1Department of Genetics and Plant Breeding, University of Agricultural Sciences, Dharwad, Karnataka, India
2Department of Crop Physiology, University of Agricultural Sciences, Dharwad, Karnataka, India
3Department of Genetics and Plant Breeding, University of Agricultural Sciences, Raichur, Karnataka, India
4Research Centre for Smart Agriculture, Centurion University of Technology and Management, Paralakhemundi, Odisha, India
*Corresponding author: shashidhara.gpb@gmail.com
Genetic variability, correlation and diversity studies were carried out during kharif 2022 using sixty advanced breeding lines of rice for yield component traits and grain quality traits under upland condition. Analysis of variance revealed the presence of significant variability among the genotypes for all the traits under study. High values of GCV and PCV observed for number of productive tillers per hill and grain yield indicated the wider range of variability for these traits. High heritability coupled with high genetic advance for plant height, number of tillers per hill, number of productive tillers per hill, panicles per sqm, test weight, grain yield, grain iron content, zinc content and protein content suggested the scope for improvement of these traits through selection. Correlation analysis unveiled positive significant association of grain yield with spikelet fertility percentage and negative significant association with grain zinc content. Genetic diversity analysis using K-means clustering formed six clusters, with highest number of genotypes grouped in cluster I. The maximum inter-cluster distance was seen between cluster IV and cluster VI (7.25) showing broader genetic diversity between the genotypes of these clusters and such genotypes can serve as divergent parents in hybridization programmes to get high heterosis and superior segregants.
⓿ Genetic variability and heritability in yield and quality traits of upland rice.
⓿ Trait association of grain yield with spikelet fertility and zinc content.
⓿ Genetic divergence among rice genotypes through K-means clustering.
Advanced breeding lines, correlation, K-means, diversity and clusters