Multiple-trait BLUP in longitudinal data analysis on Jatropha curcas breeding for bioenergy
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | LOCUS Repositório Institucional da UFV |
Texto Completo: | https://doi.org/10.1016/j.indcrop.2018.12.019 http://www.locus.ufv.br/handle/123456789/23858 |
Resumo: | Despite being a species with great potential for biodiesel production, little research has been done on the breeding of Jatropha curcas, mainly with respect to its yield across harvests. Thus, the present study was carried out to analyze longitudinal data via multiple-trait Best Linear Unbiased Prediction (BLUP) for the genetic improvement of Jatropha curcas. The experiment was set up as a randomized block design with two blocks and five plants per plot. The seed yield of 730 individuals of 73 half-sib families was evaluated over six years. Variance components and genetic parameters were estimated via Restricted Maximum Likelihood (REML). The Additive Index was used for ranking and selection purposes. Genetic correlations of low to moderate magnitude were observed between pairs of harvests. The Multiple-trait BLUP / Additive Index procedure allowed for the selection of superior families based on the predicted genetic values, considering all the harvests. Therefore, it can be efficiently applied in the breeding of Jatropha curcas. |
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Alves, Rodrigo SilvaTeodoro, Paulo EduardoPeixoto, Leonardo de AzevedoSilva, Lidiane AparecidaLaviola, Bruno GalveasResende, Marcos Deon Vilela deBhering, Leonardo LopesRocha, João Romero do Amaral Santos de Carvalho2019-03-11T18:05:46Z2019-03-11T18:05:46Z2019-040926-6690https://doi.org/10.1016/j.indcrop.2018.12.019http://www.locus.ufv.br/handle/123456789/23858Despite being a species with great potential for biodiesel production, little research has been done on the breeding of Jatropha curcas, mainly with respect to its yield across harvests. Thus, the present study was carried out to analyze longitudinal data via multiple-trait Best Linear Unbiased Prediction (BLUP) for the genetic improvement of Jatropha curcas. The experiment was set up as a randomized block design with two blocks and five plants per plot. The seed yield of 730 individuals of 73 half-sib families was evaluated over six years. Variance components and genetic parameters were estimated via Restricted Maximum Likelihood (REML). The Additive Index was used for ranking and selection purposes. Genetic correlations of low to moderate magnitude were observed between pairs of harvests. The Multiple-trait BLUP / Additive Index procedure allowed for the selection of superior families based on the predicted genetic values, considering all the harvests. Therefore, it can be efficiently applied in the breeding of Jatropha curcas.engIndustrial Crops and ProductsVolume 130, Pages 558-561, April 2019Elsevier B. V.info:eu-repo/semantics/openAccessMixed model methodologyRepeated measuresSelection indexGenetic selectionBiofuelMultiple-trait BLUP in longitudinal data analysis on Jatropha curcas breeding for bioenergyinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfreponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFVORIGINALartigo.pdfartigo.pdfTexto completoapplication/pdf722962https://locus.ufv.br//bitstream/123456789/23858/1/artigo.pdfc3a8eb9b9ca4af1f6562e1d9673186bcMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://locus.ufv.br//bitstream/123456789/23858/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52123456789/238582019-03-11 15:08:13.226oai:locus.ufv.br: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Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452019-03-11T18:08:13LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)false |
dc.title.en.fl_str_mv |
Multiple-trait BLUP in longitudinal data analysis on Jatropha curcas breeding for bioenergy |
title |
Multiple-trait BLUP in longitudinal data analysis on Jatropha curcas breeding for bioenergy |
spellingShingle |
Multiple-trait BLUP in longitudinal data analysis on Jatropha curcas breeding for bioenergy Alves, Rodrigo Silva Mixed model methodology Repeated measures Selection index Genetic selection Biofuel |
title_short |
Multiple-trait BLUP in longitudinal data analysis on Jatropha curcas breeding for bioenergy |
title_full |
Multiple-trait BLUP in longitudinal data analysis on Jatropha curcas breeding for bioenergy |
title_fullStr |
Multiple-trait BLUP in longitudinal data analysis on Jatropha curcas breeding for bioenergy |
title_full_unstemmed |
Multiple-trait BLUP in longitudinal data analysis on Jatropha curcas breeding for bioenergy |
title_sort |
Multiple-trait BLUP in longitudinal data analysis on Jatropha curcas breeding for bioenergy |
author |
Alves, Rodrigo Silva |
author_facet |
Alves, Rodrigo Silva Teodoro, Paulo Eduardo Peixoto, Leonardo de Azevedo Silva, Lidiane Aparecida Laviola, Bruno Galveas Resende, Marcos Deon Vilela de Bhering, Leonardo Lopes Rocha, João Romero do Amaral Santos de Carvalho |
author_role |
author |
author2 |
Teodoro, Paulo Eduardo Peixoto, Leonardo de Azevedo Silva, Lidiane Aparecida Laviola, Bruno Galveas Resende, Marcos Deon Vilela de Bhering, Leonardo Lopes Rocha, João Romero do Amaral Santos de Carvalho |
author2_role |
author author author author author author author |
dc.contributor.author.fl_str_mv |
Alves, Rodrigo Silva Teodoro, Paulo Eduardo Peixoto, Leonardo de Azevedo Silva, Lidiane Aparecida Laviola, Bruno Galveas Resende, Marcos Deon Vilela de Bhering, Leonardo Lopes Rocha, João Romero do Amaral Santos de Carvalho |
dc.subject.pt-BR.fl_str_mv |
Mixed model methodology Repeated measures Selection index Genetic selection Biofuel |
topic |
Mixed model methodology Repeated measures Selection index Genetic selection Biofuel |
description |
Despite being a species with great potential for biodiesel production, little research has been done on the breeding of Jatropha curcas, mainly with respect to its yield across harvests. Thus, the present study was carried out to analyze longitudinal data via multiple-trait Best Linear Unbiased Prediction (BLUP) for the genetic improvement of Jatropha curcas. The experiment was set up as a randomized block design with two blocks and five plants per plot. The seed yield of 730 individuals of 73 half-sib families was evaluated over six years. Variance components and genetic parameters were estimated via Restricted Maximum Likelihood (REML). The Additive Index was used for ranking and selection purposes. Genetic correlations of low to moderate magnitude were observed between pairs of harvests. The Multiple-trait BLUP / Additive Index procedure allowed for the selection of superior families based on the predicted genetic values, considering all the harvests. Therefore, it can be efficiently applied in the breeding of Jatropha curcas. |
publishDate |
2019 |
dc.date.accessioned.fl_str_mv |
2019-03-11T18:05:46Z |
dc.date.available.fl_str_mv |
2019-03-11T18:05:46Z |
dc.date.issued.fl_str_mv |
2019-04 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://doi.org/10.1016/j.indcrop.2018.12.019 http://www.locus.ufv.br/handle/123456789/23858 |
dc.identifier.issn.none.fl_str_mv |
0926-6690 |
identifier_str_mv |
0926-6690 |
url |
https://doi.org/10.1016/j.indcrop.2018.12.019 http://www.locus.ufv.br/handle/123456789/23858 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartofseries.pt-BR.fl_str_mv |
Volume 130, Pages 558-561, April 2019 |
dc.rights.driver.fl_str_mv |
Elsevier B. V. info:eu-repo/semantics/openAccess |
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Elsevier B. V. |
eu_rights_str_mv |
openAccess |
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Industrial Crops and Products |
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Industrial Crops and Products |
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