Analyzing rice genetic variability: Insight from PCA on diversity patterns
Ritesh Kumar Sahu, Archana S Prasad, Hemant Sahu, Vinay Premi, Sanjay Kumar Bhariya and Rahul Das Mahant
The present study was conducted to evaluate the genetic variability, heritability, genetic advance, and correlation among nine yield-contributing in a population of 186 recombinant inbred lines (RILs) derived from the cross Rkvy 211 × Chandrahasini. Observations were recorded on five randomly selected plants per RIL for days to 50% flowering, plant height, panicle length, number of tillers per plant, head rice recovery (HRR), grain length, grain breadth, length-breadth ratio and yield. Statistical analysis revealed significant genetic variability among the RILs, with phenotypic coefficient of variation (PCV) generally higher than genotypic coefficient of variation (GCV), indicating environmental influences. High heritability coupled with high genetic advance was observed for traits like plant height (98.13 & 25.19) and HRR (97.94 & 27.91), suggesting additive gene action and effective selection potential. Correlation analysis showed significant positive relationships between plant height and panicle length (r = 0.279**). Panicle length and yield (r = 0.231**), and number of tillers per plant and yield (r = 0.771**). Principal component analysis (PCA) identified four principal components explaining a total of 71.26% of the variability among traits, with grain characteristics, number of tillers, yield, panicle height, and panicle length being major contributors. These findings provide a comprehensive understanding of the genetic parameters influencing yield facilitating targeted selection and breeding of superior rice cultivars.
