Vol. 12, Issue 2 (2023)

Author(s):
Zaw Moe Aung, Sunil Kumar, Manoj Kumar, Lakshmi Chaudhary and Uma Devi

Abstract:
Chickpea (Cicer arietinum L.) is one of the most important pulses crop with Seventy-five genotypes were sown during rabi season 2019-2020. These seventy-five genotypes studied for genetic variability and diversity for seed yield and it’s contributing traits. Also, the inter-relationship and direct–indirect effects between yield and yield component traits on seed yield were studied. For all the yield and yield attributing traits were observed significant variability among the genotypes. As described in DUS Guidelines for morphological characterization of chickpea were carried out. The seed yield in Desi type had significant positive association with plant height, number of primary branches, number of secondary branches, number of pods, number of empty pods, pods weight, 100-seed weight, biological yield and harvest index. In Kabuli type seed yield had significant positive correlation with days to maturity, number of pods, pods weight, biological yield and harvest index. Path coefficient of Desi type have high positive direct effects on biological yield, harvest index, pods weight, days to first flower, number of primary branches and negative direct effect for days to 50% flowering. In Kabuli type, maximum positive direct effect on days to first flower was observed for days to maturity, number of empty pods, biological yield and negative direct effects on days to 1^stpodding, pods weight and 100-seed weight. High estimates of PCV % and GCV % of the Desi and Kabuli type of chickpea genotypes were observed for number of pods, number of empty pods, pods weight, biological yield and seed yield per plant. On the basis of phenotypic variance in Desi type genotypes viz. H 19-77, H 19-97, H 19-98, H 19-105, H 19-107, H 19-115, H 19-116 and HC 5 and Kabuli type genotypes HK 19-19 were found superior and genetically diverse. These elite genotypes exhibited superiority in the present study for yield and yield contributing traits can be exploited in advanced generation selection in future chickpea improvement programme.