Performance of qDTY QTL introgressed lines of rice (Oryza sativa L.) under target production environment

Abstract

Drought is an important factor limiting rice productivity in rainfed ecosystem. Development of high yielding drought tolerant rice varieties would increase rice production under such condition. In the present study, 116 qDTY QTL introgressed back crossed inbred lines (BILs) derived from the crosses viz., ADT (R) 45 * 3/Apo, ADT (R) 45 * 3/ Way Rarem and ADT (R) 45 * 2/Apo // ADT (R) 45 * 2/ Way Rarem along with parents were evaluated to assess their performance under target production environment. Estimates on genetic variability, trait association, direct and indirect effects of yield and yield components and principal component analysis were worked out. The results of genetic variability showed wide variation among the genotypes for different traits. High values of PCV than GCV showed the influence of environment on the traits. Genotypes could be selected based on total number of tillers per plant, number of productive tillers per plant, spikelet fertility, single plant yield, 1000 seed weight and grain yield per plot, which were found to have high heritability and genetic advance. Correlation analysis exhibited high and significant positive correlation of grain yield per plot with single plant yield and non significant positive association of all the traits except plant height that was negatively correlated. Path coefficient analysis of the genotypes showed that total number of tillers per plant had maximum direct effect on grain yield, while number of productive tillers per plant had high indirect effect on grain yield via total number of tillers. Based on genetic variability, correlation and path analysis, selection for six traits, viz., total number of tillers per plant, number of productive tillers per plant, single plant yield, spikelet fertility, 1000 seed weight and grain yield per plot, would be rewarding. The results of principal component analysis revealed that, four out of eleven principal components viz., PC1, PC2, PC3 and PC4 contributed 72.62% of the total variation with eigen values more than 1. PC1 accounted for the highest variability with 24.66% followed by PC2 (20.42%), PC3 (16.19%) and PC4 (11.35%). From this study, the traits contributing for variation were identified and the resulting genotypes would be beneficial for improving yield with drought tolerance.

Keywords

• target production environment
• variability
• correlation
• principal component analysis