Factor analysis and SREG GGE biplot for the genotype × environment interaction stratification in maize

Detalhes bibliográficos
Autor(a) principal: Fritsche-Neto,Roberto
Data de Publicação: 2010
Outros Autores: Miranda,Glauco Vieira, DeLima,Rodrigo Oliveira, Souza,Heraldo Namorato de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Ciência Rural
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782010000500007
Resumo: The objective of this study was to evaluate the use of SREG GGE biplot methodology and factor analysis to stratify the genotype×environment interaction in maize. Forty-nine early maize hybrids were evaluated in nine environments. The experimental design used was a 7×7 square lattice with two replicates. Each plot consisted of two 5m long rows spaced 0.90m apart. Grain yield data were used to perform the analysis. The results indicated the existence of two mega-environments in the State of Minas Gerais, Brazil, for early maize hybrids. The stratification of the environment by factor analysis was more selective to join the similarity the according with cultivar performance. However, this approach did not identify specific genotype x environment interactions, which is possible through SREG GGE biplot analysis.
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spelling Factor analysis and SREG GGE biplot for the genotype × environment interaction stratification in maizeZea mays L.adaptabilitystabilityThe objective of this study was to evaluate the use of SREG GGE biplot methodology and factor analysis to stratify the genotype×environment interaction in maize. Forty-nine early maize hybrids were evaluated in nine environments. The experimental design used was a 7×7 square lattice with two replicates. Each plot consisted of two 5m long rows spaced 0.90m apart. Grain yield data were used to perform the analysis. The results indicated the existence of two mega-environments in the State of Minas Gerais, Brazil, for early maize hybrids. The stratification of the environment by factor analysis was more selective to join the similarity the according with cultivar performance. However, this approach did not identify specific genotype x environment interactions, which is possible through SREG GGE biplot analysis.Universidade Federal de Santa Maria2010-05-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782010000500007Ciência Rural v.40 n.5 2010reponame:Ciência Ruralinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSM10.1590/S0103-84782010000500007info:eu-repo/semantics/openAccessFritsche-Neto,RobertoMiranda,Glauco VieiraDeLima,Rodrigo OliveiraSouza,Heraldo Namorato deeng2010-07-15T00:00:00ZRevista
dc.title.none.fl_str_mv Factor analysis and SREG GGE biplot for the genotype × environment interaction stratification in maize
title Factor analysis and SREG GGE biplot for the genotype × environment interaction stratification in maize
spellingShingle Factor analysis and SREG GGE biplot for the genotype × environment interaction stratification in maize
Fritsche-Neto,Roberto
Zea mays L.
adaptability
stability
title_short Factor analysis and SREG GGE biplot for the genotype × environment interaction stratification in maize
title_full Factor analysis and SREG GGE biplot for the genotype × environment interaction stratification in maize
title_fullStr Factor analysis and SREG GGE biplot for the genotype × environment interaction stratification in maize
title_full_unstemmed Factor analysis and SREG GGE biplot for the genotype × environment interaction stratification in maize
title_sort Factor analysis and SREG GGE biplot for the genotype × environment interaction stratification in maize
author Fritsche-Neto,Roberto
author_facet Fritsche-Neto,Roberto
Miranda,Glauco Vieira
DeLima,Rodrigo Oliveira
Souza,Heraldo Namorato de
author_role author
author2 Miranda,Glauco Vieira
DeLima,Rodrigo Oliveira
Souza,Heraldo Namorato de
author2_role author
author
author
dc.contributor.author.fl_str_mv Fritsche-Neto,Roberto
Miranda,Glauco Vieira
DeLima,Rodrigo Oliveira
Souza,Heraldo Namorato de
dc.subject.por.fl_str_mv Zea mays L.
adaptability
stability
topic Zea mays L.
adaptability
stability
description The objective of this study was to evaluate the use of SREG GGE biplot methodology and factor analysis to stratify the genotype×environment interaction in maize. Forty-nine early maize hybrids were evaluated in nine environments. The experimental design used was a 7×7 square lattice with two replicates. Each plot consisted of two 5m long rows spaced 0.90m apart. Grain yield data were used to perform the analysis. The results indicated the existence of two mega-environments in the State of Minas Gerais, Brazil, for early maize hybrids. The stratification of the environment by factor analysis was more selective to join the similarity the according with cultivar performance. However, this approach did not identify specific genotype x environment interactions, which is possible through SREG GGE biplot analysis.
publishDate 2010
dc.date.none.fl_str_mv 2010-05-01
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=S0103-84782010000500007
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782010000500007
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0103-84782010000500007
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 Universidade Federal de Santa Maria
publisher.none.fl_str_mv Universidade Federal de Santa Maria
dc.source.none.fl_str_mv Ciência Rural v.40 n.5 2010
reponame:Ciência Rural
instname:Universidade Federal de Santa Maria (UFSM)
instacron:UFSM
instname_str Universidade Federal de Santa Maria (UFSM)
instacron_str UFSM
institution UFSM
reponame_str Ciência Rural
collection Ciência Rural
repository.name.fl_str_mv
repository.mail.fl_str_mv
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