Electronic Journal of Plant Breeding

Open Access
SCOPUS
  • Year: 2019
  • Volume: 10
  • Issue: 2

Genetic diversity analysis of sesame-A bayesian clustering approach

  • Author:
  • R. Nivedha1, M. R. Duraisamy2,, Patil Santosh Ganapathi3, S. Manonmani4
  • Total Page Count: 6
  • Page Number: 748 to 753

1Agricultural Statistics, Tamil Nadu Agricultural University, Coimbatore

2Professor (Mathematics), Tamil Nadu Agricultural University, Coimbatore

3Assistant Professor (Agricultural Statistics), Tamil Nadu Agricultural University, Coimbatore

4Professor (Plant Breeding and Genetics), Tamil Nadu Agricultural University, Coimbatore

Abstract

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.

Keywords

Sesame, Clustering, Bayesian hierarchical clustering, Diversity analysis, R software