Artificial neural networks for adaptability and stability evaluation in alfalfa genotypes

Detalhes bibliográficos
Autor(a) principal: Nascimento,Moysés
Data de Publicação: 2013
Outros Autores: Peternelli,Luiz Alexandre, Cruz,Cosme Damião, Nascimento,Ana Carolina Campana, Ferreira,Reinaldo de Paula, Bhering,Leonardo Lopes, Salgado,Caio Césio
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Crop Breeding and Applied Biotechnology
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1984-70332013000200008
Resumo: The purpose of this work was to evaluate a methodology of adaptability and phenotypic stability of alfalfa genotypes based on the training of an artificial neural network considering the methodology of Eberhart and Russell. Data from an experiment on dry matter production of 92 alfalfa genotypes (Medicago sativa L.) were used. The experimental design constituted of randomized blocks, with two repetitions. The genotypes were submitted to 20 cuttings, in the growing season of November 2004 to June 2006. Each cutting was considered an environment. The artificial neural network was able to satisfactorily classify the genotypes. In addition, the analysis presented high agreement rates, compared with the results obtained by the methodology of Eberhart and Russell.
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spelling Artificial neural networks for adaptability and stability evaluation in alfalfa genotypesBioinformaticsdata simulationEberhart and RussellThe purpose of this work was to evaluate a methodology of adaptability and phenotypic stability of alfalfa genotypes based on the training of an artificial neural network considering the methodology of Eberhart and Russell. Data from an experiment on dry matter production of 92 alfalfa genotypes (Medicago sativa L.) were used. The experimental design constituted of randomized blocks, with two repetitions. The genotypes were submitted to 20 cuttings, in the growing season of November 2004 to June 2006. Each cutting was considered an environment. The artificial neural network was able to satisfactorily classify the genotypes. In addition, the analysis presented high agreement rates, compared with the results obtained by the methodology of Eberhart and Russell.Crop Breeding and Applied Biotechnology2013-07-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1984-70332013000200008Crop Breeding and Applied Biotechnology v.13 n.2 2013reponame:Crop Breeding and Applied Biotechnologyinstname:Sociedade Brasileira de Melhoramento de Plantasinstacron:CBABinfo:eu-repo/semantics/openAccessNascimento,MoysésPeternelli,Luiz AlexandreCruz,Cosme DamiãoNascimento,Ana Carolina CampanaFerreira,Reinaldo de PaulaBhering,Leonardo LopesSalgado,Caio Césioeng2013-08-20T00:00:00Zoai:scielo:S1984-70332013000200008Revistahttps://cbab.sbmp.org.br/#ONGhttps://old.scielo.br/oai/scielo-oai.phpcbabjournal@gmail.com||cbab@ufv.br1984-70331518-7853opendoar:2013-08-20T00:00Crop Breeding and Applied Biotechnology - Sociedade Brasileira de Melhoramento de Plantasfalse
dc.title.none.fl_str_mv Artificial neural networks for adaptability and stability evaluation in alfalfa genotypes
title Artificial neural networks for adaptability and stability evaluation in alfalfa genotypes
spellingShingle Artificial neural networks for adaptability and stability evaluation in alfalfa genotypes
Nascimento,Moysés
Bioinformatics
data simulation
Eberhart and Russell
title_short Artificial neural networks for adaptability and stability evaluation in alfalfa genotypes
title_full Artificial neural networks for adaptability and stability evaluation in alfalfa genotypes
title_fullStr Artificial neural networks for adaptability and stability evaluation in alfalfa genotypes
title_full_unstemmed Artificial neural networks for adaptability and stability evaluation in alfalfa genotypes
title_sort Artificial neural networks for adaptability and stability evaluation in alfalfa genotypes
author Nascimento,Moysés
author_facet Nascimento,Moysés
Peternelli,Luiz Alexandre
Cruz,Cosme Damião
Nascimento,Ana Carolina Campana
Ferreira,Reinaldo de Paula
Bhering,Leonardo Lopes
Salgado,Caio Césio
author_role author
author2 Peternelli,Luiz Alexandre
Cruz,Cosme Damião
Nascimento,Ana Carolina Campana
Ferreira,Reinaldo de Paula
Bhering,Leonardo Lopes
Salgado,Caio Césio
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Nascimento,Moysés
Peternelli,Luiz Alexandre
Cruz,Cosme Damião
Nascimento,Ana Carolina Campana
Ferreira,Reinaldo de Paula
Bhering,Leonardo Lopes
Salgado,Caio Césio
dc.subject.por.fl_str_mv Bioinformatics
data simulation
Eberhart and Russell
topic Bioinformatics
data simulation
Eberhart and Russell
description The purpose of this work was to evaluate a methodology of adaptability and phenotypic stability of alfalfa genotypes based on the training of an artificial neural network considering the methodology of Eberhart and Russell. Data from an experiment on dry matter production of 92 alfalfa genotypes (Medicago sativa L.) were used. The experimental design constituted of randomized blocks, with two repetitions. The genotypes were submitted to 20 cuttings, in the growing season of November 2004 to June 2006. Each cutting was considered an environment. The artificial neural network was able to satisfactorily classify the genotypes. In addition, the analysis presented high agreement rates, compared with the results obtained by the methodology of Eberhart and Russell.
publishDate 2013
dc.date.none.fl_str_mv 2013-07-01
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=S1984-70332013000200008
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1984-70332013000200008
dc.language.iso.fl_str_mv eng
language eng
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 Crop Breeding and Applied Biotechnology
publisher.none.fl_str_mv Crop Breeding and Applied Biotechnology
dc.source.none.fl_str_mv Crop Breeding and Applied Biotechnology v.13 n.2 2013
reponame:Crop Breeding and Applied Biotechnology
instname:Sociedade Brasileira de Melhoramento de Plantas
instacron:CBAB
instname_str Sociedade Brasileira de Melhoramento de Plantas
instacron_str CBAB
institution CBAB
reponame_str Crop Breeding and Applied Biotechnology
collection Crop Breeding and Applied Biotechnology
repository.name.fl_str_mv Crop Breeding and Applied Biotechnology - Sociedade Brasileira de Melhoramento de Plantas
repository.mail.fl_str_mv cbabjournal@gmail.com||cbab@ufv.br
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