Unravelling Genetic Divergence and Trait Dynamics in Rice (Oryza sativa L.) Genotypes through Multivariate Analysis

Rice is a vital staple crop, especially in Asia and India, but its sustainable production is threatened by population growth, limited resources, and climate change. Genetic diversity and divergence analysis are essential in rice breeding, as they enable the development of high-yielding, stress-tolerant varieties through effective parent selection and advanced statistical methods. This study aimed to evaluate genetic diversity among 29 rice genotypes using Mahalanobis D² statistics. The experiment was conducted during the kharif 2022 season at RARS, Warangal, following a randomized block design with three replications. Significant differences among genotypes were observed for all studied traits, indicating substantial variability. Based on D² analysis, the genotypes were classified into six distinct clusters, with cluster I containing the highest number of entries, followed by clusters VI and IV. The greatest intra-cluster divergence was found in cluster III, whereas the maximum inter-cluster distance occurred between clusters II and IV, suggesting the potential of these genotypes for hybridization to obtain superior recombinants. Clusters II, V, and VI exhibited higher mean values for several important traits. Principal component analysis revealed that the first three components accounted for 90.39% of total variability, with plant height, days to 50% flowering, and 1000-grain weight contributing most to divergence. These findings conclude that the presence of significant genetic diversity among the studied genotypes provides ample scope for selection and hybridization in rice improvement programs. Crosses between genotypes belonging to highly divergent clusters, particularly clusters II and IV, are recommended to exploit heterosis and obtain superior recombinants. Furthermore, traits such as plant height, days to 50% flowering, and 1000-grain weight should be prioritized during selection to enhance yield potential and adaptability.