Prediction of genetic gains by selection indices using mixed models in elephant grass for energy purposes.
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , , , , , , |
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/1082611 |
Resumo: | Genetically improved cultivars of elephant grass need to be adapted to different ecosystems with a faster growth speed and lower seasonality of biomass production over the year. This study aimed to use selection indices using mixed models (REML/BLUP) for selecting families and progenies within full-sib families of elephant grass (Pennisetum purpureum) for biomass production. One hundred and twenty full-sib progenies were assessed from 2014 to 2015 in a randomized block design with three replications. During this period, the traits dry matter production, the number of tillers, plant height, stem diameter, and neutral detergent fiber were assessed. Families 3 and 1were the best classified, being the most indicated for selection effect. Progenies 40, 45, 46, and 49 got the first positions in the three indices assessed in the first cut. The gain for individual 40 was 161.76% using Mulamba and Mock index. The use of selection indices using mixed models is advantageous in elephant grass since they provide high gains with the selection, which are distributed among all the assessed traits in the most appropriate situation to breeding programs. |
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Prediction of genetic gains by selection indices using mixed models in elephant grass for energy purposes.Matriz de energiaModelo mistoCapim elefanteEnergiaÍndice de SeleçãoGenetically improved cultivars of elephant grass need to be adapted to different ecosystems with a faster growth speed and lower seasonality of biomass production over the year. This study aimed to use selection indices using mixed models (REML/BLUP) for selecting families and progenies within full-sib families of elephant grass (Pennisetum purpureum) for biomass production. One hundred and twenty full-sib progenies were assessed from 2014 to 2015 in a randomized block design with three replications. During this period, the traits dry matter production, the number of tillers, plant height, stem diameter, and neutral detergent fiber were assessed. Families 3 and 1were the best classified, being the most indicated for selection effect. Progenies 40, 45, 46, and 49 got the first positions in the three indices assessed in the first cut. The gain for individual 40 was 161.76% using Mulamba and Mock index. The use of selection indices using mixed models is advantageous in elephant grass since they provide high gains with the selection, which are distributed among all the assessed traits in the most appropriate situation to breeding programs.Universidade Estadual do Norte Fluminense Darcy Ribeiro; Universidade Estadual do Norte Fluminense Darcy Ribeiro; Universidade Estadual do Norte Fluminense Darcy Ribeiro; Universidade Estadual do Norte Fluminense Darcy Ribeiro; Universidade Estadual do Norte Fluminense Darcy Ribeiro; Universidade Federal Rural do Rio de Janeiro; Universidade Estadual do Norte Fluminense Darcy Ribeiro; Universidade Estadual do Norte Fluminense Darcy Ribeiro; FLAVIO DESSAUNE TARDIN, CNPMS; Universidade Estadual do Norte Fluminense Darcy Ribeiro.SILVA, V. B.DAHER, R. F.ARAÚJO, M. S. B.SOUZA, Y. P.CASSARO, S.MENEZES, B. R. S.GRAVINA, L. M.NOVO, A. A. C.TARDIN, F. D.AMARAL JÚNIOR, A. T.2017-12-14T23:23:32Z2017-12-14T23:23:32Z2017-12-1420172017-12-14T23:23:32Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleGenetics and Molecular Research, Ribeirão Preto, v. 16, n. 3, p. 1-8, 2017.http://www.alice.cnptia.embrapa.br/alice/handle/doc/108261110.4238/gmr16039781enginfo: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:EMBRAPA2017-12-14T23:23:39Zoai:www.alice.cnptia.embrapa.br:doc/1082611Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542017-12-14T23:23:39falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542017-12-14T23:23:39Repositório 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 |
Prediction of genetic gains by selection indices using mixed models in elephant grass for energy purposes. |
title |
Prediction of genetic gains by selection indices using mixed models in elephant grass for energy purposes. |
spellingShingle |
Prediction of genetic gains by selection indices using mixed models in elephant grass for energy purposes. SILVA, V. B. Matriz de energia Modelo misto Capim elefante Energia Índice de Seleção |
title_short |
Prediction of genetic gains by selection indices using mixed models in elephant grass for energy purposes. |
title_full |
Prediction of genetic gains by selection indices using mixed models in elephant grass for energy purposes. |
title_fullStr |
Prediction of genetic gains by selection indices using mixed models in elephant grass for energy purposes. |
title_full_unstemmed |
Prediction of genetic gains by selection indices using mixed models in elephant grass for energy purposes. |
title_sort |
Prediction of genetic gains by selection indices using mixed models in elephant grass for energy purposes. |
author |
SILVA, V. B. |
author_facet |
SILVA, V. B. DAHER, R. F. ARAÚJO, M. S. B. SOUZA, Y. P. CASSARO, S. MENEZES, B. R. S. GRAVINA, L. M. NOVO, A. A. C. TARDIN, F. D. AMARAL JÚNIOR, A. T. |
author_role |
author |
author2 |
DAHER, R. F. ARAÚJO, M. S. B. SOUZA, Y. P. CASSARO, S. MENEZES, B. R. S. GRAVINA, L. M. NOVO, A. A. C. TARDIN, F. D. AMARAL JÚNIOR, A. T. |
author2_role |
author author author author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual do Norte Fluminense Darcy Ribeiro; Universidade Estadual do Norte Fluminense Darcy Ribeiro; Universidade Estadual do Norte Fluminense Darcy Ribeiro; Universidade Estadual do Norte Fluminense Darcy Ribeiro; Universidade Estadual do Norte Fluminense Darcy Ribeiro; Universidade Federal Rural do Rio de Janeiro; Universidade Estadual do Norte Fluminense Darcy Ribeiro; Universidade Estadual do Norte Fluminense Darcy Ribeiro; FLAVIO DESSAUNE TARDIN, CNPMS; Universidade Estadual do Norte Fluminense Darcy Ribeiro. |
dc.contributor.author.fl_str_mv |
SILVA, V. B. DAHER, R. F. ARAÚJO, M. S. B. SOUZA, Y. P. CASSARO, S. MENEZES, B. R. S. GRAVINA, L. M. NOVO, A. A. C. TARDIN, F. D. AMARAL JÚNIOR, A. T. |
dc.subject.por.fl_str_mv |
Matriz de energia Modelo misto Capim elefante Energia Índice de Seleção |
topic |
Matriz de energia Modelo misto Capim elefante Energia Índice de Seleção |
description |
Genetically improved cultivars of elephant grass need to be adapted to different ecosystems with a faster growth speed and lower seasonality of biomass production over the year. This study aimed to use selection indices using mixed models (REML/BLUP) for selecting families and progenies within full-sib families of elephant grass (Pennisetum purpureum) for biomass production. One hundred and twenty full-sib progenies were assessed from 2014 to 2015 in a randomized block design with three replications. During this period, the traits dry matter production, the number of tillers, plant height, stem diameter, and neutral detergent fiber were assessed. Families 3 and 1were the best classified, being the most indicated for selection effect. Progenies 40, 45, 46, and 49 got the first positions in the three indices assessed in the first cut. The gain for individual 40 was 161.76% using Mulamba and Mock index. The use of selection indices using mixed models is advantageous in elephant grass since they provide high gains with the selection, which are distributed among all the assessed traits in the most appropriate situation to breeding programs. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-12-14T23:23:32Z 2017-12-14T23:23:32Z 2017-12-14 2017 2017-12-14T23:23:32Z |
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 |
Genetics and Molecular Research, Ribeirão Preto, v. 16, n. 3, p. 1-8, 2017. http://www.alice.cnptia.embrapa.br/alice/handle/doc/1082611 10.4238/gmr16039781 |
identifier_str_mv |
Genetics and Molecular Research, Ribeirão Preto, v. 16, n. 3, p. 1-8, 2017. 10.4238/gmr16039781 |
url |
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1082611 |
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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1794503446569680896 |