HETEROTIC GROUP FORMATION IN PSIDIUM GUAJAVA L. BY ARTIFICIAL NEURAL NETWORK AND DISCRIMINANT ANALYSIS

Detalhes bibliográficos
Autor(a) principal: CAMPOS,BIANCA MACHADO
Data de Publicação: 2016
Outros Autores: VIANA,ALEXANDRE PIO, QUINTAL,SILVANA SILVA RED, BARBOSA,CIBELLE DEGEL, DAHER,ROGÉRIO FIGUEIREDO
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista brasileira de fruticultura (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-29452016000100151
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.
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spelling HETEROTIC GROUP FORMATION IN PSIDIUM GUAJAVA L. BY ARTIFICIAL NEURAL NETWORK AND DISCRIMINANT ANALYSISGuavagenetic variabilitymultivariate analysisheterotic groupABSTRACT 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.Sociedade Brasileira de Fruticultura2016-02-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-29452016000100151Revista Brasileira de Fruticultura v.38 n.1 2016reponame:Revista brasileira de fruticultura (Online)instname:Sociedade Brasileira de Fruticultura (SBF)instacron:SBFRU10.1590/0100-2945-258/14info:eu-repo/semantics/openAccessCAMPOS,BIANCA MACHADOVIANA,ALEXANDRE PIOQUINTAL,SILVANA SILVA REDBARBOSA,CIBELLE DEGELDAHER,ROGÉRIO FIGUEIREDOeng2016-05-03T00:00:00Zoai:scielo:S0100-29452016000100151Revistahttp://www.scielo.br/rbfhttps://old.scielo.br/oai/scielo-oai.phprbf@fcav.unesp.br||http://rbf.org.br/1806-99670100-2945opendoar:2016-05-03T00:00Revista brasileira de fruticultura (Online) - Sociedade Brasileira de Fruticultura (SBF)false
dc.title.none.fl_str_mv HETEROTIC GROUP FORMATION IN PSIDIUM GUAJAVA L. BY ARTIFICIAL NEURAL NETWORK AND DISCRIMINANT ANALYSIS
title HETEROTIC GROUP FORMATION IN PSIDIUM GUAJAVA L. BY ARTIFICIAL NEURAL NETWORK AND DISCRIMINANT ANALYSIS
spellingShingle HETEROTIC GROUP FORMATION IN PSIDIUM GUAJAVA L. BY ARTIFICIAL NEURAL NETWORK AND DISCRIMINANT ANALYSIS
CAMPOS,BIANCA MACHADO
Guava
genetic variability
multivariate analysis
heterotic group
title_short HETEROTIC GROUP FORMATION IN PSIDIUM GUAJAVA L. BY ARTIFICIAL NEURAL NETWORK AND DISCRIMINANT ANALYSIS
title_full HETEROTIC GROUP FORMATION IN PSIDIUM GUAJAVA L. BY ARTIFICIAL NEURAL NETWORK AND DISCRIMINANT ANALYSIS
title_fullStr HETEROTIC GROUP FORMATION IN PSIDIUM GUAJAVA L. BY ARTIFICIAL NEURAL NETWORK AND DISCRIMINANT ANALYSIS
title_full_unstemmed HETEROTIC GROUP FORMATION IN PSIDIUM GUAJAVA L. BY ARTIFICIAL NEURAL NETWORK AND DISCRIMINANT ANALYSIS
title_sort HETEROTIC GROUP FORMATION IN PSIDIUM GUAJAVA L. BY ARTIFICIAL NEURAL NETWORK AND DISCRIMINANT ANALYSIS
author CAMPOS,BIANCA MACHADO
author_facet CAMPOS,BIANCA MACHADO
VIANA,ALEXANDRE PIO
QUINTAL,SILVANA SILVA RED
BARBOSA,CIBELLE DEGEL
DAHER,ROGÉRIO FIGUEIREDO
author_role author
author2 VIANA,ALEXANDRE PIO
QUINTAL,SILVANA SILVA RED
BARBOSA,CIBELLE DEGEL
DAHER,ROGÉRIO FIGUEIREDO
author2_role author
author
author
author
dc.contributor.author.fl_str_mv CAMPOS,BIANCA MACHADO
VIANA,ALEXANDRE PIO
QUINTAL,SILVANA SILVA RED
BARBOSA,CIBELLE DEGEL
DAHER,ROGÉRIO FIGUEIREDO
dc.subject.por.fl_str_mv Guava
genetic variability
multivariate analysis
heterotic group
topic Guava
genetic variability
multivariate analysis
heterotic group
description 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.
publishDate 2016
dc.date.none.fl_str_mv 2016-02-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-29452016000100151
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-29452016000100151
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0100-2945-258/14
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Fruticultura
publisher.none.fl_str_mv Sociedade Brasileira de Fruticultura
dc.source.none.fl_str_mv Revista Brasileira de Fruticultura v.38 n.1 2016
reponame:Revista brasileira de fruticultura (Online)
instname:Sociedade Brasileira de Fruticultura (SBF)
instacron:SBFRU
instname_str Sociedade Brasileira de Fruticultura (SBF)
instacron_str SBFRU
institution SBFRU
reponame_str Revista brasileira de fruticultura (Online)
collection Revista brasileira de fruticultura (Online)
repository.name.fl_str_mv Revista brasileira de fruticultura (Online) - Sociedade Brasileira de Fruticultura (SBF)
repository.mail.fl_str_mv rbf@fcav.unesp.br||http://rbf.org.br/
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