Computational intelligence for studies on genetic diversity between genotypes of biomass sorghum

Authors

  • Michele Jorge da Silva Universidade Federal de Viçosa, Departamento de Biologia Geral, Avenida Peter Henry Rolfs, s/no, Campus Universitário, CEP 36570-000 Viçosa, MG.
  • Antônio Carlos da Silva Júnior Universidade Federal de Viçosa, Departamento de Biologia Geral, Avenida Peter Henry Rolfs, s/no, Campus Universitário, CEP 36570-000 Viçosa, MG.
  • Cosme Damião Cruz Universidade Federal de Viçosa, Departamento de Biologia Geral, Avenida Peter Henry Rolfs, s/no, Campus Universitário, CEP 36570-000 Viçosa, MG.
  • Moysés Nascimento Universidade Federal de Viçosa, Departamento de Estatística, Avenida Peter Henry Rolfs, s/no, Campus Universitário, CEP 36570-977 Viçosa, MG.
  • Marciane da Silva Oliveira Universidade Federal de Viçosa, Departamento de Biologia Geral, Avenida Peter Henry Rolfs, s/no, Campus Universitário, CEP 36570-000 Viçosa, MG.
  • Robert Eugene Schaffert Embrapa Milho e Sorgo, Rodovia MG-424, Km 45, Caixa Postal 285, CEP 35701-970 Sete Lagoas, MG.
  • Rafael Augusto da Costa Parrella Embrapa Milho e Sorgo, Rodovia MG-424, Km 45, Caixa Postal 285, CEP 35701-970 Sete Lagoas, MG.

DOI:

https://doi.org/10.1590/S1678-3921.pab2020.v55.26839

Keywords:

Sorghum bicolor, canonical variables, Kohonen’s self‑organized map

Abstract

The objective of this work was to evaluate the potential of computational intelligence and canonical variables for studies on the genetic diversity between biomass sorghum (Sorghum bicolor) genotypes. The experiments were carried out in the experimental field of Embrapa Milho e Sorgo, in the municipalities of Nova Porteirinha and Sete Lagoas, in the state of Minas Gerais, Brazil. The following traits were evaluated: days to flowering, plant height, fresh biomass yield, total dry biomass, and dry biomass yield. The study of genetic diversity was performed through the analysis of canonical variables. For the recognition of the organization pattern of genetic diversity, Kohonen’s self-organizing map was used. The use of canonical variables and a self-organizing map were efficient for the study of genetic diversity. The application of computational intelligence using a self-organized map is promising and efficient for studies on the genetic diversity between biomass sorghum genotypes.

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Published

2020-12-14

How to Cite

Silva, M. J. da, Silva Júnior, A. C. da, Cruz, C. D., Nascimento, M., Oliveira, M. da S., Schaffert, R. E., & Parrella, R. A. da C. (2020). Computational intelligence for studies on genetic diversity between genotypes of biomass sorghum. Pesquisa Agropecuaria Brasileira, 55(X), e01723. https://doi.org/10.1590/S1678-3921.pab2020.v55.26839

Issue

V.55, Jan./Dec., 2020 :Continuos publication

Section

GENETICS