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| Registros recuperados : 392 | |
| 83. |  | MCMANUS, C.; FALCAO, R. A.; SAUERESSIG, M. G.; MARCELINO, K. R. A. Condicao corporal de bovinos em rebanho mestico no Cerrado. In: REUNIAO ANUAL DA SOCIEDADE BRASILEIRA DE ZOOTECNIA, 37., 2000, Vicosa, MG. Anais. Vicosa, MG: SBZ, 2000. 3 p.| Biblioteca(s): Embrapa Cerrados. |
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| 85. | | MCMANUS, C.; FALCAO, R.; MARCELINO, K. R. A.; SAUERESSIG, M. G. Peso ao nascer, ao desmame e mortalidade de bovinos de corte no cerrado. In: REUNIAO ANUAL DA SOCIEDADE BRASILEIRA DE ZOOTECNIA, 37., 2000, Vicosa, MG. Anais. Vicosa, MG: SBZ, 2000. 3 p.| Biblioteca(s): Embrapa Cerrados. |
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| 87. | | FIGUEIREDO, C. C. de; RAMOS, M. L. G.; McMANUS, C. M.; MENEZES, A. M. de. Mineralização de esterco de ovinos e sua influência na produção de alface. Horticultura Brasileira, Brasilia, DF, v. 30, n. 1, p. 175-179, jan./mar. 2012.| Biblioteca(s): Embrapa Hortaliças. |
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| 90. | | BORGES, A. M.; MORETTI, J. O. C.; McMANUS, C.; MARIANTE, A. da S. Produção de populações monossexo macho de tilápia-do-nilo da linhagem Chitralada. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 40, n. 2, p. 153-159, 2005.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia; Embrapa Unidades Centrais. |
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| 91. | | SILVA, E. C. da; PIOVEZAN, U.; MCMANUS, C. M.; CAETANO, A. R.; PAIVA, S. R. Estrutura genética do suíno Monteiro (Sus scrofa) em regiões do Pantanal, MS, Brasil. In: REUNIÃO ANUAL DA SOCIEDADE BRASILEIRA DE ZOOTECNIA, 49., Brasília, DF. A produção animal no mundo em transformação: Anais. Brasília: SBZ, 2012. 3p.| Biblioteca(s): Embrapa Pantanal. |
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| 92. | | SILVA, E. C. da; PIOVEZAN, U.; MCMANUS, C. M.; CAETANO, A. R.; PAIVA, S. R. Estrutura genética do suíno Monteiro (Sus scrofa) em regiões do Pantanal, MS, Brasil. In: REUNIÃO ANUAL DA SOCIEDADE BRASILEIRA DE ZOOTECNIA, 49., Brasília, DF. A produção animal no mundo em transformação: Anais. Brasília: SBZ, 2012. 3 p.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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| 93. | | SOARES FILHO, G.; McMANUS, C.; QUESADA, M. C.; BOFILL, M. I. R. Environmental factors which influence reproduction traits in Santa Inês sheep in the Federal District, Brazil. In: GLOBAL CONFERENCE ON CONSERVATION OF DOMESTIC ANIMAL GENETIC RESOURCES, 5., 2000, Brasília, DF. Proceedings... Brasília, DF: Embrapa Recursos Genéticos e Biotecnologia, 2000. 1 CD-ROM. (Embrapa Genetic Resources and Biotechnology, Document, 49).| Biblioteca(s): Embrapa Caprinos e Ovinos. |
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| 95. | | McMANUS, C.; SOARES FILHO, G.; MARIANTE, A. da S.; LOUVANDIN, H. Fatores que influenciam os parâmetros das curvas de lactação em cabras no Distrito Federal. Revista Brasileira de Zootecnia, Viçosa, MG, v. 32, n. 6, supl. 1, p. 1614-1623, 2003.| Biblioteca(s): Embrapa Caprinos e Ovinos. |
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| 96. | | LANDIM, A. V.; CARDOSO, M. T.; CASTANHEIRA, M.; FIORAVANTI, M. C.; LOUVANDINI, H.; McMANUS, C. Fatty acid profile of hair lambs and their crossbreds slaughtered at different weights. Tropical Animal Health and Production, v. 43, n. 8, p. 1561-1566, Dec. 2011.| Biblioteca(s): Embrapa Caprinos e Ovinos. |
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| 100. | | SILVA, E. C. da; PIOVEZAN, U.; MCMANUS, C. M.; CAETANO, A. R.; PAIVA, S. R. Diversidade genética de populações do suíno Monteiro (Sus scrofa) na região do Pantanal, MS, Brasil. In: REUNIÃO ANUAL DA SOCIEDADE BRASILEIRA DE ZOOTECNIA, 49., Brasília, DF. A produção animal no mundo em transformação: Anais. Brasília: SBZ, 2012. 3p.| Biblioteca(s): Embrapa Pantanal. |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Pecuária Sudeste. Para informações adicionais entre em contato com cppse.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Gado de Leite; Embrapa Pecuária Sudeste. |
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Data corrente: |
17/11/2022 |
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Data da última atualização: |
29/11/2022 |
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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: |
CONGIO, G. F. S.; BANNINK, A.; MAYORGA, O. L.; RODRIGUES, J. P. P.; BOUGOUIN, A.; KEBREAB, E.; CARVALHO, P. C. F.; BERCHIELLI, T. T.; MERCADANTE, M. E. Z.; VALADARES-FILHO, S. C.; BORGES, A. L. C. C.; BERNDT, A.; RODRIGUES, P. H. M.; KU-VERA, J. C.; MOLINA-BOTERO, I. C.; ARANGO, J.; REIS, R. A.; POSADA-OCHOA , S. L.; TOMICH, T. R.; CASTELÁN-ORTEGA, O. A.; MARCONDES, M. I.; GÓMEZ, C.; RIBEIRO-FILHO, H. M. N.; GERE, J. I.; ARIZA-NIETO, C.; GIRALDO, L. A.; GONDA, H.; CERÓN-CUCCHI, M. E.; HERNÁNDEZ, O.; RICCI, P.; HRISTOV, A. N. |
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Afiliação: |
GUILHERMO F. S. CONGIO, Escola Superior de Agricultura Luiz de Queiroz; ANDRÉ BANNINK, Wageningen University & Research; OLGA L. MAYORGA, Colombian Corporation for Agricultural Research; JOÃO P. P. RODRIGUES, Universidade Federal Rural do Rio de Janeiro; ADELINE BOUGOUIN, University of California; ERMIAS KEBREAB, University of California; PAULO C. F. CARVALHO, Universidade Federal do Rio de Janeiro; TELMA T. BERCHIELLI, Universidade Estadual Paulista; MARIA E. Z. MERCADANTE, Agência Paulista de Tecnologia do Agronegócio; SEBASTIÃO C. VALADARES-FILHO, Universidade Federal de Viçosa; ANA L. C. C. BORGES, Universidade Federal de Minas Gerais; ALEXANDRE BERNDT, CPPSE; PAULO H. M. RODRIGUES, Universidade de São Paulo; JUAN C. KU-VERA, University of Yucatan; ISABEL C. MOLINA-BOTERO, National Agrarian University La Molina; JACOBO ARANGO, International Center for Tropical Agriculture; RICARDO A. REIS, Universidade Estadual Paulista; SANDRA L. POSADA-OCHOA, University of Antioquia; THIERRY RIBEIRO TOMICH, CNPGL; OCTAVIO A. CASTELÁN-ORTEGA, Autonomous University of the State of Mexico; MARCOS I. MARCONDES, Washington State University; CARLOS GÓMEZ, National Agrarian University La Molina; HENRIQUE M. N. RIBEIRO-FILHO, Universidade do Estado de Santa Catarina; JOSÉ I. GERE, National Technological University; CLAUDIA ARIZA-NIETO, Colombian Corporation for Agricultural Research; LUIS A. GIRALDO, National University of Colombia; HORACIO GONDA, Swedish University of Agricultural Sciences; MARÍA E. CERÓN-CUCCHI, National Institute of Agricultural Technology; OLEGARIO HERNÁNDEZ, National Institute of Agricultural Technology; PATRICIA RICCI, National Institute of Agricultural Technology; ALEXANDER N. HRISTOV, The Pennsylvania State University. |
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Título: |
Improving the accuracy of beef cattle methane inventories in Latin America and Caribbean countries. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Science of the Total Environment, v. 856, 159128, 2023. |
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DOI: |
http://dx.doi.org/10.1016/j.scitotenv.2022.159128 |
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Idioma: |
Inglês |
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Conteúdo: |
On-farm methane (CH4) emissions need to be estimated accurately so that the mitigation effect of recommended prac-tices can be accounted for. In the present study prediction equations for enteric CH4 have been developed in lieu of expensive animal measurement approaches. Our objectives were to: (1) compile a dataset from individual beef cattle data for the Latin America and Caribbean (LAC) region; (2) determine main predictors of CH4 emission variables; (3) develop and cross-validate prediction models according to dietary forage content (DFC); and (4) compare the pre-dictive ability of these newly-developed models with extant equations reported in literature, including those currently used for CH4 inventories in LAC countries. After outlier's screening, 1100 beef cattle observations from 55 studies were kept in the final dataset (similar to 50 % of the original dataset). Mixed-effects models were fitted with a random effect of study. The whole dataset was split according to DFC into a subset for all-forage (DFC = 100 %), high-forage (94 % >= DFC >= 54 %), and low-forage (50 % >= DFC) diets. Feed intake and average daily gain (ADG) were the main pre-dictors of CH4 emission (g d-1), whereas this was feeding level [dry matter intake (DMI) as % of body weight] for CH4 yield (g kg-1 DMI). The newly-developed models were more accurate than IPCC Tier 2 equations for all subsets. Sim-ple and multiple regression models including ADG were accurate and a feasible option to predict CH4 emission when data on feed intake are not available. Methane yield was not well predicted by any extant equation in contrast to the newly-developed models. The present study delivered new models that may be alternatives for the IPCC Tier 2 equa-tions to improve CH4 prediction for beef cattle in inventories of LAC countries based either on more or less readily available data. MenosOn-farm methane (CH4) emissions need to be estimated accurately so that the mitigation effect of recommended prac-tices can be accounted for. In the present study prediction equations for enteric CH4 have been developed in lieu of expensive animal measurement approaches. Our objectives were to: (1) compile a dataset from individual beef cattle data for the Latin America and Caribbean (LAC) region; (2) determine main predictors of CH4 emission variables; (3) develop and cross-validate prediction models according to dietary forage content (DFC); and (4) compare the pre-dictive ability of these newly-developed models with extant equations reported in literature, including those currently used for CH4 inventories in LAC countries. After outlier's screening, 1100 beef cattle observations from 55 studies were kept in the final dataset (similar to 50 % of the original dataset). Mixed-effects models were fitted with a random effect of study. The whole dataset was split according to DFC into a subset for all-forage (DFC = 100 %), high-forage (94 % >= DFC >= 54 %), and low-forage (50 % >= DFC) diets. Feed intake and average daily gain (ADG) were the main pre-dictors of CH4 emission (g d-1), whereas this was feeding level [dry matter intake (DMI) as % of body weight] for CH4 yield (g kg-1 DMI). The newly-developed models were more accurate than IPCC Tier 2 equations for all subsets. Sim-ple and multiple regression models including ADG were accurate and a feasible option to predict CH4 ... Mostrar Tudo |
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Thesagro: |
Bovino; Efeito Estufa; Gado de Corte; Gás; Metano; Regressão Linear. |
|
Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal |
|
Marc: |
LEADER 03486naa a2200565 a 4500
001 2148394
005 2022-11-29
008 2023 bl uuuu u00u1 u #d
024 7 $ahttp://dx.doi.org/10.1016/j.scitotenv.2022.159128$2DOI
100 1 $aCONGIO, G. F. S.
245 $aImproving the accuracy of beef cattle methane inventories in Latin America and Caribbean countries.$h[electronic resource]
260 $c2023
520 $aOn-farm methane (CH4) emissions need to be estimated accurately so that the mitigation effect of recommended prac-tices can be accounted for. In the present study prediction equations for enteric CH4 have been developed in lieu of expensive animal measurement approaches. Our objectives were to: (1) compile a dataset from individual beef cattle data for the Latin America and Caribbean (LAC) region; (2) determine main predictors of CH4 emission variables; (3) develop and cross-validate prediction models according to dietary forage content (DFC); and (4) compare the pre-dictive ability of these newly-developed models with extant equations reported in literature, including those currently used for CH4 inventories in LAC countries. After outlier's screening, 1100 beef cattle observations from 55 studies were kept in the final dataset (similar to 50 % of the original dataset). Mixed-effects models were fitted with a random effect of study. The whole dataset was split according to DFC into a subset for all-forage (DFC = 100 %), high-forage (94 % >= DFC >= 54 %), and low-forage (50 % >= DFC) diets. Feed intake and average daily gain (ADG) were the main pre-dictors of CH4 emission (g d-1), whereas this was feeding level [dry matter intake (DMI) as % of body weight] for CH4 yield (g kg-1 DMI). The newly-developed models were more accurate than IPCC Tier 2 equations for all subsets. Sim-ple and multiple regression models including ADG were accurate and a feasible option to predict CH4 emission when data on feed intake are not available. Methane yield was not well predicted by any extant equation in contrast to the newly-developed models. The present study delivered new models that may be alternatives for the IPCC Tier 2 equa-tions to improve CH4 prediction for beef cattle in inventories of LAC countries based either on more or less readily available data.
650 $aBovino
650 $aEfeito Estufa
650 $aGado de Corte
650 $aGás
650 $aMetano
650 $aRegressão Linear
700 1 $aBANNINK, A.
700 1 $aMAYORGA, O. L.
700 1 $aRODRIGUES, J. P. P.
700 1 $aBOUGOUIN, A.
700 1 $aKEBREAB, E.
700 1 $aCARVALHO, P. C. F.
700 1 $aBERCHIELLI, T. T.
700 1 $aMERCADANTE, M. E. Z.
700 1 $aVALADARES-FILHO, S. C.
700 1 $aBORGES, A. L. C. C.
700 1 $aBERNDT, A.
700 1 $aRODRIGUES, P. H. M.
700 1 $aKU-VERA, J. C.
700 1 $aMOLINA-BOTERO, I. C.
700 1 $aARANGO, J.
700 1 $aREIS, R. A.
700 1 $aPOSADA-OCHOA , S. L.
700 1 $aTOMICH, T. R.
700 1 $aCASTELÁN-ORTEGA, O. A.
700 1 $aMARCONDES, M. I.
700 1 $aGÓMEZ, C.
700 1 $aRIBEIRO-FILHO, H. M. N.
700 1 $aGERE, J. I.
700 1 $aARIZA-NIETO, C.
700 1 $aGIRALDO, L. A.
700 1 $aGONDA, H.
700 1 $aCERÓN-CUCCHI, M. E.
700 1 $aHERNÁNDEZ, O.
700 1 $aRICCI, P.
700 1 $aHRISTOV, A. N.
773 $tScience of the Total Environment$gv. 856, 159128, 2023.
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Embrapa Pecuária Sudeste (CPPSE) |
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