Correlation and Path Coefficient Analysis in F2 Segregating Population of RNR-15048 x Dokra-dokri in Rice (Oryza sativa L.)
Margam Bharath Kumar *
Professor Jayashankar Telangana Agricultural University, Rajendranagar, Hyderabad, Telangana, India and ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad, Telangana, India.
B. Vidhyadhar
Professor Jayashankar Telangana Agricultural University, Rajendranagar, Hyderabad, Telangana, India.
R. Abdul Fiyaz
ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad, Telangana, India.
Ch. Anuradha
Professor Jayashankar Telangana Agricultural University, Rajendranagar, Hyderabad, Telangana, India.
D.Srinivasa Chary
Professor Jayashankar Telangana Agricultural University, Rajendranagar, Hyderabad, Telangana, India.
*Author to whom correspondence should be addressed.
Abstract
The present experiment was conducted to study the correlation and path coefficient analysis in F2 segregating population of RNR-15048 x Dokra-Dokri taken up in augmented complete block design with two checks at ICAR-IIRR, Hyderabad during the Kharif-2022. Character association of the yield attributing traits revealed significant positive association of single plant yield with plant height, panicle length, total number of tillers, number of productive tillers, panicle weight, number of filled grains per panicle, total grains per panicle, spikelet fertility and thousand grain weight. Hence, selection for these traits could be rewarding. Path coefficient analysis revealed that number of productive tillers per plant, panicle weight, total grains per panicle, thousand grain weight, panicle length, total number of tillers per plant exhibited positive direct effect and also significant correlation with grain yield per plant. This suggests that the correlation is driven by indirect effects, highlighting the importance of considering these causal factors while selecting traits for yield improvement. Based on residual effect there is a moderate amount of unexplained variance in the yield traits indicating other attributes besides the characters studied are also contributing for yield improvement.
Keywords: F2 segregating population, correlation coefficient, path analysis, direct selection, rice