Estimation of Genetic Parameters, Selection Indices and Association Analysis of Seed Yield and Its Component Traits in Chickpea (Cicer arietinum L.) 

Chickpea (Cicer arietinum L.) is a cool season food legume crop belongs to family fabaceae, subfamily papilionacea. Primarily, it is grown in rabi season under rainfed ecology of tropical and subtropical regions of the globe. Chickpea is cultivated in around 56 countries across world and India ranked first in production and consumption. Globally, it is cultivated on 17.85 million ha area with the production of 17.23 million tons (FAOSTAT, 2018). In India, chickpea is grown in 11.89 million ha area and produced 11.38 million tonnes of grain with the productivity of 9568 kg/h (FAOSTAT, 2018). Chickpea shares 44.51% of total pulses production and covers 36.41% of the total area of pulses in India and continues to be largest chickpea producer (DAC and FW, 2018). In India, more than 68% chickpea area is under rainfed cultivation (Sharma et al., 2019) and crop suffers from various biotic and abiotic stresses. Drought is one of the most important edaphic stressors affect the chickpea crop at reproductive phase which adversity impact on productivity. Alone Uttar Pradesh produced 7.27 million tons of chickpea on 5.72 million ha area with the productivity of 1272 kg/ha. Notably, Bundelkhand region of Uttar Pradesh is a major area of chickpea cultivation, where it grows on 3.90 million ha with the production and productivity of 4.86 million tons and 1324 kg/ha respectively (Department of Agriculture, 2018-19).
 
Genetically seed yield is complex trait, controlled by cumulative effect of several genes. The direct improvement in polygenic traits is rarely possible due to low heritability and genotype × environmental interaction. Thus, estimation of association of yield component traits coupled with seed yield is a key objective in chickpea breeding program. Association of secondary traits with yield would be effective for the selection of genotypes with improved yield potential (Padmavathi et al., 2013). The selection efficiency of yield contributing characters depends on the heritability which brings out the genetic gain from the selection. The several yield component traits are responsible for indirect selection of genotypes with high yield potential to be taken into consideration in chickpea breeding programme for development of improved chickpea genotype. Therefore, correlation coefficient helps to determines how the complex trait can be improved through indirect selection of yield contributing traits (Mohan et al., 2019). The aim of present study was to estimates the contribution of component traits into seed yield through direct and indirect ways and estimates the association between components traits.
 
 

Experimental site and material
The experiment was carried out at the experimental research farm of Banda University of Agriculture and Technology, Banda U.P., India. The experimental material consisted of ninety germplasm accessions of chickpea and four check varieties viz., JG14, JG16, JAKI 9218 and Radhey. The germplasm comprised with high yielding advanced breeding lines, elite lines, released Indian varieties recommended in central zone (CZ) and North Western Zone (NWZ), genetic stocks and landraces acquired from SAUs, ICRISAT and IIPR Kanpur. The list of genotypes is given in Table 1. The experiment was laid in augmented block design during rabi season of 2018-19. The entire experimental field was divided into 9 blocks of equal size and each block had 14 entries. Out of 14 entries in a block, 10 entries were test genotypes which were not replicated while remaining 4 were check varieties. The checks were randomly allocated along with the test genotypes in a block. The row length of each entry was 2 m in length, following inter and intra row spacing of 30 cm and 10 cm, respectively.


 
Observations recorded
 
Seventeen traits were recorded at different growth stages i.e. germination, vegetative, reproductive and maturity. The post-harvest observations were also recorded on seed traits. The days to germination, early plant vigor, days to first flower initiation, days to 50% flowering, days to 100% flowering, days to first pod appearance and days to maturity represented by a single value and computed on plot basis. The data on other quantitative traits viz, plant height, height of first pod, average inter-nodal distance, number of primary branches per plant, number of secondary branches per plant, number of pods per plant, number of seeds per pod and harvest index were recorded from the five randomly selected plants from each genotype. Harvest index was calculated by dividing the biological weight of five randomly selected plants to seed yield of each genotype. 100-seed weight was calculated by weighing 100 counted seed from each genotype with automatic seed counter machine from each plot and weighed by electronic weighing balance. Total yield per plot was calculated after harvesting in an area of 1.2 m2 from each genotype and converted into kg/ha.
 
Statistical analysis
 
The averages of five randomly selected plants of each trait was subjected to analysis of variance (ANOVA) and estimates the genetic coefficient of variance and phenotypic coefficient of variance using SPAR 2.0 Package (Ahuja et al., 2008). The heritability in broad sense in per cent and expected genetic advance was calculated by the procedure suggested by Dewey and Lu (1959) and genetic advance as per cent of mean was estimated by the formula suggested by Robinson et al., (1949). The correlation coefficient analysis at phenotypic level was calculated based on formula given by Johnson et al., (1955). The path coefficient analysis was calculated according to the equation suggested by Dewey and Lu (1959). Selection index based on a number of measurements was calculated according to the equation suggested by Smith (1936). The estimators of heritability, genetic advance, correlation coefficient and path analysis were analysed using Windostat Version 9.2 from Indostat services.
 

Analysis of variance (ANOVA)
 
Analysis of variance confirms considerable genotypic variability present for all the characters under study except number of secondary branches, number of pod per plant and number of seeds per plant (Table 2). The significant difference in genotypes for flower initiation, primary branches, secondary branches, number of pods per plant and grain weight was reported by Aswathi et al., (2019) indicating the presence of variability which can be exploited through selection. There is ample scope of inclusion of identified promising genotypes in breeding program for improvement in yield and its components characters. The traits such as days to germination, days to flower initiation, days to 50% flowering, days to 100% flowering, days to first pod appearance, days to maturity, plant height, height of first pod and total grain yield were showed significant differences over the blocks. All traits except days to germination, early plant vigour, internode distance and seed index showed significant difference among the checks in contrast analysis, while days to germination, days to flower initiation, days to 50% flowering, days to 100% flowering, days to first pod appearance, days to maturity, internode distance, harvest index, seed index and total grain yield showed significant differences among test genotypes. In genotypes vs checks, days to 50% flowering, number of seed per plant, harvest index, seed index and total grain yield also showed significant difference.


 
Variability parameters
 
The phenotypic coefficient of variance (PCV), genotypic coefficient of variance (GCV), heritability, genetic advance and genetic advance as percent of mean of each parameter are presented in Table 3. The PCV for all characters was higher than their corresponding GCV indicating the influence of environment on these traits. The effect of environmental variance was also reported by Sharma et al., (2019). The highest amount of GCV was recorded in height of first pod (35.29) followed by number of seed per plant (29.77), seed index (27.50), number of primary branches (25.63) and lowest was recorded in days to maturity (3.06). Maximum PCV was estimated in number of secondary branches (41.67) followed by number of pod per plant (41.37), total grain yield (40.32), height of first pod (39.29), number of seed per pod (34.56), early plant vigour (32.35), number of primary branches (31.44), seed index (27.98) and lowest was recorded in days to maturity (3.69). Shengu et al., (2018) recorded the lower PCV and GCV for plant height, number of pod per plant, seed index and total grain yield and also reported that the small influences of environmental on the traits plant height, number of pod per plant, number of seed per plant, days to 50% flowering, days to maturity and seed index.



The traits seed index, days to first pod appearance, days to 50% flowering, height of first pod, days to flower initiation, internode distance, days to maturity, harvest index and number of primary branches had high heritability ranged from 96.61 to 66.45% whereas, trait early plant vigour, days to 100% flowering, plant height and total grain yield showed medium heritability ranged from 54.54 to 42.66%. Least degree of heritability (≤ 39.91%) were estimated for days to germination, number of secondary branches, number of seed per pod and number of pod per plant. Highest genetic advance was estimated for total grain yield (94.73), however, rest of the traits showed low degree of genetic advance. The highest genetic advance as per cent of mean at 5% level of selection intensity was recorded for the traits height of first pod (65.27%) followed by grain weight (55.69). Though, at 1% level of selection intensity, highest genetic advance as per cent of mean was observed for height of first pod (83.66) followed by grain weight (71.36), total grain yield (58.02), number of primary branches (55.16), internode distance (43.61), early plant vigour (36.43), days to germination (24.65), days to flower initiation (24.44), days to 50% flowering (22.99), plant height (20.81) and harvest index (20.74). The estimated heritability gives the information about heritable proportion of variability which would be effective for selection of genotype. These finding are in confirmation with the results of Shengu et al., (2018) who reported the highest heritability for total grain yield and Kumar et al., (2019) reported moderate heritability for number of pod per plant along with high genetic advance. The high heritability and genetic advance for seed index indicates that the trait governed by additive gene action.
 
Correlation coefficient analysis
 
The correlation coefficient is used tofind out degree and direction of the association between secondary independent and dependent variables. The correlation coefficients between all the 17 characters among germplasm lines are presented in Table 4.


 
In the present study, number of seed per pod, number of pod per plant, seed index, number of secondary branches, number of primary branches and height of first pod were found positively and significantly associated with total grain yield. The positive significant association of number of pod per plant, number of seed per pod and seed index with grain yield was reported by Samyuktha et al., (2017). He has also been reported that traits viz., days to 50% flowering and days to maturity showed significant positive association with single plant yield. Similar results have also been reported by Kuldeep et al., (2014) for number of pod per plant, number of secondary branches, plant height and Pandey et al., (2013) for days to flowering, plant height, number of total branches, number of pod per plant and seed index. The highest degree of association of total grain yield was observed with number of seed per pod (0.607) followed by with number of pod per plant (0.524), seed index (0.414), number of secondary branches (0.400), number of primary branches (0.376) and height of first pod (0.239). On the other hand, association of other characters such as days to germination, early plant vigour, days to flower initiation, days to 50% flowering, days to first pod appearance, days to 100% flowering, internode distance, plant height, days to maturity and harvest index were observed insignificant with total grain yield. The relationship between two or more variables is presented through line diagram in Fig 1.


 
Seed index showed positive and significant correlation with height of first pod and number of primary branches but negative and significant correlation with harvest index. Early plant vigour had negative and significant correlation with days to germination. Similarly, Shengu et al., (2018) reported positive and significant association between seed index and total grain yield but negative and significant association between pod length and total grain yield. The traits which have positive significant relationship with seed yield could be useful for selection of genotypes through these characters with high yield potential. These results are confirmation with the result of Kumar et al., (2019); Mir et al., (2018) and Jain et al., (2019).
 
Path analysis
 
Total grain yield had the highest positive and direct effect on the number of seed per pod (0.607), number of pod per plant (0.524), seed index (0.414), number of secondary branches (0.400), number of primary branches (0.376), height of first pod (0.239) and harvest index (0.138). These results was similar to the finding of Samyuktha et al., (2017) and Pandey et al., (2013), who estimated the maximum direct positive effect of number of pod per plant and seed index on single plant yield. The direct and indirect effects of all yields contributing components on seed yield are presented in Table 5. Lenka and Mishra (1973) suggested the measurement of direct and indirect effect of yield components on yield and characterize as negligible (0.00 to 0.09), low (0.10 to 0.19), moderate (0.20 to 0.29), high (0.30 to 0.99) and very high (> 1.00).


 
This study shows negligible or very low (0-0.09) indirect effect of the maximum characters under studies. The indirect effect of some traits viz. height of first pod via seed index (0.147), number of primary branches via seed index (0.134), number of secondary branches via number of seed per plant (0.170) and number of pod per plant via number of seed per plant (0.299) had low and moderate indirect effect on total grain yield while the negative indirect effect was recorded for harvest index via seed index (-0.104). The maximum overall positive indirect effect was observed for the traits such as number of seed per pod (0.395), seed index (0.361) and harvest index (0.250). The positive indirect effect of days to 50% flowering via biological yield, number of pod per plant, seed index and number of primary branches was also reported by Kumar et al., (2019). The direct selection of traits which have highly positive influences on the seed yield would be effective for improvement in the grain yield of genotypes. The maximum value of partial correlation was observed for number of seed per pod (0.240) followed by seed index (0.149) and number of secondary branches (0.066). The higher level of residual effect (0.586) indicated that other variables needs to be considered in future studies. The direct and indirect effect of yield contributing traits on seed yield is presented in Fig 2.
 


Selection indices
 
Seed yield is a low heritable complex trait, thus direct selection are not reliable to improve productivity. A selection index is the useful method to exploit correlation among component trait with seed yield. The result of selection indices in respect of seed yield of ten best genotypes are shown in Table 6. Selection indices were observed ranging from 629.31 to 1168.12. The highest selection index value was recorded for the genotype ICVT 181106 and the lowest for PDG-4 genotype. On the basis of the index, the 10 best genotypes were selected under studies and they were given in descending order as follows ICVT 181106, ICVT 181107, PUSA-1053, JG 218, GNG-1999, ICVT 181102, HC 5, GNG 1926, Vijay and JG 24. Asghar et al., (2010) reported that the selection indices were found most effective in improving genotype in sweet corn.

 
 

The significant positive correlation of component traits with seed yield is useful in selecting genotypes with high yield potential. Seed yield showed positive and significant correlation with number of seed per pod followed by number of pod per plant, seed index and number of primary branches. Using correlation coefficient, genotypes selection with high yield potential would be effective. The traits, number of seed per pod, number of pod per plant, seed index, number of secondary branches and number primary branches, height of first pod and harvest index had positive and direct effect on the seed yield could also be effective for direct selection of genotypes. The trait with high heritability would be important for selection of potential parents for hybridization program. The genotype ICVT 181106 identified with highest selection indices for seed yield followed by ICVT 181107, PUSA-1053, JG 218 and GNG-1999. The knowledge generated on character association, genetic parameters and selection indices through the presented study will be utilised in future chickpea breeding programme.