Best linear unbiased prediction for genetic evaluation in reciprocal recurrent selection with popcorn populations.

Detalhes bibliográficos
Autor(a) principal: VIANA, J. M. S.
Data de Publicação: 2014
Outros Autores: MUNDIM, G. B., DELIMA, R. O, SILVA, F. F. E., RESENDE, M. D. V. de
Tipo de documento: Artigo
Idioma: por
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/1011131
Resumo: The objective of the present study was to present the theory and application of best linear unbiased prediction (BLUP) in reciprocal recurrent selection (RRS). Seven progeny tests from two RRS programmes with popcorn (Zea mays L. ssp. mays [syn. Zea mays L. ssp. everta (Sturtev.) Zhuk.]) populations were conducted and analysed for expansion volume and grain yield. The interpopulation half- and full-sib family models were fitted using ASReml software. Half-sib selection is equivalent to selection for the general combining ability (GCA) of the common parents. With inbred full-sib progeny and BLUP analysis, it is possible to predict the general and specific combining ability effects. The standard error of prediction of the progeny effect was lower than the standard deviation of the best linear unbiased estimation (BLUE) estimate. For half- and full-sib RRS, the BLUE and BLUP provided highly correlated estimates of progeny genotypic values. The coincidence between selected parents ranged from 64 to 95%. With inbred full-sib progeny, the correlations between the BLUE of progeny genotypic values and the BLUP of GCA effects were lower. Consequently, the coincidence between selected parents was lower, ranging from 0 to 57%. The percentage of common selected inbred progeny based on the BLUE and BLUP of the progeny genotypic value ranged from 57 to 100%.
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spelling Best linear unbiased prediction for genetic evaluation in reciprocal recurrent selection with popcorn populations.PipocaZea mayaEspécie agrícolaMelhoramento genéticoMilhoSeleção RecorrenteThe objective of the present study was to present the theory and application of best linear unbiased prediction (BLUP) in reciprocal recurrent selection (RRS). Seven progeny tests from two RRS programmes with popcorn (Zea mays L. ssp. mays [syn. Zea mays L. ssp. everta (Sturtev.) Zhuk.]) populations were conducted and analysed for expansion volume and grain yield. The interpopulation half- and full-sib family models were fitted using ASReml software. Half-sib selection is equivalent to selection for the general combining ability (GCA) of the common parents. With inbred full-sib progeny and BLUP analysis, it is possible to predict the general and specific combining ability effects. The standard error of prediction of the progeny effect was lower than the standard deviation of the best linear unbiased estimation (BLUE) estimate. For half- and full-sib RRS, the BLUE and BLUP provided highly correlated estimates of progeny genotypic values. The coincidence between selected parents ranged from 64 to 95%. With inbred full-sib progeny, the correlations between the BLUE of progeny genotypic values and the BLUP of GCA effects were lower. Consequently, the coincidence between selected parents was lower, ranging from 0 to 57%. The percentage of common selected inbred progeny based on the BLUE and BLUP of the progeny genotypic value ranged from 57 to 100%.J M S VIANA, UFV; G. B. MUNDIM, UFV; R. O. DELIMA, UFV; F. F. E. SILVA, UFV; MARCOS DEON VILELA DE RESENDE, CNPF.VIANA, J. M. S.MUNDIM, G. B.DELIMA, R. OSILVA, F. F. E.RESENDE, M. D. V. de2015-03-11T11:11:11Z2015-03-11T11:11:11Z2015-03-1120142017-07-24T11:11:11Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleJournal of Agricultural Science, v. 152, p. 428-438, 2014.http://www.alice.cnptia.embrapa.br/alice/handle/doc/101113110.1017/S0021859613000270porinfo: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:EMBRAPA2017-08-15T22:26:18Zoai:www.alice.cnptia.embrapa.br:doc/1011131Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542017-08-15T22:26:18falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542017-08-15T22:26:18Repositório 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 Best linear unbiased prediction for genetic evaluation in reciprocal recurrent selection with popcorn populations.
title Best linear unbiased prediction for genetic evaluation in reciprocal recurrent selection with popcorn populations.
spellingShingle Best linear unbiased prediction for genetic evaluation in reciprocal recurrent selection with popcorn populations.
VIANA, J. M. S.
Pipoca
Zea maya
Espécie agrícola
Melhoramento genético
Milho
Seleção Recorrente
title_short Best linear unbiased prediction for genetic evaluation in reciprocal recurrent selection with popcorn populations.
title_full Best linear unbiased prediction for genetic evaluation in reciprocal recurrent selection with popcorn populations.
title_fullStr Best linear unbiased prediction for genetic evaluation in reciprocal recurrent selection with popcorn populations.
title_full_unstemmed Best linear unbiased prediction for genetic evaluation in reciprocal recurrent selection with popcorn populations.
title_sort Best linear unbiased prediction for genetic evaluation in reciprocal recurrent selection with popcorn populations.
author VIANA, J. M. S.
author_facet VIANA, J. M. S.
MUNDIM, G. B.
DELIMA, R. O
SILVA, F. F. E.
RESENDE, M. D. V. de
author_role author
author2 MUNDIM, G. B.
DELIMA, R. O
SILVA, F. F. E.
RESENDE, M. D. V. de
author2_role author
author
author
author
dc.contributor.none.fl_str_mv J M S VIANA, UFV; G. B. MUNDIM, UFV; R. O. DELIMA, UFV; F. F. E. SILVA, UFV; MARCOS DEON VILELA DE RESENDE, CNPF.
dc.contributor.author.fl_str_mv VIANA, J. M. S.
MUNDIM, G. B.
DELIMA, R. O
SILVA, F. F. E.
RESENDE, M. D. V. de
dc.subject.por.fl_str_mv Pipoca
Zea maya
Espécie agrícola
Melhoramento genético
Milho
Seleção Recorrente
topic Pipoca
Zea maya
Espécie agrícola
Melhoramento genético
Milho
Seleção Recorrente
description The objective of the present study was to present the theory and application of best linear unbiased prediction (BLUP) in reciprocal recurrent selection (RRS). Seven progeny tests from two RRS programmes with popcorn (Zea mays L. ssp. mays [syn. Zea mays L. ssp. everta (Sturtev.) Zhuk.]) populations were conducted and analysed for expansion volume and grain yield. The interpopulation half- and full-sib family models were fitted using ASReml software. Half-sib selection is equivalent to selection for the general combining ability (GCA) of the common parents. With inbred full-sib progeny and BLUP analysis, it is possible to predict the general and specific combining ability effects. The standard error of prediction of the progeny effect was lower than the standard deviation of the best linear unbiased estimation (BLUE) estimate. For half- and full-sib RRS, the BLUE and BLUP provided highly correlated estimates of progeny genotypic values. The coincidence between selected parents ranged from 64 to 95%. With inbred full-sib progeny, the correlations between the BLUE of progeny genotypic values and the BLUP of GCA effects were lower. Consequently, the coincidence between selected parents was lower, ranging from 0 to 57%. The percentage of common selected inbred progeny based on the BLUE and BLUP of the progeny genotypic value ranged from 57 to 100%.
publishDate 2014
dc.date.none.fl_str_mv 2014
2015-03-11T11:11:11Z
2015-03-11T11:11:11Z
2015-03-11
2017-07-24T11:11:11Z
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 Journal of Agricultural Science, v. 152, p. 428-438, 2014.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1011131
10.1017/S0021859613000270
identifier_str_mv Journal of Agricultural Science, v. 152, p. 428-438, 2014.
10.1017/S0021859613000270
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1011131
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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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)
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reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
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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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