Correlation and Path Coefficient Analysis Studies in Rice Hybrids (Oryza sativa L.)

Ch. Sucharitha *

Department of Genetics and Plant Breeding, Professor Jayashankar Telangana State Agricultural University, Agricultural College, Rajendranagar, Hyderabad, Telangana, India.

K. Sukumar

Department of Genetics and Plant Breeding, Professor Jayashankar Telangana State Agricultural University, Agricultural Polytechnic, Polasa, Jagtial, Telangana, India.

B. Laxmi Prasanna

Department of Genetics and Plant Breeding, Professor Jayashankar Telangana State Agricultural University, Regional Agricultural Research Station, Polasa, Jagtial, Telangana, India.

P. Swarna Sree

Department of Entomology, Professor Jayashankar Telangana State Agricultural University, Agricultural College, Rajendranagar, Hyderabad, Telangana, India.

*Author to whom correspondence should be addressed.


Abstract

The present investigation was carried out at Agricultural Polytechnic, Polasa, Jagtial, Telangana, to understand the correlation and path analysis for yield and yield attributing traits for 38 genotypes including 3 checks in Randomized Block Design replicated thrice during Rabi, 2022. Association studies revealed that genotypic correlation values were higher than that of phenotypic correlations. Important traits i.e., spikelet fertility (0.8151**/0.8199) followed by 1000 grain weight (0.7889**/0.7956) exhibited the highest positive significant association with single plant yield. Path coefficient analysis also revealed that the traits spikelet fertility and 1000 grain weight had reported the highest positive direct effect of on single plant yield at both genotypic and phenotypic levels. Hence, these traits could be used as selection indices for heterotic rice hybrid development.

Keywords: Correlation, path coefficient analysis, rice


How to Cite

Sucharitha, Ch., K. Sukumar, B. Laxmi Prasanna, and P. Swarna Sree. 2022. “Correlation and Path Coefficient Analysis Studies in Rice Hybrids (Oryza Sativa L.)”. International Journal of Environment and Climate Change 12 (10):972-80. https://doi.org/10.9734/ijecc/2022/v12i1030887.

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