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*Corresponding author’s e-mail:dehal_indu@rediffmail.com.1Department of Plant Breeding & Genetics, Punjab Agricultural University, Ludhiana, Punjab-141 004, India, 2ICAR-Indian Institute of Maize Research,Pusa Campus, New Delhi-110 012.

Legume Research, 39 (4) 2016 : 510-516Print ISSN:0250-5371 / Online ISSN:0976-0571

Genetic estimates and path coefficient analysis in chickpea (Cicer arietinum L.)under normal and late sown environmentsIndu Bala Dehal*1, Rama Kalia and Bhupender Kumar2

Molecular Cytogenetics and Tissue Culture Lab., Department of Crop Improvement,CSK Himachal Pradesh Agricultural University, Palampur-176 062, India.Received: 02-12-2014 Accepted: 13-07-2015 DOI:10.18805/lr.v0iOF.9288

ABSTRACTThe research was carried out to determine selection criteria using correlation and path coefficient analysis in 25 chickpea(Cicer arietinum L.) genotypes under two different environments during rabi 2008-09 at Palampur location. The genotypesshowed highly significant differences for all the characters studied in both environments. Environment I (normal sowing)exhibited its excellent potential for the traits viz., seed yield per plant, biological yield per plant, pods per plant, primarybranches per plant, days to 50% flowering, days to maturity and plant height, whereas environment II (late sowing) exhibitedit for harvest index, per cent crude protein and 100-seed weight. High heritability coupled with high genetic advance wasobserved for seed yield per plant, pods per plant and 100-seed weight in environment I. Seed yield per plant was positivelyand significantly correlated with pods per plant (E1=0.767 and E2=0.647), harvest index (E1=0.767 and E2=0.745),biological yield per plant (E1=0.612 and E2=0.537) and primary branches per plant (E1=0.422 and E2=0.515) in both theenvironments. Path coefficient analysis revealed the high direct effect of biological yield and harvest index towards seedyield per plant, whereas primary branches per plant and pods per plant showed negligible direct effect, but their indirectcontribution for it through biological yield and harvest index was high. The present study suggests that selection for highseed yield should be based on selecting high biological yield, pod per plant, high test weight and primary branches perplants in chickpea.

Key words: Correlation, Cicer arietinum, Genetic variability, Path coefficient, Yield components.

INTRODUCTIONChickpea (Cicer arietinum L.) is the third most

important pulse crop in the world and ranks first in the Indiansubcontinent and Mediterranean basin (Jain et al. 2013). Likeother pulse crops, it has multiple functions in the traditionalfarming systems in many developing countries. Chickpea isimportant because it provides food for humans as well asfeed for livestock. The chickpea seed is a good source ofcarbohydrates and proteins, which together constitute 80%of the total dry seed weight (Ahmad et al., 2010). The successin any breeding programme depends upon the nature andmagnitude of genetic variability and heritability, whichprovides better chances of selecting desired types (Kumaret al., 2013). The knowledge of inter-relationships betweendifferent traits is important in breeding for direct and indirectselection of characters that are not easily measured and thosewith low heritability (Kumar et al., 2014). Some of thecharacters are highly associated among themselves and withseed yield. The analysis of the relationships among thesecharacters and their associations with seed yield is essentialto establish selection criteria.

However, simple correlation coefficients betweenyield and yield components may not give satisfactory

results. Because, the components do not only directly affectthe yield, they also affect the yield indirectly by affectingother yield components in negative or positive manner. As atrait has helpful effect on a trait for yield, it can affect someother or all traits negatively (Walton, 1980). Under suchsituations, the path coefficient analysis helps to determinethe direct contribution of these characters and their indirectcontributions via other characters (Singh et al., 1990). Forthis reason, many of the studies on correlation and pathanalyses have been conducted in field crops. Breedingchickpea for various desirable traits is limited by the lack ofadequate selection criter ia (Meena et al. , 2014).Determination of correlation between yield and itscomponents and to estimate genetic parameters of variabilityare important for selection of favourable gene and genotypeswhile breeding (Meena et al., 2014). Therefore, the presentstudy is an attempt to determine interrelationships betweenyield and its components and assess the direct and indirecteffects of each component on seed yield. The availableinformation will be helpful to devise an efficient selectioncriterion to select the most desirable, high yielding genotypesor pure lines of chickpea.

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MATERIALS AND METHODSTwenty five chickpea genotypes were evaluated in

a randomized complete block design (RCBD) with threereplications during rabi 2008-09 at the experimental farmof the Department of Crop Improvement, CSK HPKVPalampur (Table 1). The sowing was done in two differentenvironments with two different dates of sowing vizEnvironment I (normal sown) and Environment II (latesown). For each genotype, five rows of 4m length wereplanted in each plot with 30 cm and 15cm of row to row andplant to plant distance respectively. The observations wererecorded on seed yield per plant and various othermorphometric traits viz., days to 50% flowering, days tomaturity, plant height, primary branches per plant, biologicalyield per plant, pods per plant, harvest index, 100-seedweight and per cent crude protein. Except for enumerateddata for days to flowering and maturity, rest for all traits,five plants were taken from each genotype in each replicationto record the data. Semi-micro Kjeldahl method was adoptedto determine percentage nitrogen content and a conversionfactor of 6.25 was used to calculate crude protein content(AOAC, 1970).

N% =Titre value×0.014×Volume of digest×Normality of acid used

× 100Aliquot taken × weight of sample (g)

Crude Protein (%) = N (%) × 6.25The analysis of variance for different characters

was carried by following Panse and Sukhatme (1985) usingWINDOSTAT software. Correlation coefficients atphenotypic and genotypic level were computed as per themethods suggested by (Al-Jibouri et al., 1958). Pathcoefficients were estimated according to Dewey and Lu(1959), where seed yield per plant was kept as resultantvariable and other contributing characters as causalvariables.RESULTS AND DISCUSSION

The analysis of variance (ANOVA) revealedsufficient variability due to genotypes for all the traits studied(Table 2) indicating thereby the wide range of geneticvariability and scope of selection for these traits. On thebasis of mean performance, environment I exhibited itsexcellent potential for the traits viz., seed yield per plant,biological yield per plant, pods per plant, primary branches

Table 2: Analysis of variance for different traits of chickpea in pooled over the environments

Traits Mean squaresSource Genotypes Environments Genotype X Pooled error

Environment(GXE) (E)df 24 1 24 96Days to 50% flowering 74.34** 1029.67** 37.16** 2.98Days to maturity 45.84** 6733.50** 43.10** 5.62Plant height (cm) 97.59** 12346.99** 55.07 45.54Primary branches per plant 7.63** 396.25** 5.28** 1.61Biological yield per plant (g) 2243.05** 498816.70** 2595.82** 353.06Pods per plant 333.81** 20019.62** 282.07** 26.78Seed yield per plant (g) 632.68** 18150.00** 519.06** 56.59Harvest index (%) 101.86** 2692.31** 60.73** 23.96100-seed weight (g) 47.98** 85.12** 3.67** 1.71Protein content (%) 3.87** 4.33 1.09 0.57* Significant at P 0.05; ** Significant at P 0.01; df – degree of freedom

Table 1: List of chickpea genotypes (desi type) used for phenotypic evaluation in two different dates of sowing to determine selectioncriteria for yield improvementGenotypes Source S. No. Genotypes SourceICCV-182 ICRISAT, Hyderabad 14 DKG-7-4 CSKHPKV, PalampurL-306 CSKHPKV, Palampur 15 DKG-7-3 CSKHPKV, PalampurL-334 CSKHPKV, Palampur 16 ICCV-96904 ICRISAT, HyderabadL-HR-1 CSKHPKV, Palampur 17 Himachal Chana-1 CSKHPKV, PalampurICCV-95509 ICRISAT, Hyderabad 18 DKG-7-1 CSKHPKV, PalampurHPG-17 CSKHPKV, Palampur 19 L-HR-5 CSKHPKV, PalampurBGD-112 IARI, Delhi 20 L-221 CSKHPKV, PalampurL-88-2 CSKHPKV, Palampur 21 L-HR-34 CSKHPKV, PalampurICCV-95503 ICRISAT, Hyderabad 22 L-81 CSKHPKV, PalampurHimachal Chana-2 CSKHPKV, Palampur 23 L-113 CSKHPKV, PalampurL-328 CSKHPKV, Palampur 24 ICCV-96910 ICRISAT, HyderabadL-333 CSKHPKV, Palampur 25 L-294 CSKHPKV, PalampurICCV-96911 ICRISAT, Hyderabad

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per plant, days to 50% flowering, days to maturity and plantheight, whereas environment II for harvest index, per centcrude protein and 100-seed weight (Table 3). The reductionin seed yield per plant in late sown environment was observedto be 33.54%. There is only one genotype namely DKG-7-4which exhibited less reduction in late sown environment andalso better than best check. In environment I, maximum rangewas found for biological yield per plant (166.67-313.34)followed by seed yield per plant (45.00-118.34) and podsper plant (36.80-95.00) , where as in environment II,maximum range was for biological yield per plant (93.34-153.34) followed by seed yield per plant (33.34-66.67) andharvest index (26.54-47.57) .

Similar results have been reported by (Singh et al.,2004) on the performance of chickpea genotypes i.e. higherseed yield per plant in normal sown environment. Both PCVand GCV were high (> 25%) for seed yield per plant andpods per plant in environment I and for none of the traits inenvironment II indicating wide range of observed and geneticvariability for these traits in environment I. Similar findingshave also been reported by Dwevedi and Gaibriyal (2009).Heritability in broad sense was high (>70%) for days to 50%flowering, days to maturity, biological yield per plant, podsper plant, seed yield per plant and 100-seed weight inenvironment I, for days to 50% flowering and 100-seedweight in environment II. High heritability for these traitsrevealed lesser influence of the environment and greater roleof genetic component of variation. Thus, the selection forthese traits on the basis of phenotypic expression would bemore effective and can be relied upon. For an effectiveselection programme, knowledge of the estimates ofheritability alone is not sufficient. However, genetic advanceif studied along with heritability is more useful. Highheritability coupled with high genetic advance was observedfor pods per plant, seed yield per plant and 100-seed weightin environment I and for none of the traits in environment II.It indicated the predominance of additive gene action in theinheritance of these traits and hence selection would be mosteffective. High value of additive gene effects is an indicationof high breeding value as reported by (Muhammad et al.,2005).

Seed yield per plant exhibited significant andpositive genotypic and phenotypic correlations with podsper plant, harvest index, biological yield per plant andprimary branches per plant in both the environments. Thisindicated that selection for these traits can results insignificant improvement in the seed yield per plant. Positiveassociation of seed yield per plant with primary branchesper plant, biological yield per plant, pods per plant andharvest index was also observed by other workers (Bakhshet al., 2006; Yucel et al., 2006; Ali et al., 2011). Days to50% flowering had significant and positive correlation with100-seed weight and days to maturity in environment I.

Similar result was also observed by Thakur and Sirohi(2009). The positive correlation with 100-seed weight ofdays to 50% flowering may be because of the availability ofsufficient duration for the crop grain filling. Primary branchesper plant also showed positive correlation with biologicalyield per plant and pods per plant in environment II.Significant and positive correlations were also found betweenbiological yield per plant and pods per plant in both theenvironments.

At genotypic level, the estimates of correlationcoefficients were generally nearer to that observed at thephenotypic level for most of the traits (Table 4), however,the magnitude of genotypic correlation coefficients wasrelatively higher than their corresponding phenotypic valuesfor most of the characters. This indicated that phenotypicestimates of correlation coefficient represent the genotypiccorrelation coefficient and there is less effect ofenvironments, therefore, yield improvement through thesetraits which were significantly and positively correlatedwould be effective. It is difficult from correlation alone todecide the major contributor towards seed yield, because ofpresence of significant correlations of seed yield with yieldcomponents. Genetic improvement in chickpea is mainlyfocused on seed yield by breeders.

The relations (simple correlations and pathcoefficients) among the investigated characters wererecorded significant. The path coefficients were calculatedand partitioned into direct and indirect effects by using seedyield as a dependent variable (Table 5). Seed yield per plantshowed positive correlation with four traits viz., primarybranches per plant, biological yield per plant, pods per plantand harvest index at phenotypic and genotypic levels.Although four traits showed positive correlation with theseed yield per plant but when the direct and indirectcontribution of correlations were estimated, the direct effectswere found positive and high only for two traits viz.,biological yield per plant and harvest index. Therefore, thedirect selection for these traits can be significantly contributesfor yield improvement. However, rest of the traits which arepositively correlated to the yield but does not have directeffects are involve in the yield improvement through othercomponents traits hence, it may slow down the improvementto certain level. The results corroborate the findings ofvarious workers (Ciftci et al., 2004) and Singh (2007). Theyalso reported strong direct effects of the biological yield perplant and harvest index towards seed yield per plant andsuggested greater emphasis on longer duration duringselection. Furthermore, due to the positive and highcorrelations between seed yield and harvest index (0.767**),as harvest index increases seed yield raises significantly.These results were agreement with those of Yucel andAnlarsal (2010). The genotypes studied had wide range of

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516 LEGUME RESEARCH - An International Journal

variation for morpho-metric characters, so there is morescope for improvement of these characters.

Correlation and path analysis are important toolsfor getting appropriate informations regarding inter-relationship among different characters for effective selectionprogramme. In 25 diverse genotypes of chickpea (Cicerarietinum. L.), the genotypic correlations were higher thanthe corresponding ones. Seed yield had highly significantpositive correlation with biological yield per plant, pods per

plant, harvest-index and primary branches per plant.Biological yield per plant and harvest-index had highlysignificant correlation with seed yield and its direct effectwas very strong. Pods per plant and primary branches perplant were indirect contributory component. The presentstudy suggests that selection for high seed yield should bebased on high harvest index in chickpea. Therefore, dueemphasis may be given on these characters for selecting highyielding genotypes in chickpea.

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