Genetic Diversity Analysis of Red Kernel Rice Genotypes using K-means Clustering for Grain Yield, its Components and Cooking Quality Traits

Abstract

The field experiment was conducted during kharif season (August−November), 2018 to evaluate the available red rice genotypes for genetic diversity using K-means cluster analysis for grain yield, its components and cooking quality traits at the College of Agriculture, V. C. Farm, Mandya. University of Agricultural Sciences, Bengaluru, Karnataka, India. Multivariate analysis was carried out in RCBD with 2 replications to understand the nature and magnitude of genetic divergence among sixty-four red rice genotypes. The analysis of variance showed that significant variance was observed among genotypes for all the traits studied. Based on K-means cluster analysis, optimum number of clusters formed were nine. Maximum number of genotypes grouped in cluster III (15) followed by cluster IV (12). Maximum intra-cluster distance was shown by cluster I (55.79) and cluster IX (53.50) indicating wide genetic variation among genotypes belonging to these clusters. Maximum inter-cluster distance (234.57) was recorded between cluster I and cluster IX followed by cluster VI and IX (231.49) revealing that the genotypes of these clusters were highly diverse and can be used as divergent parents for hybridization. The characters, plant height, alkali spreading value, water uptake ratio, gel consistency, days to 50% flowering and grain L/B ratio contributed 82.40% to the total divergence among the genotypes studied. Diversified red kernelled genotypes namely Rajamudi, Bramavara-8, Jenugudu, MSN-10-3, IET-19778, MSN-33-1, RP-1310-326, Champaka, Bramavara-8 and IET-16902 possessing desirable traits may prove useful for incorporation of these traits in the improvement of red rice.