Genetic Variability, Character Association and Diversity Analysis in Advanced Breeding Lines of Rice (Oryza sativa L.)
Prashant Isharwal
Department of Genetics and Plant Breeding, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, U.S. Nagar, Uttarakhand – 263145, India.
Indra Deo *
Department of Genetics and Plant Breeding, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, U.S. Nagar, Uttarakhand – 263145, India.
Namata Kumari
Department of Genetics and Plant Breeding, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, U.S. Nagar, Uttarakhand – 263145, India.
Rajat Nautiyal
Department of Genetics and Plant Breeding, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, U.S. Nagar, Uttarakhand – 263145, India.
Raj Raman
Department of Genetics and Plant Breeding, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, U.S. Nagar, Uttarakhand – 263145, India.
Abhishek Singh
Department of Genetics and Plant Breeding, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, U.S. Nagar, Uttarakhand – 263145, India.
*Author to whom correspondence should be addressed.
Abstract
Rice remains the world’s most important food crop, and raising its yield depends on how well breeders can identify and combine the right agronomic and quality traits. This study evaluated 44 rice genotypes and three released checks (Govind, Pant Dhan 12, Pant Dhan 4) at Norman E. Borlaug Crop Research Centre (NEBCRC), G.B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, during the Kharif season of 2024 in an augmented block design for ten traits: days to flowering, plant height, tiller number, flag leaf length and width, flag leaf area, panicle length, test weight, amylose content and grain yield per plant. Analysis of variance showed highly significant differences among genotypes for all ten traits, confirming useful genetic variability. Tiller number and grain yield per plant showed the highest coefficients of variation, along with high heritability (67.6% and 71.0%) and high genetic advance per cent of mean (25.8% and 25.5%), which may indicate the presence of additive gene action. Panicle length recorded the highest heritability (88.60%). Grain yield correlated most strongly with tiller number (r = 0.742) and test weight (r = 0.505), and path analysis confirmed tiller number as the largest direct contributor to yield (0.603), followed by test weight (0.212). K-means clustering based on standard Euclidean distance grouped genotypes into six clusters, with Clusters I and VI being the most divergent. Principal component analysis retained four components (eigenvalue > 1) explaining 71.11% of total variation. PC1 (25.96%) was loaded mainly by grain yield per plant, tiller number, test weight and panicle length; the biplot confirmed the cluster grouping. These findings suggest tiller number and test weight may be used as reliable selection traits, and crosses between divergent clusters may be used for further yield improvement.
Keywords: Oryza sativa, advanced breeding lines, augmented block design, genetic variability, broad-sense heritability, genetic advance, character association, path-coefficient analysis, k-means clustering, principal component analysis