Data/hora: 11/06/2024 10:21:29

Provedor de dados: | Revista Brasileira de Fruticultura
País: | Brazil
Título: | HETEROTIC GROUP FORMATION IN PSIDIUM GUAJAVA L. BY ARTIFICIAL NEURAL NETWORK AND DISCRIMINANT ANALYSIS
Autores: | CAMPOS,BIANCA MACHADO; VIANA,ALEXANDRE PIO; QUINTAL,SILVANA SILVA RED; BARBOSA,CIBELLE DEGEL; DAHER,ROGÉRIO FIGUEIREDO.
Data: | 2016-02-01
Ano: | 2016
Palavras-chave: | Guava; Genetic variability; Multivariate analysis; Heterotic group.
Resumo: | ABSTRACT  The present study aimed at evaluating the heterotic group formation in guava based on quantitative descriptors and using artificial neural network (ANN). For such, we evaluated eight quantitative descriptors. Large genetic variability was found for the eight quantitative traits in the 138 genotypes of guava. The artificial neural network technique determined that the optimal number of groups was three. The grouping consistency was determined by linear discriminant analysis, which obtained classification percentage of the groups, with a value of 86 %. It was concluded that the artificial neural network method is effective to detect genetic divergence and heterotic group formation.
Tipo: | Info:eu-repo/semantics/article
Idioma: | Inglês
Identificador: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-29452016000100151
Editor: | Sociedade Brasileira de Fruticultura
Relação: | 10.1590/0100-2945-258/14
Formato: | text/html
Fonte: | Revista Brasileira de Fruticultura  v.38 n.1 2016
Fonte: | info:eu-repo/semantics/openAccess