Regression models grouping for genotype adaptability and stability analysis
Autor(a) principal: | |
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Data de Publicação: | 2011 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Pesquisa Agropecuária Brasileira (Online) |
Texto Completo: | https://seer.sct.embrapa.br/index.php/pab/article/view/9351 |
Resumo: | The objective of this work was to provide evidences of difference among regression models, obtained by the Eberhart & Russell method, for genotype adaptability and stability analysis, and to propose a methodology for grouping similar models. The test to verify the identity of models was used in the evaluation data of 14 corn genotypes in eight environments. Once the hypothesis of equality of regression models was discarded, model grouping was performed through estimating the mean square of the reduction (MSQRed) between pairs of regression models. After obtaining these values, the smallest one was selected and its significance was verified by the F‑test. If this MSQRed is not significant, the model pair related to it comprises the initial group. The models identity verification method can be successfully used for grouping linear regression equations, obtained by the Eberhart & Russell method, in order to study genotype adaptability and stability. The similar models grouping allow the formation of genotype groups with the same statistical behavior. |
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Regression models grouping for genotype adaptability and stability analysisAgrupamento de modelos de regressão da análise de adaptabilidade e estabilidade de genótiposZea mays; Eberhart & Russell; genotype evaluation; identity of modelsZea mays; Eberhart & Russell; avaliação de genótipos; identidade de modelosThe objective of this work was to provide evidences of difference among regression models, obtained by the Eberhart & Russell method, for genotype adaptability and stability analysis, and to propose a methodology for grouping similar models. The test to verify the identity of models was used in the evaluation data of 14 corn genotypes in eight environments. Once the hypothesis of equality of regression models was discarded, model grouping was performed through estimating the mean square of the reduction (MSQRed) between pairs of regression models. After obtaining these values, the smallest one was selected and its significance was verified by the F‑test. If this MSQRed is not significant, the model pair related to it comprises the initial group. The models identity verification method can be successfully used for grouping linear regression equations, obtained by the Eberhart & Russell method, in order to study genotype adaptability and stability. The similar models grouping allow the formation of genotype groups with the same statistical behavior. O objetivo deste trabalho foi evidenciar diferenças entre modelos de regressão, obtidos pelo método de Eberhart & Russell, na análise de adaptabilidade e estabilidade de comportamento de genótipos, e propor uma metodologia de agrupamento dos modelos similares. O teste para verificar a identidade de modelos foi empregado em dados de avaliação de 14 genótipos de milho em oito ambientes. Uma vez rejeitada a hipótese de igualdade dos modelos de regressão, realizou-se o agrupamento desses modelos com base no cálculo do quadrado médio da redução (QMRed) entre pares dos modelos de regressão. Após a obtenção desses valores, foi selecionado o de menor magnitude e verificada sua significância pelo teste F. Na hipótese de esse QMRed não ser significativo, o par de modelos relacionado a ele forma o grupo inicial. O método para verificar a identidade de modelos pode ser usado com sucesso no agrupamento de equações de regressão linear obtidas pelo método de Eberhart & Russell com o objetivo de estudar a adaptabilidade e a estabilidade de genótipos. O método de agrupamento de modelos similares permite formar grupos de genótipos com o mesmo comportamento estatístico.Pesquisa Agropecuaria BrasileiraPesquisa Agropecuária BrasileiraCNPq e FUNADESPVasconcelos, Edmar Soares deCruz, Cosme DamiãoRegazzi, Adair JoséBhering, Leonardo LopesRosado, Tatiana BarbosaVasconcelos, Fernando Soares de2011-03-22info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://seer.sct.embrapa.br/index.php/pab/article/view/9351Pesquisa Agropecuaria Brasileira; v.45, n.12, dez. 2010; 1357-1362Pesquisa Agropecuária Brasileira; v.45, n.12, dez. 2010; 1357-13621678-39210100-104xreponame:Pesquisa Agropecuária Brasileira (Online)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPAporhttps://seer.sct.embrapa.br/index.php/pab/article/view/9351/6154https://seer.sct.embrapa.br/index.php/pab/article/downloadSuppFile/9351/4552info:eu-repo/semantics/openAccess2014-11-14T16:54:46Zoai:ojs.seer.sct.embrapa.br:article/9351Revistahttp://seer.sct.embrapa.br/index.php/pabPRIhttps://old.scielo.br/oai/scielo-oai.phppab@sct.embrapa.br || sct.pab@embrapa.br1678-39210100-204Xopendoar:2014-11-14T16:54:46Pesquisa Agropecuária Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Regression models grouping for genotype adaptability and stability analysis Agrupamento de modelos de regressão da análise de adaptabilidade e estabilidade de genótipos |
title |
Regression models grouping for genotype adaptability and stability analysis |
spellingShingle |
Regression models grouping for genotype adaptability and stability analysis Vasconcelos, Edmar Soares de Zea mays; Eberhart & Russell; genotype evaluation; identity of models Zea mays; Eberhart & Russell; avaliação de genótipos; identidade de modelos |
title_short |
Regression models grouping for genotype adaptability and stability analysis |
title_full |
Regression models grouping for genotype adaptability and stability analysis |
title_fullStr |
Regression models grouping for genotype adaptability and stability analysis |
title_full_unstemmed |
Regression models grouping for genotype adaptability and stability analysis |
title_sort |
Regression models grouping for genotype adaptability and stability analysis |
author |
Vasconcelos, Edmar Soares de |
author_facet |
Vasconcelos, Edmar Soares de Cruz, Cosme Damião Regazzi, Adair José Bhering, Leonardo Lopes Rosado, Tatiana Barbosa Vasconcelos, Fernando Soares de |
author_role |
author |
author2 |
Cruz, Cosme Damião Regazzi, Adair José Bhering, Leonardo Lopes Rosado, Tatiana Barbosa Vasconcelos, Fernando Soares de |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
CNPq e FUNADESP |
dc.contributor.author.fl_str_mv |
Vasconcelos, Edmar Soares de Cruz, Cosme Damião Regazzi, Adair José Bhering, Leonardo Lopes Rosado, Tatiana Barbosa Vasconcelos, Fernando Soares de |
dc.subject.por.fl_str_mv |
Zea mays; Eberhart & Russell; genotype evaluation; identity of models Zea mays; Eberhart & Russell; avaliação de genótipos; identidade de modelos |
topic |
Zea mays; Eberhart & Russell; genotype evaluation; identity of models Zea mays; Eberhart & Russell; avaliação de genótipos; identidade de modelos |
description |
The objective of this work was to provide evidences of difference among regression models, obtained by the Eberhart & Russell method, for genotype adaptability and stability analysis, and to propose a methodology for grouping similar models. The test to verify the identity of models was used in the evaluation data of 14 corn genotypes in eight environments. Once the hypothesis of equality of regression models was discarded, model grouping was performed through estimating the mean square of the reduction (MSQRed) between pairs of regression models. After obtaining these values, the smallest one was selected and its significance was verified by the F‑test. If this MSQRed is not significant, the model pair related to it comprises the initial group. The models identity verification method can be successfully used for grouping linear regression equations, obtained by the Eberhart & Russell method, in order to study genotype adaptability and stability. The similar models grouping allow the formation of genotype groups with the same statistical behavior. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011-03-22 |
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/9351 |
url |
https://seer.sct.embrapa.br/index.php/pab/article/view/9351 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://seer.sct.embrapa.br/index.php/pab/article/view/9351/6154 https://seer.sct.embrapa.br/index.php/pab/article/downloadSuppFile/9351/4552 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
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.45, n.12, dez. 2010; 1357-1362 Pesquisa Agropecuária Brasileira; v.45, n.12, dez. 2010; 1357-1362 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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1793416690861604864 |