Evaluation of genetic variability, correlation and path analysis in yield and yield contributing characters in rice (Oryza sativa L.) germplasm

This study aimed to quantify genetic variability, heritability, and genetic advance for key quantitative traits in rice, understand trait associations through correlation analysis, and unravel direct and indirect effects on yield using path coefficient analysis. Twenty-one irrigated rice genotypes were evaluated in a randomized complete block design with three replications during the 2023 kharif season in Prayagraj, Uttar Pradesh. Significant genetic variability was observed for all 12 traits studied. Number of Total Tillers exhibited the highest genotypic and phenotypic coefficients of variation. High heritability coupled with high genetic advance as percent of mean was observed for number of total tillers, flag leaf area, biomass, number of productive tillers, and number of spikelets per panicle, indicating the potential for effective selection. Correlation analysis revealed strong positive associations of biomass, number of productive tillers, and number of spikelets per panicle with grain yield. Days to maturity showed a positive correlation with yield, while plant height exhibited a negative correlation. Path coefficient analysis highlighted the importance of biomass, number of productive tillers and number of spikelets per panicle with both strong positive correlation and high direct effect on yield. Interestingly, number of productive tillers and number of spikelets per panicle, despite strong positive correlations with yield, showed substantial indirect effects through biomass, suggesting their influence on yield may largely be indirect through increased biomass. Flag leaf area demonstrated weak negative correlation with yield but positive correlations with yield components, indicating its potential indirect role in yield improvement. This study provides valuable insights for designing effective breeding strategies, emphasizing the complex interrelationships among yield-contributing characteristics and the importance of considering both direct and indirect effects in selection processes.