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| Registros recuperados : 21 | |
| 6. |  | SAINZ, R. D.; BARIONI, L. G.; PAULINO, P. V.; VALADARES FILHO, S. C.; OLTJEN, J. W. Growth patterns of Nellore vc British beef cattle breeds assessed using a dynamic, mechanistic model of cattle growth and composition. In: KEBREAB, E.; DIJKSTRA, J.; BANNINK, A.; GERRITS, W. J. J.; FRANCE, J. (Ed.). Nutrient digestion and utilization in farm animals: modelling approaches. Oxfordshire: CABI, 2006. p. 160-170.| Biblioteca(s): Embrapa Cerrados. |
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| 7. | | OLTJEN, J. W.; AHMADI, A; DUNBAR, J. R.; GARRET, W. N.; GUERRERO, J. Management strategies to maximize cattle profits. In: INTERNATIONAL CONFERENCE, 5., 1994, Orlando. Computers in agriculture: proceedings. St. Joseph, MI: ASAE, 1994. p. 165-170.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 8. | | OLTJEN, J. W.; SAINZ, R. D.; BARIONI, L. G.; MEDEIROS, S. R. de. Rate of protein growth and energy for maintenance parameter changes in the Davis Growth Model. In: EAAP INTERNATIONAL SYMPOSIUM ON ENERGY AND PROTEIN METABOLISM AND NUTRITION, 5., 2016, Krakow, Poland. Proceedings... Wageningen, Reino dos Países Baixos: Wageningen Academic Pulbishers, 2016. p. 69-70 (EAAP publication, 137). Edited by: Jacek Skomial, Hélène Lapierre| Biblioteca(s): Embrapa Gado de Corte. |
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| 9. | | AHMADI, A.; DUNBAR, J. R.; GARRETT, A. W. N.; OLTJEN, J. W.; GUERRERO, J. Taurus update-support for teaching research, and outreach. In: INTERNATIONAL CONFERENCE, 5., 1994, Orlando. Computers in agriculture: proceedings. St. Joseph, MI: ASAE, 1994. p. 183-188.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 10. | | BARIONI, L. G.; WOODWARD, S. J. R.; TEDESCHI, L. O.; MACHADO, C. F.; OLTJEN, J. W.; MARTHA JÚNIOR, G. B.; SAINZ, R. D. Current and potential contributions of mathematical modeling to management of grazing systems. In: GRASSLAND ECOPHYSIOLOGY AND GRAZING ECOLOGY, 2., 2004, Curitiba. [Anais...]. Curitiba: UFPR, 2004. 1 CD-ROM.| Biblioteca(s): Embrapa Cerrados. |
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| 11. | | ALBERTINI, T. Z.; MEDEIROS, S. R. de; TORRES JUNIOR, R. A. de A.; ZOCHI, S. S.; OLTJEN, J. W.; STRATHE, A. B.; LANNA, D. P. D. A methodological approach to estimate the lactation curve and net energy and protein requirements of beef cows using nonlinear mixed-effects modeling. Journal of Animal Science, v.90, n.11, p.3867-3878, Nov. 2012.| Biblioteca(s): Embrapa Gado de Corte. |
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| 12. | | BIASE, A. G.; DIAS, C. T. S.; BARIONI, L. G.; ALBERTINI, T. Z.; MARTORANO, L. G.; OLTJEN, J. W.; LANNA, D. P.; OLIVEIRA, P. P. A.; MEDEIROS, S. R. de; TORRES JUNIOR, R. A. de A. Dynamic mathematical model to estimate the individual performance of cross beef cattle. In: INTERNATIONAL ECOSUMMIT, 5., 2016, Montpellier. Ecological sustainability: engineering change: abstract book. [S.l.]: Elsevier, 2016. Não paginado.| Biblioteca(s): Embrapa Agricultura Digital; Embrapa Amazônia Oriental; Embrapa Pecuária Sudeste. |
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| 13. | | BIASE, A. G.; DIAS, C. T. dos S.; BARIONI, L. G.; ALBERTINI, T. Z.; MARTORANO, L. G.; OLTJEN, J. W.; LANNA, D. P. D.; OLIVEIRA, P. P. A.; MEDEIROS, S. R. de; TORRES JUNIOR, R. A. de A. Parametrization of the Davis Growth Model using data of crossbred zebu cattle. Scientia Agricola, v. 74, n. 1, p.8-17, Jan./Feb. 2017.| Biblioteca(s): Embrapa Agricultura Digital; Embrapa Amazônia Oriental; Embrapa Gado de Corte; Embrapa Pecuária Sudeste. |
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| 14. | | ALBERTINI, T. Z.; BIASE, A. G.; BARBOSA, M.; FERNANDES, P. A. P.; CASTANHEIRA, M. A.; LANNA, D. P.; NEPOMUCENO, N. H. C.; BARIONI, L. G.; MEDEIROS, S. R. de; TORRES JUNIOR, R. A. de A.; OLTJEN, J. W.; COSTA JÚNIOR, C. BeefTader (part I): optimal economical endpoint identification using mixed modeling approach decreases greenhouse gases emission and other pollutants for livestock farmers. In: INTERNATIONAL SYMPOSIUM ON GREENHOUSE GASES IN AGRICULTURE, 2., 2016, Campo Grande, MS. Proceedings... Brasília, DF: Embrapa, 2016. 502 p. (Embrapa Gado de Corte. Documentos, 216). Coordenador Roberto Giolo de Almeida. II SIGEE p. 182-186.| Biblioteca(s): Embrapa Gado de Corte. |
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| 15. | | ALBERTINI, T. Z.; BIASE, A. G.; BARBOSA, M.; FERNANDES, P. A. P.; CASTANHEIRA, M. A.; LANNA, D. P.; NEPOMUCENO, N. H. C.; BARIONI, L. G.; MEDEIROS, S. R. de; TORRES JUNIOR, R. A. de A.; OLTJEN, J. W.; COSTA JÚNIOR, C. BeefTader (part I): optimal economical endpoint identification using mixed modeling approach decreases greenhouse gases emission and other pollutants for livestock farmers. In: INTERNATIONAL SYMPOSIUM ON GREENHOUSE GASES IN AGRICULTURE, 2., 2016, Campo Grande, MS. Proceedings... Brasília, DF: Embrapa, 2016. p. 182-186. (Embrapa Gado de Corte. Documentos, 216). Coordenador: Roberto Giolo de Almeida. II SIGEE.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 16. | | ALBERTINI, T. Z.; BIASE, A. G.; BARBOSA, M.; CERQUEIRA, A. G.; GONÇALVES, H. C.; BARIONI, L. G.; CAIXETA-FILHO, V.; PÉRA, T. G.; DIAS, C. T. D. S.; MEDEIROS, S. R. de; OLTJEN, J. W.; NEPOMUCENO, N. H. C.; LANNA, D. P. D. BeefTrader: optimal economical endpoint decision support system for feedlots and meat packers. Journal of Animal Science v. 95, p. 307, 2017. Suplemento 4, Resumo 627. Edição de Abstracts do ASAS-CSAS Annual Meeting and Trade Show, Baltimore, 2017. Na publicação: S. R. Medeiros.| Biblioteca(s): Embrapa Gado de Corte. |
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| 17. | | ALBERTINI, T. Z.; BIASE, A. G.; BARBOSA, M.; CERQUEIRA, A. G.; GONÇALVES, H. C.; BARIONI, L. G.; CAIXETA-FILHO, V.; PÉRA, T. G.; DIAS, C. T. D. S.; MEDEIROS, S. R. de; OLTJEN, J. W.; NEPOMUCENO, N. H. C.; LANNA, D. P. D. BeefTrader: optimal economical endpoint decision support system for feedlots and meat packers. Journal of Animal Science, v. 95, p. 307, 2017. Suplemento 4, Resumo 627. Edição de Abstracts do ASAS-CSAS Annual Meeting and Trade Show, Baltimore, 2017. Na publicação: S. R. Medeiros.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 18. | | ALBERTINI, T. Z.; BIASE, A. G.; BARBOSA, M.; FERNANDES, P. A. P.; CASTANHEIRA, M. A.; COUTINHO, M. A. da S.; CERQUEIRA, A. G.; GONÇALVES, H. C.; LANNA, D. P.; NEPOMUCENO, N. H. C.; BARIONI, L. G.; MEDEIROS, S. R. de; TORRES JUNIOR, R. A. de A.; FREUA, M. C.; OLTJEN, J. W. BeefTrader (part III): meat industry opportunity to improve its profitability reducing greenhouse gases emission and pollutants based on optimal economical endpoint identification. In: INTERNATIONAL SYMPOSIUM ON GREENHOUSE GASES IN AGRICULTURE, 2., 2016, Campo Grande, MS. Proceedings... Brasília, DF: Embrapa, 2016. 502 p. (Embrapa Gado de Corte. Documentos, 216). Coordenador Roberto Giolo de Almeida. II SIGEE p. 191-194.| Biblioteca(s): Embrapa Gado de Corte. |
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| 19. | | ALBERTINI, T. Z.; BIASE, A. G.; BARBOSA, M.; FERNANDES, P. A. P.; CASTANHEIRA, M. A.; COUTINHO, M. A. da S.; CERQUEIRA, A. G.; GONÇALVES, H. C.; LANNA, D. P.; NEPOMUCENO, N. H. C.; BARIONI, L. G.; MEDEIROS, S. R. de; TORRES JUNIOR, R. A. de A.; FREUA, M. C.; OLTJEN, J. W. BeefTrader (part III): meat industry opportunity to improve its profitability reducing greenhouse gases emission and pollutants based on optimal economical endpoint identification. In: INTERNATIONAL SYMPOSIUM ON GREENHOUSE GASES IN AGRICULTURE, 2., 2016, Campo Grande, MS. Proceedings... Brasília, DF: Embrapa, 2016. p. 191-194. (Embrapa Gado de Corte. Documentos, 216). Coordenador: Roberto Giolo de Almeida. II SIGEE.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 20. | | BIASE, A. G.; ALBERTINI, T. Z.; BARBOSA, M.; FERNANDES, P. A. P.; CASTANHEIRA, M. A.; CERQUEIRA, A. G.; GONÇALVES, H. C.; LANNA, D. P.; NEPOMUCENO, N. H. C.; BARIONI, L. G.; MEDEIROS, S. R. de; TORRES JUNIOR, R. A. de A.; FREUA, M. C.; OLTJEN, J. W. BeefTrader (part II): optimal economical endpoint identification using nonparametric bootstrapping technique decreases greenhouse gases emission and other pollutants in feedlots. In: INTERNATIONAL SYMPOSIUM ON GREENHOUSE GASES IN AGRICULTURE, 2., 2016, Campo Grande, MS. Proceedings... Brasília, DF: Embrapa, 2016. 502 p. (Embrapa Gado de Corte. Documentos, 216). Coordenador Roberto Giolo de Almeida. II SIGEE p. 187-190.| Biblioteca(s): Embrapa Gado de Corte. |
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| Registros recuperados : 21 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Gado de Corte. Para informações adicionais entre em contato com biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Gado de Corte. |
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Data corrente: |
07/02/2013 |
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Data da última atualização: |
07/02/2013 |
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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: |
ALBERTINI, T. Z.; MEDEIROS, S. R. de; TORRES JUNIOR, R. A. de A.; ZOCHI, S. S.; OLTJEN, J. W.; STRATHE, A. B.; LANNA, D. P. D. |
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Afiliação: |
T. Z. Albertini, USP/ESALQ; SERGIO RAPOSO DE MEDEIROS, CNPGC; ROBERTO AUGUSTO DE A TORRES JUNIOR, CNPGC; S. S. Zocchi, USP/ESALQ; J. W. Oltjen, UNIVERSITY OF CALIFORNIA; A. B. Strathe, UNIVERSITY OF CALIFORNIA; D. P. D. LANNA, USP/ESALQ. |
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Título: |
A methodological approach to estimate the lactation curve and net energy and protein requirements of beef cows using nonlinear mixed-effects modeling. |
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Ano de publicação: |
2012 |
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Fonte/Imprenta: |
Journal of Animal Science, v.90, n.11, p.3867-3878, Nov. 2012. |
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Idioma: |
Inglês |
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Conteúdo: |
The objective of this study was to evaluate methods to predict the secretion of milk and net energy and protein requirements of beef cows (Bos indicus and B. taurus) after approximately 1 mo postpartum using nonlinear mixed-effect modeling (NLME). Twenty Caracu × Nellore (CN) and 10 Nellore (NL) cows were inseminated to Red Angus bulls, and 10 Angus × Nellore (AN) were bred to Canchim bulls. Cows were evaluated from just after calving (25 ± 11 d) to weaning (220 d). Milk yield was estimated by weighing calves before and after suckling (WSW) and by machine milking (MM) methods at 25, 52, 80, 109, 136, 164, 193, and 220 ± 11 d of lactation. Brody and simple linear equations were consecutively fi tted to the data and compared using information criteria. For the Brody equation, a NLME model was used to estimate all lactation profiles incorporating different sources of variation (calf sex and breed of cow, cow as a nested random effect, and within cow auto-correlation). The CV for the MM method (29%) was less than WSW (45%). Consequently, the WSW method was responsible for reducing the variance about 1.5 times among individuals, which minimized the ability to detect differences among cows. As a result, only milk yield MM data were used in the NLME models. The Brody equation provided the best fi t to this dataset, and inclusion of a continuous autoregressive process improved fi t (P < 0.01). Milk, energy and protein yield at the beginning of lactation were affected by cow genotype and calf sex (P < 0.001). The exponential decay of the lactation curves was affected only by genotype (P < 0.001). Angus × Nellore cows produced 15 and 48% more milk than CN and NL during the trial, respectively (P < 0.05). Caracu × Nellore cows produced 29% more milk than NL (P < 0.05). The net energy and net protein requirements for milk yield followed a similar ranking. Male calves stimulated their dams to produce 11.7, 11.4, and 11.9% more milk, energy and protein, respectively (P < 0.05). The MM method is better than the WSW technique to detect genetic or environmental differences in milk yield among beef cows. The data obtained by the MM method and analyzed by NLME models allows the inclusion of fi xed effects, random effects and an autoregressive process in lactation equations to describe lactation curves and net energy and protein requirements. The NLME is a powerful tool to describe differences in the secretion of milk due to heterosis and cell mammary external stimulus in beef cows. MenosThe objective of this study was to evaluate methods to predict the secretion of milk and net energy and protein requirements of beef cows (Bos indicus and B. taurus) after approximately 1 mo postpartum using nonlinear mixed-effect modeling (NLME). Twenty Caracu × Nellore (CN) and 10 Nellore (NL) cows were inseminated to Red Angus bulls, and 10 Angus × Nellore (AN) were bred to Canchim bulls. Cows were evaluated from just after calving (25 ± 11 d) to weaning (220 d). Milk yield was estimated by weighing calves before and after suckling (WSW) and by machine milking (MM) methods at 25, 52, 80, 109, 136, 164, 193, and 220 ± 11 d of lactation. Brody and simple linear equations were consecutively fi tted to the data and compared using information criteria. For the Brody equation, a NLME model was used to estimate all lactation profiles incorporating different sources of variation (calf sex and breed of cow, cow as a nested random effect, and within cow auto-correlation). The CV for the MM method (29%) was less than WSW (45%). Consequently, the WSW method was responsible for reducing the variance about 1.5 times among individuals, which minimized the ability to detect differences among cows. As a result, only milk yield MM data were used in the NLME models. The Brody equation provided the best fi t to this dataset, and inclusion of a continuous autoregressive process improved fi t (P < 0.01). Milk, energy and protein yield at the beginning of lactation were affected by cow genotype... Mostrar Tudo |
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Palavras-Chave: |
Bovino de corte; Desempenho animal. |
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Thesagro: |
Curva de Lactação; Nutrição Animal; Vaca. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 03344naa a2200253 a 4500
001 1948644
005 2013-02-07
008 2012 bl uuuu u00u1 u #d
100 1 $aALBERTINI, T. Z.
245 $aA methodological approach to estimate the lactation curve and net energy and protein requirements of beef cows using nonlinear mixed-effects modeling.$h[electronic resource]
260 $c2012
520 $aThe objective of this study was to evaluate methods to predict the secretion of milk and net energy and protein requirements of beef cows (Bos indicus and B. taurus) after approximately 1 mo postpartum using nonlinear mixed-effect modeling (NLME). Twenty Caracu × Nellore (CN) and 10 Nellore (NL) cows were inseminated to Red Angus bulls, and 10 Angus × Nellore (AN) were bred to Canchim bulls. Cows were evaluated from just after calving (25 ± 11 d) to weaning (220 d). Milk yield was estimated by weighing calves before and after suckling (WSW) and by machine milking (MM) methods at 25, 52, 80, 109, 136, 164, 193, and 220 ± 11 d of lactation. Brody and simple linear equations were consecutively fi tted to the data and compared using information criteria. For the Brody equation, a NLME model was used to estimate all lactation profiles incorporating different sources of variation (calf sex and breed of cow, cow as a nested random effect, and within cow auto-correlation). The CV for the MM method (29%) was less than WSW (45%). Consequently, the WSW method was responsible for reducing the variance about 1.5 times among individuals, which minimized the ability to detect differences among cows. As a result, only milk yield MM data were used in the NLME models. The Brody equation provided the best fi t to this dataset, and inclusion of a continuous autoregressive process improved fi t (P < 0.01). Milk, energy and protein yield at the beginning of lactation were affected by cow genotype and calf sex (P < 0.001). The exponential decay of the lactation curves was affected only by genotype (P < 0.001). Angus × Nellore cows produced 15 and 48% more milk than CN and NL during the trial, respectively (P < 0.05). Caracu × Nellore cows produced 29% more milk than NL (P < 0.05). The net energy and net protein requirements for milk yield followed a similar ranking. Male calves stimulated their dams to produce 11.7, 11.4, and 11.9% more milk, energy and protein, respectively (P < 0.05). The MM method is better than the WSW technique to detect genetic or environmental differences in milk yield among beef cows. The data obtained by the MM method and analyzed by NLME models allows the inclusion of fi xed effects, random effects and an autoregressive process in lactation equations to describe lactation curves and net energy and protein requirements. The NLME is a powerful tool to describe differences in the secretion of milk due to heterosis and cell mammary external stimulus in beef cows.
650 $aCurva de Lactação
650 $aNutrição Animal
650 $aVaca
653 $aBovino de corte
653 $aDesempenho animal
700 1 $aMEDEIROS, S. R. de
700 1 $aTORRES JUNIOR, R. A. de A.
700 1 $aZOCHI, S. S.
700 1 $aOLTJEN, J. W.
700 1 $aSTRATHE, A. B.
700 1 $aLANNA, D. P. D.
773 $tJournal of Animal Science$gv.90, n.11, p.3867-3878, Nov. 2012.
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