Multivariate analyses of rice indigenous germplasm for identification of high yield potential genotypes based on yield and its attributes

The study was carried out to estimate the extent of genetic variability and genetic parameters for yield and yield attributes along with principal components for 112 rice genotypes to determine selection criteria. Genetic variability parameters showed that the phenotypic coefficient of variation was higher than the respective genotypic coefficient of variation and heritability is high for most of the characters. High heritability with high genetic advance as per cent of mean and moderate heritability with high genetic advance as per cent mean observed for the traits indicates the heritability to be of additive nature and selection is effective for improvement of yield in the present breeding material. The principal component analysis revealed a total of five principal components during both seasons based on eigenvalues of more than 1 accounting for 74.76% and 72.80%, respectively. Coordinate 1 is comprised of 12 genotypes with the positive value of the first and second principal components common between seasons. Nine genotypes were plotted in coordinate 2 (negative values of PC1 and positive values of PC2) and were strongly associated with important yield attributing traits viz., 1000-grain weight, grain width and decorticated grain weight. The selection criterion TH + TGW + GW + YPP had high genetic advance and relative efficiency in both kharif, (sown at the beginning of the first rains during the advent of the south-west monsoon) 2022 and rabi, (sown at the end of the monsoon or the beginning of the winter) 2022-2023. The genotypes MTU 3626, Koshikari, CR 401 and SV 81C were identified based on index scores as better-ranked genotypes in both seasons. Therefore, by understanding the traits that are most important for rice yields and other desirable characteristics, one can develop more effective breeding strategies to identify the potential genotypes with desirable characteristics for crop improvement.