Principal Component Analysis and Genetic Divergence Studies for Yield and Quality Related Attributes of Hybrid Rice

Abstract

This study investigates the genetic divergence and yield and quality-related attributes of hybrid rice (Oryza sativa L.) through principal component analysis (PCA) and genetic divergence studies. Conducted during the Kharif 2022 season at the Seed Breeding Farm, Rice Improvement Project, Department of Plant Breeding & Genetics, JNKVV, Jabalpur, the research focused on 98 genotypes, evaluating 30 agronomic attributes based on DUS guidelines. Genetic variability, heritability, genetic advance, correlation, path coefficient, D2 analysis, and PCA were employed to analyze the data.The findings reveal significant genetic diversity among the genotypes, with traits like stem length, fertile spikelet, and panicle weight contributing notably to genetic divergence. PCA identified eight principal components accounting for 81.97% of the total variability, with the first component alone contributing 22.34%. The study emphasizes the importance of understanding genotypic and phenotypic characteristics for effective selection and breeding of diverse genotypes, ultimately enhancing hybrid rice technology and regional adaptability.The research highlights key traits contributing to genetic divergence and provides insights into the genetic architecture of hybrid rice, aiding in the development of high-yield, quality rice varieties. The comprehensive analysis of yield and quality traits offers a valuable resource for breeders aiming to improve hybrid rice cultivars, ensuring food security and nutritional value for the global population.