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| Registros recuperados : 125 | |
| 1. |  | RESENDE, M. D. V. de; SILVA, F. F. e. Análise estatística da interação genótipo x ambientes e normas de reação. In: RESENDE, M. D. V. de; SILVA, F. F. e; AZEVEDO, C. F. Estatística matemática, biométrica e computacional: modelos mistos, multivariados, categóricos e generalizados (REML/BLUP), inferência bayesiana, regressão, aleatória, seleção genômica, QTL, GWAS, estatística espacial e temporal, competição, sobrevivência. Viçosa, MG: UFV, 2014. p. 369-394.| Biblioteca(s): Embrapa Florestas. |
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| 3. | | RESENDE, M. D. V. de; SILVA, F. F. e. Modelos lineares generalizados e dados categóricos. In: RESENDE, M. D. V. de; SILVA, F. F. e; AZEVEDO, C. F. Estatística matemática, biométrica e computacional: modelos mistos, multivariados, categóricos e generalizados (REML/BLUP), inferência bayesiana, regressão, aleatória, seleção genômica, QTL, GWAS, estatística espacial e temporal, competição, sobrevivência. Viçosa, MG: UFV, 2014. p. 559-594.| Biblioteca(s): Embrapa Florestas. |
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| 5. | | SILVEIRA, F. G. da; SILVA, F. F. e; CARNEIRO, P. L. S.; MALHADO, C. H. M. Classificação multivariada de modelos de crescimento para grupos genéticos de ovinos de corte. Revista Brasileira de Saúde e Produção Animal, Salvador, v. 13, n. 1, p. 62-73, jan./mar., 2012.| Biblioteca(s): Embrapa Caprinos e Ovinos. |
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| 7. | | SILVA, F. F. e; SÁFADI, T.; MUNIZ, J. A.; AQUINO, L. H. de; MOURÃO, G. B. Comparação bayesiana de modelos de previsão de diferenças esperadas nas progênies no melhoramento genético de gado Nelore. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 43, n. 1, p. 37-45, jan. 2008| Biblioteca(s): Embrapa Unidades Centrais. |
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| 8. | | RESENDE, M. D. V. de; AZEVEDO, C. F.; SILVA, F. F. e. Softwares ASREML e R. In: RESENDE, M. D. V. de; SILVA, F. F. e; AZEVEDO, C. F. Estatística matemática, biométrica e computacional: modelos mistos, multivariados, categóricos e generalizados (REML/BLUP), inferência bayesiana, regressão, aleatória, seleção genômica, QTL, GWAS, estatística espacial e temporal, competição, sobrevivência. Viçosa, MG: UFV, 2014. p. 769-807.| Biblioteca(s): Embrapa Florestas. |
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| 10. | | RESENDE, M. D. V. de; AZEVEDO, C. F.; SILVA, F. F. e. Inferência bayesiana. In: RESENDE, M. D. V. de; SILVA, F. F. e; AZEVEDO, C. F. Estatística matemática, biométrica e computacional: modelos mistos, multivariados, categóricos e generalizados (REML/BLUP), inferência bayesiana, regressão, aleatória, seleção genômica, QTL, GWAS, estatística espacial e temporal, competição, sobrevivência. Viçosa, MG: UFV, 2014. p. 449-503.| Biblioteca(s): Embrapa Florestas. |
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| 13. | | SILVA, F. F. e; MUNIZ, J. A.; AQUINO, L. H. de; SÁFADI, T. Abordagem Bayesiana da curva de lactação de cabras Saanen de primeira e segunda ordem de parto. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 40, n. 1, p. 27-33, jan. 2005 Título em inglês: Bayesian approach in the lactation curve of Saanen goats from first and second calving orders.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 14. | | RESENDE, M. D. V. de; AZEVEDO, C. F.; SILVA, F. F. e. Análise estatística de dados longitudinais. In: RESENDE, M. D. V. de; SILVA, F. F. e; AZEVEDO, C. F. Estatística matemática, biométrica e computacional: modelos mistos, multivariados, categóricos e generalizados (REML/BLUP), inferência bayesiana, regressão, aleatória, seleção genômica, QTL, GWAS, estatística espacial e temporal, competição, sobrevivência. Viçosa, MG: UFV, 2014. p. 312-368.| Biblioteca(s): Embrapa Florestas. |
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| 16. | | ROSSI, R. M.; MARTINS, E. N.; LOPES, P. S.; SILVA, F. F. e. Análise bayesiana univariada e bivariada para a conversão alimentar de suínos da raça Piau. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 49, n. 10, p. 754-761, out. 2014. Título em inglês: Univariate and bivariate Bayesian analysis for feed conversion of the Piau swine breed.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 17. | | RESENDE, M. D. V. de; SILVA, F. F. e; AZEVEDO, C. F. Análise de sobrevivência e dados censurados. In: RESENDE, M. D. V. de; SILVA, F. F. e; AZEVEDO, C. F. Estatística matemática, biométrica e computacional: modelos mistos, multivariados, categóricos e generalizados (REML/BLUP), inferência bayesiana, regressão, aleatória, seleção genômica, QTL, GWAS, estatística espacial e temporal, competição, sobrevivência. Viçosa, MG: UFV, 2014. p. 595-626.| Biblioteca(s): Embrapa Florestas. |
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| 18. | | RESENDE, M. D. V. de; SILVA, F. F. e; AZEVEDO, C. F. Estatística matemática, biométrica e computacional: modelos mistos, multivariados, categóricos e generalizados (REML/BLUP), inferência bayesiana, regressão, aleatória, seleção genômica, QTL, GWAS, estatística espacial e temporal, competição, sobrevivência. Viçosa, MG: UFV, 2014. 882 p.| Biblioteca(s): Embrapa Florestas. |
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| 19. | | SILVA, H. T.; COSTA, C. N.; LOPES, P. S.; VERONEZE, R.; SILVA, F. F. e. Parâmetros genéticos para Stayabilityem bovinos da raça holandesa no Brasil. 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 Gado de Leite. |
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| 20. | | RENHE, I. R. T.; STRINCHETA, P. C.; SILVA, F. F. e; OLIVEIRA, T. V. de. Obtenção de corante natural azul extraído de frutos de jenipapo. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 44, n. 6, p. 649-652, jun. 2009. Notas científicas.
Título em inglês: Obtention of blue colorant from jenipapo fruit.| Biblioteca(s): Embrapa Agricultura Digital; Embrapa Unidades Centrais. |
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| Registros recuperados : 125 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Gado de Corte. Para informações adicionais entre em contato com cnpgc.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Gado de Corte. |
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Data corrente: |
22/12/2023 |
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Data da última atualização: |
22/12/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
RAMOS, P. B. B.; MENEZES, G. R. de O.; SILVA, D. A. DA; LOURENCO, D.; SANTIAGO, G. G.; TORRES JUNIOR, R. A. de A.; SILVA, F. F. E; LOPES, P. S.; VERONEZA, R. |
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Afiliação: |
PEDRO VITAL BRASIL RAMOS, UNIVERSIDADE FEDERAL DE VIÇOSA; GILBERTO ROMEIRO DE OLIVEIRA MENEZE, CNPGC; DELVAN ALVES DA SILVA, UNIVERSIDADE FEDERAL DE VIÇOSA; DANIELA LOURENCO, UNIVERSITY OF GEORGIA; GUSTAVO GARCIA SANTIAGO, GDM SEEDS; ROBERTO AUGUSTO DE A TORRES JUNIOR, CNPGC; FABYANO FONSECA E SILVA, UNIVERSIDADE FEDERAL DE VIÇOSA; PAULO SÁVIO LOPES, UNIVERSIDADE FEDERAL DE VIÇOSA; RENATA VERONEZE, UNIVERSIDADE FEDERAL DE VIÇOSA. |
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Título: |
Genomic analysis of feed efficiency traits in beef cattle using random regression models. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Journal Animal Breeding and Genetics, 2023. |
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DOI: |
10.1111/jbg.12840. |
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Idioma: |
Inglês |
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Notas: |
Online ahead of print. |
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Conteúdo: |
ABSTRACT - Feed efficiency plays a major role in the overall profitability and sustainability of the beef cattle industry, as it is directly related to the reduction of the animal demand for input and methane emissions. Traditionally, the average daily feed intake and weight gain are used to calculate feed efficiency traits. However, feed efficiency traits can be analysed longitudinally using random regression models (RRMs), which allow fitting random genetic and environmental effects over time by considering the covariance pattern between the daily records. Therefore, the objectives of this study were to: (1) propose genomic evaluations for dry matter intake (DMI), body weight gain (BWG), residual feed intake (RFI) and residual weight gain (RWG) data collected during an 84-day feedlot test period via RRMs; (2) compare the goodness-of-fit of RRM using Legendre polynomials (LP) and B-spline functions; (3) evaluate the genetic parameters behaviour for feed efficiency traits and their implication for new selection strategies. The datasets were provided by the EMBRAPA–GENEPLUS beef cattle breeding program and included 2920 records for DMI, 2696 records for BWG and 4675 genotyped animals. Genetic parameters and genomic breeding values (GEBVs) were estimated by RRMs under ssGBLUP for Nellore cattle using orthogonal LPs and B-spline. Models were compared based on the deviance information criterion (DIC). The ranking of the average GEBV of each test week and the overall GEBV average were compared by the percentage of individuals in common and the Spearman correlation coefficient (top 1%, 5%, 10% and 100%). The highest goodness-of-fit was obtained with linear B-Spline function considering heterogeneous residual variance. The heritability estimates across the test period for DMI, BWG, RFI and RWG ranged from 0.06 to 0.21, 0.11 to 0.30, 0.03 to 0.26 and 0.07 to 0.27, respectively. DMI and RFI presented within-trait genetic correlations ranging from low to high magnitude across different performance test-day. In contrast, BWG and RWG presented negative genetic correlations between the first 3weeks and the other days of performance tests. DMI and RFI presented a high-ranking similarity between the GEBV average of week eight and the overall GEBV average, with Spearman correlations and percentages of individuals selected in common ranging from 0.95 to 1.00 and 93 to 100, respectively. Week 11 presented the highest Spearman correlations (ranging from 0.94 to 0.98) and percentages of individuals selected in common (ranging from 85 to 94) of BWG and RWG with the average GEBV of the entire period of the test. In conclusion, the RRM using linear B-splines is a feasible alternative for the genomic evaluation of feed efficiency. Heritability estimates of DMI, RFI, BWG and RWG indicate enough additive genetic variance to achieve a moderate response to selection. A new selection strategy can be adopted by reducing the performance test to 56days for DMI and RFI selection and 77days for BWG and RWG selection. MenosABSTRACT - Feed efficiency plays a major role in the overall profitability and sustainability of the beef cattle industry, as it is directly related to the reduction of the animal demand for input and methane emissions. Traditionally, the average daily feed intake and weight gain are used to calculate feed efficiency traits. However, feed efficiency traits can be analysed longitudinally using random regression models (RRMs), which allow fitting random genetic and environmental effects over time by considering the covariance pattern between the daily records. Therefore, the objectives of this study were to: (1) propose genomic evaluations for dry matter intake (DMI), body weight gain (BWG), residual feed intake (RFI) and residual weight gain (RWG) data collected during an 84-day feedlot test period via RRMs; (2) compare the goodness-of-fit of RRM using Legendre polynomials (LP) and B-spline functions; (3) evaluate the genetic parameters behaviour for feed efficiency traits and their implication for new selection strategies. The datasets were provided by the EMBRAPA–GENEPLUS beef cattle breeding program and included 2920 records for DMI, 2696 records for BWG and 4675 genotyped animals. Genetic parameters and genomic breeding values (GEBVs) were estimated by RRMs under ssGBLUP for Nellore cattle using orthogonal LPs and B-spline. Models were compared based on the deviance information criterion (DIC). The ranking of the average GEBV of each test week and the overall GEBV average... Mostrar Tudo |
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Thesagro: |
Análise Estatística; Gado de Corte; Genótipo. |
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Thesaurus NAL: |
Beef cattle; Feed intake; Genotype; Nellore. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 03961naa a2200325 a 4500
001 2160221
005 2023-12-22
008 2023 bl uuuu u00u1 u #d
024 7 $a10.1111/jbg.12840.$2DOI
100 1 $aRAMOS, P. B. B.
245 $aGenomic analysis of feed efficiency traits in beef cattle using random regression models.$h[electronic resource]
260 $c2023
500 $aOnline ahead of print.
520 $aABSTRACT - Feed efficiency plays a major role in the overall profitability and sustainability of the beef cattle industry, as it is directly related to the reduction of the animal demand for input and methane emissions. Traditionally, the average daily feed intake and weight gain are used to calculate feed efficiency traits. However, feed efficiency traits can be analysed longitudinally using random regression models (RRMs), which allow fitting random genetic and environmental effects over time by considering the covariance pattern between the daily records. Therefore, the objectives of this study were to: (1) propose genomic evaluations for dry matter intake (DMI), body weight gain (BWG), residual feed intake (RFI) and residual weight gain (RWG) data collected during an 84-day feedlot test period via RRMs; (2) compare the goodness-of-fit of RRM using Legendre polynomials (LP) and B-spline functions; (3) evaluate the genetic parameters behaviour for feed efficiency traits and their implication for new selection strategies. The datasets were provided by the EMBRAPA–GENEPLUS beef cattle breeding program and included 2920 records for DMI, 2696 records for BWG and 4675 genotyped animals. Genetic parameters and genomic breeding values (GEBVs) were estimated by RRMs under ssGBLUP for Nellore cattle using orthogonal LPs and B-spline. Models were compared based on the deviance information criterion (DIC). The ranking of the average GEBV of each test week and the overall GEBV average were compared by the percentage of individuals in common and the Spearman correlation coefficient (top 1%, 5%, 10% and 100%). The highest goodness-of-fit was obtained with linear B-Spline function considering heterogeneous residual variance. The heritability estimates across the test period for DMI, BWG, RFI and RWG ranged from 0.06 to 0.21, 0.11 to 0.30, 0.03 to 0.26 and 0.07 to 0.27, respectively. DMI and RFI presented within-trait genetic correlations ranging from low to high magnitude across different performance test-day. In contrast, BWG and RWG presented negative genetic correlations between the first 3weeks and the other days of performance tests. DMI and RFI presented a high-ranking similarity between the GEBV average of week eight and the overall GEBV average, with Spearman correlations and percentages of individuals selected in common ranging from 0.95 to 1.00 and 93 to 100, respectively. Week 11 presented the highest Spearman correlations (ranging from 0.94 to 0.98) and percentages of individuals selected in common (ranging from 85 to 94) of BWG and RWG with the average GEBV of the entire period of the test. In conclusion, the RRM using linear B-splines is a feasible alternative for the genomic evaluation of feed efficiency. Heritability estimates of DMI, RFI, BWG and RWG indicate enough additive genetic variance to achieve a moderate response to selection. A new selection strategy can be adopted by reducing the performance test to 56days for DMI and RFI selection and 77days for BWG and RWG selection.
650 $aBeef cattle
650 $aFeed intake
650 $aGenotype
650 $aNellore
650 $aAnálise Estatística
650 $aGado de Corte
650 $aGenótipo
700 1 $aMENEZES, G. R. de O.
700 1 $aSILVA, D. A. DA
700 1 $aLOURENCO, D.
700 1 $aSANTIAGO, G. G.
700 1 $aTORRES JUNIOR, R. A. de A.
700 1 $aSILVA, F. F. E
700 1 $aLOPES, P. S.
700 1 $aVERONEZA, R.
773 $tJournal Animal Breeding and Genetics, 2023.
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