Diversity Assessment of Rice (Oryza sativa L.) Genotypes Based on Quantitative Traits and Multivariate Analysis

Abstract

Rice (Oryza sativa L.) is an important staple crop and a major contributor to food security and agricultural economies worldwide. This study evaluated the genetic diversity among 25 fine-grain rice genotypes, including advanced breeding lines and commercial checks, using 14 agro-morphological, yield, and grain quality traits under field conditions at the Rice Research Institute, Kala Shah Kaku, Punjab, Pakistan. Significant variability was observed among the genotypes for most traits, indicating substantial genetic diversity. Principal Component Analysis (PCA) revealed that the first six principal components explained 81.27% of the total variation, with PC1 and PC2 accounting for 39.87%. Traits such as panicle length, days to flowering, days to maturity, and paddy yield contributed markedly to genotype differentiation. Cluster analysis grouped the genotypes into distinct clusters, reflecting varying levels of genetic divergence. Highly divergent genotypes identified through Euclidean distance analysis may serve as valuable parents in breeding programs. The results demonstrate the effectiveness of multivariate analysis in characterizing genetic diversity and provide useful information for the selection and development of improved high-yielding rice cultivars.