Genetic Diversity and Principal Component Analysis of Yield Traits in Chickpea

Chickpea (Cicer arietinum L.) is an important cool-season food legume valued for its high protein content, nutritional quality, and resilience to dry land conditions. The crop exhibits substantial morphological and genetic variability, with two major market classes desi and kabuli differing widely in seed characteristics, plant habit, and adaptation. Enhancing chickpea productivity requires a clear understanding of genetic diversity, trait relationships, and the identification of superior parental lines for breeding programs. The present investigation evaluated 48 genotypes, including 3 checks, during Rabi 2024–25 at JNKVV, Jabalpur, to assess genetic divergence, trait contribution, and yield-associated variability. D² analysis grouped the genotypes into 17 clusters, with Cluster I containing the maximum genotypes (17). High inter-cluster distances, particularly between Cluster X and Cluster XIV, indicated wide genetic divergence suitable for obtaining transgressive segregants. Cluster mean analysis showed substantial variation for phenological, morphological, and yield traits, highlighting opportunities for selecting superior parents. Principal Component Analysis identified four components with Eigen values >1, together explaining 73.16% of total variability. PC1 (39.06%) was largely influenced by branching traits, pods per plant, biological yield, and seed yield. PC2 (17.16%) was associated with plant height, height at first fruiting node, and 100-seed weight; PC3 (9.13%) with days to flowering; and PC4 (7.79%) with harvest index. Several promising genotypes, including ICCV 241202, ICCV 241101, ICCV 241108, GL 21-18, and ICCV 241104, were identified based on principal component scores.