Agricultural Science Digest
SCOPUS
  • Year: 2025
  • Volume: 45
  • Issue: 5

Study of Genotypic and Phenotypic Variation in F2 Segregating Generation of Okra [Abelmoschus esculentus (L.) Moench]

  • Author:
  • Tanu Shiri1,*, Shailendra Singh Gaurav1, S.K. Singh2, Sourabh Jain3
  • Total Page Count: 6
  • Page Number: 766 to 771

1Department of Genetics and Plant Breeding, CCS University Campus, Meerut-250 004, Uttar Pradesh, India

2Department of Genetics and Plant Breeding, Chaudhary Chhotu Ram (PG) College, Muzaffarnagar-251 001, Uttar Pradesh, India

3Department of Science, S.D. College of Commerce, Muzaffarnagar-251 001, Uttar Pradesh, India

*Corresponding Author: Tanu Shiri, Department of Genetics and Plant Breeding, CCS University Campus, Meerut-250 004, Uttar Pradesh, India, Email: tanushiri27@gmail.com

Online published on 29 October, 2025.

Abstract

Hybrid breeding in Okra [Abelmoschus esculentus (L.) Moench] is important to improve productivity of this crop. Given that a breeder's primary goal is production, it's critical to understand the connections between the traits that have a direct and indirect impact on yield.

45 hybrids generated by crossing 10 diverse parents in structured mating design were evaluated to estimate the magnitude of their genetic variability and heritability in F2s. Mean performance across three replications were calculated for 21 traits and is assessed for their effect on yield. The recorded data were statistically analyzed at 5% level of significance by multivariate analysis using principal component and hierarchical cluster.

For all of the analyzed traits, the analysis of variance revealed a highly significant difference between population. A greater difference between PCV and GCV estimates for days to anthesis, days to 50% flowering and days to first picking indicates a greater degree of environmental control for these traits. Traits such as days to anthesis, days to 50% flowering and days to first picking shows low to moderate heritability. These findings show that there is enough genetic diversity in these parameters to support selection of better accessions. Using cluster analysis and principal component analysis (PCA), crosses were divided into groups based on their performance and the identification of the most discriminating attribute that accounted for the greatest variability. It revealed that yield per plant is highly associated with days to first picking, days to 50% flowering, days to anthesis, plant height and shoot length. Further, principal component shows 1000-seed weight and germination percentage followed by days to 50% flowering as the most discriminating trait. Hence, selection for any trait would favor future hybrids breeding programmes.

Keywords

Cluster analysis, Genetic variability, Okra, PCA