Genetic diversity in soybean [ Glycine max ( L .) Merr.] genotypes based on agro‐morphological traits using univariate and multivariate statistical techniques

Abstract Soybean [ Glycine max (L.) Merr.] is a versatile leguminous crop that plays a vital role in biodiesel production, livestock feed, and enhancing global food security. Soybean production and productivity in Ethiopia are low compared to the national potential, mainly due to the lack of high‐yielding genotypes. Substantial genetic variability is essential for developing high‐yielding, climate‐resilient soybean varieties. This study was conducted during the 2024 growing season to assess genetic variability among soybean genotypes. The experiment evaluated 528 genotypes laid out in a 22 × 24 alpha‐lattice design with two replications. Analyses of variance revealed highly significant differences among the tested genotypes for all 13 quantitative traits. Some introduced genotypes produce >4 t ha −1 . High values for both the phenotypic coefficient of variation and the genotypic coefficient of variation were observed for most of the traits. High broad‐sense heritability was recorded for days to maturity (98.5%), petiole length (97.8%), number of nodes (98.4%), plant height (85.3%), internode length (84.4%), leaf width (90.9%), leaf length (91.1%), and leaf area (93.4%). In this study, all traits showed high genetic advance as a percent of the mean; however, the highest values were observed for yield (83%), leaf area (70%), days from flowering to maturity (69%), number of nodes (53%), and leaf length (52%). This suggests that genetic gain for these traits can be effectively achieved through direct selection. Principal component analysis showed that the first four components accounted for approximately 70% of the total variation among the 13 quantitative traits. Cluster analysis identified eight divergent groups, with the maximum genetic distance between clusters IV and VII followed by Clusters II and IV, indicating the potential for selecting parental lines for hybridization. The Shannon diversity index indicated that hilum color had the highest diversity among the nine qualitative traits. Both univariate and multivariate analyses demonstrate considerable genetic variability within the evaluated soybean genotypes. This provides ample scope for selecting superior and desirable genotypes. It is highly recommended to advance the best‐performing genotypes in the future breeding programs and evaluate them across diverse locations and seasons.