Deciphering the genetic diversity among a subset of rice (Oryza sativa) germplasm accessions through principal component analysis

Rice (Oryza sativa L.) is a vital staple crop that nourishes more than half of the global population, especially in Asia. To meet the rising food demand, improving rice productivity and adaptability by effectively utilizing the genetic diversity present in germplasm accessions is essential. In this study, 300 rice germplasm accessions representing diverse sub-groups of O. sativa were evaluated during kharif 2023 at two locations, Mandya and Gangavathi, using an alpha lattice design. Phenotypic observations were recorded for 9 agro-morphological traits. Principal component analysis (PCA) was used to assess genetic diversity and identify key traits contributing to total variation. At Mandya and Gangavathi, the first 4 principal components (PCs) with eigenvalues greater than one accounted for 64.35 % and 69.01 % of the total variability, respectively. Traits such as days to 50 % flowering, productive tillers (PT), spikelet fertility (SF) and panicle weight (PW) were major contributors to variability across locations. Principal component analysis biplots effectively visualized trait interrelationships and enabled the identification of superior-performing germplasm accessions. Germplasms located near a trait vector within the same quadrant of a PCA biplot are considered superior performers for those specific traits. Accessions such as IRGC 898, IRGC 1841 and IRGC 1022 were ranked higher based on their position and alignment with key trait vectors in the biplot. These accessions can be utilised as donor parental lines for combination breeding programs and for developing biparental mapping populations to identify Quantitative Trait Loci (QTLs) linked to specific traits.