Genetic diversity assessment and fusarium wilt resistance screening in chickpea genotypes using multivariate analysis

Abstract

In the present study, genetic diversity and resistance to Fusarium wilt were evaluated in 33 chickpea genotypes along with three control varieties under wilt-sick field conditions during the rabi season of 2018–19 at Mahatma Phule Krishi Vidyapeeth, Rahuri, Maharashtra, India. The experiment was laid out in a randomized block design (RBD) with 2 replications and observations were recorded for ten important agronomic and yield-related traits. Analysis of variance (ANOVA) revealed significant differences among the genotypes for all traits studied, indicating the presence of substantial genetic variability. High heritability coupled with high genetic advance (GA) was observed for the number of pods per plant, days to 50 % flowering and 100-seed weight, suggesting the predominance of additive gene action and the effectiveness of selection for these traits in breeding programmes. Genetic divergence analysis using Mahalanobis D² statistics grouped the genotypes into 7 distinct clusters, with the maximum inter-cluster distance observed between clusters III and VII, indicating wide genetic divergence among the genotypes in these clusters. Principal component analysis (PCA) further supported the diversity pattern and K-means clustering based on PCA explained 66.63 % of the total variation, providing better discrimination among genotypes. Based on combined performance for yield attributes and Fusarium wilt resistance, the genotypes Phule G 1022-10-6, Phule G 1115-13-6 and Phule G 171101 were identified as promising. Overall, this study highlights the effectiveness of multivariate statistical approaches for identifying genetically diverse and disease-resistant chickpea genotypes for use in strategic breeding programs aimed at improving yields and resistance to Fusarium wilt.