Estimation of repeatability and genotypic superiority of elephant grass half-sib families for energy purposes using mixed models.

Detalhes bibliográficos
Autor(a) principal: VIDAL, A. K. F.
Data de Publicação: 2023
Outros Autores: DAHER, R. F., AMBRÓSIO, M., SANTANA, J. G. S., FREITAS, R. S., GRAVINA, G. de A., RODRIGUES, E. V., STIDA, W. F., SOUZA, A. G. de, LEITE, C. L., FARIAS, J. E. C., RANGEL, L. H., PEREIRA, A. V.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1154202
http://doi.org/10.1590/1678-992X-2022-0103
Resumo: The mixed-model methodology is an alternative to select genotypes for traits highly influenced by the environment. In addition, this method allows FOR estimating the repeatability coefficient and predicting the number of assessments needed for a selection process to increase reliability. This study aimed to determine the minimum number of evaluations necessary for a reliable selection process and to estimate the variance components used for predicting genetic gains between and within half-sib families of elephant grass (Cenchrus purpureus (Schumach.) Morrone) using the mixed-model methodology. Half-sib families were generated using genotypes from the Active Germplasm Bank of Elephant Grass. The experiment was performed in a randomized block design with nine half-sib families, three replicates, and eight plants per plot. We evaluated 216 genotypes (individual plants) of elephant grass. The deviance analysis was carried out, genetic parameters were estimated, gains between and within families were predicted, and repeatability coefficients were obtained using Selegen software. There was genetic variability for selection within the families evaluated. The reliability values found above 60 % for plant height and number of tillers and above 80 % for dry matter yield suggest that only two evaluations are required to select superior genotypes with outstanding reliability. Sixteen genotypes were identified and selected for their productive potential, which can be used as parents in elephant grass breeding programs for bioenergy production.
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spelling Estimation of repeatability and genotypic superiority of elephant grass half-sib families for energy purposes using mixed models.Cenchrus purpureusREML/BLUPBioenergiaCapim ElefanteThe mixed-model methodology is an alternative to select genotypes for traits highly influenced by the environment. In addition, this method allows FOR estimating the repeatability coefficient and predicting the number of assessments needed for a selection process to increase reliability. This study aimed to determine the minimum number of evaluations necessary for a reliable selection process and to estimate the variance components used for predicting genetic gains between and within half-sib families of elephant grass (Cenchrus purpureus (Schumach.) Morrone) using the mixed-model methodology. Half-sib families were generated using genotypes from the Active Germplasm Bank of Elephant Grass. The experiment was performed in a randomized block design with nine half-sib families, three replicates, and eight plants per plot. We evaluated 216 genotypes (individual plants) of elephant grass. The deviance analysis was carried out, genetic parameters were estimated, gains between and within families were predicted, and repeatability coefficients were obtained using Selegen software. There was genetic variability for selection within the families evaluated. The reliability values found above 60 % for plant height and number of tillers and above 80 % for dry matter yield suggest that only two evaluations are required to select superior genotypes with outstanding reliability. Sixteen genotypes were identified and selected for their productive potential, which can be used as parents in elephant grass breeding programs for bioenergy production.ANA KESIA FARIA VIDAL, Universidade Estadual do Norte Fluminense Darcy Ribeiro; ROGÉRIO FIGUEIREDO DAHER, Universidade Estadual do Norte Fluminense Darcy Ribeiro; MOISES AMBRÓSIO, Universidade Estadual do Norte Fluminense Darcy Ribeiro; JOSEFA GRASIELA SILVA SANTANA, Universidade Estadual do Norte Fluminense Darcy Ribeiro; RAFAEL SOUZA FREITAS, Universidade Estadual do Norte Fluminense Darcy Ribeiro; GERALDO DE AMARAL GRAVINA, Universidade Estadual do Norte Fluminense Darcy Ribeiro; ERINA VITÓRIO RODRIGUES, Universidade de Brasília; WANESSA FRANCESCONI STIDA, Universidade Estadual do Norte Fluminense Darcy Ribeiro; ALEXANDRE GOMES DE SOUZA, Universidade Estadual do Norte Fluminense Darcy Ribeiro; CLEUDIANE LOPES LEITE, Universidade Estadual do Norte Fluminense Darcy Ribeiro; JOÃO ESDRAS CALAÇA FARIAS, Universidade Estadual do Norte Fluminense Darcy Ribeiro; LEANDRO HEITOR RANGEL, Universidade Estadual do Norte Fluminense Darcy Ribeiro; ANTONIO VANDER PEREIRA, CNPGL.VIDAL, A. K. F.DAHER, R. F.AMBRÓSIO, M.SANTANA, J. G. S.FREITAS, R. S.GRAVINA, G. de A.RODRIGUES, E. V.STIDA, W. F.SOUZA, A. G. deLEITE, C. L.FARIAS, J. E. C.RANGEL, L. H.PEREIRA, A. V.2023-06-05T04:09:57Z2023-06-05T04:09:57Z2023-06-032023info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleScientia Agricola, v. 80, e20220103, 2023.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1154202http://doi.org/10.1590/1678-992X-2022-0103enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2023-06-05T04:09:57Zoai:www.alice.cnptia.embrapa.br:doc/1154202Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542023-06-05T04:09:57falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542023-06-05T04:09:57Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Estimation of repeatability and genotypic superiority of elephant grass half-sib families for energy purposes using mixed models.
title Estimation of repeatability and genotypic superiority of elephant grass half-sib families for energy purposes using mixed models.
spellingShingle Estimation of repeatability and genotypic superiority of elephant grass half-sib families for energy purposes using mixed models.
VIDAL, A. K. F.
Cenchrus purpureus
REML/BLUP
Bioenergia
Capim Elefante
title_short Estimation of repeatability and genotypic superiority of elephant grass half-sib families for energy purposes using mixed models.
title_full Estimation of repeatability and genotypic superiority of elephant grass half-sib families for energy purposes using mixed models.
title_fullStr Estimation of repeatability and genotypic superiority of elephant grass half-sib families for energy purposes using mixed models.
title_full_unstemmed Estimation of repeatability and genotypic superiority of elephant grass half-sib families for energy purposes using mixed models.
title_sort Estimation of repeatability and genotypic superiority of elephant grass half-sib families for energy purposes using mixed models.
author VIDAL, A. K. F.
author_facet VIDAL, A. K. F.
DAHER, R. F.
AMBRÓSIO, M.
SANTANA, J. G. S.
FREITAS, R. S.
GRAVINA, G. de A.
RODRIGUES, E. V.
STIDA, W. F.
SOUZA, A. G. de
LEITE, C. L.
FARIAS, J. E. C.
RANGEL, L. H.
PEREIRA, A. V.
author_role author
author2 DAHER, R. F.
AMBRÓSIO, M.
SANTANA, J. G. S.
FREITAS, R. S.
GRAVINA, G. de A.
RODRIGUES, E. V.
STIDA, W. F.
SOUZA, A. G. de
LEITE, C. L.
FARIAS, J. E. C.
RANGEL, L. H.
PEREIRA, A. V.
author2_role author
author
author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv ANA KESIA FARIA VIDAL, Universidade Estadual do Norte Fluminense Darcy Ribeiro; ROGÉRIO FIGUEIREDO DAHER, Universidade Estadual do Norte Fluminense Darcy Ribeiro; MOISES AMBRÓSIO, Universidade Estadual do Norte Fluminense Darcy Ribeiro; JOSEFA GRASIELA SILVA SANTANA, Universidade Estadual do Norte Fluminense Darcy Ribeiro; RAFAEL SOUZA FREITAS, Universidade Estadual do Norte Fluminense Darcy Ribeiro; GERALDO DE AMARAL GRAVINA, Universidade Estadual do Norte Fluminense Darcy Ribeiro; ERINA VITÓRIO RODRIGUES, Universidade de Brasília; WANESSA FRANCESCONI STIDA, Universidade Estadual do Norte Fluminense Darcy Ribeiro; ALEXANDRE GOMES DE SOUZA, Universidade Estadual do Norte Fluminense Darcy Ribeiro; CLEUDIANE LOPES LEITE, Universidade Estadual do Norte Fluminense Darcy Ribeiro; JOÃO ESDRAS CALAÇA FARIAS, Universidade Estadual do Norte Fluminense Darcy Ribeiro; LEANDRO HEITOR RANGEL, Universidade Estadual do Norte Fluminense Darcy Ribeiro; ANTONIO VANDER PEREIRA, CNPGL.
dc.contributor.author.fl_str_mv VIDAL, A. K. F.
DAHER, R. F.
AMBRÓSIO, M.
SANTANA, J. G. S.
FREITAS, R. S.
GRAVINA, G. de A.
RODRIGUES, E. V.
STIDA, W. F.
SOUZA, A. G. de
LEITE, C. L.
FARIAS, J. E. C.
RANGEL, L. H.
PEREIRA, A. V.
dc.subject.por.fl_str_mv Cenchrus purpureus
REML/BLUP
Bioenergia
Capim Elefante
topic Cenchrus purpureus
REML/BLUP
Bioenergia
Capim Elefante
description The mixed-model methodology is an alternative to select genotypes for traits highly influenced by the environment. In addition, this method allows FOR estimating the repeatability coefficient and predicting the number of assessments needed for a selection process to increase reliability. This study aimed to determine the minimum number of evaluations necessary for a reliable selection process and to estimate the variance components used for predicting genetic gains between and within half-sib families of elephant grass (Cenchrus purpureus (Schumach.) Morrone) using the mixed-model methodology. Half-sib families were generated using genotypes from the Active Germplasm Bank of Elephant Grass. The experiment was performed in a randomized block design with nine half-sib families, three replicates, and eight plants per plot. We evaluated 216 genotypes (individual plants) of elephant grass. The deviance analysis was carried out, genetic parameters were estimated, gains between and within families were predicted, and repeatability coefficients were obtained using Selegen software. There was genetic variability for selection within the families evaluated. The reliability values found above 60 % for plant height and number of tillers and above 80 % for dry matter yield suggest that only two evaluations are required to select superior genotypes with outstanding reliability. Sixteen genotypes were identified and selected for their productive potential, which can be used as parents in elephant grass breeding programs for bioenergy production.
publishDate 2023
dc.date.none.fl_str_mv 2023-06-05T04:09:57Z
2023-06-05T04:09:57Z
2023-06-03
2023
dc.type.driver.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv Scientia Agricola, v. 80, e20220103, 2023.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1154202
http://doi.org/10.1590/1678-992X-2022-0103
identifier_str_mv Scientia Agricola, v. 80, e20220103, 2023.
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1154202
http://doi.org/10.1590/1678-992X-2022-0103
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
collection Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
repository.name.fl_str_mv Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv cg-riaa@embrapa.br
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