Genetic variability, heritability, correlation and path analyses of yield components in traditional rice (Oryza sativa L.) landraces

The presence of sufficient genetic variability, the knowledge of nature of association among different characters and relative contribution of different characters to yield is a prerequisite to any breeding programme. The aim of the present study was to estimate genetic parameters of thirteen yield and yield attributing traits in 40 landraces of rice with a view to select better yield attributes in rice. The higher value of phenotypic co-efficient of variation (PCV) compared to the corresponding genotypic coefficient of variation (GCV) for all the studied traits indicated that there was an influence of the environment. Number of unfilled grains per panicle exhibited high estimates of PCV and GCV followed by number of filled grains per panicle, number of grains per panicle, flag leaf area. High heritability coupled with high genetic advance was observed in flag leaf area, pollen fertility, number of grains per panicle and number of filled grains per panicle which reflected that the direct selection of these characters based on phenotypic expression by simple selection method for yield improvement would be more reliable Grain yield per plant showed significant and positive association with days to 50% flowering, days to maturity, flag leaf area, number of total tillers per hill, number of effective tillers per hill, pollen fertility, number of grains per panicle, number of filled grains per panicle indicating selection of these characters for yield improvement may be rewarding. Both at phenotypic and genotypic level, days to 50% flowering, flag leaf area, number of effective tillers per hill, pollen fertility, panicle length, number of grains per panicle and 100 seed weight had direct positive effect on yield per plant indicating their importance during selection in yield improvement program. Moreover, the information generated from this study, can be exploited in future rice breeding program