|
|
Registros recuperados : 29 | |
1. | | OLIVEIRA, J. S. e; LOPES, F. C. F.; CARNEIRO, J. da C.; RODRIGUES, J. A. S.; LANES, E. C. M. de; RIBEIRO, E. G.; CHAVES, A. V. Digestibilidade ruminal "in situ" da matéria seca das silagens, das folhas, dos colmos, das panículas e das plantas inteiras de sete genótipos de sorgo. In: REUNIÃO ANUAL DA SOCIEDADE BRASILEIRA DE ZOOTECNIA, 42., 2005, Goiânia. A Produção animal e o foco no agronegócio: anais. Goiânia: SBZ, 2005. Biblioteca(s): Embrapa Milho e Sorgo. |
| |
2. | | MACHADO, F. S.; PEREIRA, L. G. R.; GUIMARAES JUNIOR, R.; LOPES, F. C. F.; CHAVES, A. V.; CAMPOS, M. M.; MORENZ, M. J. F. Emissões de metano na pecuária: conceitos, métodos de avaliação e estratégias de mitigação. Juiz de Fora: Embrapa Gado de Leite, 2011. 92 p. (Embrapa Gado de Leite. Documentos, 147). Biblioteca(s): Embrapa Gado de Leite. |
| |
7. | | TERRY, S. A.; RIBEIRO, R. S.; FREITAS, D. S.; DELAROTA, G. D.; PEREIRA, L. G. R.; TOMICH, T. R.; MAURÍCIO, R. M.; CHAVES, A. V. Effects of Tithonia diversifolia on in vitro methane production and ruminal fermentation characteristics. Animal Production Science, v. 56, n. 2/3, p. 437-441, 2016. Biblioteca(s): Embrapa Gado de Leite. |
| |
8. | | RIBEIRO JUNIOR, G. O.; GONÇALVES, L. C.; PEREIRA, L. G. R.; CHAVES, A. V.; WANG, Y.; BEAUCHEMIN, K. A.; McALLISTER, T. A. Effect of fibrolytic enzymes added to a Andropogon gayanus grass silage-concentrate diet on rumen fermentation in batch cultures and the artificial rumen (Rusitec). Animal, v. 9, n. 7, p. 1153-1162, 2015. Biblioteca(s): Embrapa Gado de Leite. |
| |
9. | | MEALE, S. J.; OLIVARES-PALMA, S. M.; PEREIRA, L. G. R.; MACHADO, F. S.; CARNEIRO, H.; LOPES, F. C. F.; CHAVES, A. V. Effects of biodiesel by-products on in vitro fermentation, digestion kinetics and methane production. Journal of Animal Science, v. 90, Suppl. 3, p. 601, 2012. Biblioteca(s): Embrapa Gado de Leite. |
| |
10. | | RIBEIRO JUNIOR, G. O.; TEIXEIRA, A. M.; VELASCO, F. O.; FARIA JÚNIOR, W. G.; PEREIRA, L. G. R.; CHAVES, A. V.; GONÇALVES, L. C.; McALLISTER, T. A. Production, Nutritional Quality and In vitro Methane Production from Andropogon gayanus Grass Harvested at Different Maturities and Preserved as Hay or Silage. Asian-Australasian Journal of Animal Sciences, v. 27, n. 3, p. 330-341, 2014. Biblioteca(s): Embrapa Gado de Leite. |
| |
11. | | RAMOS, A. F. O.; TERRY, S. A.; HOLMAN, D. B.; BREVES, G.; PEREIRA, L. G. R.; SILVA, A. G. M.; CHAVES, A. V. Tucumã oil shifted ruminal fermentation, reducing methane production and altering the microbiome but decreased substrate digestibility within a RUSITEC fed a mixed hay - concentrate diet. Frontiers in Microbiology, v. 9, article 1647, 2018. 11 p. Biblioteca(s): Embrapa Gado de Leite. |
| |
12. | | OLIVARES PALMA, S. M.; MEALE, S. J.; PEREIRA, L. G. R.; MACHADO, F. S.; CARNEIRO, H.; LOPES, F. C. F.; MAURICIO, R. M.; CHAVES, A. V. In vitro fermentation, digestion kinetics and methane production of oilseed press cakes from biodiesel production. Asian-Australasian Journal of Animal Sciences, v. 26, n. 8, p. 1102-1110, 2013. Biblioteca(s): Embrapa Gado de Leite. |
| |
13. | | VIEIRA, P. A. S.; PEREIRA, L. G. R.; AZEVÊDO, J. A. G.; NEVES, A. L. A.; CHIZZOTTI, M. L.; SANTOS, R. D. dos; ARAUJO, G. G. L. de; MISTURA, C.; CHAVES, A. V. Development of mathematical models to predict dry matter intake in feedlot Santa Ines rams. Small Ruminant Research, v. 112, n. 1/3, p. 78-84, 2013. Biblioteca(s): Embrapa Gado de Leite; Embrapa Semiárido. |
| |
14. | | PAIVA, C. A. V.; VELASCO, F. O.; PÔSSAS, F. P.; LIMA, J. A. M.; FERREIRA, A. L.; TOMICH, T. R.; MACHADO, F. S.; CAMPOS, M. M.; CHAVES, A. V.; PEREIRA, L. G. R. Comparação dos métodos tradicional e por processamento de imagens digitais para avaliação do escore de condição corporal em três grupos genéticos de vacas leiteiras. In: CONGRESSO INTERNACIONAL DO LEITE, 13., 2015, Porto Alegre. Anais... Juiz de Fora: Embrapa Gado de Leite, 2015. 4 p. Biblioteca(s): Embrapa Gado de Leite. |
| |
15. | | OLIVEIRA FILHO, C. A. A.; MACHADO, F. S.; FERREIRA, A. L.; PEREIRA, L. G. R.; TOMICH, T. R.; CAMPOS, M. M.; AZEVÊDO, J. A. G.; MAURÍCIO, R. M.; CHAVES, A. V.; SILVA, C. F. P. G. Energy expenditure and methane emission in dairy heifers using the face-mask method. In: ADSA ASAS JOINT ANNUAL MEETING, 2015, Orlando. Proceedings... Orlando: ADSA-ASAS, 2015. p. 131. Biblioteca(s): Embrapa Gado de Leite. |
| |
16. | | MACHADO, F. S.; GONÇALVES, L. C.; RODRIGUES, J. A. S.; RIBAS, M. N.; PÔSSAS, F. P.; JAYME, D. G.; PEREIRA, L. G. R.; CHAVES, A. V.; TOMICH, T. R. Energy partitioning and methane emission by sheep fed sorghum silages at different maturation stages. Arquivo Brasileiro de Medicina Veterinária e Zootecnia, Belo Horizonte, v. 67, n. 3, p. 790-800, 2015. Biblioteca(s): Embrapa Milho e Sorgo. |
| |
17. | | MACHADO, F. S.; RODRÍGUEZ, N. M.; GONÇALVES, L. C.; RODRIGUES, J. A. S.; RIBAS, M. N.; PÔSSAS, F. P.; JAYME, D. G.; PEREIRA, L. G. R.; CHAVES, A. V.; TOMICH, T. R. Energy partitioning and methane emission by sheep fed sorghum silages at different maturation stages. Arquivo Brasileiro de Medicina Veterinária e Zootecnia, v. 67, n. 3, p. 790-800, 2015. Biblioteca(s): Embrapa Gado de Leite. |
| |
18. | | OLIVEIRA FILHO, C. A. A.; MACHADO, F. S.; PEREIRA, L. G. R.; TOMICH, T. R.; CAMPOS, M. M.; FERREIRA, A. L.; AZEVÊDO, J. A. G.; MAURÍCIO, R. M.; CHAVES, A. V.; SILVA, C. F. P. G. Performance, heat production and methane emission in dairy heifers under different nutritional plans. In: ADSA ASAS JOINT ANNUAL MEETING, 2015, Orlando. Proceedings... Orlando: ADSA: ASAS, 2015. Biblioteca(s): Embrapa Gado de Leite. |
| |
19. | | MOURA, A. M.; TOMICH, T. R.; PEREIRA, L. G. R.; TEIXEIRA, A. M.; PACIULLO, D. S. C.; JAYME, D. G.; MACHADO, F. S.; GOMIDE, C. A. de M.; CAMPOS, M. M.; CHAVES, A. V.; GONÇALVES, L. C. Pasture productivity and quality of Urochloa brizantha cultivar Marandu evaluated at two grazing intervals and their impact on milk production. Animal Production Science, v. 57, n. 7, p. 1384-1391, 2017. Biblioteca(s): Embrapa Gado de Leite. |
| |
20. | | LIMA, J. P. O.; CARAVALHO, E. V.; PEREIRA, V. de A.; CHAVES, A. V.; FRANCO, M. L.; CARVALHO, P. P. F. DE; CÂMARA, G. I. F.; SOUZA FILHO, M. de S. M. de; FECHINE, P. B. A. Biomateriais. FECHINE, P. B. A. (Org.). Avanço no desenvolvimento de nanomaterais: Fortaleza: Imprensa Universitária UFC, 2020. Biblioteca(s): Embrapa Agroindústria Tropical. |
| |
Registros recuperados : 29 | |
|
|
| Acesso ao texto completo restrito à biblioteca da Embrapa Semiárido. Para informações adicionais entre em contato com cpatsa.biblioteca@embrapa.br. |
Registro Completo
Biblioteca(s): |
Embrapa Gado de Leite; Embrapa Semiárido. |
Data corrente: |
06/02/2014 |
Data da última atualização: |
05/02/2024 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
B - 1 |
Autoria: |
VIEIRA, P. A. S.; PEREIRA, L. G. R.; AZEVÊDO, J. A. G.; NEVES, A. L. A.; CHIZZOTTI, M. L.; SANTOS, R. D. dos; ARAUJO, G. G. L. de; MISTURA, C.; CHAVES, A. V. |
Afiliação: |
PABLO ALMEIDA SAMPAIO VIEIRA, Universidade Federal do Vale do São Francisco; LUIZ GUSTAVO RIBEIRO PEREIRA, CNPGL; JOSÉ AUGUSTO GOMES AZEVÊDO, UESC; ANDRE LUIS ALVES NEVES, CNPGL; MÁRIO LUIZ CHIZZOTTI, UFLA; RAFAEL DANTAS DOS SANTOS, CPATSA; GHERMAN GARCIA LEAL DE ARAUJO, CPATSA; CLAUDIO MISTURA, Universidade do Estado da Bahia; ALEXANDRE VIEIRA CHAVES, University of Sydney, Australia. |
Título: |
Development of mathematical models to predict dry matter intake in feedlot Santa Ines rams. |
Ano de publicação: |
2013 |
Fonte/Imprenta: |
Small Ruminant Research, v. 112, n. 1/3, p. 78-84, 2013. |
DOI: |
https://doi.org/10.1016/j.smallrumres.2012.10.007 |
Idioma: |
Inglês |
Conteúdo: |
Mathematical models to predict the dry matter intake (DMI) of feedlot Santa Ines rams were developed and evaluated in this study. The available database had 100 experimental units from 13 studies. Study effect was integrated and random effects of their interactions as components of a hybrid model. The independent variables were initially adjusted to a model which included fixed effects for y-intercept and slope and random effects in y-intercept and slope study, using unstructured covariance model (e.g.: UN-unstructured). Study effect on database was verified, and then a meta-analysis procedure to develop DMI prediction equations was performed. For validation and comparisons between existing prediction equations in the national and international literature, independent data from one survey with 21 animals were used. Validation methods of the observed and predicted DMI were based on linear regression model adjustment of the observed values over predicted values. The following variables: average live weight (ALW), metabolic live weight (MLW0.75), average daily gain (ADG) and average daily gain2 (ADGsq) presented positive correlation with DMI. In contrast diet concentrate level showed a negative correlation. Among eight models examined, the following resulting equation [DMI (g/day) = 238.74 ± 114.56 (0.0398) + 31.3574 ± 4.2737 (<0.0001) × MLW + 1.2623 ±0.2128 (<0.0001) × ADG − 5.1837 ± 0.7448 (<0.0001) × CON] has been found as the best fit model to predict DMI in feedlot Santa Ines ram MenosMathematical models to predict the dry matter intake (DMI) of feedlot Santa Ines rams were developed and evaluated in this study. The available database had 100 experimental units from 13 studies. Study effect was integrated and random effects of their interactions as components of a hybrid model. The independent variables were initially adjusted to a model which included fixed effects for y-intercept and slope and random effects in y-intercept and slope study, using unstructured covariance model (e.g.: UN-unstructured). Study effect on database was verified, and then a meta-analysis procedure to develop DMI prediction equations was performed. For validation and comparisons between existing prediction equations in the national and international literature, independent data from one survey with 21 animals were used. Validation methods of the observed and predicted DMI were based on linear regression model adjustment of the observed values over predicted values. The following variables: average live weight (ALW), metabolic live weight (MLW0.75), average daily gain (ADG) and average daily gain2 (ADGsq) presented positive correlation with DMI. In contrast diet concentrate level showed a negative correlation. Among eight models examined, the following resulting equation [DMI (g/day) = 238.74 ± 114.56 (0.0398) + 31.3574 ± 4.2737 (<0.0001) × MLW + 1.2623 ±0.2128 (<0.0001) × ADG − 5.1837 ± 0.7448 (<0.0001) × CON] has been found as the best fit model to predict DMI in feedlot S... Mostrar Tudo |
Palavras-Chave: |
Modelling; Nutritional requirements; Raça Santa Ines; Santa Ines. |
Thesagro: |
Carneiro; Matéria Seca. |
Thesaurus NAL: |
Dry matter intake; Meta-analysis; Ruminants. |
Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal |
Marc: |
LEADER 02527naa a2200337 a 4500 001 1979019 005 2024-02-05 008 2013 bl uuuu u00u1 u #d 024 7 $ahttps://doi.org/10.1016/j.smallrumres.2012.10.007$2DOI 100 1 $aVIEIRA, P. A. S. 245 $aDevelopment of mathematical models to predict dry matter intake in feedlot Santa Ines rams.$h[electronic resource] 260 $c2013 520 $aMathematical models to predict the dry matter intake (DMI) of feedlot Santa Ines rams were developed and evaluated in this study. The available database had 100 experimental units from 13 studies. Study effect was integrated and random effects of their interactions as components of a hybrid model. The independent variables were initially adjusted to a model which included fixed effects for y-intercept and slope and random effects in y-intercept and slope study, using unstructured covariance model (e.g.: UN-unstructured). Study effect on database was verified, and then a meta-analysis procedure to develop DMI prediction equations was performed. For validation and comparisons between existing prediction equations in the national and international literature, independent data from one survey with 21 animals were used. Validation methods of the observed and predicted DMI were based on linear regression model adjustment of the observed values over predicted values. The following variables: average live weight (ALW), metabolic live weight (MLW0.75), average daily gain (ADG) and average daily gain2 (ADGsq) presented positive correlation with DMI. In contrast diet concentrate level showed a negative correlation. Among eight models examined, the following resulting equation [DMI (g/day) = 238.74 ± 114.56 (0.0398) + 31.3574 ± 4.2737 (<0.0001) × MLW + 1.2623 ±0.2128 (<0.0001) × ADG − 5.1837 ± 0.7448 (<0.0001) × CON] has been found as the best fit model to predict DMI in feedlot Santa Ines ram 650 $aDry matter intake 650 $aMeta-analysis 650 $aRuminants 650 $aCarneiro 650 $aMatéria Seca 653 $aModelling 653 $aNutritional requirements 653 $aRaça Santa Ines 653 $aSanta Ines 700 1 $aPEREIRA, L. G. R. 700 1 $aAZEVÊDO, J. A. G. 700 1 $aNEVES, A. L. A. 700 1 $aCHIZZOTTI, M. L. 700 1 $aSANTOS, R. D. dos 700 1 $aARAUJO, G. G. L. de 700 1 $aMISTURA, C. 700 1 $aCHAVES, A. V. 773 $tSmall Ruminant Research$gv. 112, n. 1/3, p. 78-84, 2013.
Download
Esconder MarcMostrar Marc Completo |
Registro original: |
Embrapa Gado de Leite (CNPGL) |
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
Nenhum registro encontrado para a expressão de busca informada. |
|
|