Genetic diversity analysis of sesame - A bayesian clustering approach.

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  • Additional Information
    • Author-Supplied Keywords:
      Bayesian hierarchical clustering
      Clustering
      Diversity analysis
      R software
      Sesame
    • NAICS/Industry Codes:
      111120 Oilseed (except Soybean) Farming
    • 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. [ABSTRACT FROM AUTHOR]
    • Abstract:
      Copyright of Electronic Journal of Plant Breeding is the property of Indian Society of Plant Breeders and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
    • Author Affiliations:
      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
    • ISSN:
      0975-928X
    • Accession Number:
      10.5958/0975-928X.2019.00098.X
    • Accession Number:
      137279957
  • Citations
    • ABNT:
      NIVEDHA, R. et al. Genetic diversity analysis of sesame - A bayesian clustering approach. Electronic Journal of Plant Breeding, [s. l.], v. 10, n. 2, p. 748–753, 2019. Disponível em: . Acesso em: 20 out. 2019.
    • AMA:
      Nivedha R, Duraisamy MR, Ganapathi PS, Manonmani S. Genetic diversity analysis of sesame - A bayesian clustering approach. Electronic Journal of Plant Breeding. 2019;10(2):748-753. doi:10.5958/0975-928X.2019.00098.X.
    • APA:
      Nivedha, R., Duraisamy, M. R., Ganapathi, P. S., & Manonmani, S. (2019). Genetic diversity analysis of sesame - A bayesian clustering approach. Electronic Journal of Plant Breeding, 10(2), 748–753. https://doi.org/10.5958/0975-928X.2019.00098.X
    • Chicago/Turabian: Author-Date:
      Nivedha, R., M. R. Duraisamy, Patil Santosh Ganapathi, and S. Manonmani. 2019. “Genetic Diversity Analysis of Sesame - A Bayesian Clustering Approach.” Electronic Journal of Plant Breeding 10 (2): 748–53. doi:10.5958/0975-928X.2019.00098.X.
    • Harvard:
      Nivedha, R. et al. (2019) ‘Genetic diversity analysis of sesame - A bayesian clustering approach’, Electronic Journal of Plant Breeding, 10(2), pp. 748–753. doi: 10.5958/0975-928X.2019.00098.X.
    • Harvard: Australian:
      Nivedha, R, Duraisamy, MR, Ganapathi, PS & Manonmani, S 2019, ‘Genetic diversity analysis of sesame - A bayesian clustering approach’, Electronic Journal of Plant Breeding, vol. 10, no. 2, pp. 748–753, viewed 20 October 2019, .
    • MLA:
      Nivedha, R., et al. “Genetic Diversity Analysis of Sesame - A Bayesian Clustering Approach.” Electronic Journal of Plant Breeding, vol. 10, no. 2, June 2019, pp. 748–753. EBSCOhost, doi:10.5958/0975-928X.2019.00098.X.
    • Chicago/Turabian: Humanities:
      Nivedha, R., M. R. Duraisamy, Patil Santosh Ganapathi, and S. Manonmani. “Genetic Diversity Analysis of Sesame - A Bayesian Clustering Approach.” Electronic Journal of Plant Breeding 10, no. 2 (June 2019): 748–53. doi:10.5958/0975-928X.2019.00098.X.
    • Vancouver/ICMJE:
      Nivedha R, Duraisamy MR, Ganapathi PS, Manonmani S. Genetic diversity analysis of sesame - A bayesian clustering approach. Electronic Journal of Plant Breeding [Internet]. 2019 Jun [cited 2019 Oct 20];10(2):748–53. Available from: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=137279957&custid=s8280428