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| 12. |  | SHIOTSUKI, L.; CARDOSO, F. F.; SILVA, J. A. II V.; ALBUQUERQUE, L. G. Genetic analysis of growth traits considering the avarage numerator relationship matrix and a hierarchical Bayes model for Nellore cattle. In: ADSA CSAS ASAS JOINT ANNUAL MEETING, 2009, Montreal. Electronic abstracts... Champaign: ADSA: ASAS, 2009. p. 15-16. M40. Publicado em: Jornal of Animal Science, Champaign, v. 87, p. 15-16, 2009. Electronic Supplement 2.| Biblioteca(s): Embrapa Pecuária Sul. |
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| 13. | | ATAIDES, K. da S.; SHIOTSUKI, L.; GARCIA, B. F.; SILVA, D. A.; VARGAS, G.; CARVALHEIRO, R. Impacto do efeito de ambiente comum em características morfométricas de tambaqui (Colossoma macropomum) avaliadas aos 6 e 12 meses de idade. In: SIMPÓSIO BRASILEIRO DE MELHORAMENTO ANIMAL, 14., 2021, Santa Catarina. Passado, presente e futuro: anais. Santa Catarina: Sociedade Brasileira de Melhoramento Animal, 2021.| Biblioteca(s): Embrapa Pesca e Aquicultura. |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Pecuária Sul. Para informações adicionais entre em contato com cppsul.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Caprinos e Ovinos; Embrapa Pecuária Sul. |
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Data corrente: |
12/11/2013 |
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Data da última atualização: |
12/11/2013 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
SHIOTSUKI, L.; CARDOSO, F. F.; SILVA, J. A.; ALBUQUERQUE, L. G. |
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Afiliação: |
LUCIANA SHIOTSUKI, CNPC; FERNANDO FLORES CARDOSO, CPPSUL; Department of Animal Science, São Paulo State University (UNESP) - Botucatu, SP, Brazil; Department of Animal Science, São Paulo State University (UNESP), Jaboticabal, SP - Brazil. |
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Título: |
Comparison of a genetic group and unknown paternity models for growth traits in Nellore cattle. |
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Ano de publicação: |
2013 |
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Fonte/Imprenta: |
Journal of Animal Science, v. 91, n. 11, p. 5135-5143, Nov., 2013. |
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DOI: |
10.2527/jas.2011-4989 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract: The aim of the present study was to compare a model assuming unknown paternity and a model using genetic grouping to indicate the most adequate statistical procedure for the estimation of breeding values for animals with uncertain paternity. After data consistency, 62,212 Nellore animals, offspring of 581 bulls and 27,743 cows, were used in the analyses. The pedigree file contained 75,088 animals, including 22,810 (30.18%) offspring of multiple sires and 12,876 animals belonging to the base population with unknown parents. Three different approaches were adopted to deal with uncertain paternity of multiple-sire (MS) offspring. In the model of unknown paternity, the MS groups were ignored, and the sires of MS offspring were considered to be unknown and to belong to a single base population. In the genetic group approach, 2 definitions were used. In the first definition (GGa), ?phantom parents? for animals with uncertain paternity were attributed, defining the genetic group as the MS group. In the other approach, GGb, phantom parents for animals with uncertain paternity were also attributed; however, MS offspring were clustered in genetic groups according to their year of birth, every 3 yr, on the basis of the average of male generation interval. Univariate analyses were performed under the Bayesian approach via Markov chain Monte Carlo methods. Models were compared by deviance information criteria and the conditional predictive ordinate. According to the choice criteria results, the genetic group model defined by the generation interval of males was more appropriate for predicting the genetic merit of animals with uncertain paternity. Therefore, the use of this model is recommended for the prediction of genetic merit and classification of offspring of multiple sires. MenosAbstract: The aim of the present study was to compare a model assuming unknown paternity and a model using genetic grouping to indicate the most adequate statistical procedure for the estimation of breeding values for animals with uncertain paternity. After data consistency, 62,212 Nellore animals, offspring of 581 bulls and 27,743 cows, were used in the analyses. The pedigree file contained 75,088 animals, including 22,810 (30.18%) offspring of multiple sires and 12,876 animals belonging to the base population with unknown parents. Three different approaches were adopted to deal with uncertain paternity of multiple-sire (MS) offspring. In the model of unknown paternity, the MS groups were ignored, and the sires of MS offspring were considered to be unknown and to belong to a single base population. In the genetic group approach, 2 definitions were used. In the first definition (GGa), ?phantom parents? for animals with uncertain paternity were attributed, defining the genetic group as the MS group. In the other approach, GGb, phantom parents for animals with uncertain paternity were also attributed; however, MS offspring were clustered in genetic groups according to their year of birth, every 3 yr, on the basis of the average of male generation interval. Univariate analyses were performed under the Bayesian approach via Markov chain Monte Carlo methods. Models were compared by deviance information criteria and the conditional predictive ordinate. According to the choice crit... Mostrar Tudo |
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Palavras-Chave: |
Bayesian inference; Genetic group; Genetic group model; Grupo genético; Paternidade; Paternity tests; Uncertain paternity. |
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Thesagro: |
Bovino; Crescimento; Gado Nelore; Genética animal. |
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Thesaurus NAL: |
Animal genetics; Bayesian theory; Cattle; Models; Nellore. |
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Categoria do assunto: |
-- |
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Marc: |
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024 7 $a10.2527/jas.2011-4989$2DOI
100 1 $aSHIOTSUKI, L.
245 $aComparison of a genetic group and unknown paternity models for growth traits in Nellore cattle.$h[electronic resource]
260 $c2013
520 $aAbstract: The aim of the present study was to compare a model assuming unknown paternity and a model using genetic grouping to indicate the most adequate statistical procedure for the estimation of breeding values for animals with uncertain paternity. After data consistency, 62,212 Nellore animals, offspring of 581 bulls and 27,743 cows, were used in the analyses. The pedigree file contained 75,088 animals, including 22,810 (30.18%) offspring of multiple sires and 12,876 animals belonging to the base population with unknown parents. Three different approaches were adopted to deal with uncertain paternity of multiple-sire (MS) offspring. In the model of unknown paternity, the MS groups were ignored, and the sires of MS offspring were considered to be unknown and to belong to a single base population. In the genetic group approach, 2 definitions were used. In the first definition (GGa), ?phantom parents? for animals with uncertain paternity were attributed, defining the genetic group as the MS group. In the other approach, GGb, phantom parents for animals with uncertain paternity were also attributed; however, MS offspring were clustered in genetic groups according to their year of birth, every 3 yr, on the basis of the average of male generation interval. Univariate analyses were performed under the Bayesian approach via Markov chain Monte Carlo methods. Models were compared by deviance information criteria and the conditional predictive ordinate. According to the choice criteria results, the genetic group model defined by the generation interval of males was more appropriate for predicting the genetic merit of animals with uncertain paternity. Therefore, the use of this model is recommended for the prediction of genetic merit and classification of offspring of multiple sires.
650 $aAnimal genetics
650 $aBayesian theory
650 $aCattle
650 $aModels
650 $aNellore
650 $aBovino
650 $aCrescimento
650 $aGado Nelore
650 $aGenética animal
653 $aBayesian inference
653 $aGenetic group
653 $aGenetic group model
653 $aGrupo genético
653 $aPaternidade
653 $aPaternity tests
653 $aUncertain paternity
700 1 $aCARDOSO, F. F.
700 1 $aSILVA, J. A.
700 1 $aALBUQUERQUE, L. G.
773 $tJournal of Animal Science$gv. 91, n. 11, p. 5135-5143, Nov., 2013.
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Embrapa Caprinos e Ovinos (CNPC) |
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