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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. |
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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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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. |
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Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal |
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Marc: |
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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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Registro original: |
Embrapa Pecuária Sudeste (CPPSE) |
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Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
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Registro Completo
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Biblioteca(s): |
Embrapa Agroindústria Tropical; Embrapa Semiárido; Embrapa Solos; Embrapa Suínos e Aves; Embrapa Unidades Centrais. |
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Data corrente: |
26/03/2021 |
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Data da última atualização: |
08/12/2021 |
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Tipo da produção científica: |
Autoria/Organização/Edição de Livros |
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Autoria: |
SILVA, M. S. L. da; MATTHIENSEN, A.; BRITO, L. T. de L.; LIMA, J. E. F. W.; CARVALHO, C. J. R. de (ed.). |
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Afiliação: |
MARIA SONIA LOPES DA SILVA, CNPS; ALEXANDRE MATTHIENSEN, CNPSA; LUIZA TEIXEIRA DE LIMA BRITO, CPATSA; JORGE ENOCH FURQUIM WERNECK LIMA, CPAC; CLAUDIO JOSE REIS DE CARVALHO, CNPAT. |
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Título: |
Clean water and sanitation: contributions of Embrapa. |
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Título original: |
Água e saneamento: contribuições da Embrapa. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Brasília, DF : Embrapa, 2020. |
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Páginas: |
101 p. |
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Descrição Física: |
PDF : il. color. |
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Série: |
(Sustainable development goal, 6). |
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ISBN: |
978-65-86056-23-5 |
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Idioma: |
Inglês |
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Notas: |
Translated by Paulo de Holanda Morais. |
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Conteúdo: |
In this book, Embrapa exposes its interfaces and synergies with SDG 6 (ensure the availability and sustainable management of water and sanitation for all) and its respective targets, showing the alignment of this SDG with 3 of its 5 impact axes and with 4 of the 12 strategic objectives, expressed in its VI Plano Diretor (VI Master Plan). |
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Palavras-Chave: |
Conservação do ecosistema; ODS 6. |
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Thesagro: |
Abastecimento de Água; Desenvolvimento Sustentável; Políticas Públicas; Poluição; Produção Agrícola; Produção Animal; Qualidade da Água; Recurso Hídrico; Saneamento Rural. |
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Thesaurus NAL: |
Public policy; Sustainable development; Water resources. |
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Categoria do assunto: |
--
B Sociologia Rural
P Recursos Naturais, Ciências Ambientais e da Terra |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/222188/1/SDG-6.pdf
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/222270/1/Clean-water-and-sanitation-contributions-of-Embrapa.pdf
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Marc: |
LEADER 01524nam a2200385 a 4500
001 2130908
005 2021-12-08
008 2020 bl uuuu 00u1 u #d
020 $a978-65-86056-23-5
100 1 $aSILVA, M. S. L. da
240 $aÁgua e saneamento: contribuições da Embrapa.
245 $aClean water and sanitation$bcontributions of Embrapa.$h[electronic resource]
260 $aBrasília, DF : Embrapa$c2020
300 $a101 p.$cPDF : il. color.
490 $a(Sustainable development goal, 6).
500 $aTranslated by Paulo de Holanda Morais.
520 $aIn this book, Embrapa exposes its interfaces and synergies with SDG 6 (ensure the availability and sustainable management of water and sanitation for all) and its respective targets, showing the alignment of this SDG with 3 of its 5 impact axes and with 4 of the 12 strategic objectives, expressed in its VI Plano Diretor (VI Master Plan).
650 $aPublic policy
650 $aSustainable development
650 $aWater resources
650 $aAbastecimento de Água
650 $aDesenvolvimento Sustentável
650 $aPolíticas Públicas
650 $aPoluição
650 $aProdução Agrícola
650 $aProdução Animal
650 $aQualidade da Água
650 $aRecurso Hídrico
650 $aSaneamento Rural
653 $aConservação do ecosistema
653 $aODS 6
700 1 $aMATTHIENSEN, A.
700 1 $aBRITO, L. T. de L.
700 1 $aLIMA, J. E. F. W.
700 1 $aCARVALHO, C. J. R. de
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Embrapa Unidades Centrais (AI-SEDE) |
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