ASSESSMENT OF GENETIC DIVERGENCE IN TOMATO THROUGH AGGLOMERATIVE HIERARCHICAL CLUSTERING AND PRINCIPAL COMPONENT ANALYSIS

Abstract

For the improvement of qualitative and quantitative traits, existence of variability has prime importance in plant breeding. Data on different morphological and reproductive traits of 47 tomato genotypes were analyzed for correlation, agglomerative hierarchical clustering and principal component analysis (PCA) to select genotypes and traits for future breeding program. Correlation analysis revealed significant positive association between yield and yield components like fruit diameter, single fruit weight and number of fruits plant-1. Principal component (PC) analysis depicted first three PCs with Eigen-value higher than 1 contributing 81.72% of total variability for different traits. The PC-I showed positive factor loadings for all the traits except number of fruits plant-1. The contribution of single fruit weight and fruit diameter was highest in PC-1. Cluster analysis grouped all genotypes into five divergent clusters. The genotypes in cluster-II and clusterV exhibited uniform maturity and higher yield. The D2 statistics confirmed highest distance between cluster- III and clusterV while maximum similarity was observed in cluster-II and cluster-III. It is therefore suggested that crosses between genotypes of cluster-II and cluster-V with those of cluster-I and cluster-III may exhibit heterosis in F1 for hybrid breeding and for selection of superior genotypes in succeeding generations for cross breeding programme.