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Research Article Open access CC BY 4.0

Exploring Genetic Variability and Diversity in Exotic Germplasm Collection of Cocoa (Theobroma cacao L.)

Reshma S Nair, Minimol J S, Nayana Narayanan, Shilpa K S, Jiji Joseph

Journal of Advances in Biology & Biotechnology · pp. 1363–1371 · Published 23 Oct 2024

10.9734/jabb/2024/v27i101555

Abstract

The current research investigates the genetic variation and diversity in exotic accessions of cocoa to identify materials with desired characteristics as well as important traits contributing to yield and variability. The experiment was conducted at Cocoa Research Centre, Kerala Agricultural University, from 2021 to 2023. The study comprises 23 exotic genotypes in which observations were recorded on quantitative traits on flowers, pods, and beans. Statistical analysis was carried out based on the observations recorded. The morphological evaluation revealed ample variability among the genotypes for all the quantitative characters studied. The average dry bean weight recorded was 1.08 grams, which is a desirable trait in selecting individuals with high processing efficiency for the chocolate industry. Characters such as single bean dry weight, pod value, pod index, and efficiency index have recorded high values of GCV, heritability and genetic advance as percent of the mean. Principal component (PC) analysis showed that the first three PCs with more than one Eigen-value contributed to 92.18 percent of total variability among the germplasm. Yield components viz. pod value, total bean weight pod-1 and single bean dry weight significantly contribute to maximum variability among the exotic germplasm. Moreover, genotypes were grouped into five clusters based on hierarchical agglomerative clustering technique. Hybridization program involving superior genotypes identified in diverse clusters as parents can produce high-yielding hybrids. The high values recorded for the genetic parameters by yield components suggest the selection of genotypes based on which can result in better-performing progeny.

Quantitative traits correlation principal component analysis dendrogram Pod value

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