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| Registros recuperados : 20 | |
| 1. |  | 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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| 2. | | CARRARA, E. R.; LOPES, P. S.; VERONEZE, R.; PEREIRA, R. J.; ZADRA, L. E. F.; PEIXOTO, M. G. C. D. Assessment of runs of homozygosity, heterozygosity-rich regions and genomic inbreeding estimates in a subpopulation of Guzerá (Bos indicus) dual-purpose cattle. Journal of Animal Breeding and Genetics, v. 141, n. 2, p. 207-219, 2024.| Biblioteca(s): Embrapa Gado de Leite. |
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| 3. | | VERNEQUE, R. da S.; VERONEZE, R.; PANETTO, J. C. do C.; SILVA, M. V. G. B.; TORAL, F. L. B. A contribuição do melhoramento animal para a pecuária de leite. In: VILELA, D.; FERREIRA, R. de P.; FERNANDES, E. N.; JUNTOLLI, F. V. (Ed.). Pecuária de leite no Brasil: cenários e avanços tecnológicos. Brasília, DF: Embrapa, 2016. p. 255-264.| Biblioteca(s): Embrapa Gado de Leite. |
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| 4. | | DIANA, T. F.; CALDERANO, A. A.; ROSTAGNO, H. S.; MARQUES, M. R. de L.; TAVERNARI, F. de C.; VERONEZE, R.; ALBINO, L. F. T. Apparent calcium retention and digestibility coefficients of limestone with different particle sizes in laying hens. Scientia Agricola, v. 80, n. e20210258, 2023.| Biblioteca(s): Embrapa Suínos e Aves. |
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| 5. | | SILVA, H. T.; LOPES, P. S.; CARVALHEIRA, J.; SILVA, D. A.; SILVA, A. A.; SILVA, F. F.; VERONEZE, R.; THOMPSON, G.; COSTA, C. N. Autoregressive model for genetic evaluation of longitudinal reproductive traits in Brazilian Holstein cattle. Reproduction in Domestic Animals, v. 56, n. 3, p. 391-399, 2021.| Biblioteca(s): Embrapa Gado de Leite. |
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| 6. | | SILVA, D. A.; COSTA, C. N.; SILVA, A. A.; SILVA, H. T.; LOPES, P. S.; SILVA, F. F.; VERONEZE, R.; THOMPSON, G.; AGUILAR, I.; CARVALHEIRA, J. Autoregressive and random regression test-day models for multiple lactations in genetic evaluation of Brazilian Holstein cattle. Journal of Animal Breeding and Genetics, v. 137, n. 3, p. 305-315, 2020.| Biblioteca(s): Embrapa Gado de Leite. |
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| 7. | | SILVA, H. T.; LOPES, P. S.; COSTA, C. N.; SILVA, A. A.; SILVA, D. A.; SILVA, F. F.; VERONEZE, R.; THOMPSON, G.; CARVALHEIRA, J. Autoregressive single-step model for genomic evaluation of longitudinal reproductive traits in portuguese holstein cattle. Journal of Animal Breeding and Genetics, v. 138, n. 3, p. 349-359, 2021.| Biblioteca(s): Embrapa Gado de Leite. |
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| 8. | | SILVA, A. A.; SILVA, D. A.; LOPES, P. S.; SILVA, H. T.; VERONEZE, R.; THOMPSON, G.; COSTA, C. N.; CARVALHEIRA, J. SNP substitution effects for SCS changes across environmental gradients in Portuguese dairy cattle. In: ANNUAL MEETING OF THE EUROPEAN FEDERATION OF ANIMAL SCIENCE, 73., 2022, Porto. Book of abstracts... Rome: European Federation of Animal Science, 2022. p. 136.| Biblioteca(s): Embrapa Gado de Leite. |
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| 9. | | SILVA, A. A.; SILVA, D. A.; SILVA, F. F.; COSTA, C. N.; SILVA, H. T.; LOPES, P. S.; VERONEZE, R.; THOMPSON, G.; CARVALHEIRA, J. GWAS and gene networks for milk-related traits from test-day multiple lactations in Portuguese Holstein cattle. Journal of Applied Genetics, v. 61, p. 465-476, 2020.| Biblioteca(s): Embrapa Gado de Leite. |
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| 10. | | SILVA, A. A.; SILVA, D. A.; LOPES, P. S.; SILVA, H. T.; VERONEZE, R.; THOMPSON, G.; CARVALHEIRA, J.; COSTA, C. N. Genomic predictions including unknown parent groups for milk traits in Portuguese Holstein cattle. In: ANNUAL MEETING OF THE EUROPEAN FEDERATION OF ANIMAL SCIENCE, 73., 2022, Porto. Book of abstracts... Rome: European Federation of Animal Science, 2022. p. 135.| Biblioteca(s): Embrapa Gado de Leite. |
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| 11. | | SILVA, D. A.; LOPES, P. S.; COSTA, C. N.; SILVA, A. A.; SILVA, H. T.; SILVA, F. F.; VERONEZE, R.; THOMPSON, G.; CARVALHEIRA, J. Genotype by environment interaction for Holstein cattle populations using autoregressive and within- and across-countrymulti-trait reaction norms test-day models. Animal, v. 15, 100084, 2021.| Biblioteca(s): Embrapa Gado de Leite. |
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| 12. | | SILVA, A. A.; SILVA, F. F.; SILVA, D. A.; SILVA, H. T.; COSTA, C. N.; LOPES, P. S.; VERONEZE, R.; THOMPSON, G.; CARVALHEIRA, J. Genotype imputation strategies for Portuguese Holstein cattle using different SNP panels. Czech Journal of Animal Science, v. 64, n. 9, p. 377-386, 2019.| Biblioteca(s): Embrapa Gado de Leite. |
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| 13. | | SOARES, T. L. da S.; SANTOS, F. L. C.; PEIXOTO, M. G. C. D.; CARRARA, E. R.; BRUNELI, F. A. T.; VERONEZE, R.; LOPES, P. S. A interação genótipo-ambiente já afeta características leiteiras e idade ao primeiro parto em animais Guzerá. Revista Guzerate, ano 2, n. 2, p. 66-70, maio 2023.| Biblioteca(s): Embrapa Gado de Leite. |
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| 14. | | COSTA, E. V.; DINIZ, D. B.; VERONEZE, R.; RESENDE, M. D. V. de; AZEVEDO, C. F.; GUIMARÃES, S. E. F.; SILVA, F. F.; LOPES, P. S. Estimating additive and dominance variances for complex traits in pigs combining genomic and pedigree information. Genetics and Molecular Research, v. 14, n. 2, p. 6303-6311, June 2015.| Biblioteca(s): Embrapa Florestas. |
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| 15. | | CARRARA, E. R.; LOPES, P. S.; REIS, A. C. Z.; SILVA, J. X.; DIAS, L. C. de C. M.; SCHULTZ, E. B.; MARQUES, D. B. D.; SILVA, D. A. da; VERONEZE, R.; ANDRADE, R. G.; PEIXOTO, M. G. C. D. NASA POWER satellite meteorological system is a good tool for obtaining estimates of the temperature-humidity index under Brazilian conditions compared to INMET weather stations data. International Journal of Biometeorology, v. 67, n. 7, p. 1273-1277, 2023.| Biblioteca(s): Embrapa Gado de Leite. |
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| 16. | | ROCHA, R. de F. B.; OTTO, P. I.; SILVA, M. V. G. B.; MARTINS, M. F.; MACHADO, M. A.; VERONEZE, R.; LEANDRO, F. D.; PEREIRA, S. M.; GUIMARÃES, S. E. F.; PANETTO, J. C. do C. Repeatability and random regression models to estimate genetic parameters for oocyte and embryo production in the Gir breed. Animal Production Science, v. 62, n. 17, p. 1661-1670, 2022.| Biblioteca(s): Embrapa Gado de Leite. |
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| 17. | | DUARTE, D. A. S.; FORTES, M. R. S.; DUARTE, M. de S.; GUIMARÃES, S. E. F.; VERARDO, L. L.; VERONEZE, R.; RIBEIRO, A. M. F.; LOPES, P. S.; RESENDE, M. D. V. de; SILVA, F. F. e. Genome-wide association studies, meta-analyses and derived gene network for meat quality and carcass traits in pigs. Animal Production Science, v. 58, n. 6, p. 1100-1008, May 2018.| Biblioteca(s): Embrapa Florestas. |
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| 18. | | CARRARA, E. R.; PEIXOTO, M. G. C. D.; SILVA, A. A. da; BRUNELI, F. A. T.; VENTURA, H. T.; ZADRA, L. E. F.; JOSAHKIAN, L. A.; VERONEZE, R.; LOPES, P. S. Genomic prediction in Brazilian Guzerá cattle: application of a single-step approach to productive and reproductive traits. Tropical Animal Health and Production, v. 55, article 48, 2023.| Biblioteca(s): Embrapa Gado de Leite. |
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| 19. | | CARRARA, E. R.; PEIXOTO, M. G. C. D.; VERONEZE, R.; SILVA, F. F. e; RAMOS, P. V. B.; BRUNELI, F. A. T.; ZADRA, L. E. F.; VENTURA, H. T.; JOSAHKIAN, L. A.; LOPES, P. S. Genetic study of quantitative traits supports the use of Guzerá as dual-purpose cattle. Animal Bioscience, v. 35, n. 7, p. 955-963, 2022.| Biblioteca(s): Embrapa Gado de Leite. |
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| 20. | | OTTO, P. I.; GUIMARÃES, S. E. F.; VERARDO, L. L.; AZEVEDO, A. L. S.; VANDENPLAS, J.; SOARES, A. C. C.; SEVILLANO, C. A.; VERONEZE R; PIRES, M. de F. A.; FREITAS, C. de; PRATA, M. C. de A.; FURLONG, J.; VERNEQUE, R. da S.; MARTINS, M. F.; PANETTO, J. C. do C.; CARVALHO, W. A.; GOBO, D. O. R.; SILVA, M. V. G. B.; MACHADO, M. A. Genome-wide association studies for tick resistance in Bos taurus × Bos indicus crossbred cattle: A deeper look into this intricate mechanism. Journal of Dairy Science, v. 101, n. 12, p. 11020-11032, 2018.| Biblioteca(s): Embrapa Gado de Leite. |
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| Registros recuperados : 20 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Gado de Leite. Para informações adicionais entre em contato com cnpgl.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Gado de Leite. |
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Data corrente: |
13/01/2020 |
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Data da última atualização: |
06/02/2024 |
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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: |
SILVA, D. A.; COSTA, C. N.; SILVA, A. A.; SILVA, H. T.; LOPES, P. S.; SILVA, F. F.; VERONEZE, R.; THOMPSON, G.; AGUILAR, I.; CARVALHEIRA, J. |
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Afiliação: |
CLAUDIO NAPOLIS COSTA, CNPGL. |
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Título: |
Autoregressive and random regression test-day models for multiple lactations in genetic evaluation of Brazilian Holstein cattle. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Journal of Animal Breeding and Genetics, v. 137, n. 3, p. 305-315, 2020. |
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DOI: |
https://doi.org/10.1111/jbg.12459 |
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Idioma: |
Inglês |
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Conteúdo: |
Autoregressive (AR) and random regression (RR) models were fitted to test-day records from the first three lactations of Brazilian Holstein cattle with the objective of comparing their efficiency for national genetic evaluations. The data comprised 4,142,740 records of milk yield (MY) and somatic cell score (SCS) from 274,335 cows belonging to 2,322 herds. Although heritabilities were similar between models and traits, additive genetic variance estimates using AR were 7.0 (MY) and 22.2% (SCS) higher than those obtained from RR model. On the other hand, residual variances were lower in both traits when estimated through AR model. The rank correlation between EBV obtained from AR and RR models was 0.96 and 0.94 (MY) and 0.97 and 0.95 (SCS), respectively, for bulls (with 10 or more daughters) and cows. Estimated annual genetic gains for bulls (cows) obtained using AR were 46.11 (49.50) kg for MY and -0.019 (-0.025) score for SCS; whereas using RR these values were 47.70 (55.56) kg and -0.022 (-0.028) score. Akaike information criterion was lower for AR in both traits. Although AR model is more parsimonious, RR model assumes genetic correlations different from the unity within and across lactations. Thus, when these correlations are relatively high, these models tend to yield to similar predictions; otherwise, they will differ more and RR model would be theoretically sounder. |
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Palavras-Chave: |
Autoregression; Legendre polynomials; Random regression. |
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Thesaurus NAL: |
Dairy cattle. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02289naa a2200289 a 4500
001 2118639
005 2024-02-06
008 2020 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1111/jbg.12459$2DOI
100 1 $aSILVA, D. A.
245 $aAutoregressive and random regression test-day models for multiple lactations in genetic evaluation of Brazilian Holstein cattle.$h[electronic resource]
260 $c2020
520 $aAutoregressive (AR) and random regression (RR) models were fitted to test-day records from the first three lactations of Brazilian Holstein cattle with the objective of comparing their efficiency for national genetic evaluations. The data comprised 4,142,740 records of milk yield (MY) and somatic cell score (SCS) from 274,335 cows belonging to 2,322 herds. Although heritabilities were similar between models and traits, additive genetic variance estimates using AR were 7.0 (MY) and 22.2% (SCS) higher than those obtained from RR model. On the other hand, residual variances were lower in both traits when estimated through AR model. The rank correlation between EBV obtained from AR and RR models was 0.96 and 0.94 (MY) and 0.97 and 0.95 (SCS), respectively, for bulls (with 10 or more daughters) and cows. Estimated annual genetic gains for bulls (cows) obtained using AR were 46.11 (49.50) kg for MY and -0.019 (-0.025) score for SCS; whereas using RR these values were 47.70 (55.56) kg and -0.022 (-0.028) score. Akaike information criterion was lower for AR in both traits. Although AR model is more parsimonious, RR model assumes genetic correlations different from the unity within and across lactations. Thus, when these correlations are relatively high, these models tend to yield to similar predictions; otherwise, they will differ more and RR model would be theoretically sounder.
650 $aDairy cattle
653 $aAutoregression
653 $aLegendre polynomials
653 $aRandom regression
700 1 $aCOSTA, C. N.
700 1 $aSILVA, A. A.
700 1 $aSILVA, H. T.
700 1 $aLOPES, P. S.
700 1 $aSILVA, F. F.
700 1 $aVERONEZE, R.
700 1 $aTHOMPSON, G.
700 1 $aAGUILAR, I.
700 1 $aCARVALHEIRA, J.
773 $tJournal of Animal Breeding and Genetics$gv. 137, n. 3, p. 305-315, 2020.
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