Multivariate Analysis of Genetic Variability and Trait Association in Indian Mustard (Brassica juncea L.)

Abstract

Background: Genetic improvement of Indian mustard (Brassica juncea L.) depends on the availability of exploitable genetic variability and a clear understanding of the relationships among yield-contributing traits. Identification of key selection criteria and genetically diverse parental lines is essential for enhancing seed yield and productivity. Aim: The study aims to assess genetic variability, trait associations, direct and indirect effects of yield-related traits, and genetic divergence among Indian mustard genotypes for yield improvement. Methods: Sixty Indian mustard genotypes along with two standard checks (RH 725 and RH 749) were evaluated during the Rabi season of 2023–24 at CCS Haryana Agricultural University, Hisar, using an augmented design. Nineteen morpho-physiological and yield-attributing traits were recorded. Genetic variability parameters, phenotypic and genotypic correlations, path coefficient analysis, and hierarchical cluster analysis were employed to identify important selection traits and genetically diverse genotypes. Results: Substantial genetic variability was observed for most traits. High genotypic and phenotypic coefficients of variation, coupled with high heritability and genetic advance as a percentage of the mean, were recorded for seed yield per plant, secondary branches per plant, leaf area index, photosynthetic rate, stomatal conductance, and carotenoid content, indicating predominance of additive gene action. Seed yield exhibited significant positive correlations with siliqua length, seeds per siliqua, siliquae on the main shoot, branching traits, plant height, 1000-seed weight, stomatal conductance, and chlorophyll content. Path analysis revealed that siliqua length exerted the highest positive direct effect on seed yield, followed by seeds per siliqua, plant height, siliquae on the main shoot, 1000-seed weight, and stomatal conductance. Cluster analysis grouped the genotypes into four distinct clusters, with the greatest genetic divergence observed between Clusters I and II. Genotypes Pusa Krishma, M 35, JD 6, and TM-106 were identified as superior for multiple desirable traits. Conclusion: Siliqua length, seeds per siliqua, branching traits, and physiological efficiency parameters emerged as reliable selection criteria for seed yield improvement. Crosses involving genetically divergent and high-performing genotypes from Clusters I and II may facilitate the development of superior, high-yielding Indian mustard cultivars.