Evaluation of Morphological Traits, Yield Performance and Genetic Variability of Soybean (Glycine max L.) Genotypes in the Madhupur Tract of Bangladesh
Soybean improvement depends on the identification of genetically diverse germplasm with superior agronomic performance. This study evaluated the phenotypic diversity, yield potential, and genetic variability of a large and diverse panel of 278 soybean genotypes under the agro-ecological conditions of the Madhupur Tract, Bangladesh, during November 2023 to April 2024. The experiment was conducted in a randomized complete block design with two replications. Morphological, phenological, physiological, and yield-related traits were recorded and analyzed using analysis of variance, correlation, principal component analysis (PCA), and genetic parameter estimation. Considerable variation was observed for all evaluated traits. Pointed ovate leaves (58.3%), white flowers (38.1%), indeterminate growth habit (97.8%), medium plant height (64.7%), medium maturity (85.3%), and medium seed size (54.3%) predominated among the genotypes. Grain yield per plant (GY) ranged from 0.46 to 20.06 g, with BS-53 recording the highest yield, while several other genotypes also exhibited comparatively superior yield and favorable agronomic characteristics. BS-260 matured earliest (88 days) and BS-18 exhibited the highest leaf chlorophyll content. GY showed strong positive correlations with seeds per plant (r = 0.906 ***) and pods per plant (r = 0.862 ***). PCA explained 67.4% of the total phenotypic variation in the first two principal components. High broad-sense heritability coupled with high genetic advance for most traits suggested substantial genetic variability and potential responsiveness to selection under the conditions of the present study. The comprehensive characterization of this diverse germplasm panel and the identification of high-yielding and agronomically favorable genotypes provide a valuable resource for soybean selection and breeding in Bangladesh, while the promising genotypes warrant further multi-location and multi-season validation.