MULTIVARIATE ANALYSIS OF GENETICALLY DIVERSE GERMPLASM LINES FOR YIELD, GRAIN QUALITY AND PROTEIN CONTENT IN RICE (Oryza sativa L.)

Abstract

A diverse set of 147 rice genotypes was evaluated for yield, grain protein content (GPC) and grain quality traits. The main objective was to understand the relationship of GPC with yield and important quality traits. Interestingly, GPC had a significant positive correlation with HRR (0.24), indicating that it is possible to identify lines with high GPC and HRR. Further, GPC exhibited significant negative correlation with GC (-0.33) and kernel length (-0.20) and a negative correlation with single plant yield (SPY; - 0.12). Head rice recovery % (HRR), another important trait kernel breadth (KB; -0.39) and amylose content (AC; -0.22). Regression analysis showed that GPC in rice grain is mostly influenced by gel consistency (GC), AC, HRR and hulling %. The principal component analysis (PCA) showed that four ‘Principal Components’ (PCs) contributed to maximum variability (~72.0%) and hierarchical clustering grouped the genotypes into 10 divergent clusters. The genetic diversity among the 147 genotypes evaluated was mostly contributed by Length to Breadth ratio (L:B), kernel length (KL), GC and KB. Clustering indicated that there was high degree of heterogeneity in clusters III to X and this could be exploited in identifying desirable recombinants through hybridization. The results have indicated that through proper evaluation and well panned breeding programs, it is possible to develop high yielding nutritionally enriched rice cultivars that could aid in addressing the both food and nutritional security.