Use of the REML/BLUP methodology for the selection of sweet orange genotypes
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Pesquisa Agropecuária Brasileira (Online) |
Texto Completo: | https://seer.sct.embrapa.br/index.php/pab/article/view/26946 |
Resumo: | The objective of this work was to select superior sweet orange (Citrus sinensis) genotypes with higher yield potential based on data from eight harvests, using the residual or restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) methodology. The experiment was carried out from 2002 to 2008 and in 2010 in the municipality of Rio Branco, in the state of Acre, Brazil. Analyzes of deviance were performed to test the significance of the components of variance according to the random effects of the used model, and parameters were estimated from individual genotypic and phenotypic variances. A selection intensity of 20% was adopted regarding genotypic selection, i.e., only the best 11 of the 55 genotypes tested were selected. The estimates of the genetic parameters show the existence of genetic variability and the selection potential of the studied sweet orange genotypes. The genotypic correlation between harvests is of low magnitude, except for the variable average fruit mass, and, as a reflex, there is a change in the ordering of the genotypes. Genotypes 5, 48, 19, 14, and 47 stand out as being the most productive, and, therefore, are the most suitable for selection purposes. Genotypes 14 and 47 show superior performance for the character set evaluated. |
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Use of the REML/BLUP methodology for the selection of sweet orange genotypesUso da metodologia REML/BLUP para seleção de genótipos de laranjeira-doceCitrus sinensis; genetic gain; genetic variability; productivityCitrus sinensis; ganho genético; variabilidade genética; produtividadeThe objective of this work was to select superior sweet orange (Citrus sinensis) genotypes with higher yield potential based on data from eight harvests, using the residual or restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) methodology. The experiment was carried out from 2002 to 2008 and in 2010 in the municipality of Rio Branco, in the state of Acre, Brazil. Analyzes of deviance were performed to test the significance of the components of variance according to the random effects of the used model, and parameters were estimated from individual genotypic and phenotypic variances. A selection intensity of 20% was adopted regarding genotypic selection, i.e., only the best 11 of the 55 genotypes tested were selected. The estimates of the genetic parameters show the existence of genetic variability and the selection potential of the studied sweet orange genotypes. The genotypic correlation between harvests is of low magnitude, except for the variable average fruit mass, and, as a reflex, there is a change in the ordering of the genotypes. Genotypes 5, 48, 19, 14, and 47 stand out as being the most productive, and, therefore, are the most suitable for selection purposes. Genotypes 14 and 47 show superior performance for the character set evaluated.O objetivo deste trabalho foi selecionar genótipos superiores de laranjeira-doce (Citrus sinensis) com maior potencial produtivo com base em dados de oito safras, com uso da metodologia “residual or restricted maximum likelihood/best linear unbiased prediction” (REML/BLUP). O experimento foi realizado de 2002 a 2008 e em 2010, no município de Rio Branco, no estado do Acre, Brasil. Análises de deviance foram realizadas para testar a significância dos componentes da variância de acordo com os efeitos aleatórios do modelo utilizado, e os parâmetros foram estimados a partir das variâncias genotípicas e fenotípicas individuais. Foi adotada uma intensidade de seleção de 20% em relação à seleção genotípica, ou seja, apenas os melhores 11 dos 55 genótipos testados foram selecionados. As estimativas dos parâmetros genéticos mostram a existência de variabilidade genética e o potencial de seleção dos genótipos de laranjeira-doce estudados. A correlação genotípica entre as safras é de baixa magnitude, exceto para a variável massa média dos frutos, e, como reflexo, há uma mudança na ordenação dos genótipos. Os genótipos 5, 48, 19, 14 e 47 se destacam como os mais produtivos e, portanto, são os mais adequados para fins de seleção. Os genótipos 14 e 47 apresentam desempenho superior para o conjunto de caracteres avaliados.Pesquisa Agropecuaria BrasileiraPesquisa Agropecuária BrasileiraCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorEmbrapa AcreUniversidade Federal do AcreCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorEmbrapa AcreUniversidade Federal do AcreCapistrano, Márcia da CostaAndrade Neto, Romeu de CarvalhoSantos, Vanderley Borges dosLessa, Lauro SaraivaResende, Marcos Deon Vilela deMesquita, Antônio Gilson GomesGurgel, Fábio de Lima2021-09-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://seer.sct.embrapa.br/index.php/pab/article/view/26946Pesquisa Agropecuaria Brasileira; V.56, Jan./Dec., 2021: Publicação contínua em volume anual; e02032Pesquisa Agropecuária Brasileira; V.56, Jan./Dec., 2021: Publicação contínua em volume anual; e020321678-39210100-104xreponame:Pesquisa Agropecuária Brasileira (Online)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPAenghttps://seer.sct.embrapa.br/index.php/pab/article/view/26946/14905Direitos autorais 2021 Pesquisa Agropecuária Brasileirainfo:eu-repo/semantics/openAccess2022-05-18T18:27:35Zoai:ojs.seer.sct.embrapa.br:article/26946Revistahttp://seer.sct.embrapa.br/index.php/pabPRIhttps://old.scielo.br/oai/scielo-oai.phppab@sct.embrapa.br || sct.pab@embrapa.br1678-39210100-204Xopendoar:2022-05-18T18:27:35Pesquisa Agropecuária Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Use of the REML/BLUP methodology for the selection of sweet orange genotypes Uso da metodologia REML/BLUP para seleção de genótipos de laranjeira-doce |
title |
Use of the REML/BLUP methodology for the selection of sweet orange genotypes |
spellingShingle |
Use of the REML/BLUP methodology for the selection of sweet orange genotypes Capistrano, Márcia da Costa Citrus sinensis; genetic gain; genetic variability; productivity Citrus sinensis; ganho genético; variabilidade genética; produtividade |
title_short |
Use of the REML/BLUP methodology for the selection of sweet orange genotypes |
title_full |
Use of the REML/BLUP methodology for the selection of sweet orange genotypes |
title_fullStr |
Use of the REML/BLUP methodology for the selection of sweet orange genotypes |
title_full_unstemmed |
Use of the REML/BLUP methodology for the selection of sweet orange genotypes |
title_sort |
Use of the REML/BLUP methodology for the selection of sweet orange genotypes |
author |
Capistrano, Márcia da Costa |
author_facet |
Capistrano, Márcia da Costa Andrade Neto, Romeu de Carvalho Santos, Vanderley Borges dos Lessa, Lauro Saraiva Resende, Marcos Deon Vilela de Mesquita, Antônio Gilson Gomes Gurgel, Fábio de Lima |
author_role |
author |
author2 |
Andrade Neto, Romeu de Carvalho Santos, Vanderley Borges dos Lessa, Lauro Saraiva Resende, Marcos Deon Vilela de Mesquita, Antônio Gilson Gomes Gurgel, Fábio de Lima |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior Embrapa Acre Universidade Federal do Acre Coordenação de Aperfeiçoamento de Pessoal de Nível Superior Embrapa Acre Universidade Federal do Acre |
dc.contributor.author.fl_str_mv |
Capistrano, Márcia da Costa Andrade Neto, Romeu de Carvalho Santos, Vanderley Borges dos Lessa, Lauro Saraiva Resende, Marcos Deon Vilela de Mesquita, Antônio Gilson Gomes Gurgel, Fábio de Lima |
dc.subject.por.fl_str_mv |
Citrus sinensis; genetic gain; genetic variability; productivity Citrus sinensis; ganho genético; variabilidade genética; produtividade |
topic |
Citrus sinensis; genetic gain; genetic variability; productivity Citrus sinensis; ganho genético; variabilidade genética; produtividade |
description |
The objective of this work was to select superior sweet orange (Citrus sinensis) genotypes with higher yield potential based on data from eight harvests, using the residual or restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) methodology. The experiment was carried out from 2002 to 2008 and in 2010 in the municipality of Rio Branco, in the state of Acre, Brazil. Analyzes of deviance were performed to test the significance of the components of variance according to the random effects of the used model, and parameters were estimated from individual genotypic and phenotypic variances. A selection intensity of 20% was adopted regarding genotypic selection, i.e., only the best 11 of the 55 genotypes tested were selected. The estimates of the genetic parameters show the existence of genetic variability and the selection potential of the studied sweet orange genotypes. The genotypic correlation between harvests is of low magnitude, except for the variable average fruit mass, and, as a reflex, there is a change in the ordering of the genotypes. Genotypes 5, 48, 19, 14, and 47 stand out as being the most productive, and, therefore, are the most suitable for selection purposes. Genotypes 14 and 47 show superior performance for the character set evaluated. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-09-06 |
dc.type.none.fl_str_mv |
|
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://seer.sct.embrapa.br/index.php/pab/article/view/26946 |
url |
https://seer.sct.embrapa.br/index.php/pab/article/view/26946 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://seer.sct.embrapa.br/index.php/pab/article/view/26946/14905 |
dc.rights.driver.fl_str_mv |
Direitos autorais 2021 Pesquisa Agropecuária Brasileira info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Direitos autorais 2021 Pesquisa Agropecuária Brasileira |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Pesquisa Agropecuaria Brasileira Pesquisa Agropecuária Brasileira |
publisher.none.fl_str_mv |
Pesquisa Agropecuaria Brasileira Pesquisa Agropecuária Brasileira |
dc.source.none.fl_str_mv |
Pesquisa Agropecuaria Brasileira; V.56, Jan./Dec., 2021: Publicação contínua em volume anual; e02032 Pesquisa Agropecuária Brasileira; V.56, Jan./Dec., 2021: Publicação contínua em volume anual; e02032 1678-3921 0100-104x reponame:Pesquisa Agropecuária Brasileira (Online) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Pesquisa Agropecuária Brasileira (Online) |
collection |
Pesquisa Agropecuária Brasileira (Online) |
repository.name.fl_str_mv |
Pesquisa Agropecuária Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
pab@sct.embrapa.br || sct.pab@embrapa.br |
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1793416670289592320 |