Abstract

Rice (Oryza sativa) is a major cereal crop that contributes significantly to global food security. Here, the aim of this study was to create scientific information on nature and magnitude of genetic variability and inter-relationship among yield and related agro-morphological attributes and also to explore the pattern of diversity among some local rice germplasms. Fourty seven local rice genotypes were evaluated following randomized complete block design with three replications. Analysis of variance manifested significant differences (P ≤ 0.001) among the genotypes based on all studied traits except leaf width reflecting broad spectrum of variability which offer an ample chances for selection. The phenotypic coefficient of variation (PCV) was higher than the corresponding genotypic coefficient of variation (GCV) for all the traits except filled grain panicle-1 indicating that there was an influence of environment on majority of the studied traits. Similarly, moderate broad-sense heritability with high genetic advance as percent of mean of majority of the traits also indicated the accumulation of additive gene effects and suggested direct selection for those characters for economic feasibility. Correlation analysis revealed significant positive and negative correlation among the traits. Principal component analysis showed that the first two principal components of the considered traits accounted for about 37.9% of the total variation and pointed out a wide variation among the genotypes. The dendrogram of cluster analysis grouped 47 rice genotypes into four clusters. Cluster II incorporated the highest number of genotypes followed by Cluster I. In terms of high yield potentiality cluster III had highest cluster mean for rice yield, followed by cluster IV. Data from this study offer a valuable gene pool from the traditional local rice germplasms which can be employed in future rice breeding program for either varietal improvement or developing new variety.

Key words: Rice genotypes, morphological traits, genetic variability, character association, diversity analysis