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

• Autor(a) principal: Silva, Michele Jorge da
• Data de Publicação: 2020
• Outros Autores: Silva Júnior, Antônio Carlos da, Cruz, Cosme Damião, Nascimento, Moysés, Oliveira, Marciane da Silva, Schaffert, Robert Eugene, Parrella, Rafael Augusto da Costa
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Pesquisa Agropecuária Brasileira (Online)
• Texto Completo: https://seer.sct.embrapa.br/index.php/pab/article/view/26839
• topic: Sorghum bicolor; canonical variables; Kohonen’s self‑organized map; Sorghum bicolor; variáveis canônicas; mapa auto‑organizável de Kohonen

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.