Evaluation of Morphological Diversity in Rice Lines through Multivariate Analysis

Enhancing rice productivity is a continuous challenge due to the increasing demand. To improve rice grain yield and quality attributes, knowledge of genetic diversity is crucial. Therefore, this study used multivariate analysis to reveal the genetic diversity of twenty-five R lines. This study observed the most significant divergence in productive tiller number (PT), having a CV of 19.23%, which was followed by total grains panicle-1 (19.15%) and filled grains panicle-1 (16.94%). Principal Component Analysis (PCA) revealed that 98.21% of the total variability was contributed by the first two components. The genotype-by-trait biplot revealed that total grain panicle-1 (TG/P), filled grain panicle-1 (FG/P), and fertility rate (FR) are the three traits that contribute more to genotype variation. Strong, significantly positive associations were found between FG/P and TG/P, plant height (PH) and TG/P, FR, and grain length (GL), FR and grain length breadth ratio (L/B), GL and L/B. Strong, significantly negative associations were found between TG/P and FR, TG/P and GL, TG/P and L/B, PH and FR, and grain breadth (GB) and L/B. Cluster analysis and genetic dissimilarity study suggest that genotypes A14, A17, and A20 are more diverse and could be potential sources of genetic diversity in breeding programs.

Keywords: Genetic diversity; PCA; Correlation; Genetic dissimilarity.