Multivariate Analysis of Genetic Diversity and Yield Attributing Traits in Indian Mustard [Brassica juncea (L.) Czern. and Coss.]

Background: The present study aimed to evaluate genetic diversity and identify key traits contributing to yield improvement in 53 accessions of Brassica juncea using multivariate analyses. Methods: Thirteen agro-morphological traits were assessed under an augmented randomized block design. Significant variation among genotypes was observed for most traits through ANOVA, highlighting the scope for genetic enhancement. Result: Principal component analysis revealed that the first three principal components explained 75.5% of the total variance, primarily influenced by shoot length, plant height, siliquae traits and yield attributes. The PCA biplot showed clear trait associations and grouped similar genotypes such as Pusa Bold, RH 119 and 53-14-24D. Mahalanobis D² clustering organized the genotypes into seven distinct clusters, with maximum inter-cluster distance indicating high divergence between clusters VI and VII. The study provides useful insights for breeders to select diverse parents and prioritize traits for the development of high-yielding cultivars.