Genotype selection based on multiple traits in cotton crops: The application of genotype by yield*trait biplot

Detalhes bibliográficos
Autor(a) principal: Peixoto, Marco Antônio
Data de Publicação: 2022
Outros Autores: Evangelista, Jeniffer Santana Pinto Coelho, Coelho, Igor Ferreira, Carvalho, Luiz Paulo, Farias, Francisco José Correa, Teodoro, Paulo Eduardo, Bhering, Leonardo Lopes
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Acta Scientiarum. Agronomy (Online)
Texto Completo: http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/54136
Resumo: In cotton crops, the cotton seed yield significantly contributes with the success of any cultivar. However, other traits are considered when an ideotype is pointed out in the selection, such as the fiber quality traits. The aim of this study was to applied genotype by yield*trait (GYT) biplot to a multi-environment trial data of cotton genotypes and selected the best genotypes. For this end, thirteen genotypes from nineteen trials were assessed. Seven traits were evaluated [cotton seed yield (SY), fiber percentage (FP), fiber length (FL), fiber uniformity (FU), short fiber index (SFI), fiber strength (FS), and elongation (EL)] and residual error variances structures [identity variance (IDV) and diagonal (Diag)] were tested by bayesian information criterion. After, the REML/BLUP approach was applied to predict the genetic values of each trait and the selective accuracy were measured from the prediction. Then, the GYT-biplot were applied to the data. For SP and SFI traits, the model with Diag residual variance was indicated, whereas for SY FL, FU, FS, and EL traits the model with IDV residual variance demonstrated the best fit to the data. Values of accuracy were higher than 0.9 for all traits analyzed. In the GYT-biplot acute angles were find for all traits relations, which means high correlation between the yield*traits combination. Besides that, the correlation still can be seen in the GYT-biplot, as shown by the magnitudes of the angles between the pairs Yield*FU-Yield*FS and Yield*FS-Yield*EL. Also, the GYT-biplot indicates the genotype G4 with the best performance for Yield*FS, Yield*SFI, Yield*FU, Yield*FL, and Yield*FP combined. The genotypes G4, G1, G13, G8, and G9 represent those genotypes with yield advantage over the other cultivars. Then, the genotype G4 combines all desirable characteristics and demonstrate have large potential in the cotton breeding. The GYT approach were valuable and were highly recommended in cotton breeding programs for selection purpose in a multivariate scenario.
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spelling Genotype selection based on multiple traits in cotton crops: The application of genotype by yield*trait biplot Genotype selection based on multiple traits in cotton crops: The application of genotype by yield*trait biplot biplot analysis; genotype by trait (GT) analysis; multi-environmental trial; residual error variance.biplot analysis; genotype by trait (GT) analysis; multi-environmental trial; residual error variance.In cotton crops, the cotton seed yield significantly contributes with the success of any cultivar. However, other traits are considered when an ideotype is pointed out in the selection, such as the fiber quality traits. The aim of this study was to applied genotype by yield*trait (GYT) biplot to a multi-environment trial data of cotton genotypes and selected the best genotypes. For this end, thirteen genotypes from nineteen trials were assessed. Seven traits were evaluated [cotton seed yield (SY), fiber percentage (FP), fiber length (FL), fiber uniformity (FU), short fiber index (SFI), fiber strength (FS), and elongation (EL)] and residual error variances structures [identity variance (IDV) and diagonal (Diag)] were tested by bayesian information criterion. After, the REML/BLUP approach was applied to predict the genetic values of each trait and the selective accuracy were measured from the prediction. Then, the GYT-biplot were applied to the data. For SP and SFI traits, the model with Diag residual variance was indicated, whereas for SY FL, FU, FS, and EL traits the model with IDV residual variance demonstrated the best fit to the data. Values of accuracy were higher than 0.9 for all traits analyzed. In the GYT-biplot acute angles were find for all traits relations, which means high correlation between the yield*traits combination. Besides that, the correlation still can be seen in the GYT-biplot, as shown by the magnitudes of the angles between the pairs Yield*FU-Yield*FS and Yield*FS-Yield*EL. Also, the GYT-biplot indicates the genotype G4 with the best performance for Yield*FS, Yield*SFI, Yield*FU, Yield*FL, and Yield*FP combined. The genotypes G4, G1, G13, G8, and G9 represent those genotypes with yield advantage over the other cultivars. Then, the genotype G4 combines all desirable characteristics and demonstrate have large potential in the cotton breeding. The GYT approach were valuable and were highly recommended in cotton breeding programs for selection purpose in a multivariate scenario.In cotton crops, the cotton seed yield significantly contributes with the success of any cultivar. However, other traits are considered when an ideotype is pointed out in the selection, such as the fiber quality traits. The aim of this study was to applied genotype by yield*trait (GYT) biplot to a multi-environment trial data of cotton genotypes and selected the best genotypes. For this end, thirteen genotypes from nineteen trials were assessed. Seven traits were evaluated [cotton seed yield (SY), fiber percentage (FP), fiber length (FL), fiber uniformity (FU), short fiber index (SFI), fiber strength (FS), and elongation (EL)] and residual error variances structures [identity variance (IDV) and diagonal (Diag)] were tested by bayesian information criterion. After, the REML/BLUP approach was applied to predict the genetic values of each trait and the selective accuracy were measured from the prediction. Then, the GYT-biplot were applied to the data. For SP and SFI traits, the model with Diag residual variance was indicated, whereas for SY FL, FU, FS, and EL traits the model with IDV residual variance demonstrated the best fit to the data. Values of accuracy were higher than 0.9 for all traits analyzed. In the GYT-biplot acute angles were find for all traits relations, which means high correlation between the yield*traits combination. Besides that, the correlation still can be seen in the GYT-biplot, as shown by the magnitudes of the angles between the pairs Yield*FU-Yield*FS and Yield*FS-Yield*EL. Also, the GYT-biplot indicates the genotype G4 with the best performance for Yield*FS, Yield*SFI, Yield*FU, Yield*FL, and Yield*FP combined. The genotypes G4, G1, G13, G8, and G9 represent those genotypes with yield advantage over the other cultivars. Then, the genotype G4 combines all desirable characteristics and demonstrate have large potential in the cotton breeding. The GYT approach were valuable and were highly recommended in cotton breeding programs for selection purpose in a multivariate scenario.Universidade Estadual de Maringá2022-03-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/5413610.4025/actasciagron.v44i1.54136Acta Scientiarum. Agronomy; Vol 44 (2022): Publicação contínua; e54136Acta Scientiarum. Agronomy; v. 44 (2022): Publicação contínua; e541361807-86211679-9275reponame:Acta Scientiarum. Agronomy (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMenghttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/54136/751375153834Copyright (c) 2022 Acta Scientiarum. Agronomyhttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessPeixoto, Marco Antônio Evangelista, Jeniffer Santana Pinto Coelho Coelho, Igor Ferreira Carvalho, Luiz Paulo Farias, Francisco José Correa Teodoro, Paulo Eduardo Bhering, Leonardo Lopes2022-04-01T17:14:11Zoai:periodicos.uem.br/ojs:article/54136Revistahttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgronPUBhttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/oaiactaagron@uem.br||actaagron@uem.br|| edamasio@uem.br1807-86211679-9275opendoar:2022-04-01T17:14:11Acta Scientiarum. Agronomy (Online) - Universidade Estadual de Maringá (UEM)false
dc.title.none.fl_str_mv Genotype selection based on multiple traits in cotton crops: The application of genotype by yield*trait biplot
Genotype selection based on multiple traits in cotton crops: The application of genotype by yield*trait biplot
title Genotype selection based on multiple traits in cotton crops: The application of genotype by yield*trait biplot
spellingShingle Genotype selection based on multiple traits in cotton crops: The application of genotype by yield*trait biplot
Peixoto, Marco Antônio
biplot analysis; genotype by trait (GT) analysis; multi-environmental trial; residual error variance.
biplot analysis; genotype by trait (GT) analysis; multi-environmental trial; residual error variance.
title_short Genotype selection based on multiple traits in cotton crops: The application of genotype by yield*trait biplot
title_full Genotype selection based on multiple traits in cotton crops: The application of genotype by yield*trait biplot
title_fullStr Genotype selection based on multiple traits in cotton crops: The application of genotype by yield*trait biplot
title_full_unstemmed Genotype selection based on multiple traits in cotton crops: The application of genotype by yield*trait biplot
title_sort Genotype selection based on multiple traits in cotton crops: The application of genotype by yield*trait biplot
author Peixoto, Marco Antônio
author_facet Peixoto, Marco Antônio
Evangelista, Jeniffer Santana Pinto Coelho
Coelho, Igor Ferreira
Carvalho, Luiz Paulo
Farias, Francisco José Correa
Teodoro, Paulo Eduardo
Bhering, Leonardo Lopes
author_role author
author2 Evangelista, Jeniffer Santana Pinto Coelho
Coelho, Igor Ferreira
Carvalho, Luiz Paulo
Farias, Francisco José Correa
Teodoro, Paulo Eduardo
Bhering, Leonardo Lopes
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Peixoto, Marco Antônio
Evangelista, Jeniffer Santana Pinto Coelho
Coelho, Igor Ferreira
Carvalho, Luiz Paulo
Farias, Francisco José Correa
Teodoro, Paulo Eduardo
Bhering, Leonardo Lopes
dc.subject.por.fl_str_mv biplot analysis; genotype by trait (GT) analysis; multi-environmental trial; residual error variance.
biplot analysis; genotype by trait (GT) analysis; multi-environmental trial; residual error variance.
topic biplot analysis; genotype by trait (GT) analysis; multi-environmental trial; residual error variance.
biplot analysis; genotype by trait (GT) analysis; multi-environmental trial; residual error variance.
description In cotton crops, the cotton seed yield significantly contributes with the success of any cultivar. However, other traits are considered when an ideotype is pointed out in the selection, such as the fiber quality traits. The aim of this study was to applied genotype by yield*trait (GYT) biplot to a multi-environment trial data of cotton genotypes and selected the best genotypes. For this end, thirteen genotypes from nineteen trials were assessed. Seven traits were evaluated [cotton seed yield (SY), fiber percentage (FP), fiber length (FL), fiber uniformity (FU), short fiber index (SFI), fiber strength (FS), and elongation (EL)] and residual error variances structures [identity variance (IDV) and diagonal (Diag)] were tested by bayesian information criterion. After, the REML/BLUP approach was applied to predict the genetic values of each trait and the selective accuracy were measured from the prediction. Then, the GYT-biplot were applied to the data. For SP and SFI traits, the model with Diag residual variance was indicated, whereas for SY FL, FU, FS, and EL traits the model with IDV residual variance demonstrated the best fit to the data. Values of accuracy were higher than 0.9 for all traits analyzed. In the GYT-biplot acute angles were find for all traits relations, which means high correlation between the yield*traits combination. Besides that, the correlation still can be seen in the GYT-biplot, as shown by the magnitudes of the angles between the pairs Yield*FU-Yield*FS and Yield*FS-Yield*EL. Also, the GYT-biplot indicates the genotype G4 with the best performance for Yield*FS, Yield*SFI, Yield*FU, Yield*FL, and Yield*FP combined. The genotypes G4, G1, G13, G8, and G9 represent those genotypes with yield advantage over the other cultivars. Then, the genotype G4 combines all desirable characteristics and demonstrate have large potential in the cotton breeding. The GYT approach were valuable and were highly recommended in cotton breeding programs for selection purpose in a multivariate scenario.
publishDate 2022
dc.date.none.fl_str_mv 2022-03-09
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 http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/54136
10.4025/actasciagron.v44i1.54136
url http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/54136
identifier_str_mv 10.4025/actasciagron.v44i1.54136
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/54136/751375153834
dc.rights.driver.fl_str_mv Copyright (c) 2022 Acta Scientiarum. Agronomy
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2022 Acta Scientiarum. Agronomy
https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Estadual de Maringá
publisher.none.fl_str_mv Universidade Estadual de Maringá
dc.source.none.fl_str_mv Acta Scientiarum. Agronomy; Vol 44 (2022): Publicação contínua; e54136
Acta Scientiarum. Agronomy; v. 44 (2022): Publicação contínua; e54136
1807-8621
1679-9275
reponame:Acta Scientiarum. Agronomy (Online)
instname:Universidade Estadual de Maringá (UEM)
instacron:UEM
instname_str Universidade Estadual de Maringá (UEM)
instacron_str UEM
institution UEM
reponame_str Acta Scientiarum. Agronomy (Online)
collection Acta Scientiarum. Agronomy (Online)
repository.name.fl_str_mv Acta Scientiarum. Agronomy (Online) - Universidade Estadual de Maringá (UEM)
repository.mail.fl_str_mv actaagron@uem.br||actaagron@uem.br|| edamasio@uem.br
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