Genetic diversity analysis of sesame – A bayesian clustering approach
Diversity in plant genetic resources (PGR) provides opportunity for plant breeders to develop new and improved cultivars with desirable characteristics viz., high yield, pest and disease resistance, photosensitivity and high oil quality. Genetic diversity is a ubiquitous feature of all species in nature. Therefore, different genotypes of sesame were used for diversity analysis. Different clustering techniques were widely used for the analysis of diversity. In this paper, Bayesian hierarchical clustering algorithm is applied which can be interpreted as a novel fast bottom-up approximate inference method. Finally, this method clusters the genotypes into various groups with their corresponding genotypes in respective clusters.
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