Indian Journal of Agricultural Research

  • Chief EditorV. Geethalakshmi

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Indian Journal of Agricultural Research, volume 49 issue 1 (february 2015) : 77-82

Genetic divergence, correlation and path coefficient analysis in okra

R.K. Sharma, K. Prasad*
1B.P.S. Agricultural College, Purnea–854 302, India
Cite article:- Sharma R.K., Prasad* K. (2024). Genetic divergence, correlation and path coefficient analysis in okra. Indian Journal of Agricultural Research. 49(1): 77-82. doi: 10.5958/0976-058X.2015.00011.6.

ABSTRACT

Twenty okra genotypes were evaluated for genetic divergence, correlation and path coefficient for yield and its contributing attributes. Differences for the studied characters among the selected genotypes were significant and indicated the existence of variability among them. The results indicated that genotype Sel.-7, 71-14 and KS-312 were among the tallest. The phenotypic variance and coefficient of variation were higher than their respective genotypic variance and coefficient of variation for all the traits indicated the environmental effects on their expression. The differences between genetic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) were high for fruit diameter (FD) followed by number of branches per plant (NB), days to 50% flowering (DF), fruit weight (FW) and days to first harvest (FH) indicating the vulnerability of traits to environmental influences reflects the possibilities of varietal improvement. The difference between genotypic and phenotypic correlation coefficient indicates the influence of environmental effects. Number of fruits per plant (NP) and fruit weight (FW) contributed major maximum direct positive effect to fruit yield per plot, whereas number of branches per plant (NB) and days to first harvest (FH) showed highest negative direct effect on yield component. Plant height, however, showed highest positive indirect effect via number of fruits per plant and negative indirect effect via fruit weight. Number of branches (NB) showed positive indirect effect via number of fruits per plant (0.7655) and plant height (0.2728) and negative indirect effect via fruit weight (-0.2830). The estimated residual effect found was 0.0118 indicated about 98.82% of variability in fruit yield was contributed by studied yield affecting characters.

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