Selection criteria and multivariate analysis for identification of Turkey berry (Solanum torvum ) genotypes for genetic improvement by using correlation and principal components analysis

DOI: 10.37992/2023.1403.114

  • Nitish Kumar Jena, P. Irene Vethamoni, T. Saraswathi,
  • N. Senthil and D. Uma

Abstract

Loss of biodiversity, which has an impact on both plant development and genetic advancement, disrupts the fundamental services that ecosystems provide to humanity. Variability assessment is a challenging topic. Multivariate statistics can be useful for comparing and evaluating genetic variability. The data of 16 different morpho-physiological variables were subjected to several multivariate approaches, including principal component (PC) and correlation coefficient analysis, in order to assess the diversity of the twenty Turkey berry genotypes. The correlation coefficients discovered through this analysis were used to gauge the strength of the association between the traits. In this study, Pearson correlation analysis revealed a significant correlation between the observed phenotypic traits. Among these traits, number of branches per plant , number of leaves, leaf area, number of flowers per cluster, number of flower cluster per plant, number of fruits per cluster, number of fruit cluster per plant, and fruit diameter exhibited a positive and significant correlation with fresh fruit yield per plant, whereas days of first flowering exhibited a negative and significant correlation with fresh fruit yield per plant. Principal component (PC) analysis revealed that the first three PCs had Eigen values greater than 1, accounting for 81% of the overall variation. For morphological features, PC 1 accounted for the largest variability of 57% of the overall variation, and the lowest contribution (10%) was recorded by PC3. The genotypes St007, St006, St008, St010, St011, St001, St009, St018, St020, St003, St004, and St005 were shown to be more varied and better performers in terms of fresh fruit yield and yield contributing features based on the primary factor scores. According to research findings, the genotypes of Turkey berries identified in this work would serve as useful genetic tools for boosting the productivity of the fruits for upcoming breeding endeavors, especially in light of the unpredictability of climate change.

Keyword : Turkey berry, character association, correlation analysis, principal component analysis and quality parameter.

Published
03-10-2023
How to Cite
Nitish Kumar Jena, P. Irene Vethamoni, T. Saraswathi, N. Senthil and D. Uma

Selection criteria and multivariate analysis for identification of Turkey berry Solanum torvum genotypes for genetic improvement by using correlation and principal components analysis

. 2023. Electronic Journal of Plant Breeding, 14 3, 884-892. Retrieved from https://www.ejplantbreeding.org/index.php/EJPB/article/view/4817
Issue
Vol 14 No 3 (2023): EJPB
Section
Research Article

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