Genotypic superiority of Psidium Guajava S1 families using mixed modeling for truncated and simultaneous selection
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Scientia Agrícola (Online) |
Texto Completo: | https://www.revistas.usp.br/sa/article/view/183310 |
Resumo: | The purpose of this study was to conduct selection, genetic parameter estimation, and prediction of genetic values for 18 S1 families of guava trees using mixed model methodology and simultaneous selection of traits by means of the additive selection index, multiplicative selection index, and mean rank adapted from Mulamba. All families analyzed were obtained by means of self-fertilization of superior genotypes (full siblings) from the genetic breeding program of guava trees at the Universidade Estadual do Norte Fluminense. An experimental randomized block design with 18 S1 families, three replicates, and ten plants per plot was used. A total of 540 genotypes (individual plants) of guava tree were evaluated. Genetic parameter estimation and selection of the best genotypes based on the genetic value were performed using the statistical procedure, from the Selegen-REML/BLUP program. The analyses of the additive selection index, multiplicative selection index, and the sum of rank adapted from Mulamba were also performed under the Selegen program. During the evaluation by the individual BLUPs, families 1, 12, 4, 6, and 8 contributed to most of the genotypes selected for the traits under evaluation, suggesting their significant potential to generate high quality and high yield genotypes. In the selection indexes via mixed models, the multiplicative index showed higher values for genetic gains (74 %), followed by the mean rank index adapted from Mulamba (19 %), and the additive index (2 %). |
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Scientia Agrícola (Online) |
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Genotypic superiority of Psidium Guajava S1 families using mixed modeling for truncated and simultaneous selectioninbreedingguava treemixed modelsbreedingThe purpose of this study was to conduct selection, genetic parameter estimation, and prediction of genetic values for 18 S1 families of guava trees using mixed model methodology and simultaneous selection of traits by means of the additive selection index, multiplicative selection index, and mean rank adapted from Mulamba. All families analyzed were obtained by means of self-fertilization of superior genotypes (full siblings) from the genetic breeding program of guava trees at the Universidade Estadual do Norte Fluminense. An experimental randomized block design with 18 S1 families, three replicates, and ten plants per plot was used. A total of 540 genotypes (individual plants) of guava tree were evaluated. Genetic parameter estimation and selection of the best genotypes based on the genetic value were performed using the statistical procedure, from the Selegen-REML/BLUP program. The analyses of the additive selection index, multiplicative selection index, and the sum of rank adapted from Mulamba were also performed under the Selegen program. During the evaluation by the individual BLUPs, families 1, 12, 4, 6, and 8 contributed to most of the genotypes selected for the traits under evaluation, suggesting their significant potential to generate high quality and high yield genotypes. In the selection indexes via mixed models, the multiplicative index showed higher values for genetic gains (74 %), followed by the mean rank index adapted from Mulamba (19 %), and the additive index (2 %).Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz2021-01-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/sa/article/view/18331010.1590/1678-992X-2019-0179Scientia Agricola; v. 78 n. 2 (2021); e20190179Scientia Agricola; Vol. 78 Núm. 2 (2021); e20190179Scientia Agricola; Vol. 78 No. 2 (2021); e201901791678-992X0103-9016reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/sa/article/view/183310/169963Copyright (c) 2021 Scientia Agricolahttp://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessAmbrósio, Moisés Viana, Alexandre Pio Ribeiro, Rodrigo Moreira Preisigke, Sandra Costa Cavalcante , Natan Ramos Silva, Flavia Alves da Torres, Géssica Xavier Sousa, Carlos Misael Bezerra de 2021-03-18T18:32:17Zoai:revistas.usp.br:article/183310Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2021-03-18T18:32:17Scientia Agrícola (Online) - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
Genotypic superiority of Psidium Guajava S1 families using mixed modeling for truncated and simultaneous selection |
title |
Genotypic superiority of Psidium Guajava S1 families using mixed modeling for truncated and simultaneous selection |
spellingShingle |
Genotypic superiority of Psidium Guajava S1 families using mixed modeling for truncated and simultaneous selection Ambrósio, Moisés inbreeding guava tree mixed models breeding |
title_short |
Genotypic superiority of Psidium Guajava S1 families using mixed modeling for truncated and simultaneous selection |
title_full |
Genotypic superiority of Psidium Guajava S1 families using mixed modeling for truncated and simultaneous selection |
title_fullStr |
Genotypic superiority of Psidium Guajava S1 families using mixed modeling for truncated and simultaneous selection |
title_full_unstemmed |
Genotypic superiority of Psidium Guajava S1 families using mixed modeling for truncated and simultaneous selection |
title_sort |
Genotypic superiority of Psidium Guajava S1 families using mixed modeling for truncated and simultaneous selection |
author |
Ambrósio, Moisés |
author_facet |
Ambrósio, Moisés Viana, Alexandre Pio Ribeiro, Rodrigo Moreira Preisigke, Sandra Costa Cavalcante , Natan Ramos Silva, Flavia Alves da Torres, Géssica Xavier Sousa, Carlos Misael Bezerra de |
author_role |
author |
author2 |
Viana, Alexandre Pio Ribeiro, Rodrigo Moreira Preisigke, Sandra Costa Cavalcante , Natan Ramos Silva, Flavia Alves da Torres, Géssica Xavier Sousa, Carlos Misael Bezerra de |
author2_role |
author author author author author author author |
dc.contributor.author.fl_str_mv |
Ambrósio, Moisés Viana, Alexandre Pio Ribeiro, Rodrigo Moreira Preisigke, Sandra Costa Cavalcante , Natan Ramos Silva, Flavia Alves da Torres, Géssica Xavier Sousa, Carlos Misael Bezerra de |
dc.subject.por.fl_str_mv |
inbreeding guava tree mixed models breeding |
topic |
inbreeding guava tree mixed models breeding |
description |
The purpose of this study was to conduct selection, genetic parameter estimation, and prediction of genetic values for 18 S1 families of guava trees using mixed model methodology and simultaneous selection of traits by means of the additive selection index, multiplicative selection index, and mean rank adapted from Mulamba. All families analyzed were obtained by means of self-fertilization of superior genotypes (full siblings) from the genetic breeding program of guava trees at the Universidade Estadual do Norte Fluminense. An experimental randomized block design with 18 S1 families, three replicates, and ten plants per plot was used. A total of 540 genotypes (individual plants) of guava tree were evaluated. Genetic parameter estimation and selection of the best genotypes based on the genetic value were performed using the statistical procedure, from the Selegen-REML/BLUP program. The analyses of the additive selection index, multiplicative selection index, and the sum of rank adapted from Mulamba were also performed under the Selegen program. During the evaluation by the individual BLUPs, families 1, 12, 4, 6, and 8 contributed to most of the genotypes selected for the traits under evaluation, suggesting their significant potential to generate high quality and high yield genotypes. In the selection indexes via mixed models, the multiplicative index showed higher values for genetic gains (74 %), followed by the mean rank index adapted from Mulamba (19 %), and the additive index (2 %). |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-01-06 |
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://www.revistas.usp.br/sa/article/view/183310 10.1590/1678-992X-2019-0179 |
url |
https://www.revistas.usp.br/sa/article/view/183310 |
identifier_str_mv |
10.1590/1678-992X-2019-0179 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://www.revistas.usp.br/sa/article/view/183310/169963 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2021 Scientia Agricola http://creativecommons.org/licenses/by-nc/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2021 Scientia Agricola http://creativecommons.org/licenses/by-nc/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz |
publisher.none.fl_str_mv |
Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz |
dc.source.none.fl_str_mv |
Scientia Agricola; v. 78 n. 2 (2021); e20190179 Scientia Agricola; Vol. 78 Núm. 2 (2021); e20190179 Scientia Agricola; Vol. 78 No. 2 (2021); e20190179 1678-992X 0103-9016 reponame:Scientia Agrícola (Online) instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Scientia Agrícola (Online) |
collection |
Scientia Agrícola (Online) |
repository.name.fl_str_mv |
Scientia Agrícola (Online) - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
scientia@usp.br||alleoni@usp.br |
_version_ |
1800222794518102016 |