Best linear unbiased prediction for genetic evaluation in reciprocal recurrent selection with popcorn populations.
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , , , |
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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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 |
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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1794503439285223424 |