Estimation of genotypic and phenotypic correlations coefficients for yield related traits of rice under Sodic soil

Abstract

Background and Objective: Global demand for food is rising because of population growth, increasing affluence and changing dietary habits. Rice is the major source of calories of more than half of the total global population. It is the world's third largest crop after maize and wheat. This research sought to determine the correlations between grain yield and its contributing traits and to measure the direct and indirect effects on grain yield in rice. Materials and Methods: On the basis of relationship of grain yield with yield contributing traits, the best genotype can be selected and utilized in breeding program. The estimates of genotypic and phenotypic correlation coefficients between eleven characters were computed together and also the direct and indirect effects of 11 characters viz., days to 50% flowering, days to maturity, plant height (cm), panicle bearing tillers per plant, panicle length (cm), spikelets per panicle, spikelet fertility (%), biological yield per plant (g), harvest-index (%), L/B ratio and grain yield per plant (g) on grain yield per plant estimated by path coefficient analysis using phenotypic and genotypic correlations. Results: According to results, the estimates of genotypic correlation coefficients between eleven characters were generally similar in sign but higher in magnitude than the corresponding phenotypic correlation coefficients. The highest positive both phenotypic and genotypic direct effect on grain yield per plant was exerted by biological yield per plant followed by harvest-index. In contrast, high order of negative both phenotypic and genotypic indirect effects were extended by biological yield per plant on grain yield per plant via harvest index, spikelets per panicle (-0.123) and plant height (-0.103). The direct effects of remaining nine characters were too low to be considered important and the rest of the estimates of indirect effects obtained in path analysis were negligible. The estimate of residual factors (0.091) obtained in both the path analysis was low whether it is direct or indirect. Conclusion: This represents highly favorable situation for obtaining high response to selection in improving yield and yield components in rice.