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VOL. 8, ISSUE 4 (2026)
Elucidating the trait association and path coefficient analysis for pod yield, yield component & quality traits in groundnut (Arachis hypogaea L.)
Authors
D Jyoshna, N Sabitha, K John, P Latha
Abstract
The present investigation was carried out to assess character association and path coefficient analysis for pod yield and its component traits in groundnut (Arachis hypogaea L.). Twenty-five groundnut genotypes, along with two checks (Visishta and K-6), were evaluated in a Randomized Block Design with three replications at the dryland farm of S.V. Agricultural College, Tirupati, during kharif, 2025. Observations were recorded on sixteen physiological, yield and quality traits. Phenotypic and genotypic correlation studies revealed that kernel yield plant⁻¹, hundred pod weight, harvest index, hundred kernel weight, specific leaf area at 60 DAS, dry haulm yield plant⁻¹ and plant height exhibited highly significant positive association with pod yield plant⁻¹ at both phenotypic and genotypic levels, whereas days to 50% flowering showed a significant negative association. Path coefficient analysis revealed that kernel yield plant⁻¹ recorded the highest positive direct effect on pod yield plant⁻¹ at both the phenotypic and genotypic levels, followed by harvest index, plant height and hundred pod weight, while most of the remaining traits influenced pod yield mainly through their indirect effects via kernel yield plant⁻¹. The low residual effect (phenotypic = 0.007; genotypic = 0.001) indicated that the traits studied accounted for almost all the variability in pod yield. Hence, kernel yield plant⁻¹, hundred pod weight and harvest index may be considered reliable selection indices for improving pod yield in groundnut.
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Pages:1-5
How to cite this article:
D Jyoshna, N Sabitha, K John, P Latha "Elucidating the trait association and path coefficient analysis for pod yield, yield component & quality traits in groundnut (Arachis hypogaea L.)". International Journal of Agriculture and Plant Science, Vol 8, Issue 4, 2026, Pages 1-5
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