm may be due to the presence of rare/desirableallele(s) or block of adapted genes influencing thebiosynthesis of carotenoids. Thus, identification of lineswith higher KC and further analysis of its behaviouracross the different environmental conditions seems tobe a key element in improvement of KC in maize.Sandmann and Albrecht (1994) reported thatenvironmental factors influence carotenogenesis inmaize.The differential response of the genotypes across

the environments affects the selection gain as well asthe development of cultivars with broad adaptability andstability. Plenty of useful information about genotype-environment interaction (GEI), adaptability and stabilityin many crops including maize is available. However,most of the studies focus on yield-related traits, whilelimited attempts have been made to quantify genotype-enviroment interaction, adaptability and stability ofcarotenoid contents in maize. Therefore, the presentinvestigation was planned to identify the promisinggermplasm showing adaptability and stability forcarotenoids and grain yield. It was also decided to findout whether carotenoid content is related to grain yieldand kernel colour or not.


Thirty two maize collections from Uttarakhand (29yellow and 3 white grain) were evaluated along with twocheck varieties viz., ‘Pant Sankul Makka-3’ and ‘Pragati’under three environments i.e. normal nitrogen dose andirrigated (E1), low nitrogen and rainfed (E2) and lownitrogen and excess soil moisture condition (E3) inrandomized complete block design during 2009-10 at theCrop Research Centre of Govind Ballabh Pant Universityof Agriculture and Technology, Pantnagar, Uttarakhand.Each plot consisted of two rows of 4 m. Inter row andintra row spacing was maintained at 75 cm and 25 cm,respectively. Low nitrogen dose means 40 kg/ha andexcess soil moisture means ponding water of 5 cmcontinuously for 7 days preceding flowering. Grain yieldwas calculated at 15% moisture content. Each genotypeCorresponding author Email: [email protected]


20 [Vol. 2. No. 1 & 2]

Table 1. Pooled analysis of variance for kernel carotenoids and grain yield in maize

Source of variation Mean square

Degree of freedom Kernel carotenoids (µg/g) Grain yield (q/ha)

Genotype 33 245.92** 235.39**Environment 2 61.96** 20.34G×E 66 17.14** 51.27*E+(G×E) 68 18.46 50.36E (linear) 1 123.94** 40.68G×E (linear) 33 24.32** 53.47Pooled deviation 34 9.66** 47.63**Pooled error 1 9 8 1.46 27.86

‘*’ and ‘**’-Significant at 5% and 1% probability level

Table 2. Grain yield and kernel carotenoids in maize under different environment

Genotypes E1 E2 E3Grain yield Carotenoids Grain yield Carotenoids Grain yield Carotenoids

(q/ha) (µg/g) (q/ha) (µg/g) (q/ha) (µg/g)PML-1 38.65 31.53 46.31 41.67 35.99 31.58PML-2 27.03 41.81 25.77 31.59 39.98 33.78PML-3 49.31 33.69 36.87 39.35 20.88 40.80PML-4 37.32 38.38 34.65 35.36 41.79 29.05PML-5 38.65 32.93 39.98 21.49 26.02 21.13PML-6 39.98 42.29 42.65 28.84 39.69 35.33PML-7 35.99 42.21 29.77 35.68 30.11 41.98PML-8 37.32 33.47 35.99 28.97 24.43 28.5PML-9 32.91 31.66 19.10 26.91 16.69 25.79PML-10 63.97 28.05 44.43 26.18 46.65 26.42PML-11 46.65 32.05 42.39 23.20 55.75 27.57PML-12 21.76 30.38 23.99 32.94 28.88 36.51PML-13 31.99 2.07 19.99 2.47 23.99 4.25PML-14 31.99 24.88 23.95 29.08 39.21 26.62PML-15 34.65 22.06 26.66 32.68 27.06 28.71PML-16 30.65 35.82 23.99 33.49 28.88 30.57PML-17 30.65 37.07 54.88 33.28 59.94 38.39PML-18 26.66 34.67 38.21 22.63 31.09 24.61PML-19 45.32 4.67 34.65 3 .4 22.21 4.12PML-20 46.65 40.39 52.42 30.34 44.43 33.47PML-21 41.32 5.42 34.65 3.36 39.98 4.83PML-22 47.98 36.24 44.87 26.27 49.87 36.09PML-23 49.31 27.48 49.31 38.34 57.75 35.91PML-24 33.32 34.81 50.20 25.78 51.09 37.91PML-25 23.99 29.57 30.65 31.66 43.10 29.11PML-26 29.32 35.50 31.09 27.96 39.09 28.6PML-27 35.99 41.39 44.43 34.51 51.09 34.83PML-28 26.66 35.32 26.21 26.65 22.66 26.3PML-29 33.32 30.88 26.66 44.59 30.03 33.93PML-30 23.99 38.72 23.99 35.73 26.66 30.40PML-31 33.32 37.23 45.77 35.8 51.87 36.42PML-32 30.65 31.19 35.54 31.65 37.32 30.03Pragati (c) 45.54 28.55 52.42 27.77 53.31 34.72Pant Sankul 45.32 39.35 49.31 33.91 52.66 37.28GM 36.71 31.52 36.52 28.93 37.95 29.58

was quantified for kernel carotenoids (µg/g dry matterbasis) using Quick carotenoids extraction protocol(Schaub et al. 2004). Behaviour of grain yield and kernelcarotenoids across the environments was quantified bythe procedure given by Eberhart and Russell (1966).Linear regression was analysed to establish correlationbetween KC with grain yield and kernel colour.


The combined analysis of variance revealed theexistence of significant genetic variance in the maizecollections evaluated for both KC and grain yield (Table1). Significant GEI for KC and grain yield indicated thatthe expressions of both the traits are influenced by theenvironment, highlighting the need for a detailed study

DOSAD AND SINGH


to identify genotypes for greater adaptability andphenotypic stability (Sandmann and Albrecht, 1994; Rioset al. 2009).

The range of variation for grain yield was found tovary from 21.76 to 63.97 q/ha with a population meanof 36.71 q/ha in E1, from 19.10 to 54.88 q/ha withpopulation mean of 36.52 q/ha in E2, and from 16.69 to59.94 q/ha with a population mean of 37.95 q/ha in E3.Estimates on KC varied from 2.07 µg/g in white graingenotype to 42.29 µg/g with a population mean of 31.52µg/g, from 2.47 µg/g in white genotypes to 44.59 µg/g

with a population mean of 28.93 µg/g and from 4.12 µg/gin white grained genotypes to 41.98 µg/g with populationmean of 29.58 µg/g in E1, E2 and E3, respectively (Table2). The highest carotenoid content was observed to be44.59 µg/g however Harjes et al. (2008) reported KC upto 66 µg/g in 282 maize germplasm and based on analysisof 1245 samples of maize, Berardo et al., (2009) reportedthe range of total carotenoids from 1.09 ìg/g to 61.10 ìg/g dry weights. Lower concentration of KC observed inthe present investigation may be due to the type ofmaterials used.

Table 3. Stability parameters for kernel carotenoids and grain yield in maize

Genotypes Kernel carotenoid Grain yield

(µg/g) Bi S2di (q/ha) Bi S2di

PML-1 34.93 -3.01* 34.67** 40.32 -5.41 13.16PML-2 35.73 3.98 -0.40 30.93 10.17 -9.08PML-3 37.95 -2.52* 4.56 35.69 -15.49* 110.04*PML-4 34.26 2.00 30.27** 37.92 4.51 -7.60PML-5 25.19 4.79* 5.89* 34.89 -9.96 -9.15PML-6 35.49 4.81* 5.58* 40.77 -1.42 -6.36PML-7 39.96 1.96 12.93** 31.95 -1.57 12.23PML-8 30.31 1.92 1.07 32.58 -8.95 -4.70PML-9 28.12 2.10 2.79 22.90 -5.83 103.31*PML-10 26.88 0.75 -0.45 51.68 -4.07 199.99**PML-11 27.61 3.15 2.39 48.26 8.66 -5.75PML-12 33.28 -1.49 10.41** 24.88 4.27 -4.66PML-13 2.93 -0.38 1.69 25.32 -0.54 64.96PML-14 26.86 -1.45 0.75 31.71 8.96 11.26PML-15 27.82 -3.94* 0.59 29.46 -2.04 26.33PML-16 33.29 1.31 7.08* 27.84 1.67 11.18PML-17 36.25 0.97 10.19** 48.49 10.84 340.25**PML-18 27.30 4.76* 0.17 31.99 -1.89 54.33PML-19 4.06 0.44 -0.39 34.06 -12.34* 76.05PML-20 34.74 3.80 -0.25 47.83 -4.24 3.31PML-21 4.54 0.68 0.08 38.65 2.00 10.79PML-22 32.87 2.97 32.68** 47.57 2.79 -5.89PML-23 33.91 -4.22** -0.44 52.13 6.26 -8.59PML-24 32.83 2.31 59.56** 44.87 5.59 153.80**PML-25 30.11 -0.57 2.05 32.58 11.17 29.59PML-26 30.69 3.06 0.46 33.17 6.45 -4.78PML-27 36.91 2.82 0.72 43.83 7.41 39.70PML-28 29.42 3.64 3.40 25.18 -2.76 -8.82PML-29 36.47 -4.43** 31.68** 30.00 0.55 12.56PML-30 34.95 1.87 22.18** 24.88 1.98 -9.22PML-31 36.48 0.52 -0.44 43.65 8.16 89.77PML-32 30.96 0.00 0.91 34.51 2.75 5.51Pragati (c) 30.35 -0.52 27.64** 50.42 2.67 18.40Pant Sankul Makka-3 (c) 36.85 1.86 2.01 49.10 3.65 1.83Mean 30.00 0.99 37.06 1.00SE(±) 2.2 1.63 4.88 6.31

STABILITY AND ADAPTABILITY IN MAIZE

22 [Vol. 2. No. 1 & 2]

Based on performance pooled over theenvironments, ‘PML-23’ followed by ‘PML-10’exhibited higher grain yield than the best checkcomposite variety ‘Pragati’ (Table 3). However, thesethree genotypes were statistically on par in yieldperformance. Local collection ‘PML-9’ gave minimumyield. The kernel of ‘PML-7’ consisted of highest amountof KC which was significantly superior over thecarotenoids levels of the best check ‘Pant Sankul’Makka-3. The other promising genotypes for KC were‘PML-3’ (37.95 µg/g), ‘PML-27’ (36.91 µg/g), ‘PML-31’ (36.48µg/g), ‘PML-29’ (36.47µg/g), ‘PML-17’(36.25 µg/g). These landraces may be used to constitutea population with high kernel carotenoids and can beused directly as varieties or can be used for developmentof inbred lines with high carotenoid content. Burt et al.(2006) developed maize lines with a mean KC between43.6 and 88.3 µg/g evidencing the possibility ofsuccessfully increasing the KC levels in maize grains.Three genotypes namely ‘PML-13’ (2.93µg/g), ‘PML-19’ (4.06µg/g) and ‘PML-21’ (4.54µg/g) with white graincolour had meager amount of carotenoids.

Stability analysis indicated that ‘PML-23’ hadhighest grain yield and non-significant deviation fromlinearity and therefore ‘PML-23’ seems to be stableacross the environments. However, regression valuesmore than unity revealed that it is adapted to favourableenvironmental conditions. The stability of ‘PML-10’, thesecond highest yielding genotype was found to be poordue to significant deviation from regression. The fourlocal collections namely ‘PML-11’, ‘PML-17’, ‘PML-20’ and ‘PML-22’ having numerically less butstatistically on par yield with the best check, exhibiteddifferential response in terms of stabili ty andadaptability. The PML-17 was identified to be unstabledue to significant deviation from regression. The PML-11 and PML-22 were found to be stable but adapted tobetter environment whereas PML-20 was found to haveadaptability to less favourable environment. Thecomposite varieties namely ‘Pant Sankul Makka-3, and‘Pragati’ were found to be stable and best adapted tofavourable environment. The remaining genotypes didnot qualify the stability criteria as they were either lowin yield potential or had significant deviation fromregression. None of the genotypes fulfill the requirementof average stability i.e. high grain yield, unit regressionand non-significant deviation from regression.

The ‘PML-7’ was identified to be significantlysuperior over the best check variety ‘Pant Sankul Makka-3’ and other test genotypes for KC. Due to significantdeviation from unity, ‘PML-7’ did not qualify as a stablegenotype. Two collections namely ‘PML-3’ and ‘PML-27’ having KC numerically superior over the best check

were found to be stable due to non-significant deviationfrom regression but better adapted to unfavourable andfavourable environments due to regression coefficientless and more than unity, respectively. Out of sevengenotypes found on par in terms of carotenoids contentwith best check, four genotypes namely, ‘PML-29’,‘PML-17’, ‘PML-6’ and ‘PML-1’ were found to beunstable due to significant deviation from regression.The remaining three genotypes were found to be stablebut ‘PML-31’ was adapted to unfavourable environmentbecause of regression less than unity, and ‘PML-20’ and‘PML-2’ were found to be adapted under favourableenvironmental condition because of regression valuehigher than unity. Composite variety ‘Pragati’ was foundto be unstable because of significant deviation fromregression whereas the other check variety namely ‘PantSankul Makka-3’ was identified to be stable with betteradaptation to favourable environments. It is interestingto note that none of the genotypes fulfill the criteria ofgeneral adaptability for KC. The result of the presentinvestigation necessitates the need for further researchon the adaptability and stability of KC since maize iscultivated throughout the year under different culturalpractices and environmental conditions Since there arevery few published literatures on this aspect, the presentwork therefore, seems to be important for theunderstanding of GEI for carotenoids in maize.Information on stability and adaptability of carotenoidsin maize cultivars and germplasm is also essentiallyrequired for spread and/or exchange of plant materialsand technologies of cultivation and processing (Rios etal. 2009).

Maize kernel colour of each line was recorded andbroadly grouped into dark yellow, yellow, light yellow,orange, light orange and white colour to assess relationbetween kernel colour and carotenoids content. Fivegenotypes with dark yellow kernel colour had KC from27.30 to 34.93 ìg/g, six lines with yellow kernel colourvaried in KC from 25.19 to 37.95 ìg/g whereas two lineswith light kernel colour had 26.82 and 27.82 ìg/g of KC.Eleven orange kernel colour genotypes varied in KC from30.31 to 39.96 ìg/g whereas seven genotypes with lightorange colour had KC from 29.42 to 36.85 ìg/g.

The kernel colour score generated from 1 to 5 wereregressed over to carotenoids content. The regressionanalysis revealed non-significant relation between kernelcolour and carotenoids content. The coefficient ofdetermination of kernel colour on carotenoids contentwas also found to be low (R2 = 0.186, Fig. 1). The resultsof the present investigation, therefore, indicated thatkernel colour cannot be used reliably for selection ofgenotypes with higher carotenoids content. Similarobservations were also noted earlier by Harjes et al.

DOSAD AND SINGH


Figure 1. Relation of kernel colour and total carotenoids in maize (0- white, 1- Dark yellow, 2- Yellow, 3- light yellow, 4- Orange, 5- Light orange).

Figure 2. Relation between grain yield and kernel carotenoids in maize

STABILITY AND ADAPTABILITY IN MAIZE

24 [Vol. 2. No. 1 & 2]

(2008) and Mishra and Singh (2010). The relation of KClevels was also analysed with grain yield. Regressionanalysis revealed very low correlation between KC leveland grain yield. The coefficient of determination wasalso found to be very low (R2 =0.06, Fig 2). Thus, it isevident from the present investigation that grain yieldand KC is not correlated and they need to be selectedindependently in improvement programme.

The germplasm identified to be promising for grainyield were ‘PML-23’, ‘PML-10’, ‘PML-17’, ‘PML-11’,‘PML-20’ and ‘PML-22’ whereas for KC, ‘PML-7’, ‘PML-3’, ‘PML-27’, ‘PML-31’ and ‘PML-29’ were identified tobe the five promising landraces. When both the traitsi.e. grain yield and KC were considered together, thelandraces namely ‘PML-1’, ‘PML-6’, ‘PML-17’, ‘PML-27’, ‘PML-31’ emerged as the promising ones. Thegenotypes identified may serve as potential donorparticularly for improvement of carotenoids in maizehybrids or composites. The present investigation alsorevealed that selection based on kernel colour is notreliable for selecting lines with higher carotenoidscontent.

REFERENCES

Berardo, N., Mazzinelli, G., Valoti, P., Lagana, P., Redaelli, R.2009. Characterization of maize germplasm for thechemical composition of the grain. J. Agric. Food Chem.57: 2378-2384.

Burt, A. J., Smid, M. P., Shelp, B. J., Lee, E. A. (2006). Highcarotenoid maize project: increased accumulation andmodified chemical profiles. In: Higman S (ed) Procedingsof the International Plant Breeding Symposium. Mexico,p.55.

Eberhart, S. A. and Russell, W. A. (1966). Stability parametersfor comparing varieties. Crop Sci., 6: 36-40.

Harjes, C. E., Rocheford, T. R., Bai, L., Brutnell, T. P., Kandianis,C. B., Sowinski, S. G., Stapleton, A. E. , RatnakarVallabhaneni, R., Williams, M., Wurtzel, E. T., Yan, J.,Buckler, E. S. (2008). Natural Genetic Variat ion inLycopene Epsilon Cyclase Tapped for MaizeBiofortification. Science, 319: 330-333.

Mishra, P., Singh, N. K. (2010). Spectrophotometric and TLCbased characterization of kernel carotenoids in shortduration maize. Maydica, 55:95-100.

Nestel, P., Bouis, H. E., Meenakshi, J. V., Pfeiffer, W. (2006).Biofortification of staple food crops. J. Nutr., 136: 1064-1067.

Oaim, M., Stein, A. J., Meenakshi, J. V. (2007). Economics ofbiofortification. Agril. Econ., 37: 119-133.

Rios, S. de A., Paes, M. C. D., Borem, A., Cruz, C. D., Guimaraes,P. E. de O., Schaffert, R. E., Cardoso, W. S., Pacheco, C. A.P. (2009). Adaptability and stability of carotenoids in maizecultivars. Crop Breed. Appl. Biotech., 9: 313-319.

Sandmann, G., Albrecht, M. (1994). Light-stimulated carotenoidbiosynthesis during transformation of maize etiolplasts isregulated by increased activity of isopentenylpyrophosphate isomerase. Plant Physiol., 105: 529-534.

Schaub, P., Beyer, P., Islam, S., Rocheford, T. (2004). Maizequick carotenoid extraction protocol (http:/ /www.cropsci.uiuc.edu/faculty/rocheford/ quick_carotenoid_analysis_ protocol.pdf)

DOSAD AND SINGH


Genotypic variability for morphological traits among land races in maize(Zea mays L.)

J.M. PATEL

Maize Research Station, S.D. Agricultural University, Bhiloda, Gujarat

ABSTRACT

Significant variations were recorded among the land races for various morphological and yield attributingcharacters in maize. High values for phenotypic coefficient of variation and genotypic coefficient of variation wererecorded for cob yield, whereas these values were moderate for ear height. Phenotypic coefficient of variation washigher than corresponding genotypic coefficient of variation. Very high estimates of heritability were found for cobyield (98.41%) followed by ear height (97.53%) and plant height (90.62%). Days to 50% tasseling and days to 75% dryhusk showed high estimates of heritability. The value of genetic advance ranged from 0.19% (ear girth) to 35.30% (cobyield/ha). Cob yield and ear height exhibited high genotypic coefficient of variation, heritability and relatively highgenetic advance indicating additive genetic effects.

Key words: Land race, Maize, Morphological traits, Variability

Maize is one of the most important cereal crops withwider adaptability and high yield potential. In Gujarat,maize is cultivated mostly in rainfed conditions andoccupies more than 4 lakh ha area. The tribals aroundthe mountains of aravalli hills of northern Gujarat stillgrow land races which are extra early maturity thusproviding drought escaping mechanism. Thedevelopment of new varieties depends on the magnitudeof genetic variability in the base population. Geneticdiversity created in farmers’ field over thousands of yearsset off by genetic diversity present in wild relatives ofcrop provide the base material for improving theproductivity through techniques of modern plantbreeding. Land races are varieties of crops that evolvedand were improved by farmers over many generationswithout the use of modern plant breeding techniques.Little information is available on land races of northernparts of Gujarat surrounding aravalli hills for maize crop.The present study was conducted to estimate the natureand magnitude of variability for cob yield and yieldrelated attributes among land races and to evaluate theperformance of various land races under field conditions.


The present study was conducted at MaizeResearch Station, S.D. Agricultural University, Bhilodaduring kharif 2010. Twenty five land races and one

composite variety of normal yellow maize was grown inrandomized block design with two replications,maintaining row to row and plant to plant distance of 60and 20 cm distance, respectively. The crop was grownfollowing the recommended agronomic practices. Theobservations on cob yield, days to 50% tassel, days to50% silk and days to 75% dry husk were recorded onplot base, whereas other traits were recorded from 5randomly selected plants from each replication. Statisticalanalysis was carried out by using indistat softwareprogramme.


Significant to highly significant differences wereobserved between the genotypes for all the traits exceptcob girth (Table 1). The magnitude of mean squares wasrelatively small. The mean data on genotypic, phenotypicand environmental variances, GCV (%), PCV (%), H2(bs)(% )and GA (%) showed considerable phenotypic andgenotypic variations among the genotypes for all thetraits under consideration except ear girth (Table 2).Genotypic variance for the traits ranged from 0.01 for eargirth to 186321.3 for cob yield per hectare.

A thorough probe into mean data revealed that daysto 50% tasselling ranged from 41-50 (Table 2). Maximumdays (41) for this trait was observed by ‘Allana mahuda’


26 [Vol. 2. No. 1 & 2]

Table 1. Analysis of variance for various (mean squares) characters of maize

Character Replication Genotype Error

Degree of freedom 1 25 25

Days to 50% tassel 8.48 5.93** 1.00

Days to 50% silk 2.32 4.80** 1.60

Days to 75% dry husk 96.94 3.82** 0.54

Plant height 521.65 73.69* 6.91

Ear height 1.92 60.07* 1.48

Cob girth 0.07 1.64 1.62

Cob yield 1529797.1 1598056.4** 25413.9

Table 2. Range, mean, genotypic, phenotypic and environmental variance, GCV, PCV, H2(bs) and GA as percent of mean for various characters inmaize

Character Range Mean Genotypic Phenotypic Environmental GCV PCV H2 (bs) GA asvariance variance variance (%) (%) % % of mean

Days to 50% tassel 41-50 43.75 2.46 2.96 0.50 3.58 3.93 83.10 6.73

Days to 50% silk 47-56 50.48 1.59 2.40 0.80 2.50 3.07 66.50 4.21

Days to 75% dry husk 59-65 61.36 1.64 1.91 0.27 2.08 2.25 85.80 3.98

Plant height (cm) 192-218 201.07 33.39 36.85 3.45 2.87 3.01 90.60 5.63

Ear height (cm) 92-114 100.53 29.30 30.00 0.74 5.38 5.45 98.00 11.00

Cob girth (cm) 11-14.50 13.01 0.01 0.82 0.81 0.81 6.97 14.00 0.19

Cob yield/plot 3714-7141 5132.52 786321.3 799028.20 12706.98 17.27 17.41 98.40 35.30

local. Days to silking varied significantly among thegenotypes with a range of 47-56 days and a mean of 50.5(Table 2). The genotype ‘Antarsumba took’ took minimumdays to 50% silking (47.0). Plant height ranged from 192to 218 cm with maximum contribution from composite‘GM 2’ whereas minimum contribution from ‘Rajpur local’was recorded. Ear height ranged from 92 to 114 cm and‘Allana mahuda’ had low cob placement variety.Maximum cob girth was attained by ‘Khokhara borderlocal’, whereas ‘Antarsumba local’ produced lowest cobgirth. Maximum cob yield per hectare was recorded by‘Mevda local’ (7141.0) followed by ‘Dhorasvar local’(6729.55) (Table 3). All the genotypes matured earlier thancomposite ‘GM 2’ which implies the significance of landraces for selection for early maturity.

The magnitude of genotypic coefficient of variationwas less than phenotypic coefficient of variationindicating involvement of environmental factors in theexpression of these traits (Table 2). Phenotypiccoefficients of variation were highest for cob yield perhectare (17.41) followed by ear girth (6.97). Cob yield perhectare also showed highest genotypic coefficient ofvariation (17.27). Moderate PCV and GCV estimates wererecorded for ear height (5.45 and 5.38). Low estimates of

PCV and GCV were found for days to 50% silk, days to75% dry husk, plant height and cob girth. Although themoderate to high values of genotypic coefficients ofvariation for cob yield indicate that this trait might beimproved by further selection. Cob yield was found tobe the most heritable trait in land races studied with98.41% followed by ear height (97.53%) and plant height(90.62%). Similar results were reported by Hemavathy etal. (2008). Days to 50% tasseling and days to 75% dryhusk showed high estimates of heritability indicated thatselection for these traits in maize would be the mosteffective for the expression of these traits in thesucceeding generations. The results are confirmed withthe findings of Sumathi et al. (2005), Alkae et al. (2008)and Kashaini et al. (2008). Very low heritability wasrecorded for cob girth due to low genetic variance. Similarreport was noted by Hemavathy et al. (2008). Expectedgenetic advance values are expressed as percentage ofthe genotypic mean for each character so thatcomparison could be made among various traits, whichhad different units of measurement. The value of geneticadvance ranged from 0.19% (ear girth) to 35.30% (cobyield/ha). Days to 50% silking, plant height and days to50% tasseling showed relatively moderate genetic

PATEL


advance. However, their heritability estimates were high.High heritability in addition to high genetic advance isan important tool for predicting the resultant effect ofselecting the best individual. In this study, cob yieldwas observed to be such a type of expression. Thepresence of high heritability with moderate geneticadvance has been reported to suggest the effect of equalcontribution of additive and non-additive gene action.High heritability coupled with very low genetic advancewas recorded for each girth suggesting the contributionof non additive gene action in controlling this trait.

High GCV along with high heritability and geneticadvance will provide better information than a singleparameter (Sahoo et al., 1990). Hence in this study, cobyield and ear height exhibited high GCV, high heritability

and relatively high genetic advance indicating additivegenetic effects and can easily be transferred tosucceeding generations.

REFERENCES

Alkae, C.O., Ojo, D.K., Oduwaye, O.A. and Adekoya, M.A.(2008). ASSET Series A 8(1): 14-27.

Hemavathy, A., Balaji, K., Ibrahim, S.M., Anand, G. and Sankar,D. (2008). Agricultural Science Digest 28(2): 112-114.

Kashiani, P., Saleh, G., Abdullah, S.N. and Abdullah N.A.P. (2008).Proceedings of the 10th Symposium of Malaysian Society ofApplied Biology, Nov. 6-8 Malaysia, pp. 48.

Sahoo, S.C., Mishra, S.N. and Mishia, R.S. (1990). Newsletter 8:29-30.

Sumathi, P. , Nirmalakumari , A. and Mohanraj , K. (2005).Agricultural Journal 92(10-12): 612-617.

Table 3. Mean performance of agronomic traits of land races of maize

Genotype Cob yield Plant height Ear height Cob girth Days to 50% Days to 50% Days to 75%tasseling silking dry husk

Sebaliya 5606.13 194.00 104.50 12.75 43.50 49.50 60.50

Patliya 4163.72 199.85 104.00 14.25 44.50 50.50 62.00

Pathora 4426.03 200.00 100.00 12.50 43.50 49.50 60.00

Bhamriya 5517.28 207.00 106.50 12.50 45.50 50.50 60.00

Ambai gadha 3714.23 210.50 104.00 12.00 43.50 49.50 61.00

Dholavani 4881.51 209.00 100.50 13.00 44.50 50.50 61.00

Atarsumba 4241.19 211.50 103.00 11.00 43.50 49.50 61.50

Atarsumba 5444.54 197.50 100.50 11.50 44.50 47.50 60.00

Sarsav 6269.77 201.50 109.50 13.00 44.50 52.00 62.00

Abhapur 4666.58 204.00 102.50 13.50 43.50 51.00 59.50

Alana Mahuda 6546.19 203.00 92.00 12.50 41.00 49.50 61.00

Khokhra Border 5250.85 201.00 99.00 14.50 42.50 49.50 59.50

Chorimala 6064.88 198.00 99.00 12.50 43.00 51.00 60.50

Torda Bavariya 4681.68 200.50 93.50 12.50 45.50 52.50 61.50

Rampuri 4087.28 196.00 93.00 12.50 43.00 49.50 61.00

Panchal 4221.03 196.50 100.50 14.00 41.50 51.50 61.00

Lakhapur 5423.98 196.00 94.50 14.00 42.50 51.00 61.00

Kaliyakuva 4284.96 199.50 102.50 14.00 42.50 51.00 60.50

Bothivada 4726.23 203.00 100.50 12.00 43.50 50.00 62.50

Rajgor 5775.70 200.00 97.50 13.25 44.00 49.00 62.50

Rajpur 4335.06 192.00 99.50 12.75 44.50 50.00 63.50

Godha 4888.32 194.00 94.00 13.75 43.00 50.00 62.00

Mevda 7141.94 196.00 93.00 14.00 43.50 49.00 61.50

Rinchavada 5071.17 197.50 98.00 12.50 41.50 51.00 64.50

Dhorasvar 6729.35 202.00 108.50 14.25 45.00 50.00 60.50

GM 2 5585.99 218.00 114.00 13.50 50.00 56.00 65.00

GENOTYPIC VARIABILITY AMONG LAND RACES IN MAIZE

28 [Vol. 2. No. 1 & 2]

Genetic diversity studies in newly derived inbred lines of maize(Zea mays L.)

MRUTHUNJAYA C. WALI, UDAYKUMAR KAGE, H.L. NADAF,C.P. MANSUR AND S.I. HARLAPUR

All India Coordinated Maize Improvement ProjectAgricultural Research Station, University of Agricultural Sciences, Arabhavi 591 218

ABSTRACT

The present investigation was carried out to know the genetic diversity among the newly derived inbred lines ofmaize during kharif, 2011. In this experiment, 79 inbred lines and three checks were evaluated and observations wererecorded for 13 quantitative traits. Analysis of variance revealed high significant difference among all inbred lines.Inbred lines were grouped into 14 clusters, indicating the presence of genetic diversity. The cluster I is having highestnumber of genotypes (67). The maximum inter cluster distance was observed between clusters II and XII (22.41) andhighest intra-cluster distance was in cluster XII (5.46) and also a wide range of variation was observed in cluster meanperformance for the characters studied. These genetically diverse inbred lines can be further used for developingsuperior hybrids and can also be utilized in developing synthetics and composites.

Key words: Cluster, Genetic diversity, Inbred lines, Maize, Variance

Germplasm, prerequisite for any breedingprogramme, serves as a valuable source material as itprovides scope for building of genetic variability. Studyof variability, heritability and genetic advance in thegermplasm will help to ascertain the real potential valueof the genotype. Mahalanobis D2 statistical analysisis a very useful tool in studying the nature and the causeof diversity prevalent in the available germplasm.Genetic diversity plays an important role in plantbreeding because hybrids between lines of diverse origindisplay a greater heterosis compared to those betweenclosely related strains i.e. in maize, increased geneticdifference between inbred lines resulted in a greaterheterosis in their hybrids. However, the maximumheterosis generally occurs at an optimal or intermediatelevel of diversity.


The present investigation was carried out atArabhavi during kharif 2011. The experiment comprisedof newly derived 79 inbred lines from different sourcepopulations of tropical origin by continuous inbreeding.These 79 inbred lines were used along with three checksviz., KDMI-10, KDMI-16 and CI-5 to study the genetic

diversity. All 82 inbred lines were grown following therecommended field practices. The experiment was carriedout in a randomized complete block design and replicatedtwice. The experimental unit was two rows for each entrywith 4 m row length and 75 cm apart with the intra rowdistance of 20 cm. The observations were recorded fromten plants randomly selected from each plot for 13quantitative traits viz., days to 50 percent tasseling, daysto 50 percent silking, plant height, ear height, days to 75percent brown husk maturity, ear length, ear girth, numberof kernel rows per ear, number of kernels per row, 100grain weight, grain yield per hectare, shelling percentageand folder yield per hectare. Diversity analysis was doneusing Mahalanobis D2 statistics and inter cluster distancewas calculated by the formulae described by Singh andChaudhary (1977).


The analysis of variance carried out for the yield andits component characters among 82 inbred lines differedsignificantly for all characters. The D2 analysis carried outinvolving 82 inbreds for 13 characters revealed thataltogether 14 clusters have been formed (Table 2), whereincluster I had a maximum of 67 genotypes, cluster XII have3 genotypes and remaining cluster II, III, IV, V, VI, VII, VIII,




ble

1. A

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or y

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82

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riat

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Deg

rees

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Day

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Day

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Plan

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Deg

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%)

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Tabl

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Dis

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82

inbr

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int

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Sl n

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1I

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1, 2

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4,

5,

6, 7

, 8,

9,

10,

11,

12,

13,

14,

16,

17,

18,

19,

20,

21,

22,

23,

24,

25,

27,

28,

29,

30,

31,

32,

33,

34,

36,

37,

39,

40,

41,

42,

43,

44,

45,

46,

47,

49,

50,

51,

53,

54,

56,

57,

58,

59,

60,

61,

62,

65,

67,

68,

69,

70,

71,

72,

73,

76,

77,

78,

79

2II

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3II

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5

GENETIC DIVERSITY IN INBRED LINES OF MAIZE

30 [Vol. 2. No. 1 & 2]

IX, X, XI, XIII and XIV were all monogenotypic. Thegenotypes within the clusters, by and large, exhibit a narrowrange of genetic variability.

While studying the contribution of individualcharacters towards divergence among the 13 charactersstudied (Table 3), plant height (30.65%), days to 75 percentbrown husk maturity (22.55%) and ear height (16.65%)contributed highly for divergence. So, these characters mustbe given weightage for selecting diverse parents forbreeding programme. Whereas, other characters like grainyield per hectare (8.7%), number of kernels per row(6.14%), days to 50 percent tasseling (5.03%), 100 grainweight (2.11%), number of kernel rows per ear (1.96%),ear girth (1.6%), shelling percentage (1.6%), ear length(1.48%), fodder yield/hectare (1.39%) and days to 50 percentsilking (0.15%) contributed very little for divergence. Moreet al. (2006) reported that leaf area per plant, plant heightand days to 50 percent flowering were the majorcontributors towards divergence, while studying foragemaize.

Based on the intra and inter cluster distances usingSD2 values (Table 4), the maximum intra-cluster distancewas recorded within cluster XII (5.46), while it was lowestfor the genotype of cluster I (4.73) indicating that thegenotypes of these clusters might be differing marginallyin their genetic architecture and it can be considered thatthe genotypes belonging to clusters II and XII (22.4) havinghighest inter cluster distances followed by cluster IV and

XII (22.2), clusters IX XII (21.9) and cluster III and XII(21.57), suggesting that hybridization between divergentgroups may lead to higher magnitude of heterosis for thecharacters concerned. However, Arunachalam et al. (1984)opined that crosses between two divergent groups of parentsare less successful in achieving required magnitude ofheterosis. On the other hand, the crosses between genotypesexhibiting a narrow range of variability as revealed by shortinter cluster distances may not be worthwhile to get desiredextent of heterosis. This is probably because parents withsimilarity may possess common alleles governing thecharacters and may not help in complementation in thehybrid combination. Similarly, parents exhibiting greaterdivergence may also lack nick well ability. This is speciallybeing observed in distant crosses (interspecific) for yieldrelated traits. However, many studies are on the record thatwhenever parents with moderate divergence are used forcrossing, they throw out significant level of desiredheterosis (Arunachalam et al., 1984 and Singh et al., 2005).

Different characters revealed by cluster mean analysis(Table 5) indicated that the contrasting genotypes for daysto 50 percent tasseling and for days to 50 percent silkingare being grouped in clusters III, IV, VII and XII, for plantheight in clusters II and XII, for ear height in clusters XIand XII, for days to 75 percent brown husk maturity inclusters III and XII, for ear length character in clusters IXand VIII, for ear girth in clusters IV and XII, for number ofkernel rows per ear in clusters IV and XIII, for number ofkernels per ear in clusters XIII and VIII, for 100 grain

Table 3. Percent contribution of character towards divergence in 82 inbred lines

Sl. No. Characters Characters Contribution (%)

1 Days to 50 percent tasseling 5.03

2 Days to 50 percent silking 0.15

3 Plant height (cm) 30.65

4 Ear height (cm) 16.65

5 Days to 75 percent brown husk maturity 22.55

6 Ear length (cm) 1.48

7 Ear girth (cm) 1.6

8 Number of kernel rows per ear 1.96

9 Number of kernels per row 6.14

10 100-grain weight (g) 2.11

11 Grain yield (q/ha) 8.7

12 Shelling percentage (%) 1.6

13 Fodder yield (t/ha) 1.39

WALI ET AL


ble

4. A

vera

ge i

ntra

and

int

er c

lust

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ista

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valu

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f in

bred

lin

es

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ster

sI

IIII

IIV

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IV

IIV

III

IXX

XI

XII

XII

XIV

I4.

736.

896.

146.

376.

025.

856.

085.

97.

126.

727.

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234.

246.

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556.

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223.

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5.46

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817

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XII

I0

8.78

XIV

0

Tabl

e 5.

Clu

ster

mea

ns o

f in

bred

lin

es f

or 1

3 ch

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ters

Clu

ster

Day

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50

Day

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ngth

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(cm

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75%

BH

M(c

m)

(cm

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els

/w

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t (g

)(q

/ha)

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ield

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50.6

812

8.15

54.6

888

.73

13.8

54.

0613

.23

30.2

830

.89

30.6

880

.82

3.11

II50

.50

50.0

094

.50

41.4

587

.50

11.4

54.

0713

.00

29.9

025

.50

27.8

681

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2.50

II49

.50

51.0

097

.25

43.3

586

.50

13.3

54.

0013

.20

28.2

031

.50

12.9

179

.29

1.25

IV49

.50

49.0

099

.55

38.0

088

.50

13.4

83.

4010

.60

24.2

025

.00

11.7

780

.16

1.34

V50

.50

50.0

010

4.40

48.1

588

.00

13.5

53.

6114

.30

33.9

021

.50

43.3

690

.12

2.09

VI

51.0

051

.00

131.

2053

.75

93.5

014

.20

3.55

12.0

028

.50

24.5

023

.17

81.5

85.

84V

II49

.50

50.5

010

5.75

38.7

589

.50

15.0

53.

8913

.10

33.1

027

.00

10.7

279

.16

0.92

VII

I50

.00

50.5

014

1.95

55.3

093

.50

17.7

55.

0114

.80

39.7

040

.00

49.9

282

.95

3.17

IX50

.50

50.5

010

1.85

34.0

090

.50

9.95

3.89

11.8

023

.30

24.0

019

.80

77.6

12.

17X

50.5

050

.50

105.

2541

.90

91.5

013

.15

4.16

15.2

026

.00

18.5

023

.00

81.2

42.

36X

I51

.50

52.0

011

2.30

32.8

091

.00

12.9

54.

3014

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30.7

034

.00

47.2

384

.47

4.34

XII

65.0

066

.67

176.

6710

1.50

94.3

315

.40

6.02

15.0

530

.81

33.0

032

.96

82.8

63.

69X

III

50.0

051

.00

117.

3049

.80

89.0

010

.25

4.10

17.0

020

.90

18.5

026

.99

79.2

24.

00X

IV51

.00

51.0

015

7.80

58.8

087

.50

14.8

24.

3614

.00

28.7

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.00

43.0

783

.15

8.17

BH

M –

Bro

wn

husk

mat

urity

GENETIC DIVERSITY IN INBRED LINES OF MAIZE

32 [Vol. 2. No. 1 & 2]

weight in clusters IV and X, XIII, for grain yield per hectarein clusters VII and VIII, for shelling percentage in clusterIX and V and for fodder yield in clusters VII and IV.

However, it is always desirable to look for genotypeshaving more than one desirable trait and belonging todifferent clusters as in case of clusters XII, which is beinggrouped with genotypes for days to 50 percent tasseling,days to 50 percent silking, plant height, ear height, days to75 percent brown husk maturity and ear girth. Whereas,cluster VIII possessed genotypes with high number of kernelrows per ear, number of kernels per row and grain yield/hectare.

REFERENCES

Arunachalam, V., Bandopadhya, A., Nigam, S.N. and Gibbons, R.W.(1984). Heterosis in relation to genetic genetic divergence andspecific combining ability in groundnut. (Arachis hypogaea L.).Euphytica. 33: 33-39.

More, A.J., Bhoite, K.D. and Pardeshi, S.R. (2006). Genetic diversitystudies in forage maize (Zea mays L.). Res. Crops. 7(3): 728-730.

Singh, P., Sain, D., Dwivedi, V.K., Kumar, Y. and Sangwan, O. (2005).Genetic divergence studies in maize (Zea mays L.). AnnalsAgri. Bio. Res. 10 (1): 43-46.

Singh, R.K. and Chaudhary, B.D. (1977). Biometrical Methods inQuantitative Genetic Analysis. Kalyani Publishers, New Delhi,p.266.

WALI ET AL


Weed management in quality protein maize (Zea may L.) under rainfedconditions of southern Rajasthan

DILIP SINGH, A.K. SINGH1 C.M. PARIHAR1, S.L. JAT1 AND ASHOK KUMAR1

AICRP on Maize, Maharana Pratap University of Agriculture and Technology, Udaipur 313 001

ABSTRACT

The field experiment was conducted during rainy season of 2012 at Udaipur to compare the different weed controlpractices in quality protein maize. Minimum intensity and dry matter of grassy weeds and sedges were found with twohand weeding treatment. However, weed intensity of broad leaf weeds was minimum under pre-emergence applicationof atrazine 0.5 kg/ha. The highest quality protein maize grain yield was recorded with two hand weeding. However,among different treatments, pre-emergence application of atrazine 0.5 kg/ha was the best in terms of productivity andbenefits. The other approaches for management of weeds viz., use of organic mulch, and growing of cowpea as covercrop for suppressing weed growth could not prove fruitful for weed management and enhancing productivity ofquality protein maize.

Key words: Quality protein maize, Weed management

Maize, an important cereal crop is mainly consumedas staple food in various forms in southern Rajasthan.Besides this, maize is a main ration for poultry birds andits stover is used as fresh or dry fodder. In recent pasthigh yielding single cross hybrids of quality proteinmaize were developed by addition of opaque-2 mutantgene with higher lysine and tryptophane contents(Prasanna et al., 2001). This assumes a great significancein overcoming problem of malnutrition in tribal populationof southern Rajasthan. Weeds compete with crop plantsfor nutrients, moisture, sunlight and space, therebyreduce crop yield to the extent of 50-80 percent (Chopraand Chopra, 2010). Therefore, it seems that there is needto give more emphasis on weed management forenhancing productivity of quality protein maize duringkharif season.


The field experiment was conducted during kharif2012 at Instructional farm, Rajasthan College ofAgriculture Udaipur, which is situated in the lap ofAravali hills at 24035’ N latitude and 74042’ E longitudewith an altitude of 579.5 meters above mean sea level.The soil of the experimental site was clay loam in texture,slightly alkaline in reaction (pH 7.8), medium in available

nitrogen (275.1 kg/ha), phosphorus (12.5 kg/ha) and highin potassium (301.1 kg/ha) status. The experimentcomprising 8 treatment combinations (Atrazine 0.5 kg/ha as pre-emergence; Atrazine 0.5 kg/ha at 20 days aftersowing (DAS); Pendimethalin 1.0 kg/ha pre-emergence,Organic mulch 6 t/ha; Maize + cow pea (2 row) as covercrop; One hand weeding at 20 DAS; Two hand weedingat 20 and 40 DAS and weedy check) were laid out inrandomized block design and replicated four times. Asper treatment, atrazine and pendimethalin were appliedas pre or post emergence with knapsack sprayer havingflat fan nozzle using 350 L water/ha for spray. The seedwas dibbled at a spacing of 25 cm in each row made at 60cm. Thinning was done at15 days after sowing in orderto maintain the optimum plant population. The crop wasfertilized with recommended dose of fertilizers and raisedunder rainfed conditions. Net returns and B:C ratio were

1Directorate of Maize Research, Pusa Campus,New Delhi 110 012Corresponding author Email: [email protected]

Table 1. Important weed flora in maize field

Grassy weeds Broad leaf weeds Sedges

Echinochloa Phyllanthus niruri Cyperus rotunduscrusgalli (L.) Hook f. L.Echinochloa Digera arvensis —colonum (L.) Forsk.Cynodon Commelinadactylon (L.) benghalensis L.

Trianthemaportulacastrum L.Partheniumhysterophorus L.


34 [Vol. 2. No. 1 & 2]Ta

ble

2. E

ffec

t of

wee

d m

anag

emen

t pr

actic

es o

n in

tens

ity a

nd d

ry w

eigh

t of

div

erse

wee

d flo

ra i

n ra

infe

d kh

arif

mai

ze.

Tre

atm

ents

Wee

d in

tens

ity a

t 50

DA

S (p

er m

2 ar

ea)

Wee

d in

tens

ity a

t ha

rves

t (p

er m

2 ar

ea)

W

eed

dry

mat

ter

at 5

0 D

AS

(per

m2

area

)

Gra

ssy

wee

dsB

road

lea

f w

eed

Sedg

esG

rass

y w

eeds

Bro

ad l

eaf

wee

dSe

dges

Gra

ssy

wee

dsB

road

lea

f w

eed

Sedg

es

Atr

azin

e 0.

5 kg

/ha

PE51

(4.2

)6.

7(2.

7)5.

0(2.

3)17

(4.2

)5.

3(2.

4)8.

0(2.

9)6.

81.

30.

10

Atr

azin

e 0.

5 kg

/ha

20 D

AS

135(

6.7)

15.0

(3.9

)5.

0(2.

3)35

(6.0

)14

.0(3

.8)

8.3(

3.0)

17.5

3.0

0.11

Pend

imet

halin

1.0

kg/

ha P

E91

(5.5

)12

.3(3

.6)

4.3(

2.2)

25(5

.1)

15.0

(3.9

)7.

7(2.

9)11

.42.

70.

12

Org

anic

mul

ch 6

t/ha

241(

9.0)

45.0

(6.7

)5.

0(2.

3)69

(8.3

)40

.0(6

.4)

8.3(

3.0)

32.2

9.5

0.12

Mai

ze +

cow

pea

(2

row

) as

cov

er c

rop

270(

9.5)

64.0

(8.0

)6.

0(6.

0)81

(9.0

)62

.7(7

.9)

8.0(

2.9)

38.3

12.6

0.12

One

han

d w

eedi

ng a

t 20

DA

S14

1(6.

9)45

.3(6

.8)

3.0(

1.9)

40(6

.4)

42.0

(6.5

)7.

3(2.

8)18

.29.

30.

08

Two

hand

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ding

at

20 a

nd 4

0 D

AS

46(4

.0)

10.0

(3.2

)2.

3(1.

7)14

(3.8

)12

.0(3

.5)

5.7(

2.5)

7.5

2.1

0.07

Wee

dy c

heck

360(

11.0

)76

.3(8

.8)

5.0(

2.3)

104(

10.2

)70

.3(8

.4)

2.3(

2.3)

42.3

16.3

0.10

SEm

±0.

034

0.03

20.

022

0.03

80.

033

0.01

30.

155

0.07

40.

002

CD

(P=0

.05)

0.10

20.

096

0.06

60.

117

0.10

10.

041

0.47

00.

223

0.00

6

Figu

re i

n pa

rent

hesi

s in

dica

tes

orig

inal

val

ueFi

gure

out

side

par

enth

esis

indi

cate

s “X

tran

sfor

med

val

ue

Tabl

e 3.

Eff

ect o

f wee

d m

anag

emen

t pra

ctic

es o

n cr

op p

heno

logy

, yie

ld a

nd e

cono

mic

s

Trea

tmen

tsD

ays

to 5

0% s

ilkin

gC

obs/

plot

Stov

er y

ield

(q/h

a)G

rain

yie

ld (q

/ha)

Net

retu

rns

(A/h

a)B

:C ra

tio

Atra

zine

0.5

kg/

ha P

E (p

re-e

mer

genc

e)54

.083

.062

.440

.336

370

2.21

Atra

zine

0.5

kg/

ha 2

0 D

AS

54.3

78.0

44.2

30.4

2279

71.

39

Pend

imet

halin

1.0

kg/

ha P

E53

.378

.048

.532

.425

550

1.54

Org

anic

mul

ch 6

t/ha

54.0

75.0

32.5

24.4

1412

30.

84

Mai

ze +

cow

pea

(2 ro

w) a

s co

ver c

rop

54.0

70.0

29.3

22.4

1149

70.

68

One

han

d w

eedi

ng a

t 20

DA

S54

.078

.043

.530

.317

857

0.84

Two

hand

wee

ding

at 2

0 an

d 40

DA

S54

.386

.064

.842

.429

243

1.12

Wee

dy c

heck

54.7

40.0

21.6

14.4

2597

0.16

SEm

±0.

186

0.34

60.

349

0.33

3—

—

CD

(P=0

.05)

NS

1.05

01.

058

1.00

9—

—

SINGH ET AL


calculated on basis of prevailing market prices of inputsand produce.


Weed intensityMinimum weed intensity of grassy weeds and

sedges at 50 days after sowing and at harvest stages wererecorded under two hand weeding treatment (Table 2).However, at same stages minimum intensity of broadleaves weeds were recorded with atrazine 0.5 kg/ha (PE)application, which were significantly lower comparedto rest of the treatments. Application of atrazine 20 DAS(PE), pendimethalin, use of organic mulch @ 6 t/ha, andgrowing of cow pea as cover crop for suppressing weedgrowth did not prove fruitful for weed control in rainfedquality protein maize crop.

Weed dry matterApplication of atrazine 0.5 kg/ha (PE) which was

significantly lower as compared to rest of the treatments(Table 2). The next best treatment in terms of reducingweed dry matter was two hand weeding at 20 and 40DAS. The other new approaches for management ofweeds failed to suppress weed growth thus recordedhigher weed dry matter compared to pre emergenceapplication of atrazine 0.5 kg/ha and two hand weedingtreatments of weed control.

Yield attributes and yieldThe highest number of cobs/plot and grain and

stover yields of maize were recorded under two hand

weeding treatment, which were significantly higher overrest of the treatments (Table 3). Among the remainingtreatments, pre-emergence application of atrazine 0.5 kg/ha proved to be the best in terms of yield attributes andyield. The reduced competition for resources under thesetreatments due to lower weed population and dry mattercompared to other treatments led to higher yield underatrazine application and pre-emergence Resultscorroborated with the findings of Sinha et al. ( 2005).

EconomicsThe highest net returns and B:C ratio were recorded

with the pre-emergence application of atrazine 0.5 kg/ha,which was more than rest of the treatments, proved bestand profitable which was more than rest of the treatments(Table 3). Economically as well in terms of yield the newapproaches of weed control were not proved profitablecompared to existing practices.

REFERENCES

Chopra, N.K. and Chopra, N. (2010). Evaluation of tillagesystem and herbicides under rice (Oryza sativa)-wheat(Triticum aestivum) cropping system. Indian J. Agron.55(4): 304-307.

Prassanna, B.M., Vasal, S.K., Kassahun, B. and Singh, N.V. (2001).Quality protein maize. Curr. Sci. 81: 1308-1319.

Sinha, S.P., Prasad, S.M. and Singh, S.J. (2005). Nutrient utilizationby winter maize (Zea mays) and weeds as influenced byintegrated weed management. Indian J. Agron. 50(4): 303-304.

WEED MANAGEMENT IN QUALITY PROTEIN MAIZE

36 [Vol. 2. No. 1 & 2]

Evaluation of zinc fortified fertilizer in maize (Zea mays L.)

G. MANJULATHA

Agricultural Research Station, Acharya N.G. Ranga Agricultural University, Karimnagar

ABSTRACT

A field experiment was conducted to evaluate the zinc fortification of fertilizers in maize crop (DHM 117) for twoseasons of rabi 2010-11 and kharif 2011 at Karimnagar on red sandy loam soils. The results indicated that there was nosignificant difference in maize yield and yield attributes with different fortified fertilizer treatments during rabi 2010-11 andkharif 2011. However, among different treatments, the higher grain yield was recorded with application of 14:35:14 complexfertilizer fortified with AvZnO @ 0.5% compared to all other fertilizer treatments. Among fertilizers (DAP, 20:20:00:15 and14:35:14 complex) fortification treatments, the maize grain yield was higher when fertilizers was fortified with AvZnO @ 0.5%followed by zinc sulphate mono hydrate @ 0.5% fortification than non-fortified fertilizer application treatments in anyfertilizer. The 14:35:14 complex fertilizer fortified with AvZnO @ 0.5% recorded 12.4 and 9.2 % higher grain yield respectivelyduring rabi 2010-11 and kharif 2011 than compared to maize yield with application of same complex fertilizer withoutfortification. The mean zinc content in kernel recorded higher in maize crop applied with 14:35:14 complex fertilizer fortifiedwith AvZnO @ 0.5%. Higher zinc content in soil after kharif 2011 was recorded with application of 14-35-14 complex fertilizerfortified with AvZnO @ 0.5%. This was followed by zinc content in soil with application of same complex fertilizer fortifiedwith zinc sulphate mono hydrate @ 0.5% (1.75 mg/kg of soil) and application of 20:20:00:15 complex fertilizer fortified withAvZnO @ 0.5% (1.66 mg/kg of soil).

Key words: Fortification, Maize, Yield and yield attributes, Zinc content

Maize is high input responsive crop. Besides N,P,K,micronutrient, zinc also plays important role in growth andproduction of maize. Nearly 50% of the cereal cultivatedsoils have been reported containing low amount of plantavailable zinc concentration due to low organic matter, soilmoisture and high levels of pH and CaCo3. Soils with lowplant available zinc adversely affects maintenance of bettercrop yield and nutritional quality of harvested grains (Rashidand Ryan,2004). Maintenance of sufficient amount of plantavailable zinc in soils appears to be a pre-requisite. Thiscan be effectively realized by developing the new geniticallybiofortified plant genotypes and the application of zincfertilizers i.e. agronomic biofortification, (Bouis,1996). Thesestrategies provide cost-effective and sustainable solutionsto the global zinc deficiency problem. The plant breedingstrategy is a long term process. In addition, the success ofthe plant breeding approach might be affected by adversesoil chemical factors such as extreme pH values, low organicmatter and low soil moisture which limit plant availabilityand root uptake of zinc in soils. In this context, to addressthe zinc deficiency problem agronomically by fertilizerfortification, the present study was planned to evaluatethe effect of zinc fortified fertilizers on maize crop.


The field experiment was conducted during rabiseason of 2010-11 and kharif 2011 at Karimnagar situatedat 79o15 East longitude, 18o 30 north latitude with anelevation of 259.15 m above mean sea level. It is coveredunder Northern Telangana Agro Climatic Zone of AndhraPradesh which falls under semi arid climate with dry hotsummer and cold winters. The rain fall during rabi 2010-11was 219.5 mm in 16 rainy days and 559.2 mm in 32 rainydays was received from July to November during kharif2011. The soil of the experimental field is red sandy loam intexture, neutral in reaction and low in zinc content (0.218mg/kg of soil). The experiment was laid out in RBD designwith 10 treatments and replicated thrice (Table 1). The maizehybrid, DHM 117 was sown on 16 December 2012 duringrabi 2010-11and harvested on 30 March 2011 and duringkharif 2011, the sowing was taken up on 02 July 2011 andharvested on 10 November 2011. Uniform culturaloperations and plant protection measures were adopted inall the treatments. This spacing of 75 cm x 20 cm andcommon fertilizer dose of 240-60-50 kg and 200-60-50 NPK/ha was applied respectively during rabi 2010-11 and kharif



Table 1 : Treatment details

T1 Recommended dose of ‘P’ as basal through DAP + Recommended dose of ‘N’ as basal as 3 splits + Recommended dose of ‘K’as basal (50%) and at flowering (50%).

T2 Recommended dose of ‘P’ as basal through DAP is to be fortified with Zinc Sulphate Monohydrate @ 0.5% (i.e. 70 kg DAPis to be fortified with 1 kg Zinc Sulphate Mono) + Recommended ‘N’ and ‘K’ as in T1.

T3 Recommended dose of ‘P’ as basal through DAP is to be fortified with AvZnO @ 0.5% (i.e.70 kg DAP is to be fortified with0.5 L AvZnO) + Recommended ‘N’ and ‘K’ as in T1.

T4 Recommended dose of ‘P’ as basal through 20:20:00:15 complex + Recommended dose of N’ as basal and 3 splits +Recommeded dose of ‘K’ as basal (50%) and at flowering (50%).

T5 Recommended dose of ‘P’ as basal through 20:20:00:15 is to be fortified with Zinc Sulphate Mono hydrate @ 0.5% (i.e. 160kg 20:20 is to be fortified with2.275 kg Zinc Sulphate Mono) + Recommended ’N’ and ‘K’ as in T1.

T6 Recommended dose of ‘P’ as basal through 20:20:00:15 is to be fortified with AvZnO @ 0.5% (i.e. 160 kg 20:20is to befortified with 1.14 L AvZnO) + Recommended ‘N’ and ‘K’ as in T1.

T7 Recommended dose of ‘P’ as basal through 14:35:14 + T8Recommended dose of ‘N’ as basal and 3 splits + Recommededdose of ‘K’ as basal (50%) and at flowering (50%).

T8 Recommended dose of ‘P’ as basal through 14:35:14 is to be fortified with Zinc Sulphate Mono hydrate @ 0.5% (i.e. 92 kg14:35:14 is to be fortified with 1.3 kg Zinc Sulphate Mono) + Recommended ‘N’ and ‘K’ as in T1.

T9 Recommended dose of ‘P’ as basal through 14:35:14 is to be fortified with AvZnO @ 0.5% (i.e. 92 kg 14:35:14 is to befortified with 0.65L AvZnO) + Recommended ‘N’ and ‘K’ as in T1.

T10 Recommended customised fertilizers Grade 18:27:6:5:0.5 as basal and 14:00:21 as Top Dressing.

2011 with entire P as basal, recommended dose of N in fourequal splits and recommended dose of K as basal (50%)and at flowering (50%) by adjusting the requirement ofdifferent fertilizers. The fortification rate followed was zincsulphate monohydrate @ 14.2 kg/ton of fertilizer and AvZnO@ 7.12 l/ton of fertilizer. The observations on yield andyield parameters were recorded. The post harvest soil andkernel sample were collected treatment wise and analysisfor zinc content in soil and kernel by atomic absorptionspectrophotometer was carried out.


Growth and yield attributes of maizeThe plant height at harvest, cob length and girth,

number of rows/cob and number of grains/row of cob andsingle cob weight recorded during rabi 2010-11 and kharif2011 could not show significant differences betweendifferent fortification treatments under test. (Table 2).However, when compared between fortified and non-fortified fertilizers, all the attributes recorded higher valueswith application of fertilizers (DAP, 20:20:00:15 or 14-35-14complex ) fortified with AvZnO @ 0.5% followed byfortification with Zinc sulphate mono hydrate @ 0.5% thanfertilizers application alone without fortification during boththe seasons Kanwal et al. (2010) also found similar findings.

Grain yieldThe grain yield of different treatments (Table 3)

indicated that there is no significant statistical difference

with different fertilizer and fortification treatments duringrabi season of 2010-11 and kharif 2011. However, amongdifferent treatments, the grain yield recorded the highest(9,448 kg/ha during rabi 2010-11 and 9011 kg/ha in kharif2011) with application of 14:35:14 complex fertilizer fortifiedwith AvZnO @ 0.5% which was significantly highercompared to all other fertilizer treatments. The grain yieldin with 14:35:14 complex fertilizer fortified with AvZnO @0.5% were 12.4 and 9.2% higher respectively during rabi2010-11 and kharif 2011 application of same complexfertilizer without fortification and 2.9 and 3.9% increase inyield, respectively during rabi 2010-11 and kharif 2011was recorded with zinc sulphate mono hydrate @ 0.5%fortified same complex fertilizer application over non fortifiedsame complex fertilizer. The grain yield with 20:20:00:15complex fertilizers fortified with AvZnO @ 0.5% resulted in13.5 and 12% increase in yield respectively during rabi2010-11 and kharif 2011 than non-fortified same complexfertilizer application and 4 and 6.6 % higher yield resultedwith same complex fertilizer fortified with zinc sulphate monohydrate @ 0.5 % respectively during rabi 2010-11 and kharif2011 over non fortified same complex fertilizer applicationalone.

While the application of DAP fortified with AvZnO @0.5% recorded an increase of 8.4 and 7.4% over non fortifiedsame fertilizer application respectively during rabi 2010-11and kharif 2011. The percent increase of 2.1 and 4.6 wasobserved with application of same fertilizer fortified withzinc sulphate mono hydrate @ 0.5% compared to non

ZINC FORTIFIED FERTILIZER IN MAIZE

38 [Vol. 2. No. 1 & 2]Ta

ble

2. Y

ield

attr

ibut

es o

f m

aize

as

inf

luen

ced

by f

ortif

icat

ion

of f

ertil

izer

s

Tre

atm

ents

Plan

t he

ight

at

Cob

len

gth

(cm

)C

ob g

irth

(cm

)N

o. o

f ro

ws/

No.

of

kern

els/

Sing

le c

obha

rves

t (c

m)

cob

row

of

cob

wt

(g)

Rab

iK

hari

fR

abi

Kha

rif

Rab

iK

hari

fR

abi

Kha

rif

Rab

iK

hari

fR

abi

Kha

rif

201

0-11

2011

2010

-11

2011

2010

-11

2011

2010

-11

2011

2010

-11

2011

2010

-11

2011

RD

F as

DA

P21

2.0

199.

021

.317

.516

.715

.515

.013

.841

.431

.027

3.8

180.

6R

DF

as D

AP

Forti

fied

with

Zin

c21

8.2

200.

221

.617

.817

.015

.815

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.043

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185.

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lpha

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ono

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@ 0

.5%

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F as

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rtifie

d w

ith22

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213.

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16.5

15.6

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5)N

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SN

SN

SN

SN

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S

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Gra

in a

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ield

of m

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forti

ficat

ion

of fe

rtiliz

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(kg

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Gra

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yie

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738,

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20:0

0:15

For

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inc

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15 F

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:14

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10,6

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35:1

4 Fo

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339,

448

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8:27

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8,84

87,

328

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709

717

983

718

LSD

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5)N

SN

SN

SN

S

MANJULATHA


fortified DAP application alone. Further, the use of complexfertilizer of 14:35:14, 20:20:00:15 and DAP fortified withAvZnO @ 0.5% recorded higher maize grain yield of 16.8,16.2 and 10.9% respectively during rabi 2010-11 and 18.7,18.0 and 12.6% respectively during kharif 2011 as comparedto the use of customized fertilizer grade 18:27:6:5:0.5 as basaland 14:00:21 as top dressing. The superiority of fertilizers(DAP, 20:20:00:15 complex and 14:35:14 complex) fortifiedwith AvZnO or zinc sulphate monohydrate when comparedto non fortified same fertilizer application may be attributedto the pronounced role of micronutrient zinc in the enzymaticaction, photosynthesis, translocation of carbohydrates andassimilation etc., which have improved the yield attributesof cob length, girth, no. of rows/cob, no. of kernels/rowetc., as is evident from the table which inturn resulted inincreased cob and grain yield in zinc fortified treatmentswhen compared to non-fortified fertilizer application.

Cob yieldThe cob yield of maize also indicated non-significant

difference between different fortification treatments andfollowed the similar trend as that of grain yield. Amongdifferent treatments, however higher cob yield was recordedwith application of 14:35:14 complex fertilizer fortified withAvZnO @ 0.5% (11,033 and 10,638 kg/ha respectively duringrabi 2010-11 and kharif 2011 ) over all other fertilizertreatments. This was followed by application of 20:20:00:15complex fertilizer fortified with AvZnO @ 0.5% (10875 and10556 kg/ha respectively during rabi 2010-11 and kharif2011). Among fertilizers (DAP, 20:20:00:15 and 14:35:14complex) fortification treatments, the maize cob yield washigher when fertilizers was fortified with AvZnO @ 0.5%followed by zinc sulphate mono hydrate @ 0.5% fortification

than compared to non-fortified fertilizer applicationtreatments in any fertilizer (Table 3).

Zinc content in soilAt the end of two seasons, the higher value of zinc

content in soils was found in treatments where fertilizerswere fortified with AvZnO @ 0.5% followed by ZnSo4monohydrate @ 0.5% than fertilizer application alonewithout fortification and also over the initial soil zinc level.The zinc content in soil also improved when fertilizers arefortified with zinc sulphate monohydrate @ 0.5% comparedto non fortified fertilizer application. The application of DAPand complex fertilizer 14:35:14 and 20:20:00:15 alone withoutfortification recorded lower zinc content in soil than initialsoil zinc content in soils indicating uptake of zinc by maizecrop from the soil leading to depletion of initial soil zinccontent by fertilizer application alone treatment withoutmicronutrient application during both the seasons (Table 4).

Zinc content in kernelAll the fertilizer applications (DAP, 14:35:14 and

20:20:00:15) fortified with AvZnO @ 0.5% recorded highervalues of zinc content in kernels than fertilizer applicationfortified with zinc sulphate monohydrate @ 0.5% which inturn recorded higher values over non fortified fertilizerapplication alone (Table 5). Welch (2002) and Furlani et al.(2005) also reported similar findings.

The zinc content in maize kernel and soil increasedwhen applied with any fertilizer DAP or 20:20:00:15 or 14-35-35 complex, fortified with AvZnO @ 0.5% followed byapplication of fertilizers fortified with zinc sulphatemonohydrate compared to non fortified fertilizer application

Table 4. Zinc content in soil and maize kernel as influenced by fortification of fertilizers

Treatments Zinc content in soil Zinc content in kernel( mg/kg of soil ) mg/kg of kernel sample (PPM)

Rabi 2010-11 Kharif 2011 Rabi 2010-11 Kharif 2011

RDF as DAP 0.134 0.12 8.7 10.4

RDF as DAP Fortified with Zinc Sulphate Mono hydrate @ 0.5% 0.304 1.08 10.2 15.4

RDF as DAP Fortified with AvZnO @ 0.5% 0.402 1.38 11.1 19.3

RDF as 20:20:00:15 complex 0.210 0.15 10.1 11.3

RDF as 20:20:00:15 Fortified with Zinc Sulphate Mono hydrate @ 0.5% 0.350 1.20 11.0 17.8

RDF as 20:20:00:15 Fortified with AvZnO @ 0.5% 0.394 1.66 14.3 18.7

RDF as 14:35:14 complex 0.212 0.19 14.3 14.4

RDF as 14:35:14 Fortified with Zinc Sulphate Mono hydrate @ 0.5% 0.350 1.75 15.4 20.1

RDF as 14:35:14 Fortified with AvZnO @ 0.5% 0.422 2.04 21.8 23.4

Recommenede customised fertilizers Grade 18:27:6:5:0.5 0.320 1.03 10.4 12.8as basal and 14:00:21 as Top Dressing.

Initial Zinc content in soil 0.218

ZINC FORTIFIED FERTILIZER IN MAIZE

40 [Vol. 2. No. 1 & 2]

even though the grain yield of maize and yield attributes indifferent treatments indicated no significant and statisticaldifference with different fertilizer and fortificationtreatments. The findings of Maftoum and Karimian (1989)confirmed the results.

REFERENCES

Bouis, H.E. (1996). Enrichment of food staples through plantbreeding: A new strategy for fighting micronutrientmalnutrition. Nutr. Rev. 54: 131-137.

Furlani A.M.C., Furlani, P.R., Meda, A.R. and Durate, A.P. : Efficiencyof Maize cultivars for zinc uptake and use. Sci. Agric. 62:264-273.

Harris, A. Rashid, Miraj, G., Arif, M. and Shah, H. (2007). On farmseed priming with zinc sulphate-A cost effective way to increasethe maize yields of resources-poor farmers. Field Crops Res.110: 119-127.

Kanwal, S., Rahmentullah, M.A. and Bakhat, H.F.S.G. (2010). Zincpartitioning in maize grain after soil fertilization with zincsulfate. Int. J. Agric. Biol. 12: 299-302.

Maftoum, M. and Karimian, N. (1989). Relative efficiency of twozinc sources for maize (Zea maysl.) in two calcareous soilsfrom an arid area of Iran. Agronomie 9: 771-775.

Rashid, A and Ryan, J. (2004). Micronutrient constraints to cropproduction in soils with Mediterranean- type characterisitics: AReview. J. Plant Nutr. 27: 959-975.

Welch, R.M. (2002). The impact of nutrients in food crops on globalhuman health. Plant Soil 247: 83-90.

MANJULATHA


Forage production potential of various maize cultivars grown forbaby corn

M. SHANTI, R. BALAJI NAIK, T. SHASHIKALA AND CH. CHIRANJEEVI

AICRP on Forage Crops, ARI, Rajendranagar, Hyderabad 500 030

ABSTRACT

The experiment was conducted during kharif season to study the baby corn and fodder production potential offifteen maize varieties. These include varieties developed for fodder, baby corn, green cob as well as for seed. Thehighest baby cob yield was recorded by ‘Harsha’-11 followed by ‘Vivek-17’, Him-129, Bioseed-1 and ‘Vivek-11’,.Similarly, higher green fodder yields of baby corn were found in Vivek-11, Him-129, Varun, Ashwini, Baby Corn-1 andJ-1006. The mean crude protein content of husk decreased from 13.97% (first cob harvest) to 9.04% (third cob harvest)while it increased from 9.19% to 10.94% in baby cobs, respectively indicating channelization of protein to reproductiveparts of plant with increasing age of crop. The more monetary return was worked out from baby corn genotypes thanother genotypes and baby corn genotypes also provided nutritious fodder through stalks and husk to cattle.

Key words: Baby corn, Crude protein, Economics, Fodder potential, Varieties

Maize is a crop with increasing production everyyear especially in the state of Andhra Pradesh. Maize iscultivated in 7.83 lakh hectares with a production of 27.6lakh tonnes in Andhra Pradesh during 2009-10 (DOES,2010). Irrespective of the stage of harvest the rest of theplant is ideally used as fodder for cattle. Majority offarmers grow any variety of maize for baby corn. It hasbeen a practice by farmers in peri-urban areas to meetthe local baby corn demand. But these genotypes don’tprovide the better quality baby cobs and nutritiousfodder. Hence, an experiment to understand the babycorn and fodder production potential of various cultivarswhen grown for baby corn in peri-urban areas wasplanned.


In a field study fifteen varieties of maize viz., ‘Vivek-9’, ‘Vivek-11’, ‘Vivek-15’, ‘Vivek-17’, ‘Baby corn-1’,‘Ashwini’, ‘Bioseed-1’, ‘Madhuri’, ‘Harsha’, ‘Him-129’,‘H-2187’, ‘Varun’, ‘HQPM-1’, African Tall and J-1006developed for different uses i.e., grain, green cob, babycorn as well as fodder varieties were tested for babycorn potential and their subsequent utilization as fodder.

The experiment was laid out during kharif seasonat Hyderabad in a randomised block design with fifteen

varietal treatments in three replications. Varieties weregrown in 5 m X 4 m size plots under spacing of 45 cm X20 cm and with recommended dose of fertilization(120:80:50 N:P2O5:K2O). Standard package of practiceswere adopted in crop production. All the fifteen varietieswere sown for baby corn and the parameters viz.,earliness of baby cob appearance, baby cobs produced,yield of baby cob, yield of green fodder at harvest ofbaby cob and crude protein green fodder were studied.Economics was worked out on the basis of prevailingmarket prices of input and output.


Baby corn and green fodder yieldHighest yield of baby corn was observed in Harsha

while those of Him-129, Vivek-17, Bioseed-1 and Vivek-11 were all on par (Table 1). Most of the varietiesexclusively released for baby corn gave highest babycorn yields ranging from 66.04 q/ha (Vivek-11) to 68.96q/ha (Harsha). However, some of the varieties like Vivek-9, Baby corn-1, Vivek-15 performed poorly which couldbe attributed to their non-adoptability to the local agro-climate. Traditional maize varieties like ‘Ashwini’ (50.43q/ha), ‘Madhuri’ (50.75 q/ha), ‘Varun’ (49.18), ‘BH-2187’(49.04) recorded commendable yields next to baby cornvarieties,while lowest yields of baby corn were observed


42 [Vol. 2. No. 1 & 2]

Table 1. Baby corn and green fodder yield of different varieties

S.No. Cultivar Baby corn yield (q/ha) Green fodder yield (q/ha)

1 Vivek-11 63.04 275.93

2 Baby corn-1 56.72 259.26

3 Ashwini 50.43 268.52

4 Vivek-17 68.02 157.41

5 Bioseed -1 60.16 203.70

6 Vivek-9 45.93 194.44

7 Maduri 50.75 175.93

8 Harsha 68.96 203.70

9 Him -129 66.31 240.74

10 Vivek-15 58.00 166.67

11 BH-2187 49.04 222.22

12 Varun 49.18 282.41

13 HQPM-1 35.66 166.67

14 African tall 29.09 180.56

15 J-1006 42.50 236.11

S.Em(+) 3.24 24.61

C.D.(0.05) 9.84 74.65

C.V (%) 8.7 16.1

Table 2. Crude protein in stalks (%) at different stages

S.No. Cultivar At harvest of At harvest of At harvest of At harvest of1st cob 2nd cob 3rd cob 4th cob

1 Vivek-11 13.13 9.19 7.00 -

2 Baby corn-1 10.94 10.72 9.84 7.66

3 Ashwini 7.44 6.56 6.13 -

4 Vivek-17 11.81 9.63 7.00 6.78

5 Bioseed-1 12.03 6.56 5.91 -

6 Vivek-9 8.75 8.53 7.00 -

7 Maduri 8.75 7.00 6.13 -

8 Harsha 9.84 7.66 7.22 -

9 Him-129 7.66 7.00 - -

10 Vivek-15 9.84 6.78 - -

11 BH 2187 10.06 - - -

12 Varun 10.28 7.22 - -

13 HQPM-1 4.81 - - -

14 African tall 10.06 6.13 - -

15 J-1006 8.97 7.88 7.44 -

SHANTI ET AL


in ‘HQPM-1’ (35.66 q/ha) and fodder varieties, ‘AfricanTall’ (29.09 q/ha).

There was a significant variation in green fodderyield among the fifteen varieties. Higher green fodderyields were found in order of ‘Varun’ > ‘Vivek-11’ >‘Ashwin’ > ‘Baby Corn-1’ > ‘Him-129’ and ‘J-1006’.However, these were all on par with each other. Lowestyields of green fodder were recorded in ‘Vivek-17’followed by ‘HQPM-1’ and ‘Vivek-15’. The exclusivefodder varieties followed by ‘African Tall’ and ‘J-1006’recorded 180.56 and 236.11 q/ha, respectively. Similarresults were also reported by Ashoka et al. (2009).Similarly, Sahoo (2001) also reported highest baby cornand green fodder yields in varieties ‘VL-16’ and Madhuri

while studying fodder potential of varieties of baby cornvarieties.

Crude protein content of green fodder and sheath (husk)of baby cob

The crude protein percent in stalks was highest(Table 2) at harvest of first baby cob ranging between4.81 (HQPM-1) to 13.13% (Vivek-11). However, withharvest of each cob the crude protein percent of stalksdeclined gradually indicating more partitioning ofprotein to reproductive parts of plant with age of crop.The variety Vivek-11, which recorded highest crudeprotein 8.75% at harvest of first cob and there after crudeprotein content reduced with succeeding harvesting.Similar decreasing trend with advancing age of crop was

Table 3. Crude protein content (%) in baby cobs and sheaths

Cultivar First pick Second pick Third pick Mean

Baby corn cobs

V-11 8.09 9.19 14.44 10.57

V-17 9.63 12.69 11.81 11.38

BC-1 9.19 12.25 10.94 10.79

Mean 8.97 11.38 12.40 10.91

Baby corn sheaths

V-11 14.88 10.06 8.75 11.23

V-17 12.69 13.13 10.72 12.18

BC-1 13.13 12.69 7.66 11. 6

Mean 13.57 11.96 9.04 11.52

Table 4. Economics of different cultivars

Cultivar Total cost of cultivation Income (A/ha)

Cob Green fodder Net income (A/ha) BC ratio

Vivek-11 14,729 63,040 27,593 75,904 6.15

Baby corn-1 14,729 56,720 25,926 67,917 5.61

Ashwini 15,633 50,430 26,852 61,649 4.94

Vivek-17 15,633 68,020 15,741 68,128 5.36

Bioseed -1 14,729 60,160 20,370 65,801 5.47

Vivek-9 14,729 45,930 19,444 50,645 4.44

Maduri 14,729 50,750 17,593 53,614 4.64

Harsha 14,729 68,960 20,370 74,601 6.06

Him -129 13,825 66,310 24,074 76,559 6.54

Vivek-15 13,825 58,000 16,667 60,842 5.40

BH-2187 12,921 49,040 22,222 58,341 5.52

Varun 13,825 49,180 28,241 63,596 5.60

HQPM-1 12,921 35,660 16,667 39,406 4.05

African tall 14,729 29,090 18,056 32,417 3.20

J-1006 14,729 42,500 23,611 51,382 4.49

FORAGE PRODUCTION POTENTIAL OF BABY CORN CULTIVARS

44 [Vol. 2. No. 1 & 2]

observed invariably in all varieties. However, it isimportant to note that crude protein % of Baby corn-1 isvery high even at harvest of third cob i.e., 9.84%. Thecrude protein % of high quality protein maize (HQPM-1) was lowest i.e, 4.8% which could be possibly due tomore partitioning of crude protein to the cob, a characterfor which it was developed.

The variation in crude protein percent of baby cobs(dehusked) and their respective sheaths (husk) wasanalysed in three popular baby corn varieties studied viz.,Vivek-11, Vivek-17 and Baby corn-1. The study showedthat there was a gradual decrease (Table 3) in crudeprotein content of husk from first pick to third pick i.e.,from 14.88% (first pick), 10.06% (second pick) and 8.75% (third pick) as in case of Vivek-11 and so in othervarieties Vivek-17 and Baby corn-1. On the contrary,the crude protein % of cob (dehusked) increasedgradually from first pick to third pick in the three babycorn varieties tested with mean values of 8.97 % (firstpick) < 11.38% (second pick) < 12.40 % (third pick).This indicates that the protein content of husk is beingchannelized to cob with advancing age of cob. This alsoinfers that with advancing age of crop (with each pick)the channelization of protein is increasing to thereproductive parts of plant (dehusked cob). This alsohighlights that the husk of cobs can also be efficientlyused as fodder owing to its high crude protein content.

Earliness of cob emergenceThe first baby cob emerged at 44 days in most of

the varieties viz., ‘Vivek-11’, ‘Baby corn-1’, ‘Vivek-17’,‘Bioseed-1’, ‘Madhuri’, ‘Him-129’, ‘Vivek-15’. The cobemergence was at 49 days in Ashwini, Harsha, BH-2187,Varun and J-1006. The fodder variety African tallregistered baby cob emergence at 72 day, while HQPM-1 recorded cob emergence at 62 day. In most of thevarieties the economic period of baby corn productionwas completed by 72-79 day.

Maximum number of four cobs was harvested from‘Baby corn-1’ and ‘Vivek-17’ while most of the varietiesyielded 3 baby cobs commendably. However, varieties‘BH-2187’, ‘HQPM-1’ yielded only single cob and did

not show potential for second cob bearing. The popularfodder varieties yielded two baby cobs. The studyrendered that baby corn picking was completed by 80days i.e., within 2 months twenty days, thereby renderingland free for next crop production. Having a crop of maizeas baby corn has proved very remunerative Basu et al.(2009).

EconomicsThe economics in terms of returns from baby corn

yields and green fodder yields were calculated (Table4). The net returns for Him-129 was highest. This varietyalso registered a B:C ratio of 6.54 but was closelyfollowed by ‘Vivek-11’ and ‘Harsha’. Varieties ‘BC-1’,‘Vivek-17’, ‘Bioseed-1’, ‘Vivek-15’, ‘BH-2187’recorded 5.52 while Varun recorded B:C Ratio between5.52 and 5.61. However lowest B:C ratios were recordedin fodder varieties African tall and J-1006 recorded 3.2and 4.49, respectively while HQPM-1 recorded 4.05.High monetary return was reported when maize wasgrown for baby corn by Nandal et al. (2010).

On the basis of experimentation it may be concludedthat baby corn genotypes not only gave more returnsbut also provided good quality fodder.

REFERENCES

Ashoka, P. Anand, S.R. Mudalagiriyappa Smitha, R. (2009). Effectof macro and micronutrients with organics on growth,quality, yield and economics of baby corn (Zea mays L.) inTungabhadra Command Area. Crop Res. 37(1/3): 15-18.

Basu, B. Kundu, C.K. Sanchita Mondai Pintoo BandopadhyayDe, D. K. (2009). Evaluation of forage production potentialof maize grown for baby corn and green cob under newalluvial zone of West Bengal. Indian Agriculturist 53(3/4):177-181.

DOES (2010) (52nd Edition), Directorate of Economics andStatistics, Govt. of A.P., Hyderabad.

Nandal, J.K. Vishal Gupta Partap, P.S. Tehlan, S.K. (2010).Potential of baby corn cultivation in crop diversification underrice-wheat cropping system. Indian Hort. 67 (Special Issue):276-278.

Sahoo, S.C. (2011). Yield and economics of baby corn (Zea maysL.) as affected by varieties and levels of nitrogen. RangeManagement and Agroforestry 32(2): 135-137.

SHANTI ET AL


Effect of tied ridging on soil moisture conservation and yield of maizeunder rainfed condition

K.H. PATEL, S.K. SINGH , A.S. BHANVADIA, P.M. PATEL AND S.M. KHANORKAR

Main Maize Research Station, Anand Agricultural University, Godhra 389001 (Panchmahals)

ABSTRACT

Higher soil moisture content was recorded under tied ridges sowing method as compared to flat bed. Plantheight, dry cob weight and total grain and fodder yield kg/ha were also superior in tied ridging between 2.0 m sowing,the the second best was tied ridging between 3.0 m, while tied ridging between 4.0 m was found to be less effective andit seems at par with flat bed (control). Maize sown on tied ridging at 2 m2 resulted in maximum grain and fodder yield.The tied ridging at 2.0 m, 3.0 m and 4.0 m interval resulted in 35.20%, 19.99% and 8.33% increase in grain yield andfodder yield was recorded 36.42%, 21.16% and 8.35% higher at Godhra, but in case of Dahod, it resulted in 63.79%,28.21% and 17.36% higher grain yield; and fodder yield was recorded 40.39%, 20.93% and 11.06% higher over flat bed(control), respectively. The highest net return F 24256/ha was found in 2 m interval tied ridging with 2.86 cost : benefitratio.

Key words: Economics, Maize, Rainfed, Soil moisture conservation, Tied ridges

Maize is generally grown in rainfed environments inthe developing world (FAO, 1978). The crop performanceis often constrained by water deficits in semi-arid regions.As a result, the crop frequently suffers from moisture stressat some stage during its growth period (Johnson et al.,1986) with the ultimate result of reduced yields. Substantialyield increases can be obtained through soil waterconservation and the efficient use of it by the crop. Theuse of tied ridges, as in-situ soil and water conservationtechnique, is known to be beneficial for increasing cropyields (Morin et al., 1984). Tied ridging is also known to beof importance in reducing runoff (Kowal, 1970) by helpinghold rain water on the soil, and thus giving it time to infiltrate(Macartney et al., 1971).

The yield has been found to vary depending on theamount and distribution of rainfall, soil type and the cropgrown. Limited information is available on the effect of tiedridges on improving yield of maize in India. Therefore, thestudy was conducted to evaluate the effect of tied ridgeson growth and yield of maize in rainfed area of Godhra(Panchmahals) and Dahod, Gujrat (India).


The experiment was conducted during kharif seasonfrom 2007 to 2009 at the Main Maize Research Station,

Godhra and Hill Millet Research Station, Dahod situated inAnand Agricultural University. The test variety was ‘GujaratMaize-4’. Four treatments of tied ridging, viz., T1 - flat bedsowing (control), T2 - tied ridging between 2.0 m,T3 - tiedridging between 3.0 m and T4 - tied ridging between 4.0 mwere tested in complete random block design with fivereplications. The soil of the experimental field was sandyloam having a pH range from 6.8 to 7.5. Available contentsof phosphorus was medium and potassium was high. The50% nitrogen and whole amount of phosphorus wasapplied as basal, while remaining nitrogen was applied intwo equal splits at tesseling and milking stage. The spacingbetween row was 60 cm and between plant was 20 cm andfertilizer does was 60:40:00 NPK kg/ha. The crop was grownwith the recommended weed and pest managementpractices.

The experiment was rainfed, however, supplementaryirrigation was applied to save the experiment whennecessary. Plant growth and yield attributing parameterswere taken on five plants selected randomly from eachtreatment for recording data at different stages. Afterthreshing of cobs from each plot was weight throughelectrical balance and converted into kg/ha. Plant growthand yield attributes, grain and fodder yield data werecollected at physiological maturity. Data collected weresubjected to statistical analysis using MSTATC computersoftware package. Significantly different means wereseparated using Least Significant Difference (LSD) test.Corresponding author Email: [email protected]


46 [Vol. 2. No. 1 & 2]

Weekly soil moisture was recorded under different soildepth (0-15 cm, 15-30 cm, 30-45 cm). The soil moisturepercent (% dry weight basis) was calculated using thefollowing formula.

100Wd

WwWwMC ××

=

Where, MC = Moisture content (%), Ww = Weightof wet soil (g), Wd= Weight of dry soil (g)


Growth and yield attributesPlant height and cob weight/plant differed

significantly, while cob length and cob girth showed non-significant differences in tied ridging treatments (Table 1).

The tallest plant was found with planting in the tiedridging between 2.0 m (T-2) followed by tied ridgingcultivation between 3.0 m (T3) at Godhra and Dahod.These two treatments were statistically at par, butsignificantly higher than all other techniques. This couldbe attributed to the capacity of tied ridges to retain waterfor longer time so that the crop have utilized for its growth.In line to this, Wiyo et al., (2000) reported that tied ridgingdecreased surface runoff from the field and increasedretention of rainwater within the field.

Dry weight of cob dehulled varied significantly dueto different treatments. In Tied ridging between 2.0 m (T2)sowing produced maximum weight of dry cob, followedby tied ridging between 3.0 m (T3), while flat bed (control)produced minimum dry weight of cob, respectively at boththe locations.

Grain yieldThe grain yield differed significantly between the

treatments (Table 1). Maize sown on tied ridging between2.0 m gave maximum grain yield, which was 35.2 and63.8% higher over flat bed planting at Godhara and Dahodrespectively. Similarly, 3.0 and 4.0 m spaced tied plantingrecorded 19.99% and 28.21% and 8.30% and 17.36%higher yields over flat-bed planting, respectively at Godharaand Dahod. Vedove et al. (1996) found that grain yield ofmaize was greater with ridging which was attributed to thegreater amount of available N under this system.

Fodder yieldThe highest fodder yield was recorded for maize

planted in the tied ridging between 2.0 m by an increase of36.42% over flat bed planting (control) (Table 1). Similarly,planting in tied ridging between 3.0 m and 4.0 m resulted in

a fodder yield increase of 21.16% and 20.93%; and 8.35%and 11.06%, respectively over the flat bed planting at boththe locations. The lowest fodder yield of maize was recordedfrom flat bed planting at both the locations. The results ofMotsi et al. (2000) corroborate these findings.

EconomicsMaize sown on tied ridges, between 2.0 m, 3.0 m 4.0 m

and flat bed incurred A 13,035/ha, A 12,535/ha andA 12,035/ha on total cost of production, respectively (Table1). Regarding net return, tied ridging planting between 2.0m gave the highest net return of A 24,256/ha, followed bytied ridging between 3.0 m A 19,663/ha and tied ridgingbetween 4.0 m A17,515/ha. These results clearlydemonstrate that maize sown on tied ridging between 2.0m gave an additional income over tied ridging between 3.0m, 4.0 m and flat bed (control) of A 4593, A 6,741 andA 8,876/ha. Maximum net return A 24,256 and cost : benefitratio (CBR) 2.86 was obtained in tied ridging treatment T2(2 m). Minimum gross return in A15,580 and CBR 2.41were observed in tied ridging treatment T1 (Flat bed). Thepresent results are supported by the findings of Memon(2007) found that grain yield and economics analysis ofmaize was higher with tied ridging plots.

Soil moisture contentThe soil moisture content before tillage operation was

19.44% (Table 2). The soil moisture content at 0-15 cmdepth after each irrigation in all treatments was recorded(88.71 to 47.91%) from first irrigation (23 July) to lastirrigation (8 October). There was marked difference in alltreatments. The result of moisture content showed that soilmoisture was conserved more in tied ridging plot ascompared to other treatments probably due to the fact thatin ridge plot water holding capacity was higher due to highlooseness of soil particles. The present result is supportedby Gyurioza et al. (1999).

In middle Gujarat Agro Climate Zone growing maizecultivation under rainfed conditions should be done byridging at 2.0 m across furrows after sowing of maize forsecuring higher grain yield with net return.

ACKNOWLEDGEMENTS

We deeply acknowledge the All India CoordinatedResearch Project (AICRP) on Maize, Directorate of MaizeResearch, New Delhi and Director Research, AnandAgricultural University, Anand, Gujarat for the financialassistance. Deep appreciation is expressed to my technicalstaff for assistance with the management of the experimentand data collection in the field as well as lab.

PATEL ET AL


ble

1. E

ffec

t of

tie

d ri

dgin

g tr

eatm

ents

on

plan

t gr

owth

and

attr

ibut

es,

yiel

d an

d ec

onom

ics

of m

aize

(po

oled

dat

a of

thr

ee y

ears

)

Tre

atm

ents

Plan

t he

ight

(cm

)C

ob w

eigh

t (g

/pla

nt)

Gra

in y

ield

(kg

/ha)

Fodd

er y

ield

Cos

t of

Net

ret

urn

Cos

t:(k

g/ha

)cu

ltiva

tion

(‘A

/ha)

bene

fit

(A/h

a) r

atio

God

hra

Dah

odG

odhr

aD

ahod

God

hra

Dah

odG

odhr

aD

ahod

T 1 (F

lat

bed)

con

trol

165

164

272

290

2,30

12,

453

3,31

73,

605

26,6

1511

,035

15,5

80

T2

(2 m

)20

520

236

841

33,

111

3,71

84,

525

5,48

637

,291

13,0

3524

,256

T3

(3 m

)18

219

232

735

52,

761

3,14

54,

019

4,61

032

,198

12,5

3519

,663

T4(

4 m

)16

917

929

433

82,

492

2,87

93,

594

4,23

629

,550

12,0

3517

,515

SEm

±5.

855.

969.

1013

.28

76.5

711

7.32

123.

6917

3.86

CD

(0.

005)

18.7

220

.62

29.1

237

.90

244.

9533

4.95

395.

6749

6.37

Tabl

e 2.

Eff

ect

of t

ied

ridg

ing

on s

oil

moi

stur

e co

nten

t pe

rcen

tage

at

diff

eren

t de

pths

Tre

atm

ent

Soil

Dep

thW

eekl

y so

il m

oist

ure

cont

ent

(%)

23/0

730

/07

05/0

812

/08

19/0

826

/08

03/0

910

/09

17/0

924

/09

1/10

8/10

T 1 (F

lat

bed)

con

trol

0-15

88.7

185

.38

46.3

381

.42

81.1

348

.34

83.3

180

.12

47.3

280

.46

48.1

267

.13

15-3

088

.88

85.4

346

.39

81.4

681

.18

48.4

083

.36

80.1

747

.38

80.5

148

.18

67.1

9

30-4

588

.96

85.5

046

.45

81.4

981

.24

48.4

683

.42

80.2

347

.44

80.5

748

.24

67.2

4

T2

(2 m

)0-

1594

.71

90.1

251

.13

87.4

186

.40

53.2

389

.19

84.1

852

.18

84.1

253

.14

72.1

9

15-3

094

.83

90.1

951

.23

87.4

886

.46

53.2

989

.24

84.2

452

.23

84.1

953

.19

72.2

4

30-4

594

.90

90.2

651

.39

87.5

486

.54

53.3

689

.29

84.2

952

.28

84.2

453

.26

72.2

9

T3

(3 m

)0-

1591

.80

87.3

748

.42

84.1

983

.78

50.1

387

.13

82.3

249

.46

82.1

149

.13

68.2

6

15-3

091

.88

87.4

348

.47

84.2

683

.84

50.1

987

.21

83.3

849

.54

82.1

649

.19

68.3

3

30-4

591

.96

87.4

948

.53

84.3

483

.91

50.2

487

.27

82.4

349

.61

83.2

349

.24

68.3

9

T4

(4 m

)0-

1589

.63

85.9

146

.54

82.2

381

.91

48.7

885

.12

80.9

647

.91

80.5

447

.23

67.7

3

15-3

089

.68

85.9

646

.59

82.2

981

.94

48.8

485

.18

80.9

947

.95

80.6

347

.37

67.7

6

30-4

589

.76

85.9

946

.66

82.3

581

.94

48.9

185

.23

81.0

847

.99

80.6

947

.43

67.8

1

TIED RIDGING AND SOIL MOISTURE CONSERVATION IN MAIZE

48 [Vol. 2. No. 1 & 2]

REFERENCES

FAO (1978). Report on the agro-ecological zones project,Vol. I. Methodology and results for Africa. WorldResources Report 48, Rome. 158 p.

Gyuricza C., Peter, L. Laszlo, P. and Birkas M. (1999). Effectof ridge on the physical status of the soil and on themaize yield. Novenytermeles (Hungary) 48(6): 631–645.

Johnson, E.C., Fischer, K.S. Edmeades, G.O.and Palmer,A.F.E. (1986). Recurrent selection for reduced plantheight in lowland tropical maize. Crop Sci. 26: 253-260.

Kowal, J. (1970). The hydrology of a small catchment basinat Samaru, Nigeria. III. Assessment of surface runoffunder varied land management and vegetation cover.Nigerian Agric. J. 7: 120-123.

Macartney, J.C., Northwood, P.J. Degg, M. and Dawsen, R.(1971). The effect of different cultivation techniqueson soil structure conservation and establishment andyield of maize at Kongwa, Central Tanzenia. TropicalAgric. (Trinidad) 48(1): 9-23.

Memon, S.Q., Baig, B. Mirza, and Mari, G.R. (2007). Tillagepractices and effect of sowing methods on growthand yield of maize crop. Agricultura Tropica Et.Subtropica 40(3): 89-100.

Morin, J., Witz, R.A.E., Benyamini, Y., Hoogmoed, W.B. andEtkin, H. (1984). Tillage practices for soil and waterconservation in the semi-arid zone. II. Developmentof the basin tillage system in wheat fields. Soil TillageRes. 4: 155-164.

Motsi, K.E., Chuma, E. and Mukamuri, B.B. (2000).Rainwater harvesting for sustainable agriculture incommunal lands of Zimbabwe. Physics Chemistry ofthe Earth 29: 1069-1073.

Vedove G. delle, Giovanardi, R. and Ceccon P. (1996). Soilphysical properties, growth and yield of maize grownon ridges. Rivista di Agronomia (Italy) 30 (4): 571–579.

Wiyo, K.A., Kasomekera, Z.M. and Feyen, J. (2000). Effectof tied ridging on soil water status of maize crop underMalawi conditions. Agric. Water Management 45: 101-125.

PATEL ET AL


Response of summer maize (Zea mays) to irrigation schedules and zinclevels under middle Gujarat conditions

R.V. HAJARI1, J.B. PATEL2, K.H. PATEL AND S.K. SINGH

Main Maize Research Station, Anand Agricultural University, Godhra 389 001

ABSTRACT

A field experiment to study the response of summer maize (Zea mays L.) to irrigation schedules based IW:CPEratio and zinc levels was conducted during summer season of 2009, in middle Gujarat conditions an loamy sand soilof Anand. After applying first irrigation just immediately after sowing of the crop and second light irrigation after oneweek of sowing and rest of the irrigation should be scheduled at IW:CPE ratio 1.0. The crop should be fertilized with25 kg ZnSO4/ha.

Key words: IW:CPE ratio, Summer maize, Zinc levels

Maize (Zea mays L.) is one of the oldest and mostproductive cereal food crop. In India, it is emerging as thirdmost important crop after rice and wheat. Maize can becultivated in diverse production environment ranging fromtemperate hill zone to the semiarid regions. Water is the secondmost important basic input for increasing the cropproductivity and production after fertilization. Among thedifferent irrigation scheduling approaches theclimatologically approach based on the ratio betweenirrigation water (IW) and cumulative pan evaporation (CPE)was found to be the most appropriate, as it integrates all theweather parameters giving their natural weightage in a givensoil-water plant continuum. Irrigation scheduling based onpan evaporation is likely to increased agriculture productionat least to the tune of 15 to 20 percent (Dastane, 1972).

Moreover, application of micronutrient also playssignificant role in improvement of maize grain yield. Amongmicronutrients, zinc plays an important role inphotosynthesis, nitrogen metabolism and regulates auxinconcentration of the plants. In maize, Zn deficiency appearsduring the early growth stage and the plants exhibit stuntedgrowth. Patel et al. (1999) reported that Zn deficiency hasbeen observed in middle and North Gujarat regions to theextent of 25%. In middle Gujarat region, well irrigation facilityis available up to March. Hence, maize crop can be takenvery well under such irrigated conditions. Keeping thesein view, an experiment was planned and conducted.


The field experiment was conducted during summer2009 at Agronomy Farm, B.A. College of Agriculture, AnandAgricultural University, Anand, Gujarat. The experimentalsoil was loamy sand in texture having good drainagecapacity and soil moisture retention capacity with pH (7.8),EC (0.12 dS/m), low organic carbon (0.30%) and availablenitrogen (139.50 kg/ha), and high available phosphorus(29.50 kg/ha), available potassium (351.26 kg/ha) andavailable Zinc contents (0.041 ppm). Twelve treatmentcombinations composed of four levels of irrigation [(Control(Irrigation at an interval of 10-12 days), irrigation at 0.6 IW: CPE ratio, irrigation at 0.8 IW : CPE ratio, irrigation at 1.0IW : CPE ratio)] in main plots and three zinc levels (Control,12.5 kg ZnSO4 ha-1 , 25.0 kg ZnSO4 ha-1) in sub plots wasconducted in split plot design. The full dose of phosphorus@ 60 kg/ha in the form of single super phosphate andnitrogen 120 kg/ha in the form of urea (half quantity ofnitrogen were applied open furrows as basal applicationand remaining half quantity of nitrogen was applied as topdressing at knee high stage. The Zn was applied as basalapplication as per the treatments. Irrigation was scheduledas per treatments with the irrigation depth of 50 mm in eachirrigation. The irrigation water in the field was measured byusing 7.5 cm size parshall flume.


Growth attributes

Plant height was influenced by irrigation schedulesand zinc levels could not affect the plant height (Table 1).Days to tasselling and days to silking were recorded and

1Agriculture Officer, Agricultural Research Station, Anand AgriculturalUniversity, Derol2Associate Professor, BA College of Agriculture, Anand AgriculturalUniversity, AnandCorresponding author Email: [email protected]


50 [Vol. 2. No. 1 & 2]

found that the irrigation schedules and zinc levelssignificantly influenced both there parameters of summermaize (Table 1). More days to tasselling and days to silkingwere recorded under irrigation schedule of 1.0 IW/CPEratio and zinc level of 25 kg ZnSO4, while minimum days totasselling and silking were taken under irrigation schedule(control) and no zinc application (Zn0). This might be dueto the comparatively higher water stress at this treatmentand 0 kg ZnSO4/ha which will suppress the vegetativegrowth and enhanced the early flush of flowering andincreased level of zinc. These results are similar to thosereported by Singh (2001).

Yield attributesThe yield attributes viz. number of cobs per plant was

significantly influenced by irrigation schedules and zinclevels (Table 1). Maximum number of cobs/plant wasrecorded under 1.0 IW/CPE ratio and zinc (25 kg ZnSO4),while minimum number of cobs per plant was recorded underirrigation schedule (Control) and zinc level (0 kg Zn/ha).These might be due to the reason that higher quantity ofwater application, creates favourable conditions for plantsin respect to water availability, providing congenialconditions for proper development of higher number ofcobs per plant. These results are in accordance with thosereported by Singh (2001). With increasing levels of zinc,more number of cobs/plant was found, which might be dueto better nourishment of crops under higher doses of zincresulted in more vegetative growth. Similarly, cob lengthand cob girth were significantly influenced by irrigationschedules based on IW:CPE ratio and zinc levels (Table 1).Higher cob length and cob girth were recorded underirrigation schedule of 1.0 IW/CPE ratio. These might bedue to constant soil moisture availability up to later growthstage of plant. These finding are in corroboration with theresult of Rajendra and Singh (1999).

The 100 grain weight was also significantly varied byirrigation schedules and zinc levels (Table 1). More valuesof 100 grain weight was recorded under 1.0 IW/CPE ratioand 25 kg ZnSO4/ha and lower under irrigation schedule(Control) and no zinc application. These might be due tosufficient supply of irrigation water with zinc fertilization tothe crop during growth period ultimately provided bettergrowth in terms of better grain filling.

YieldThe highest grain and stover yield were recorded

under 1.0 IW/CPE ratio and 25 kg ZnSO4/ha. This might be

due to optimum irrigation provided constant moisture incrop root zone, which might have favoured in more releaseof nutrients from soil moisture regime and resulted in highergrain yield. Similar results were also reported by Sani etal.(2008). The higher stover yield under higher level ofirrigation schedules might have due to better vegetativegrowth in terms of plant height obviously resulted intomore stover yield. Secondly, under sufficient soil moisturein the soil profile with IW:CPE ratio, the more plant nutrientswere available and translocated to produce higher greenmatter and might have resulted in to more stover yield.These results are in close confirmation with the findings ofSingh (2001). Harvest index was also influenced by irrigationschedules based on IW:CPE ratio while the effect of zincwas found to be non significant (Table 1).

Water use efficiencyWater use efficiency influenced by irrigation

schedules and zinc levels was found to be significant (Table1). Maximum water use efficiency was recorded underirrigation schedule (0.8 IW/CPE ratio) and zinc level (25 kgZnSO4/ha) and minimum under irrigation schedule (0.6 IW/CPE ratio) and no zinc level. These results might be due toincrease in grain yield produced under different irrigationlevels was comparatively more as the quantity of waterapplied. These findings are in accordance with thosereported by Singh (2001).

EconomicsThe highest net return of A 29,298/ha was obtained

under irrigation schedule of 1.0 IW:CPE with the benefit :cost ratio (BCR) value of 2.19. The next best irrigationschedule was (0.8 IW:CPE) which recorded the netrealization of A 26,889/ha with the BCR value of 2.15.Thehigher net return with higher level of irrigation was mightbe due to higher yields (Table 2). Similar results were alsoreported by Patel et al. (2005). The highest net realizationwas 25 kg/ha which recorded the net realization of A33,892/ha with maximum BCR value of 2.98. These results arein close conformity of those reported by Sawarkar et al.(1999).

To secure higher yields and net returns from summermaize, grown on loamy soil of Gujarat, it is recommendedthat crop should be irrigated at 1.0 IW/CPE ratio with 50 cmIW, after applying two irrigations just after sowing and oneweek after sowing with 25 kg ZnSO4/ha application.

HAJARI ET AL


ble

1. P

lant

gro

wth

and

Yie

ld a

ttrib

utes

as

influ

ence

d by

irr

igat

ion

sche

dule

s ba

sed

on I

W:C

PE r

atio

and

zin

c le

vels

Tre

atm

ents

Plan

t he

ight

Day

s to

Day

s to

Num

ber

ofC

ob l

engt

hC

ob g

irth

(cm

)10

0 gr

ain

Har

vest

Wat

er u

se(c

m)

tass

ellin

gsi

lkin

gco

bs p

er p

lant

(cm

)w

eigh

tin

dex

(%)

effi

cien

cy(g

)(k

g/ha

-mm

)

Irri

gatio

n sc

hedu

les

Con

trol

(Ir

riga

tion

at a

n in

terv

al o

f17

4.88

59.4

764

.31

1.27

13.6

612

.23

20.9

532

.09

6.09

10-1

2 da

ys)

Irrig

atio

n at

0.

6

IW

: C

PE r

atio

177.

8660

.04

64.9

61.

3013

.95

12.3

521

.06

31.3

97.

23

Irrig

atio

n at

0.

8

IW

: C

PE r

atio

183.

4260

.14

65.0

81.

3614

.66

13.0

024

.69

32.9

06.

80

Irrig

atio

n at

1.

0

IW

: C

PE r

atio

188.

8360

.49

65.5

01.

4916

.22

14.3

625

.15

33.8

76.

27

C.

D.

(P=

0.0

5)N

S0.

690.

710.

191.

221.

542.

61N

S0.

61

Zinc

lev

els

Con

trol

179.

2759

.65

64.5

21.

2614

.07

12.1

720

.66

32.4

05.

91

12.5

kg

ZnSO

4 ha

-118

1.72

59.9

764

.88

1.42

14.5

412

.90

23.8

731

.85

6.49

25.0

kg

ZnSO

4 ha

-118

2.76

60.4

965

.48

1.48

15.2

713

.87

24.3

533

.43

7.40

C.

D.

(P=

0.05

)N

S0.

520.

560.

150.

870.

951.

84N

S0.

35

Tab

le 2

. Y

ield

and

eco

nom

ics

as i

nflu

ence

d by

irr

igat

ion

sche

dule

s ba

sed

on I

W:C

PE r

atio

and

zin

c le

vels

Tre

atm

ent

Y

ield

(kg/

ha)

Cos

t of

cul

tivat

ion

Gro

ss r

etur

nN

et r

etur

nB

enef

it :

cost

Gra

in y

ield

Stov

er y

ield

(A/h

a)(A

/ha)

(‘/h

a)ra

tio (

BC

R)

Irri

gatio

n sc

hedu

les

Con

trol

(Ir

riga

tion

at a

n in

terv

al o

f 10

-12

days

)2,

681

5,67

921

,552

33,7

5012

,198

1.56

Irrig

atio

n at

0.

6

IW

: C

PE r

atio

3,54

37,

771

22,1

6244

,801

22,6

392.

02

Irrig

atio

n at

0.

8

IW

: C

PE r

atio

4,01

48,

157

23,3

8350

,272

26,8

892.

15

Irrig

atio

n at

1.

0

IW

: C

PE r

atio

4,32

58,

436

24,6

0453

,902

29,2

982.

19

Zinc

lev

els,

Con

trol

3,25

86,

802

16,0

5740

,939

24,8

822.

54

12.5

kg

ZnSO

4 ha

-13,

570

7,63

716

,751

44,9

9828

,247

2.68

25.0

kg

ZnSO

4 ha

-14,

095

8,09

417

,223

51,1

1533

,892

2.98

Pric

e of

mai

ze g

rain

and

sto

ver

A11

00 a

nd 0

.75/

kg

RESPONSE OF SUMMER MAIZE (ZEA MAYS) TO IRRIGATION AND ZINC LEVELS

52 [Vol. 2. No. 1 & 2]HAJARI ET AL

REFERENCES

Dastane, N. G. (1972). A practical manual for water use research inagriculture. Navbharat Prakashan, Pune-4.

Patel, J.B., Patel, V.J. and Patel, J.R. (2005). Influence of differentmethods of irrigation and nitrogen levels on crop growth rate andyield of maize (Zea mays L.). Indian J. Crop Sci. 1 (1-2): 175-177.

Patel, K.P., George, V., Patel, J.A., Ramani, V.P. and Patel, K.C. (1999).Three decades of AICRP on Micronutrients Anand. Ed, byMicronutrient project (ICAR), GAU, Anand, pp: 1-20.

Rajendran, K. and Sunder Singh, S.D. (1999). Effect of irrigationregimes and nitrogen levels on yield, water requirement,water use efficiency and quality of baby corn (Zea maysL.). Agric. Sci. Digest Karnal. 19(3) : 159-161.

Sani, B.M., Oluwasemire, K.O. and Mohammed, H.I. (2008). Effectof irrigation and plant density on the growth, yield and wateruse efficiency of early maize in the Nigerian Savanna. ARPNJ. of Agric. and Bio. Sci. 3 (2): 33-40.

Singh, S.D. (2001). Effect of irrigation regimes and nitrogenlevels on growth, yield and quality of baby corn. Madras

Agric. J. 88(7-9): 367-370.


Effect of plant population and nutrient levels on periodical growth andyield of baby corn hybrids

V. SOBHANA AND ASHOK KUMAR1

Division of Agronomy, Indian Agricultural Research Institute, New Delhi

ABSTRACT

A field experiment with four combinations of hybrids (‘HM 4’ and ‘PEHM 2’) and plant population levels (66,666and 83,333 plants/ha) in main plots and four nutrient levels (control, N112.5, P19.6, K 37.5; N150, P26.2, K50, and N187.5, P32.75,K 62.5 kg/ha) in sub plots was in split plot design and replicated thrice conducted during kharif season of 2010 at NewDelhi. ‘HM 4’ recorded the tallest plants at 40 and 50 days after sowing with more leaf area index and LCC score at 30days after sowing, dry matter accumulation and SPAD score at 30 and 50 days after sowing. The root system of ‘HM4’ in terms of their volume and dry weight was also stronger compared to ‘PEHM 2’. ‘HM 4’ recorded higher baby cornyield over ‘PEHM 2’. Increase in plant population from 66,666 to 83,333 plants/ha improved the plant height at 40 and50 days after sowing, whereas dry matter accumulation, leaf area index at all the growth stages and root dry weight androot volume at pre tasselling stage showed the reverse trend with increasing the plant population level. All the growthparameters viz. plant height, dry matter accumulation and leaf area index improved with increasing nutrient levels fromcontrol to N187.5 P32.75 K62.5. Similarly, the highest values of LCC score and SPAD were found with highest dose of N187.5P32.75 K62.5. Higher baby corn yield were obtained with 83,333 than 66,666 plants/ha. Marked improvement in baby cornyield was noticed with each increase in nutrient level from control to the highest level of N187.5 P32.75 K62.5 .

Key words: Baby corn, Dry matter accumulation, Leaf area index, LCC score, Plant height, Root parameters, SPADreading

Baby corn is a unique crop for its amenability todiverse uses, enormous potentiality, multiple benefitsand better opportunities for crop diversification (Dasset al., 2009). In India, baby corn is emerging as a potentialremunerative crop among the progressive farmers.Despite several advantages including more returns, thebaby corn does not occupy adequate acreage in ourcountry, probably due to unawareness of its use andtaste, non- availability of suitable variety and productiontechnologies. The production technologies of baby corndiffer from normal maize, which are to be because of lesscrop duration and sole interest in producing morenumbers of young ears from baby corn (Pandey et al.,1998). Among the various agro-techniques, selection ofsuitable variety, adequate plant population and nutrientsupply are the major inputs for harnessing moreproduction of baby corn per unit land area. Ignoranceabout its use and economic importance and non-availability of appropriate production technology are the

major constraints for its popularization in Indianagriculture. Considering these, attempts have been madeto identify the best hybrid and optimize its nutrient andplanting density requirement.

METERIALS AND METHODS

The field experiment was conducted during kharifseason of 2010 at Indian Agricultural Research Institute,New Delhi. The sandy loam soil of experimental fieldwas low in organic carbon and available N, and mediumin available P and K with pH 7.6. The field experimentwas conducted in split plot design with four combinationsof hybrids (‘HM 4’ and ‘PEHM 2’) and plant population(66,666 and 83,333 plants/ha) in main plots and fournutrient levels (Control, N112.5, P19.6, K37.5; N150, P26.2, K50and N187.5, P32.75, K62.5 kg/ha) in sub plots and replicatedthrice. The five plants were randomly selected and taggedfor measuring plant height. However, other growthparameters viz. leaf area index, dry matter accumulationwere measured from three randomly sampled plants. Fortaking LCC reading the top most fully expanded leaf fromsample plants (3 plants from centre three rows) were

1Directorate of Maize Research, Indian Agricultural ResearchInstitute, New Delhi 110 012Corresponding author Email: [email protected]


54 [Vol. 2. No. 1 & 2]

selected and the colour was measured against the sun.The SPAD reading was recorded with the help of SPADmeter as per the procedure. The LCC and SPAD readingswere recorded at 30, 40 and 50 DAS. The baby corn earswere harvested within 2-3 days of silk emergence.


Growth parametersGrowth parameters viz. plant height, dry matter

accumulation and leaf area index enhanced withincreasing the crop age and reached the highest at 50days after sowing (Table 1). The rate of increase of plantheight (4.97cm/day) and dry matter was more between30 and 40 days after sowing stage as compared to 40-50days after sowing stage. Leaf area index also showedthe same trend (Table 1). Significant variations in plantheight were obtained between two hybrids at 40 and 50days after sowing. However, differences in leaf areaindex at only 30 days after sowing, dry matteraccumulation at 30 days after sowing and 50 days aftersowing between two hybrids were significant (Table 1).‘HM 4’ recorded taller plants than ‘PEHM 2’ at 40 daysand 50 days after sowing with more values of leaf areaindex at 30 days after sowing and dry matteraccumulation at 30 and 50 days after sowing stages. Themore values of all growth parameters in ‘HM 4’ was dueto better root system, which might have resulted in more

uptake and availability of nutrients to the crop plants.There were significant differences in all the growthparameters viz. plant height, leaf area index and drymatter accumulation due to different levels of plantpopulation and nutrients at all the stages of crop growthexcept plant height at 30 days after sowing and leaf areaindex 40 days after sowing due to varying plantpopulation levels, where the differences were nonsignificant (Table 1). Increase in plant population from66,666 to 83,333 plants/ha improved the plant height at40 days and 50 days after sowing while, dry matteraccumulation and leaf area index showed the reversetrend with increasing the plant population level from66,666 to 83,333 plants/ha. Increased plant populationfrom 66,666 to 83,333 plants/ha improved the plantheight might be due to intra-row plant competition forlight and other environmental resources. The findingsof Kumar (2008) confirm the results. However, reductionin dry matter accumulation and leaf area index withincreasing the plant population level might be becauseof higher intra-row plant competition for space, moisture,nutrients, light and other environmental resources under83,333 plants/ha level. Zarapkar (2006) and Kunjir etal. (2007) had the similar observations regarding growthcharacter of baby corn and sweet corn, respectively.Taller plants were recorded with increasing NPK levelsfrom control to N187.5 P32.75 K62.5 at 40 and 50 days afterplanting (Table 1). However at 30 days stage increase in

SOBHANA AND KUMAR

Table 1. Effect of hybrids, plant population and nutrient levels on growth parameters of babycorn

Treatment Plant height(cm) Drymatter accumulation Leaf area index(g/plant)

Days after sowing Days after sowing Days after sowing

30 40 50 30 40 50 30 40 50

Hybrid‘HM 4’ 40.5 90.2 111.8 11.8 33.1 58.6 2.6 3.9 4.1‘PEHM 2’ 35.7 81.1 105.8 11.1 32.6 56.9 2.4 3.8 4.1SEm± 0.3 0.5 0.6 0.1 0.4 0.2 0.0 0.1 0.1LSD (P=0.05) NS 1.7 2.3 0.6 NS 0.7 0.1 NS NSPlant population (plants/ha)66,666 37.8 83.5 106.8 12.0 34.8 59.1 2.6 4.0 4.283,333 38.3 87.7 110.7 10.9 30.9 56.3 2.3 3.8 4.0SEm± 0.3 0.5 0.6 0.1 0.4 0.2 0.0 0.1 0.0LSD (P=0.05) NS 1.7 2.3 0.6 1.7 0.7 0.1 NS 0.2Nutrient level (kg/ha)Control 34.4 69.4 91.8 8.5 26.5 40.6 1.6 2.8 3.0N112.5 P19.6 K37.5 38.6 85.7 107.9 11.6 32.4 55.5 2.4 3.9 4.1N150 P26.2 K50 39.4 91.6 116.1 12.5 35.6 65.7 2.9 4.3 4.5N187.5 P32.75 K62.5 40.0 95.8 119.5 13.1 37.0 69.1 3.1 4.5 4.7SEm± 0.3 0.9 0.9 0.2 0.5 0.7 0.1 0.1 0.1LSD (P=0.05) 0.9 2.7 2.7 0.5 1.6 2.3 0.3 0.3 0.3

[April & October 2013] 55 EFFECT OF PLANT POPULATION AND NUTRIENT LEVELS IN BABY CORNTa

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56 [Vol. 2. No. 1 & 2]SOBHANA AND KUMAR

plant height was found with increasing levels up to N150P26.2 K50. Each increase in NPK levels from control to N187.5P32.75 K62.5 resulted in more plant dry matter at all thegrowth stages. But leaf area index improved up to N150P26.2 K50 level at all crop growth stages. Further increasein NPK levels from N150 P26.2 K50 to N187.5 P32.75 K62.5 kg/hacould not improve the leaf area index to the level ofsignificance. The higher availability and uptake of N, Pand K with increased nutrient levels might be the maincause for better growth.

Root studiesSignificant variations in volume and dry weight of

roots were observed due to different baby corn hybrids;and levels of plant population and nutrients (Table 2).Better root system in terms of their volume and dryweight was found with ‘HM 4’ as compared to ‘PEHM2’. Increasing plant population from 66,666 to 83,333plants/ha resulted in significant reduction in bothvolume and dry weight of roots. However, there wasmarked improvement in these root parameters with eachincrease in NPK level from control to the highest dosei.e. N187.5 P32.75 K62.5. There it may be pointed out that thistype of response may mainly be regarded due to lowerplant competition for space and resources at lower plantpopulation level and better availability of nutrients athigher doses of nutrients (Zang et al., 1998).

LCC and SPAD valuesThere was significant variation in LCC values due

to varying plant population levels at 30 and 40 days stageand due to nutrient application rates at all the growthstages (Table 2). At 30 days after sowing stage ‘HM 4’exhibits higher LCC values than ‘PEHM 2’. With theincrease in plant population from 66,666 to 83,333plants/ha, lower value of LCC score at 30 and 40 daysstage was found. With regards to effect of nutrient levelson LCC score, the highest dose of N187.5 P32.75 K32.75 hadsignificantly more value than control at all the stages ofcrop growth. However, no variation in LCC betweenhybrids was observed. The difference in SPAD readingdue to varying hybrids were significant at 30 and 40days after sowing stage and due to different nutrientlevels at all the stages of crop growth (Table 1). However,there was no significant effect of different plantpopulation levels was found on SPAD values at all thegrowth sages of the crop. There was significantimprovement in SPAD value with each increase in NPKlevel up to the highest dose of N187.5 P32.75 K62.5 at all thegrowth stages except 30 days stage where, difference inSPAD values between N112.5 P19.6 K37.5 and N150 P26.2 K50could not reach to the level of significance. Higher valueof LCC and SPAD reading were recorded at lower planting

density (63,333 plants/ha) probably might be due to moregreenness of leaves with higher chlorophyll contents.LCC score and SPAD values are closely related with leafnitrogen concentration and more concentration isdependent on more availability and uptake of nutrientsat higher nutrient levels. Byju and Anand (2009) alsoreported that leaf colour chart score and SPAD value areclosely correlated with yield and leaf N concentration.

YieldThe influence of varying baby corn hybrids; and

levels of plant population and nutrients on baby cornyield was significant (Table 2). ‘HM 4’ recorded morebaby corn yield compared to ‘PEHM 2’, and thesedifferences in yields were of significant level. Similarly,the plant population of 83,333 plants/ha recordedsignificantly more baby corn yield over 63,333 plants/ha. In general there was 46.8, 61.0 and 70.1 %improvement in baby corn yield due to application ofN112.5 P19.6 K37.5. N150 P26.2 K50 and N187.5 P32.75 K62.5 levels overcontrol respectively, and these enhancements were ofsignificance level.

It may be concluded that ‘HM 4’ hybrid is a betterhybrid of baby corn for getting higher productivity andthe crop should be planted with 83,333 plants/ha withthe application of 187.5N, 32.75P, 62.5K kg/ha.

REFERENCES

Byju, G. and Anand, M.H. (2009). Leaf colour chart andchlorophyll-meter based leaf nitrogen estimation and theirthreshold values for real time nitrogen management incassava. Communications in Soil science and Plant Analysis40 : 2816–2832.

Dass, S., Yadav, V.K., Kwatra, A., Sekhar, J.C. and Yadav, Y.(2009). Baby corn production technology and valueaddition. Directorate of Maize Research, Technical Bulletin,2009/11. pp 1-46.

Kumar, A. (2008). Productivity, economics and nitrogen-useefficiency of specialty corn (Zea mays) as influenced byplanting density and nitrogen fertilization. Indian Journalof Agronomy 53(4): 306-309.

Kunjir, S.S., Chavan, S.A., Bhagat, S.B. and Zende, N.B. (2007).Effect of planting geometry, nitrogen levels andmicronutrients on the growth and yield of sweet corn. CropProtection and Production 2(3): 25-27.

Pandey, A.K, Mani, V.P, Singh, R.D. and Chauhan, V.S. (1998).Technologies for baby corn production in hills of northwestern Himalayas. Indian Farming 47(1): 10-12.

Zang, Z., Pan, M.T., HU, F., Zhou, X., Zang, Z. and Zhou, X.H.(1998). The function in yield promotion of the maize bythe use of fertile soil. Zhejiang Nongye Kexue 1: 31–32.

Zarapkar, D.S. (2006). Effect of spacing and yield on growthand yield of baby corn. M.Sc. Thesis submitted to Dr.Balasaheb Sawant Konkan Krishi Vidyapeeth, Dapoli(India).


Maize grain losses due to Sitophilus oryzae L. and Sitotroga cerealella(Oliv.) infestation during storage

P. LAKSHMI SOUJANYA, J.C. SEKHAR AND P. KUMAR1

Winter Nursery Centre, Directorate of Maize Research, Rajendranagar, Hyderabad 500 030

ABSTRACT

A study was conducted with the objective of assessing the comparative grain damage and weight loss in maize dueto infestation by varying population densities of Sitophilus oryzae (5, 10, 50 and 100 adults/ 500 g maize grain) andSitotroga cerealella (50, 100, 150, 200 eggs/ 200 g maize grain) over a four month storage period. Significantdifferences were observed between initial and final insect densities of Sitophilus oryzae and Sitotroga cerealella.The maximum percent grain damage (53.30, 59.78) and weight loss (14.0, 4.9) was recorded at an initial populationdensity of 100 adults and 200 eggs of Sitophilus oryzae and Sitotroga cerealella, respectively. The final insectpopulation and weight loss due to Sitophilus oryzae exceeded that of Sitotroga cerealella whereas grain damage washigh in Sitotroga cerealella infested maize at 120 days after storage. The Pearson correlation coefficient was positiveand highly significant between infestation levels and progeny emerged (r = 0.82, r = 0.99), infestation levels andgrain damage (r = 0.89, r = 0.95), infestation levels and grain weight loss (r = 0.93, r = 0.94) for Sitophilus oryzae andSitotroga cerealella, respectively.

Maize is susceptible to storage pests which causesubstantial quantitative, nutritional and qualitativelosses depending on the pest species and duration ofstorage. Insect attack constitutes a major cause of lossesof stored maize in the tropics and these losses have beenreported from 10 to 30% during a storage period of 6months (Tefera et al., 2011) much higher than lossescaused by rodents and micro organisms. Rice weevil,Sitophilus oryzae (L.) and angoumois grain moth,Sitotroga cerealella (Oliv.) are principal pests of storagemaize, capable of multiplying to large populationscausing tremendous damage and weight loss to grain byhollowing them out. The larvae of these pests tunnelinside the kernels causing substantial damage and renderthe grain more susceptible to secondary insect pests(Weston and Rattlingourd, 2000). Though infestationcommences in the field itself but most of the damageoccurs during storage period. Feeding of the larvae insidethe grains provides the best additional protection fromdirect contact with applied insecticides which is animportant factor that contributes to serious loss ofgrains. The presence of insects also raises the graintemperature, due to their feeding activity, resulting inhot spots (Mills, 1989) which in turn stimulates seed

deterioration and further fungal activity. The estimationof post harvest losses would provide knowledge aboutthe extent of losses which ultimately helps in thedevelopment of management strategies. The presentstudy aims to assess the magnitude of damage causedby Sitophilus oryzae and Sitotroga cerealella in storedmaize at varying population levels over a four monthstorage period.


Two experiments were separately carried out forSitophilus oryzae and Sitotroga cerealella with fourvarying population levels of Sitophilus oryzae (5, 10,50 and 100 adults/ 500 g grain) and Sitotroga cerealella(50, 100, 150, 200 eggs/ 200 g grain) over a four monthstorage period. Five hundred gram of maize grains wereplaced in a one-litre plastic jar and covered with muslincloth. About 200 unsexed adults of Sitophilus oryzaewere separately introduced into the plastic jar. After 10days of oviposition, all adult insects of the insects wereremoved. Adult emergence was monitored daily andthose emerged on the same day were transferred toplastic jars containing fresh grains and kept at the sameexperimental conditions until sufficient number of suchinsects were obtained. Different insect densities 5, 10,50 and 100 adults of non sexed Sitophilus oryzae werereleased per each replicate in plastic jars containing five

1Directorate of Maize Research, Pusa Campus,New Delhi -110 012 IndiaCorresponding author Email: [email protected]


58 [Vol. 2. No. 1 & 2]

Table 1. Effect of Sitophilus oryzae and Sitotroga cerealella initial population density on grain damage and weight loss at 120 days aftermaize grain storage

Treatment Sitophilus oryzae Sitotroga cerealella

Grain damage (%) Weight loss (%) Grain damage (%) Weight loss (%)

50 19.33B ±5.61 2.42 B±0.98 22.50C ± 1.98 2.22C ± 0.27

100 25.33 B±3.67 3.84AB ±0.54 40.25B ± 2.26 3.88B± 1.45

150 45.67 A±5.55 8.23AB ±2.24 53.75A ± 2.50 4.09AB ± 0.68

200 53.33A ±4.25 14.03A ±4.74 59.75A ± 2.23 4.91A± 0.24

Each value is the mean of four replicates (mean ± SD). Figures in parentheses are angular transformed values. Means followed by the same letter arenot significantly different from each other using Duncan’s Multiple Range Test.

LAKSHMI SOUJANYA ET AL

Figure:1 Effect of S.oryzae initial population density on adult emergence at 120 days after maize grain storage

Figure:2 Effect of S.cerealella initial egg density on adult emergence at 120 days after maize grain storage rgence at 120 days after maize grain storage

[April & October 2013] 59MAIZE GRAIN LOSSES DUE TO INFESTATION DURING STORAGE

hundred grams of maize grains (11% moisture content)and kept for 120 days. Eggs of Sitotroga cerealellawere obtained by placing about 100 freshly-emerged adultmoths in a one litre plastic jar containing 100 grams ofmaize grains and folded wax paper. The insects wereallowed to mate and lay eggs for seven days. After sevendays, the adults were separated and the eggs laid in thecrevices of the folded paper were collected after 24 h.Two hundred grams of maize grains were taken in plasticjars and different egg densities 50, 100, 150 and 200 eggsof Sitotroga cerealella were added per each replicate.The treatments were arranged in completely randomiseddesign with four replications in laboratory. After 4months, the plastic jars were opened, the contentseparated into grains and number of insects emerged,number of kernels damaged, weight of damaged andundamaged kernels were recorded. The number ofinsects emerged were square root transformed whilepercent grain damage and weight loss were angulartransformed in order to stabilize the variance. Thetransformed data were analyzed using one-way analysisof variance by SAS VERSION 9.3. Significant differencesbetween means were separated using DMRT (P < 0.05).


Significant differences were observed betweeninitial insect density and final insect density forSitophilus oryzae (F= 8.19, P < 0.001) and for Sitotrogacerealella ( F =7.25 , P < 0.001) after 120 days of maizestorage (Figures 1 and 2). There was an increasing trendin the final insect density with a corresponding increasein an initial insect density and storage time. Significantdifferences were observed between initial insectdensities in percent grain damage for both Sitophilusoryzae (F= 3.85, P < 0.001) and Sitotroga cerealella (F=9.34, P < 0.001) at 120 days after storage. The minimum(19.33) and maximum (53.33) percent grain damage wasrecorded at 50 and 100 insect density of Sitophilus oryzae(Table 1) and in case of Sitotroga cerealella, theminimum (22.50) and maximum (59.75) percent graindamage was observed at 50 and 200 egg densities (Table1) after 120 days of storage, respectively. There weresignificant differences among initial insect densities inaffecting grain weight losses for both Sitophilus oryzae(F= 4.79, P< 0.001) and Sitotroga cerealella (Table 1)(F= 18.94, P< 0.001) respectively at 120 days after storage.Waktole and Ayana (2012) reported that percent graindamage and weight losses by Sitophilus zeamaisincreased with storage period of six months. The percentweight loss due to feeding by Sitophilus oryzae andSitotroga cerealella ranged from 2.42 to 14.03 and 2.22to 4.91, respectively with varying population levels. Themaximum percent grain weight loss was caused byS.oryzae which might be due to extensive tunnelling to

the grain. The present results are in agreement withDerera et al. (2001) who reported grain losses rangingfrom 20 - 90% caused by Sitophilus zeamais in storeduntreated maize grains. However, maximum percent graindamage was inflicted in Sitotroga cerealella infestedmaize (59.75) compared to Sitophilus oryzae (53.33).Togola et al. (2010) reported that infestation by Sitotrogacerealella in many rice-producing zones caused 3-18 %grain damage , depending on the area and length ofstorage. This is comparable to present results withslight percentage modification in grain damage whichmay be due to size of grain sample, method andduration of study. The damage by Sitotroga cerealellaalso ranged from 3% to 18 % over 4 months storageperiod in infested samples of rice (Abou et al., 2010).The Pearson correlation coefficient was positive andhighly significant between infestation levels andprogeny emerged (r = 0.82, r = 0.99), infestation levelsand grain damage (r = 0.89 r = 0.95), infestation levelsand grain weight loss (r = 0.93, r = 0.94) for Sitophilusoryzae and Sitotroga cerealella, respectively. Thepresent findings are in agreement with Uttam et al.(2002)who reported significant positive correlation with theinsect population of S. cerealella and percent ofdamaged grains (+0.95) and percent grain weight loss(+0.85) when infested with different rice varieties.

REFERENCES

Abou, T., Francis, E.N., Daniel, C.C., Tolulope, A. (2010).Presence, populations and damage of the angoumois grainmoth, Sitotroga cerealella (Olivier) (Lepidoptera,Gelechiidae), on rice stocks in Benin. Cahiers Agriculture19 (3): 205-209.

Derera, J., Pixley, V., and Giga, D.P. (2001). Resistance ofmaize to the maize weevil. Antibiosis African Crop Sci. J.9 :431-440.

Mills, J. (1989). Spoilage and heating of stored agriculturalproducts. Prevention, detection and control. pp.101.Agriculture Canada Pub.1823E.

Tefera, T., Mugo, S., and Likhayo, P. (2011). Effect of insectpopulation density and storage time on grain damage andweight loss in maize due to the maize weevil Sitophiluszeamais and the larger grain borer Prostephanus truncatus.African Journal of Agric. Res. 6 (10): 2249 –2254.

Togola, A., Nwilene, F.E., Chougourou D.C., and Agunbiade, T.(2010). Presence, populations and damage of the angoumoisgrain moth, Sitotroga cerealella (Olivier) (Lepidoptera,Gelechiidae), on rice stocks in Benin. Cahiers Agriculture19: 205-209.

Uttam, J.R., Verma, R.A., Singh, D.R. (2002). Studies oncorrelation between insect population of Sitotroga cerealellaand Rhizopertha dominica with percentage of damagedgrain and loss in weight of different rice varieties. Indian J.Entomol. 64 (3): 279-282.

Waktole, S., and Ayana, A. (2012). Storage pests of maize andtheir status in Jimma Zone Ethiopia. African J. Agric. Res.,7 (28): 4056-4060.

60 [Vol. 2. No. 1 & 2]

Farmers participatory research on chemical control of turcicum leaf blightdisease in maize

V. BHARATHI, K. KANAKADURGA, R. SUDHAKAR AND L. KISHAN REDDY1

Seed Research & Technology Centre, AcharyaN.G. Ranga Agricultural University, Rajendranagar, Hyderabad

Key words: Farmers participatory, Fungicidal management, Maize, Turcicum

1Associate Director of Research, RARS, ANGRAU, Jagtial, KarimnagardistrictCorresponding author Email: [email protected]

Maize is the largest covered area cereal and foddercrop in Nizamabad district in Andhra Pradesh and holds70% share of the total cropped area (8.5 lakh ha).Nizamabad district is the largest producer of maize inIndia and the average yields are low due to severalconstraints (ANGRAU, 2003). It is cultivated both underdrop system and normal irrigation practices. Among thefoliar diseases affecting maize, turcicum leaf blightcaused by Exserohilum turcicum (Pass.) Leonard andSuggs, is a major constraint in large scale cultivationand production of maize both in kharif and rabi causingreduction in grain and fodder yield ranging between 16-65% (Kachpur and Hedge, 1988). Recently this diseasehas occurred in alarming proportions reducing grain andstraw yield. In the previous years leaf spot diseases werenot observed prominently in Andhra Pradesh, due tofarmer’s outlook recently released hybrids comes intocultivation were prone to this disease. Farmers were nothabituated to take up the sprayings of fungicides and donot know to take up the control measures as the diseaseusually appears in the older leaves and late in the seasonreaching maximum intensity during cob formation stage.Most of the hybrids in the district are prone to this diseaseresulting in severe defoliation. Therefore efforts weremake to conduct the on-farm trial to test the effect offungicides on maize turcicum blight disease on Kaveri225 hybrid in Nizamabad district during 2006-2008 byDistrict agricultural advisory and training centre,ANGRAU to explore the effectiveness of chemicalcontrol.

On-farm trials were conducted during kharif seasonsof 2008-011. A locally popular hybrid Kaveri 225Susceptible to TLB was used for the study. The cropwas planted on raised furrow 45 and 35 cm between theplants in the rows. In each location, six farmers were

selected for the study on the basis of report of theprevious incidence of the disease from institute’s surveyreport. The villages were Argul, Padkal and Armurcovering three mandals Jakhranpalli, Velpur and Armur.The size of the plot was half an acre with two treatmentsviz., spraying with fungicide (protected) and withoutfungicide (unprotected), The spray fluid consists ofpropiconazole @ 1 ml/l of water using 500 l of spraysolution per hectare.

The treatments were applied as foliar spray at kneehigh stage and the another at 15 days (approximately at55 days after sowing) after first spray observations onTLB disease were recorded at 10 days interval selectingfifteen plants were randomly from each plot andindividual leaf was rated using modified 9 scale. (1-9scale) C Pegak & Sharma, 1983

The percent disease index was calculated by usingthe following formula (Percent avoidable loss = Vp-Vu/Vp x 100), where Vp-yield in protected plot, Vu = yield inunprotect plot. The observations on grain yield, coblength, stover yield and shelling percentage wererecorded from the plots and data were statisticallyanalysed. The average loss in all the parameters wascalculated.

During the three year period (2008-2011) asignificant difference on the incidence of turcicum leafblight was observed between protected and unprotectedplots in three villages of three mandals. Two sprayingsof propiconazole were taken up at 45 and 55 days with10 days interval was found significantly superior andrecorded low PDI of 23.5, 32 and 36.8 as against 64.8,60.7 and 62.3% in control plots in Argul, Padagala andArmur villages, respectively. The average per diseaseincidence of blight was higher in all the three years inunprotected plot than in protected plot (Table 1). Thepercent disease control in protected plots was 63,47 and40% in Argul, Padigala and Armur villages, respectively.


SHORT COMMUNICATION


Table 1. Effect of fungicides on turcicum leaf blight incidence, yield, cob length, stover yield and benefit cost ratio in maize

Parameters Name of villages

Argul Padgal Armur Mean

Leaf blight incidence (PDI)

Protected plot 23.5(26.9) 32.1(34.5) 36.8(38.4) 30.8(32.6)

Unprotected plot 64.8(52.6) 60.7(52.3) 62.3(65.1) 62.6(65.2)

% disease control 63.7 47.0 40.9 50.0

CD (5%)

Cob length (cm)

Protected plot 14.2 15.4 13.6 14.4

Unprotected plot 12.1 14.6 11.3 12.6

% disease control 17.0 22.2 20.3 19.8

CD (5%) 0.59 0.69 1.01

Yield (kg/ha)

Protected plot 47.4 45.1 45.0 45.8


% disease control 18 14 20 17.3

CD (5%) 1.19 0.66 1.06

Stover yield (kg/ha)

Protected plot 7.8 6.9 7.2 7.3


% disease control 20.0 15.0 20.0 18.3

CD (5%) 0.93 0.77 0.89

Shelling percentage

Protected plot 52.4 57.2 54.5 54.7


% disease control 12 29.1 14.7 18.6

CD (5%) 2.69 4.88 1.69

Cost benefit ratio 1:2.01 1:2.16 1:1.87 1:2.01

These results are in agreement with Singh et al. (2005)who reported minimum PDI with propiconazole spray @0.1% in wheat. The fungicidal sprays might have addedadvantage over attacking pathogen and often providessuperior foliar protection and triggering effect onsecondary spread on the paghogen.

The fungicidal spray might have effectivelycontrolled the pathogen by inhibiting the sporegermination, hence a large portion of leaf laminaremained unaffected. This was an advantage to the farmerof this region as it was used as a fodder for the turmericpredominant area.

During three yeas, grain yield and stover yield weresignificantly higher in protected plots compared tounprotected plots. The average increase in grain andstover yields was 14 to 20% and 15 to 20%, respectively.Sprayed plots recorded grain yield of 47.4, 45.1 and 45.0

q/ha in Argul, Padagal and Armur villages, respectivelycompared to 40.1, 39.6 and 37.4 q/ha in unprotected plot.Same trend was observed with regard to stover yields.More stover yields of 7.8, 7.2 and 6.9 q/ha were recordedin protected plots against 6.5, 6.0 ad 6.0 in unprotectedplots of Argul, Padagal and Armur villages, respectively.According to Ranga Reddy et al. (2004) two sprays ofpropiconazole (0.1%) resulted in highest grain yield andstover yield of maize.

Timely protection measures i.e., fungicidal sprayfor the control of turcicum leaf blight resulted in lowleaf drop, higher grain yield and stover yields. Similarresults were also observed in maize by Khadekar et al.(2004). In addition, the shelling percentage was alsohigher in protected plots (62.4, 67.2 and 64.5%) as againstcontrol (50.7, 52.6 and 50.1%) plots. Similarly,significantly maximum cob length was recorded infungicidal sprayed plots (14.2, 15.4 and 13.6 cm) as

FARMERS PARTICIPATORY RESEARCH IN MAIZE

62 [Vol. 2. No. 1 & 2]

against unprotected plots (12.1, 11.6 and 10.3 cm). Thereduction in shelling percentage, cob length, grain yieldsin unprotected plots might be due to reduction inphotosynthetic area because of drying followed bydefoliation of diseased leaves as there is relation betweenphotosynthesis and yield (Pant et al., 2001). Whendefoliation of diseases laved coincided with the cobfilling stage of the crop, it leads to reduction in yieldattributes and yield. Application of fungicides increasedthe cob length substantially (17 to 22%) over controldue to translocation of photosynthates from source ofsink (Mayer et al., 1973). Application of fungicidal sprayresulted in mean cost benefit ratio of 1:2.01. Control ofleaf blight with fungicidal application at the optimal timeresulted in good economic returns. Hence, there is a needto apprise the farming community about the timelycontrol of leaf blight in maize.

SUMMARY

Fungicidal evaluation in farmers participatory infers thatthe timely fungicidal spray to the maize crop affectedwith severe leaf blight that spraying the crop at 40-55days age with 10 days intervals yields better crop withhigh yield. Sprayed plots recorded grain yield of 47.4,45.1 and 45.0 q/ha in Argul, Padgal and Armoor village,respectively compared to 40.1, 39.6 and 37.4 q/ha inunprotected plot. Lower percent disease incidence wasrecorded in three villages with 23.5, 32 and 36.8% as

against 64.8, 60.7 and 62.3% in protected and unprotectedplots respectively with high benefit cost ratio of 1:2.01.

REFERENCS

ANGRAU (2003). Report on compendium of maize diseases inNizamabad and Karimnagar districts. Published in Annual Reportof Regional Agricultural Research Station, Jagtial, Karimnagar,ANGRAU, pp. 12-15.

Harkapur, S.L., Kulkarni, M.S. and Srikant Kulkarni, P. (2009).Assessment of crop loss due to leaf blight in maize. IndianPhytopath. 62: 144-154.

Kachapur, M.R. and Hedge, R.K. (1988). Studies on turcicum leafblight of maize caused by Exserohilum turcicum. Plant Pathol.6: 33-35.

Khadekar, S.A., Harkapur, S., Shripad Kulkarni, I. and Deshpande,V.I. (2010). Integrated management of Turcicum leaf blightof maize caused by Exserohilum turcicum (Pass.). Leonard &Suggs. Karnataka J. Agric. Sci. 23: 372-373.

Mayer, B.S., Anderson, D.B., Bohing, R.H. and Fratianne, D.G.(1973). Introduction to Plant Pathology. D. Van NostrantCompany, New York. 367 pp.

Pant, S.K., Pramodkumar, S. and Chauhan, V.S. (2001). Effect ofturcicum leaf blight on photosynthesis in maize. IndianPhytopath. 54: 251-252.

Ranga Reddy, R., Sudhakar, M and He malatha, T. (2004). Effect offugicides on turcicum leaf blight management in maize. AnnualReport, Maize Research Station Rajendranagar, pp 64-66.

Singh, D.P., Sinha, V.C. and Goel, L. (2005). Chemical control ofleaf blight of wheat. Indian J. Agric. Res. 39 (3): 229-231.

BHARATHI ET AL


Constraints in scientific maize cultivation

V.K. YADAV, TUHINA VIJAY1, P. SUPRIYA AND K.P. SINGH

Directorate of Maize Research, Pusa Campus, New Delhi 110 012

Key words: Constraints, Maize

1Purnea Mahila Mahavidyalaya, Purnea, BiharCorresponding author Email: [email protected]

Maize (Zea mays) is one of the most important corpin the world. It is next in importance only to rice andwheat and has an acreage around 8.55 million hectareswith a production of 21.73 million tonnes in India. As ithas potential far higher than any other cereal, it issometimes referred to as the miracle crop. Bihar statehas 0.94 lakh sq.km of the geographical area. The maizecrop occupies about 8% of the total area among thedifferent crops grown in the state. During 2011-12, themaize yields in kharif and rabi seasons were 2.35 tonnes/ha and 2.40 tonnes/ha respectively. Haryana state has3.8 m.ha of cultivable area and maize is grown, on anarea of 12 thousand ha, with production of 27 thousandtonnes. During 2011-12, the productivity of maize inKharif season is 2.66 tonnes/ha. Rajasthan has thelargest area of maize in India i.e., 1 million ha withproduction of 1.1 million tonnes and productivity of 1.1kg/ha. During 2011-12 the maize yield in kharif and rabiseasons is 1.58 tonnes/ha and 3.43 tonnes/harespectively. In Gujarat, during 2011-12, the maize yieldin kharif season is 1.39 tonnes/ha and in rabi season is1.91 tonnes/ha. (DOES, 2013)

While cultivating the maize crop, the farmers comeacross various problems like less availability of inputs,water scarcity, etc. It is important to understand theconstraints for adoption of scientific maize cultivation.The present study was undertaken with specific objectiveto identify constraints in adoption of scientific maizecultivation. The study was conducted in four states i.e.,Bihar, Haryana, Rajasthan and Gujarat during 2005-06.The progressive district, in terms of maize cultivationwas selected from each state namely Begusarai,Kurukshetra, Udaipur and Panchmahal districts fromstates of Bihar, Haryana, Rajasthan and Gujaratrespectively. Then, two blocks from each district; andfrom each block, two villages and from each village,group of homogenous farmers were selected by using

multi stage random sampling technique. Data from thefarmers was collected by using PRA tools i.e., focussedgroup interview and preference ranking. Constraints inthe present study have been operationalized as problemsperceived by the farmers during maize cultivation. It wasascertained by asking open-ended question to a groupof farmer respondents using focused group interviewtechnique.

Focused group interview can be defined as smallgroup of people brought to a central location for aninterview a discussion with a moderator who focusesdiscussion on various issues in accordance with a generaloutline of question areas. Steps used for focused groupinterview include preparing few homogenous groups,asking the group to discuss about a specific problem,the researcher facilitates the discussion when needed andviews expressed were noted down by the researcher.Constraints in maize cultivation were ascertained fromgroup of farmers and subsequently ranked by keyinformant in each village. It involved ranking of a set ofconstraints by an individual on the basis of severity.Constraints in maize cultivation were ascertained fromgroup of farmers in each selected village, andsubsequently these were ranked by key informants onthe basis of severity of problem by assigning a score of6 for the most severe constraint and 1 score for the leastsevere constraint. Rank I was given to most severeconstraint and rank VI/V for least severe constraint.

Among various constraints in Bihar less availabilityof good quality inputs ranks an one which includes lessavailability of quality seed, fertilizer, micro nutrients,insecticide/ pesticide and electricity (Table 1). Lack ofirrigation/ costly irrigation holds second rank thatincludes expensive irrigation, less availability ofirrigation water. Drainage problem ranks three.Occurrence of natural calamities, involvement ofmiddlemen in selling the produce, less availability ofcredit facility ranks fourth. High interest rate of moneylenders, scarcity of labour during peak season and lowpurchasing power holds rank five. Low purchasing power


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64 [Vol. 2. No. 1 & 2]

Table 1. Constraints in maize cultivation in different states

Constraints Rank

Bihar

Less availability of good quality inputs (seed, fertilizer & pesticide) I

Lack of irrigation facilities/ costly irrigation II

Drainage problem/ stagnant water III

Occurrence of natural calamities/ flood & drought IV

Involvement of middlemen/ mediator in selling the produce IV

Unavailability/ less availability of credit facility IV

High interest rate of money lenders V

Scarcity of labour during peak season (sowing, harvesting, etc.) V

Less purchasing power of farmers V

Haryana

Less availability of input at appropriate time (seed, fertilizer & pesticides) I

High cost of inputs (seed, fertilizer, irrigation etc) II

Less access to information III

More incidence of pest VI

Not getting remunerative price of produce IV

Adulteration in seed and fertilizer V

Rajasthan

Damage of crop in the field by wild animals (Neelgai & Monkey) I

Scarcity of irrigation water (dependent upon nature)/ Lack of irrigation facility II

Less availability of good quality inputs (especially seed and electricity) II

Lack of remunerative price ( selling price) of produce III

Lack of interest in farming among younger generation IV

Less knowledge of scientific cultivation of maize V

Less purchasing power of farmers V

Occurrence of salinity problem in the field V

Gujarat

Water scarcity / extreme heat I

Less access to irrigation water II

Less access to quality seed V

Less access to fertilizer III

Less availability of labour IV

YADAV ET AL


of the farmers includes farmers unable to hire labour dueto less money at the time of harvest and non availabilityof farm machinery at affordable prices.

Among various constraints in Haryana, lessavailability of good quality inputs ranks one whichincludes less availability of quality seed, fertilizer, micronutrients, insecticides/ pesticides and electricity (Table1). High cost of inputs holds second rank that includesexpensive irrigation, expensive fertilizers and expensivehybrid varieties. Less access to information ranks threewhich includes information on dose of fertilizer to beapplied, information on quality of seed used for sowing,information on proper markets, information on minimumsupport price provided by Government etc. Moreincidence of pest (insect, disease, weed) ranks fourth.Adulteration in seed and fertilizer ranks five. Not gettingremunerative price of produce ranks sixth.

Among various constraints in Rajasthan, damageof crop in the field by wild animals (Neelgai & Monkey)ranks one (Table 1). Scarcity of irrigation water andless availability of good quality inputs which includesless availability of electricity and less availability ofgood quality seed ranks two. Lack of remunerative priceof produce ranks three. Lack of interest in farming amongyounger generation ranks fourth. Less access toinformation that includes less knowledge of scientificcultivation of maize, less purchasing power of farmersand occurrence of salinity problem in the field ranks five.

Among various constraints in Gujarat waterscarcity/ extreme heat ranks one, less access to irrigationwater ranks two, less access to fertilizer ranks three, lessavailability of labour ranks fourth and less access toquality seed ranks five (Table 1).

SUMMARY

Constraints in maize cultivation have been assessedin four states namely Bihar, Haryana, Rajasthan andGujarat. The data regarding problems faced by farmersduring maize cultivation was collected throughquestionnaires, focused group discussions etc. Theconstraints were tabulated and ranked. The most severeproblem faced in each state include less availability ofgood quality inputs in Bihar, less availability of input atappropriate time in Haryana, damage of crop in the fieldby wild animals in Rajasthan and water scarcity/extremeweather in Gujarat.

REFERENCES

DOES (2013). Department of Economics and Statist ics,Department of Agriculture and Co-operation, KrishiBhawan, New Delhi.

Vision 2030 (2011), Directorate of Maize Research, Pusa campus,New Delhi.

CONSTRAINTS IN SCIENTIFIC MAIZE CULTIVATION

LANDMARK PAPERS OF MAIZE RESEARCH IN 2013

Paper

The maize Gá gene COMPACTPLANT2functions in CLAVATA signalling tocontrol shoot meristem size. Nature.502:555–558

Peter Bommert et al. (2013). Quantitativevariation in maize kernel row number iscontrolled by the FASCIATEDEAR2 locus. Nature Genetics. 45:334–337

Aaron Lorenz and Thomas Hoegemeyer(2013).The phylogenetic relationships ofUS maize germplasm. Nature Genetics.45: 844–845

Regulski et al. (2013). The maizemethylome influences mRNA splice sitesand reveals widespread paramutation-like switches guided by small RNA. Ge-nome research. 23 (10):1651-1662

Gent et al. (2013). CHH islands: de novoDNA methylation in near-genechromatin regulation in maize. Genomeresearch. 23 (4): 628-637

Eveland et al. (2013). Regulatory modulescontrolling maize inflorescencearchitecture. Genome research.doi:10.1101/gr.166397.113

S.No.

1.

2.

3.

4.

5

6.

JournalImpactFactor

36.8

35.352

35.352

13.608

13.608

13.608

Key Findings

Shows that single pass trans-membrane receptors act as G-Protein Coupled Receptors (GPCR) in plants, challengingthe dogma that GPCRs are exclusively7TM proteins.

Reports that modulation of fundamental stem cellproliferation controlled pathway has the potential toenhance maize yield.

Performed re-sequencing of hundreds of US and Chineseelite maize inbred lines and reported changes in the maizegenome that accompanied modern breeding.

A landmark paper in maize epi-genetics presenting acomprehensive genome-wide map of cytosine methylationfor two maize inbred lines, B73 and Mo17.Unravels, therole of small RNAs in the methylation phenomenon.

This seminal work throws light on the specific geneticfeatures that trigger DNA methylation- a phenomenon thathad intrigued maize geneticists for years. Thanks to thisstudy, the fundamental process of RNA-directed DNAmethylation (RdDM), where 24-nt siRNAs direct de novomethylation to repetitive DNA, is now understood in greaterdetail.

Genetic control of tassel branching is a primary determinantof yield, regulating seed number and harvesting ability, yetlittle is known about the molecular networks that shapegrain-bearing inflorescences of cereal crops. This paperuncovers some discrete developmental modules thatfunction in determining grass-specific morphology andprovides a basis for targeted maize improvement.

(Compiled by Sapna, Pranjal Yadava and Ishwar Singh, Directorate of Maize Research, Pusa Campus,New Delhi 110012)

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