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

Detalhes bibliográficos
Autor(a) principal: Dallastra, Anderson [UNESP]
Data de Publicação: 2014
Outros Autores: Unêda-trevisoli, Sandra Helena [UNESP], Ferraudo, Antonio Sergio [UNESP], Di Mauro, Antonio Orlando [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1590/S1806-66902014000300021
http://hdl.handle.net/11449/110061
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 geneAbordagem multivariada na seleção de progênies de soja superiores e portadoras do gene RRGlycine maxVariabilidade genéticaAnálise multivariadaGlycine 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.A eficiência do aproveitamento da variabilidade genética, existente ou criada, aumenta quando esta é devidamente explorada e analisada. A incorporação de eventos biotecnológicos aos programas de melhoramento tem sido uma prática usual. O pesquisador tem como desafio, o desenvolvimento constante de novas e melhores cultivares. O objetivo deste experimento foi selecionar progênies com caracteres superiores e portadoras ou não do gene RR, oriundas de cruzamentos bi-parentais em soja, com o auxílio de técnicas multivariadas. O experimento foi conduzido em delineamento experimental do tipo famílias com testemunhas intercaladas no ano agrícola 2010/2011 e 2011/2012 em Jaboticabal-SP, Brasil. Na geração F3, foram selecionadas plantas fenotipicamente superiores, sendo estas avaliadas para os caracteres: número de dias para o florescimento, número de dias para a maturidade, altura de inserção da primeira vagem, altura de planta na maturidade, acamamento, valor agronômico, número de ramos, número de vagens por planta, peso de 100 sementes, número de sementes por planta e produção de grãos por planta. Diante dos resultados, verifica-se a possibilidade de selecionar progênies superiores através da análise de componentes principais. A análise de agrupamentos, através do método de K-means, une as progênies de acordo com os caracteres de maior importância em cada grupo e, através do método de Ward, identificou por meio do dendrograma a estrutura de similaridade e divergência entre as progênies selecionadas. Os dois métodos são eficientes no auxilio da seleção de progênies.UNESP Faculdade de Ciências Agrárias e Veterinárias Departamento de Produção VegetalUNESP Faculdade de Ciências Agrárias e Veterinárias Departamento de Ciências ExatasUNESP Faculdade de Ciências Agrárias e Veterinárias Departamento de Produção VegetalUNESP Faculdade de Ciências Agrárias e Veterinárias Departamento de Ciências ExatasUniversidade Federal do CearáUniversidade Estadual Paulista (Unesp)Dallastra, Anderson [UNESP]Unêda-trevisoli, Sandra Helena [UNESP]Ferraudo, Antonio Sergio [UNESP]Di Mauro, Antonio Orlando [UNESP]2014-10-01T13:08:47Z2014-10-01T13:08:47Z2014-09-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article588-597application/pdfhttp://dx.doi.org/10.1590/S1806-66902014000300021Revista Ciência Agronômica. Universidade Federal do Ceará, v. 45, n. 3, p. 588-597, 2014.1806-6690http://hdl.handle.net/11449/11006110.1590/S1806-66902014000300021S1806-66902014000300021WOS:000336967200021S1806-66902014000300021.pdf7159757610060958127565251882209550248675334980260000-0003-3060-924XSciELOreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengRevista Ciência Agronômica0.6050,498info:eu-repo/semantics/openAccess2024-06-07T13:56:53Zoai:repositorio.unesp.br:11449/110061Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:55:32.896886Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Multivariate approach in the selection of superior soybean progeny which carry the RR gene
Abordagem multivariada na seleção de progênies de soja superiores e portadoras do gene RR
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 [UNESP]
Glycine max
Variabilidade genética
Análise multivariada
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 [UNESP]
author_facet Dallastra, Anderson [UNESP]
Unêda-trevisoli, Sandra Helena [UNESP]
Ferraudo, Antonio Sergio [UNESP]
Di Mauro, Antonio Orlando [UNESP]
author_role author
author2 Unêda-trevisoli, Sandra Helena [UNESP]
Ferraudo, Antonio Sergio [UNESP]
Di Mauro, Antonio Orlando [UNESP]
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Dallastra, Anderson [UNESP]
Unêda-trevisoli, Sandra Helena [UNESP]
Ferraudo, Antonio Sergio [UNESP]
Di Mauro, Antonio Orlando [UNESP]
dc.subject.por.fl_str_mv Glycine max
Variabilidade genética
Análise multivariada
Glycine max
Genetic variability
Multivariate analysis
topic Glycine max
Variabilidade genética
Análise multivariada
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 2014-10-01T13:08:47Z
2014-10-01T13:08:47Z
2014-09-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1590/S1806-66902014000300021
Revista Ciência Agronômica. Universidade Federal do Ceará, v. 45, n. 3, p. 588-597, 2014.
1806-6690
http://hdl.handle.net/11449/110061
10.1590/S1806-66902014000300021
S1806-66902014000300021
WOS:000336967200021
S1806-66902014000300021.pdf
7159757610060958
1275652518822095
5024867533498026
0000-0003-3060-924X
url http://dx.doi.org/10.1590/S1806-66902014000300021
http://hdl.handle.net/11449/110061
identifier_str_mv Revista Ciência Agronômica. Universidade Federal do Ceará, v. 45, n. 3, p. 588-597, 2014.
1806-6690
10.1590/S1806-66902014000300021
S1806-66902014000300021
WOS:000336967200021
S1806-66902014000300021.pdf
7159757610060958
1275652518822095
5024867533498026
0000-0003-3060-924X
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Revista Ciência Agronômica
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dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.format.none.fl_str_mv 588-597
application/pdf
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 SciELO
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
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institution UNESP
reponame_str Repositório Institucional da UNESP
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repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
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