Multivariate Assessment of Genetic Variation and Trait Associations in Moth bean (Vigna aconitifolia Jacq.)

Genetic variability, trait associations, and genetic divergence was studied among 49 moth bean genotypes. Analysis of variance showed significant genetic variation for most of the growth and yield-related traits. Correlation analysis revealed strong positive associations of total pods, clusters, and reproductive traits on branches with seed yield, while test weight was largely independent, allowing simultaneous improvement of yield and seed size. Principal component analysis explained 67.4% of total variability with the first two components; PC1 highlighted reproductive traits driving yield variation, and PC2 emphasized seed size and pod distribution. Leveraging these results, three PCA-based multi-trait selection indices—Yield Index, Seed Size Index, and Architecture Index—were constructed using respective trait loadings to streamline simultaneous selection of complex traits aligned with breeding objectives. Cluster analysis using Mahalanobis D² distances and Ward’s minimum variance method grouped genotypes into five distinct clusters revealing substantial genetic divergence. Unique genotypes in single-genotype clusters offer valuable genetic resources for broadening crop diversity. This integrative approach combining phenotypic variance, multivariate analysis, and genetic clustering provides a robust framework for effective parent selection and accelerated genetic gain in moth bean.