AGRICULTURAL RESEARCH COMMUNICATION CENTRE

www.arccjournals.com / www.ijarjournal.comIndian J. Agric. Res.., 48 (6) 429-436, 2014

doi:10.5958/0976-058X.2014.01326.2

STUDIES OF VARIABILITY AND ASSOCIATION OF YIELD WITH SOMEAGROMOPHOLOGICAL CHARACTERS IN BREAD

WHEAT (TRITICUM AESTIVUM L.)

Vijay Kumar* , P.K Sharma1, Hitesh Kumar and Vikas Gupta2

Department of Genetics and Plant Breeding,Ch. Charan Singh University, Meerut-250 004, India

Received: 11-10-2013 Accepted: 19-08-2014

ABSTRACTThe experiment was conducted to study the variability parameters, correlations and path coefficient

for ten agronomically important traits in the 40 bread wheat genotypes. Genotypic coefficient ofvariation (GCV) was less as compared to that of phenotypic coefficient of variation (PCV) for all thecharacters. Plant height and grain weight per plant had high GCV, heritability and genetic advance(as percentage of mean). This indicated that these characters were governed by additive gene effectand can be improved through selection effectively. Highly positive and significant correlation reportedfor grain yield per plant with number of tiller per plant, number of spikelets per spike, 100-grainweight and grain weight of main spike. The present study indicated that number of tillers per planthad highest direct effect on seed yield per plant both at genotypic levels and grain weight of mainspike.

Key words: Correlation, Genetic advance, Heritability, Path coefficient.

*Corresponding author’s e-mail: v.k9181@gmail.com, 1Department of Genetics and Plant Breeding, MSKJUAT, Banda,210001, India, 2 Division of Crop Improvement, Directorate of Wheat Research, Karnal-132 001, India

INTRODUCTIONWheat (Triticum aestivum L.em.Thell.) is

one of the most important staple foods of the world,occupying 17% of the total crop acreage worldwideand feeding about 40% of the population. Becauseof its high economic value and place among the foodcrops, it is also known as “The King of Cereals”. Itscontribution to total food grains production isapproximately 30-34%. Following the introductionof dwarfing gene (rht) based high yielding varietiesof spring wheat during sixties; India witnessed amajor breakthrough in wheat grain production(Swaminathan, 1987) from 12 million tons in 1965to 72 million tons in 1999-2000 and productivityincrease from 0.6 to 2.7 tons per hectare. Wheat isgrown in diverse agro-climatic conditions from 110

N to 350 N from 720 E to 920 E and from almost sealevel to very high altitudes. In India, wheat producingstates mainly lie between 200 N to 320 N. Wheatgrown on commercial scale belongs to three speciesof the genus Triticum namely Triticum aestivum(bread wheat or common wheat), T. durum

(Marcaroni wheat) and T. dicoccum (Emmer khapliwheat). The common wheat (T. aestivum; 2n= 42),is the most important and accounts for nearly 86per cent of the total area under wheat cultivation inIndia. The macaroni wheat (T. durum) is the next inimportance with approximately a little over 12 percent of the total wheat area under its cultivation.

Improvement of the crop depends upon themagnitude of genetic variability of economiccharacters. Therefore, the measurement, evaluationand manipulation of genetic variability in desireddirection become extremely important in any yieldimprovement program. The extent of geneticvariability in a specific breeding population dependsupon the genotypes included in it.

The aim of the present investigation was tostudy the genetic variability interrelationship andpath analysis in 40 genotypes on 10 characters ofwheat (Triticum aestivum L.). It will provide aneffective means to assess the extent of availablevariability, which will be useful for selecting superior

430 INDIAN JOURNAL OF AGRICULTURAL RESEARCH

TABLE 1: List of wheat genotypes used for studying variability and character association

Sl. No. Variety name Sl. No. Variety name Sl. No. Variety name Sl. No. Variety name

1 WH-196 11 MUW-44 21 UP-2338 31 CDWR-95262 MUW-45 12 Infector 22 CPAN-4061 32 PBW-4353 CDWR-9535 13 CPAN-6143 23 HW-1081 33 HD-22044 PBW-218 14 HD-114 24 WH-556 34 HD-26875 CDWR-9540 15 CPAN-6079 25 PBW-343 35 MUW-1186 CPAN-4062 16 PBW-325 26 CPAN-1910 36 K-93057 HD-2189 17 CPAN-4066 27 PH-132 37 HD-23298 Raj-1575 18 HD-2667 28 PBW-118 38 UP-23589 MUW-107 19 Malviya 29 UP-2425 39 Raj-368210 VL-687 20 UP-262 30 CDWR-9567 40 CPAN-1964

genotypes on the basis of their phenotypicexpression so as to use them in breeding programmeto improve the agronomically important characters.

MATERIALS AND METHODSPlant material: The experimental material consistedof 40 genotypes (Table 1) mainly released varietiesand advanced breeding lines which were planted ina RBD (Randomized Block Design) with threereplications during rabi 2005-2006 and 2006-2007at research fields of Ch. Charan Singh University,Meerut (U.P.) India. The plot size was three rows of3 m length, row to row and plant to plant spacingwas kept at 30 and 10 cm, respectively. Therecommended agronomic practices were followedto raise a healthy crop. The data were recorded onfive randomly selected competitive plants from eachplot on 10 characters viz., days to 50 per centflowering, days to 75 per cent maturity, plant height(cm), productive tillers per plant, spike length (cm),number of spikelets per spike, 100-grain weight (g),grain yield per plant (g), grain weight of main spike(defoliated) and grain weight of main shoot (nondefoliated). The mean of three replications was usedfor statistical analysis to compute genetic parameters(Genotypic and phenotypic coefficient of variation,heritability in the broad sense and genetic advance),correlation coefficients, and path coefficient analysiswith direct and indirect effect on yield using SPAR2.0 software computing program.

RESULTS AND DISCUSSIONAssessment of variability: The mean sum ofsquares due to genotypes was significant for all thecharacters indicating that the variation was due togenetic effects (Table 2). Though variability in apopulation is crucial for any crop improvement, it isonly criteria for deciding the gain under a breedingprogram. Phenotypic and genotypic variance and

coefficient of variation can help in this regard.Genotypic coefficient of variation (GCV) was lessas compared to that of phenotypic coefficient ofvariation (PCV) for all the characters (Table 3).Maximum variance (phenotypic and genotypic) wasexhibited by grain weight per plant (g), plant height,number of tillers per plant and spike length (cm)whereas minimum variance was recorded for daysto maturity. Similar results on variability for differentcharacters were reported by Mondal et al. (1991),Yadav and Mishra (1992), Pawar et al (2003), Guptaet al. (2004), Asif et al. (2004), Shahnaz-Menon etal. (2005) and Qaisar-Mahmood et al. (2005). TheGCV and PCV values were found to be very distantto each other for most of the characters. The distantrelationship between GCV and PCV indicated thatcharacters are much influenced by environmentalfactors. High amount of phenotypic and genotypicvariation was observed for the characters like grainweight per plant, plant height, spike length, numberof tillers per plant suggesting the presence of largeamount of variability. Wide range of differences foryield and its components were reported by Thakuret al 1989. Bahadur and Lodhi. (1993) and Sharmaet al. (1995). Since all the above characters havehigh range of variation and are more affected by theenvironmental factors, it is difficult to improve thecharacters through selection. The characters like 100-grain weight, grain weight of main spike, number ofspikes and days to 50 percent flowering, whichpossess moderate value of GCV and PCV can alsobe considered for selection.

Heritability estimates and genetic advancein a population provides information about theexpected gain in the following generation. The mostimportant function of heritability estimates, inthe genetic studies of quantitative characters is their

431Vol. 48, No. 6, 2014

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predictive role; possible advance through selectionbased on phenotypic values can be predicted onlyfrom knowledge of the degree of correspondencebetween phenotypic and genotypic values. Heritablevariation can be estimated with the greater degreeof accuracy, when heri tabili ty is studied inconjunction with genetic advance. Thus, it is clearthat a character with high genotypic coefficient ofvariation (GCV) and high heritability will have highgenetic advance. It can be stated that high heritabilityfor a trait does not necessarily mean that it will alsoshow high genetic gain, unless it is coupled with highgenotypic coefficient of variation (GCV). Theheritability, which is a ratio of genotypic andphenotypic variance, is mainly due to the additivegene effect in narrow sense. But in the broad sense,it includes both additive as well as non-additive geneeffects. The heritability values estimated in thepresent study expressed in broad sense. Moreover,broad sense heritability and narrow sense heritabilityare generally negatively correlated (Kempthorne,1957). If heritability was mainly due to additiveeffects, it would be associated with high genetic gainand if it is due to non-additive then genetic gainwould be low (Panse and Sukhatme 1957).

An estimate of heritability (h2) gives theproportion of total phenotypic variance that is dueto genetic causes and thus heritable. It may varywidely between populations and also from oneenvironment to another in the same material.Heritability is used in both broad sense and narrowsense. In crop environment, only the geneticcomponent of variation is important, since only thiscomponent is transmitted to the next generation. Thebroad sense heritability considered genetic variabilityin relation to total phenotypic variability andheritability in narrow sense take into account onlythe additive portion of the genetic variability. Highheritability indicated that the characters were lessinfluenced by the environment.

Characters such as days to 50 per centflowering, number of spikelets per spike, 100-grainweight and days to maturity showed moderate andlow GCV but also showed moderates heritability.Grain weight of mains spike reveals that highheritability but also show equally high geneticadvance Table 3. Johnson et al. (1955) suggestedthat character with high heritability coupled with

432 INDIAN JOURNAL OF AGRICULTURAL RESEARCH

TABLE 3: Heritability, genetic advance, genetic advance as per cent of mean, GCV and PCV of in wheat duringpooled analysis

Agro morphological Characters Phenotypic Genotypic Heritability Genetic advance ascoefficient variation coefficient variation ( percent) per cent of mean

Days to 50 percent flowering 7.02 3.55 25.5 3.69Days to maturity 1.41 1.15 67.3 1.95Plant height (cm) 12.21 12.17 99.3 24.97Number of tillers per plant 9.55 8.24 74.4 14.65Spike length (cm) 10.29 8.23 64 13.57No. spikelets per spike 6.19 4.51 53.2 6.78100-grain weight (g) 8.88 7.25 66.7 12.05Grain weight per plant (g) 14.5 12.38 72.9 21.78Grain weight of main spike (no treated) 4.5 3.93 76.4 7.23Grain weight of main spike (treated) 8.59 8.32 93.9 16.75

high genetic advance would respond to selectionbetter than those with high heritability and lowgenetic advance.

Moderate heritability and genetic advancewas observed for spikelets per spike and grain weightof main spike. It is indicated that these parametersare governed by additive gene action and could beequally improved through selection. On the otherhand, days to 75 per cent maturity exhibited highheritability with low genetic advance, indicated thatthis character was governed by non-additive genesand selection would not be effective for this character.

Plant height and grain weight per plant hadhigh GCV, heritability and genetic advance (aspercentage of mean). This indicated that thesecharacters were governed by additive gene effect andcan be improved through selection effectively. Onthe other hand, days to 75 percent maturity exhibitedlow GCV and genetic advance with moderateheritability indicating non-additive gene effect andfor improving this character heterosis breeding orrecurrent selection should be followed. Genotypeswhich exhibited both high variability and heritabilityalong with high genetic advance for certaincharacters may be evaluated in multi-location trialsand can be isolated as donors for these charactersor used as parents in hybrid development program.

Correlation and Path Coefficient Analysis:Among the selection parameters, correlation betweendifferent characters play vital role in developingappropriate selection criteria for the improvementof wheat genotypes. Data revealed from Table 4 and5 that in the present study in general, the genotypiccorrelation coefficient were higher than phenotypiccorrection coefficient.

On this basis, it could be interpreted thatthere was a strong inherent genotypic relationshipbetween the characters studied, but their phenotypicexpression was impeded by the influence ofenvironmental factors. It is revealed from Table 4that grain yield per plant showed highly positivesignificant correlation with number of tiller per plant,number of spikelets per spike, 100-grain weight andgrain weight of main spike. Days to 50% floweringshowed positive correlation with days to maturityand number of spikes per plant whereas negativecorrelation with spike length. Significant and positivecorrelation between grain weight of main spike andspike length, number of spikelets per spike, 100-grainweight, and grain weight defoliated spike. Our resultsare in close agreement with the results obtained byMohan et al. (1993), Rana and Sharma (1997),Bhutta and Chaudhary (1999), Mondal and Khajuria(2001), Singh and Dwivedi (2002), Indoo et al.(2004) and Quisar Mahmood et al. (2005). Theincrease in seed yield per plant was linear until theincrease in one component does not decrease theother component i.e. there was no genetic slippage.Thus, the intensity of selection for componentcharacters must be based on nature and magnitudeof covariance among them to obtain maximum seedyield per plant.

With the inclusion of more variables incorrelation studies, the indirect association becomesmore complex. Two characters may show correlationjust because they are correlated with a commonthird one. In such circumstances, path coefficientanalysis provides an effective means of finding outdirect and indirect effect of association and permitsa critical examination of specific forces acting toproduce a given correlation and measure the relativeimportance of each factor.

433Vol. 48, No. 6, 2014

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434 INDIAN JOURNAL OF AGRICULTURAL RESEARCH

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435Vol. 48, No. 6, 2014

In the present study, seed yield per plant hasbeen taken as dependent variable, whereas,remaining 9 characters were considered asindependent variables contributing towards yield. Itwas concluded that number of tillers per plant hadhighest direct effect on seed yield per plant atgenotypic levels and grain weight of main spike atphenotypic level (Table 6 and 7).

At the genotypic level, number of tillers perplant, grain weight of main spike (defoliated),number of spikelets per spike, days to maturity and100-grain weight exhibited maximum direct positiveeffect on seed yield per plant but this direct effectwas nullified by their indirect effect on seed yieldper plant through each other. Number of tillers perplant and number of spikelets per spike exhibitedhighest direct positive effect on seed yield per plantat genotypic level and also the positive correlation.

Days to maturity exhibited positive directeffect on grain yield per plant and positive correlationwith grain yield per plant. 100-grain weight haddirect positive effect on grain yield per plant andpositive correlation with grain yield. Grain weightof main spike exhibited negative direct effect on grainyield and positive highly significant correlation with

grain yield. Grain weight of main spike had directpositive effect on grain yield and highly significantpositive correlation with grain yield. Days to 50%flowering exhibited negative direct effect on grainyield per plant and positive correlation with grainyield. Plant height and grain weight mains spike haddirect negative effect on grain yield per plant whilenegative correlation with grain yield. This result wasexhibited on the basis of genotypic path. Phenotypicpath showed direct positive effect of the characterson grain yield per plant except number of spikeletsper spike and 100-grian weight. Days to maturity,productive tillers per plant and grain weigh of mainspike showed positive direct effect on seed yield andalso had positive correlation but productive tillersper plant showed highly significant positivecorrelation with grain yield. The present findings arein close conformity with earlier reports of Bahadurand Lodhi (1993), Singh and Dwivedi (2002), Ismail(2001) and Dokuyucu et al. (2002).

The residual effect was associated with thevalues of standard positive regression 0.6209 atgenotypic level and 0.5467 at phenotypic level, whichindicated the contribution of remaining factor thanthose studied.

REFERENCESAsif, M., Mujahid, M.Y, Kisana, N.S, Mustafa, S.Z. and Ahmed, I. (2004). Heritability genetic variability and path

coefficient of some traits in spring wheat. Sarhad J. Agric. 20: 87-91.Bahadur, R. and Lodhi, G.P. (1993). Variability and association studies in wheat (Triticum aestivum L.). Crop Res. 9:

313-316.Bhutta, W.M. and Chaudhary, M.A. (1999). Association analysis of some drought related traits in spring wheat. J.

Animal and Plant Sci. 9: 77-80.Docuyucu, T., Akkaya. and Akcura, M. (2002). Path analysis of yield and some yield traits of durum wheat. Turkish J.

Field crops. 7: 31-39.Gupta, R,S., Singh, R.P., and Tiwari, D.K. (2004). Analysis of heritability and genetic advance in bread wheat (Triticum

aestivum L.). Advance-in-Plant Sci. 17: 303-305.Indoo, Bhagat., Randhawa, A.S. and Sharma, S.K. (2004). Path analysis in wheat. J Res. Punjab Agric. Univ. 41: 63-84.Ismail, A.A. (2001). Identification of selection traits for yield improvement of bread wheat using path analysis. Assiut J.

Agric. Sci. 32: 63-84.Johnson, H.W., Robinson, H.F. and Comstock, R.E. (1955). Estimates of genetic and environmental variability in

soyabean. Agron. J. 49: 314-318.Kempthorne, O. (1957). An Introduction to Genetic Statistics. Wiley & Sons: New York.Mohan D.S. R, Singh H and Khola O P S (1993). Correlation and path analysis in chickpea (Cicer arietinum L.).

Legume Res. 13: 25-35.Mondal, A.S., Chaudhary, S. and Ghosal, K.K. (1991). Genotypic and phenotypic variability in wheat. Envt. and Eco.

9: 926-928.Mondal, S.K. and Khajuria, M.R. (2001). Correlation and path analysis in bread wheat (Triticum aestivum L.) under

rainfed condition. Environ. and Eco. 18: 405-408.Panse, V.G. and Sukhatme, P.V. (1957). Statistical Methods of Agricultural Workers. ICAR Publication New Delhi.Pawar, S.V., Patil, S.C, Naik, R.M. and Jambhale, V.M. (2003). Genetic variability and heritability in wheat. J.

Maharashtra Agric. Univ. 27: 324-325.

436 INDIAN JOURNAL OF AGRICULTURAL RESEARCH

Qaisar-Mahmood, Qureshi, A.S., Khan, M.R., Tajammal, M.A. and Yousuf- HAyat (2005). Genetic veariability, heterosis,character association and path analysis of yield components in wheat (Triticum aestivum L.). Intern J Biol andBiotechnol. 2: 995-999.

Rana, V.K. and Sharama, S.C. (1997). Correlation among some morpho-physiological characters associated withdrought tolerance in wheat. Crop improv. 24: 194-198.

Shahnaz-Memon, Ansari, B.A. and Munoiza- Baloch. (2005). Estimation of genetic and variation for agro-economictraits in spring wheat (Triticum aestivum L.). India J. Plant Sci. 4: 171-175.

Sharma, D.J., Yadav, R.K. and Sharma, R.K. (1995). Genetic variability and association of some yield component inwinter x spring nursery wheat. Adv. Pl. Sci. 8: 95-99.

Singh, S.P. and Dwivedi, V.K. (2002). Character association and path analysis in wheat (Triticum aestivum L.). Agric.Sci. Digest. 22: 255-257.

Swaminathan, M.S. (1987). The green revolution. In: The Future Development of Maize and Wheat in the Third World.CIMMYT, Mexico, D.F. 163 pp.

Thakur, S.K., Rao, S.K., koutu, G.K. and Srivastava, A.M. (1989) Genetic variability and path analysis in segregatingpopulation of wheat. Agric. Sci. Digest. 9: 159-161.

Yadav, R.K. and Mishra, R.K. (1992). Genetic variability and association with some quantitative characters in wheat.Agric. Sci. Digest. 12: 17-20.