Multivariate approach in the selection of superior soybean progeny which carry the RR gene

Detalhes bibliográficos
Autor(a) principal: Dallastra,Anderson
Data de Publicação: 2014
Outros Autores: Unêda-Trevisoli,Sandra Helena, Ferraudo,Antonio Sergio, Di Mauro,Antonio Orlando
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista ciência agronômica (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902014000300021
Resumo: Efficiency in the use of genetic variability, whether existing or created, increases when properly explored and analysed. Incorporation of biotechnology into breeding programs has been the general practice. The challenge for the researcher is the constant development of new and improved cultivars. The aim of this experiment was to select progenies with superior characteristics, whether or not carriers of the RR gene, derived from bi-parental crosses in the soybean, with the help of multivariate techniques. The experiment was carried out in a family-type experimental design, including controls, during the agricultural year 2010/2011 and 2011/2012 in Jaboticabal in the Brazilian State of São Paulo. From the F3 generation, phenotypically superior plants were selected, which were evaluated for the following traits: number of days to flowering; number of days to maturity; height of first pod insertion; plant height at maturity; lodging; agronomic value; number of branches; number of pods per plant; 100-seed weight; number of seeds per plant; grain yield per plant. Given the results, it appears possible to select superior progeny by principal component analysis. Cluster analysis using the K-means method links progeny according to the most important characteristics in each group and identifies, by the Ward method and by means of a dendrogram, the structure of similarity and divergence between selected progeny. Both methods are effective in aiding progeny selection.
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spelling Multivariate approach in the selection of superior soybean progeny which carry the RR geneGlycine maxGenetic variabilityMultivariate analysisEfficiency in the use of genetic variability, whether existing or created, increases when properly explored and analysed. Incorporation of biotechnology into breeding programs has been the general practice. The challenge for the researcher is the constant development of new and improved cultivars. The aim of this experiment was to select progenies with superior characteristics, whether or not carriers of the RR gene, derived from bi-parental crosses in the soybean, with the help of multivariate techniques. The experiment was carried out in a family-type experimental design, including controls, during the agricultural year 2010/2011 and 2011/2012 in Jaboticabal in the Brazilian State of São Paulo. From the F3 generation, phenotypically superior plants were selected, which were evaluated for the following traits: number of days to flowering; number of days to maturity; height of first pod insertion; plant height at maturity; lodging; agronomic value; number of branches; number of pods per plant; 100-seed weight; number of seeds per plant; grain yield per plant. Given the results, it appears possible to select superior progeny by principal component analysis. Cluster analysis using the K-means method links progeny according to the most important characteristics in each group and identifies, by the Ward method and by means of a dendrogram, the structure of similarity and divergence between selected progeny. Both methods are effective in aiding progeny selection.Universidade Federal do Ceará2014-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902014000300021Revista Ciência Agronômica v.45 n.3 2014reponame:Revista ciência agronômica (Online)instname:Universidade Federal do Ceará (UFC)instacron:UFC10.1590/S1806-66902014000300021info:eu-repo/semantics/openAccessDallastra,AndersonUnêda-Trevisoli,Sandra HelenaFerraudo,Antonio SergioDi Mauro,Antonio Orlandoeng2014-05-26T00:00:00Zoai:scielo:S1806-66902014000300021Revistahttp://www.ccarevista.ufc.br/PUBhttps://old.scielo.br/oai/scielo-oai.php||alekdutra@ufc.br|| ccarev@ufc.br1806-66900045-6888opendoar:2014-05-26T00:00Revista ciência agronômica (Online) - Universidade Federal do Ceará (UFC)false
dc.title.none.fl_str_mv Multivariate approach in the selection of superior soybean progeny which carry the RR gene
title Multivariate approach in the selection of superior soybean progeny which carry the RR gene
spellingShingle Multivariate approach in the selection of superior soybean progeny which carry the RR gene
Dallastra,Anderson
Glycine max
Genetic variability
Multivariate analysis
title_short Multivariate approach in the selection of superior soybean progeny which carry the RR gene
title_full Multivariate approach in the selection of superior soybean progeny which carry the RR gene
title_fullStr Multivariate approach in the selection of superior soybean progeny which carry the RR gene
title_full_unstemmed Multivariate approach in the selection of superior soybean progeny which carry the RR gene
title_sort Multivariate approach in the selection of superior soybean progeny which carry the RR gene
author Dallastra,Anderson
author_facet Dallastra,Anderson
Unêda-Trevisoli,Sandra Helena
Ferraudo,Antonio Sergio
Di Mauro,Antonio Orlando
author_role author
author2 Unêda-Trevisoli,Sandra Helena
Ferraudo,Antonio Sergio
Di Mauro,Antonio Orlando
author2_role author
author
author
dc.contributor.author.fl_str_mv Dallastra,Anderson
Unêda-Trevisoli,Sandra Helena
Ferraudo,Antonio Sergio
Di Mauro,Antonio Orlando
dc.subject.por.fl_str_mv Glycine max
Genetic variability
Multivariate analysis
topic Glycine max
Genetic variability
Multivariate analysis
description Efficiency in the use of genetic variability, whether existing or created, increases when properly explored and analysed. Incorporation of biotechnology into breeding programs has been the general practice. The challenge for the researcher is the constant development of new and improved cultivars. The aim of this experiment was to select progenies with superior characteristics, whether or not carriers of the RR gene, derived from bi-parental crosses in the soybean, with the help of multivariate techniques. The experiment was carried out in a family-type experimental design, including controls, during the agricultural year 2010/2011 and 2011/2012 in Jaboticabal in the Brazilian State of São Paulo. From the F3 generation, phenotypically superior plants were selected, which were evaluated for the following traits: number of days to flowering; number of days to maturity; height of first pod insertion; plant height at maturity; lodging; agronomic value; number of branches; number of pods per plant; 100-seed weight; number of seeds per plant; grain yield per plant. Given the results, it appears possible to select superior progeny by principal component analysis. Cluster analysis using the K-means method links progeny according to the most important characteristics in each group and identifies, by the Ward method and by means of a dendrogram, the structure of similarity and divergence between selected progeny. Both methods are effective in aiding progeny selection.
publishDate 2014
dc.date.none.fl_str_mv 2014-09-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902014000300021
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902014000300021
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S1806-66902014000300021
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 do Ceará
publisher.none.fl_str_mv Universidade Federal do Ceará
dc.source.none.fl_str_mv Revista Ciência Agronômica v.45 n.3 2014
reponame:Revista ciência agronômica (Online)
instname:Universidade Federal do Ceará (UFC)
instacron:UFC
instname_str Universidade Federal do Ceará (UFC)
instacron_str UFC
institution UFC
reponame_str Revista ciência agronômica (Online)
collection Revista ciência agronômica (Online)
repository.name.fl_str_mv Revista ciência agronômica (Online) - Universidade Federal do Ceará (UFC)
repository.mail.fl_str_mv ||alekdutra@ufc.br|| ccarev@ufc.br
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