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Registro Completo |
Biblioteca(s): |
Embrapa Gado de Leite; Embrapa Pecuária Sudeste. |
Data corrente: |
16/09/2022 |
Data da última atualização: |
16/09/2022 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
CONGIO, G. F. S.; BANNINK, A.; MAYORGA, O. L.; RODRIGUES, J. P. P.; BOUGOUIN, A.; KEBREAD, E.; SILVA, R. R.; MAURÍCIO, R. M.; SILVA, S. C. DA; OLIVEIRA, P. P. A.; MUÑOZ, C.; PEREIRA, L. G. R.; GÓMEZ, C.; ARIZA-NIETO, C.; RIBEIRO-FILHO, H. M. N.; CASTELÁN-ORTEGA, O. A.; ROSERO-NOGUERA, J. R.; TIERI, M. P.; RODRIGUES, P. H. M.; MARCONDES, M. I.; ASTIGARRAGA, L.; ABARCA, S.; HRISTOV, A. N. |
Afiliação: |
GUILHERMO F. S. CONGIO, UNIVERSIDADE DE SÃO PAULO; ANDRÉ BANNINK, WAGENINGEN UNIVERSITY & RESEARCH; OLGA L. MAYORGA, COLOMBIAN CORPORATION FOR AGRICULTURAL RESEARCH; JOÃO P. P. RODRIGUES, UNIVERSIDADE FEDERAL DO SUL E SUDESTE DO PARÁ; ADELINE BOUGOUIN, UNIVERSITY OF CALIFORNIA; ERMIAS KEBREAD, UNIVERSITY OF CALIFORNIA; RICARDO R. SILVA, UNIVERSIDADE FEDERAL DE MINAS GERAIS; ROGÉRIO M. MAURÍCIO, UNIVERSIDADE FEDERAL DE SÃO JOÃO DEL REI; SILA C. DA SILVA, UNIVERSIDADE DE SÃO PAULO; PATRICIA PERONDI ANCHAO OLIVEIRA, CPPSE; CAMILA MUÑOZ, INSTITUTO DE INVESTIGACIONES AGROPECUARIAS; LUIZ GUSTAVO RIBEIRO PEREIRA, CNPGL; CARLOS GÓMEZ, NATIONAL AGRARIAN UNIVERSITY LA MOLINA; CLAUDIA ARIZA-NIETO, COLOMBIAN CORPORATION FOR AGRICULTURAL RESEARCH; HENRIQUE M. N. RIBEIRO-FILHO, UNIVERSIDADE ESTADUAL DE SANTA CATARINA; OCTAVIO A. CASTELÁN-ORTEGA, AUTONOMOUS UNIVERSITY OF THE STATE OF MEXICO; JAIME R. ROSERO-NOGUERA, UNIVERSITY OF ANTIOQUIA; MARIA P. TIERI, NATIONAL INSTITUTE OF AGRICULTURAL TECHNOLOGY; PAULO H. M. RODRIGUES, UNIVERSIDADE DE SÃO PAULO; MARCOS I. MARCONDES, WASHINGTON STATE UNIVERSITY; LAURA ASTIGARRAGA, UNIVERSITY OF THE REPUBLIC OF URUGUAY; SERGIO ABARCA, NATIONAL INSTITUTE OF INNOVATION AND AGRICULTURAL TECHNOLOGY TRANSFER; ALEXANDER N. HRISTOV, THE PENNSYLVANIA STATE UNIVERSITY. |
Título: |
Prediction of enteric methane production and yield in dairy cattle using a Latin America and Caribbean database. |
Ano de publicação: |
2022 |
Fonte/Imprenta: |
Science of the Total Environment, v. 825, n. 153982, p. 1-11, 2022. |
ISBN: |
0048-9697 |
DOI: |
https://doi.org/10.1016/j.scitotenv.2022.153982 |
Idioma: |
Inglês |
Conteúdo: |
ABSTRACT: Successful mitigation efforts entail accurate estimation of on-farm emission and prediction models can be an alternative to current laborious and costly in vivo CH4 measurement techniques. This study aimed to: (1) collate a database of individual dairy cattle CH4 emission data from studies conducted in the Latin America and Caribbean (LAC) region; (2) identify key variables for predicting CH4 production (g d−1) and yield [g kg−1 of dry matter intake (DMI)]; (3) develop and cross-validate these newly-developed models; and (4) compare models' predictive ability with equations currently used to support national greenhouse gas (GHG) inventories. A total of 42 studies including 1327 individual dairy cattle records were collated. After removing outliers, the final database retained 34 studies and 610 animal records. Production and yield of CH4 were predicted by fitting mixed-effects models with a random effect of study. Evaluation of developed models and fourteen extant equations was assessed on all-data, confined, and grazing cows subsets. Feed intake was the most important predictor of CH4 production. Our best-developed CH4 production models outperformed Tier 2 equations from the Intergovernmental Panel on Climate Change (IPCC) in the all-data and grazing subsets, whereas they had similar performance for confined animals. Developed CH4 production models that include milk yield can be accurate and useful when feed intake is missing. Some extant equations had similar predictive performance to our best-developed models and can be an option for predicting CH4 production from LAC dairy cows. Extant equations were not accurate in predicting CH4 yield. The use of the newly-developed models rather than extant equations based on energy conversion factors, as applied by the IPCC, can substantially improve the accuracy of GHG inventories in LAC countries. MenosABSTRACT: Successful mitigation efforts entail accurate estimation of on-farm emission and prediction models can be an alternative to current laborious and costly in vivo CH4 measurement techniques. This study aimed to: (1) collate a database of individual dairy cattle CH4 emission data from studies conducted in the Latin America and Caribbean (LAC) region; (2) identify key variables for predicting CH4 production (g d−1) and yield [g kg−1 of dry matter intake (DMI)]; (3) develop and cross-validate these newly-developed models; and (4) compare models' predictive ability with equations currently used to support national greenhouse gas (GHG) inventories. A total of 42 studies including 1327 individual dairy cattle records were collated. After removing outliers, the final database retained 34 studies and 610 animal records. Production and yield of CH4 were predicted by fitting mixed-effects models with a random effect of study. Evaluation of developed models and fourteen extant equations was assessed on all-data, confined, and grazing cows subsets. Feed intake was the most important predictor of CH4 production. Our best-developed CH4 production models outperformed Tier 2 equations from the Intergovernmental Panel on Climate Change (IPCC) in the all-data and grazing subsets, whereas they had similar performance for confined animals. Developed CH4 production models that include milk yield can be accurate and useful when feed intake is missing. Some extant equations had... Mostrar Tudo |
Palavras-Chave: |
Empirical modeling; Enteric methane; Equação de previsão; GHG inventory; Inventário de GEE; Metano entérico; Modelagem empírica; Modelo linear; Prediction equations. |
Thesagro: |
Dieta; Gado Leiteiro; Metano; Produção; Rendimento. |
Thesaurus Nal: |
Diet; Linear models. |
Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal P Recursos Naturais, Ciências Ambientais e da Terra |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1146525/1/PredictionOfEntericMethaneProductionAndYieldInDairyCattleUsingALatinAmericaAndCaribbeanDatabase.pdf
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Marc: |
LEADER 03612naa a2200601 a 4500 001 2146525 005 2022-09-16 008 2022 bl uuuu u00u1 u #d 022 $a0048-9697 024 7 $ahttps://doi.org/10.1016/j.scitotenv.2022.153982$2DOI 100 1 $aCONGIO, G. F. S. 245 $aPrediction of enteric methane production and yield in dairy cattle using a Latin America and Caribbean database.$h[electronic resource] 260 $c2022 520 $aABSTRACT: Successful mitigation efforts entail accurate estimation of on-farm emission and prediction models can be an alternative to current laborious and costly in vivo CH4 measurement techniques. This study aimed to: (1) collate a database of individual dairy cattle CH4 emission data from studies conducted in the Latin America and Caribbean (LAC) region; (2) identify key variables for predicting CH4 production (g d−1) and yield [g kg−1 of dry matter intake (DMI)]; (3) develop and cross-validate these newly-developed models; and (4) compare models' predictive ability with equations currently used to support national greenhouse gas (GHG) inventories. A total of 42 studies including 1327 individual dairy cattle records were collated. After removing outliers, the final database retained 34 studies and 610 animal records. Production and yield of CH4 were predicted by fitting mixed-effects models with a random effect of study. Evaluation of developed models and fourteen extant equations was assessed on all-data, confined, and grazing cows subsets. Feed intake was the most important predictor of CH4 production. Our best-developed CH4 production models outperformed Tier 2 equations from the Intergovernmental Panel on Climate Change (IPCC) in the all-data and grazing subsets, whereas they had similar performance for confined animals. Developed CH4 production models that include milk yield can be accurate and useful when feed intake is missing. Some extant equations had similar predictive performance to our best-developed models and can be an option for predicting CH4 production from LAC dairy cows. Extant equations were not accurate in predicting CH4 yield. The use of the newly-developed models rather than extant equations based on energy conversion factors, as applied by the IPCC, can substantially improve the accuracy of GHG inventories in LAC countries. 650 $aDiet 650 $aLinear models 650 $aDieta 650 $aGado Leiteiro 650 $aMetano 650 $aProdução 650 $aRendimento 653 $aEmpirical modeling 653 $aEnteric methane 653 $aEquação de previsão 653 $aGHG inventory 653 $aInventário de GEE 653 $aMetano entérico 653 $aModelagem empírica 653 $aModelo linear 653 $aPrediction equations 700 1 $aBANNINK, A. 700 1 $aMAYORGA, O. L. 700 1 $aRODRIGUES, J. P. P. 700 1 $aBOUGOUIN, A. 700 1 $aKEBREAD, E. 700 1 $aSILVA, R. R. 700 1 $aMAURÍCIO, R. M. 700 1 $aSILVA, S. C. DA 700 1 $aOLIVEIRA, P. P. A. 700 1 $aMUÑOZ, C. 700 1 $aPEREIRA, L. G. R. 700 1 $aGÓMEZ, C. 700 1 $aARIZA-NIETO, C. 700 1 $aRIBEIRO-FILHO, H. M. N. 700 1 $aCASTELÁN-ORTEGA, O. A. 700 1 $aROSERO-NOGUERA, J. R. 700 1 $aTIERI, M. P. 700 1 $aRODRIGUES, P. H. M. 700 1 $aMARCONDES, M. I. 700 1 $aASTIGARRAGA, L. 700 1 $aABARCA, S. 700 1 $aHRISTOV, A. N. 773 $tScience of the Total Environment$gv. 825, n. 153982, p. 1-11, 2022.
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Registro original: |
Embrapa Pecuária Sudeste (CPPSE) |
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Registro Completo
Biblioteca(s): |
Embrapa Hortaliças. |
Data corrente: |
03/05/2000 |
Data da última atualização: |
04/12/2002 |
Autoria: |
MAKISHIMA, N. |
Afiliação: |
Embrapa Hortaliças, Brasília, DF. |
Título: |
Cultivo do aipo: Apium graveolens L. |
Ano de publicação: |
1987 |
Fonte/Imprenta: |
Hortinforme, Brasília, DF, n. 2, p. 10, jan./mar. 1987. |
Idioma: |
Português |
Conteúdo: |
Botânica, Cultivares e épocas de plantio; Clima e solo; Calagem e adubação; Plantio; Tratos culturais e fitossanitários; Colheita. |
Palavras-Chave: |
Aipum graveolens; Control; Controle; Diseases; Fertilization; Harvest; Pest insects; Salsão. |
Thesagro: |
Adubação; Aipo; Apium Graveolens; Botânica; Calagem; Clima; Colheita; Comercialização; Consumo; Doença; Época de Plantio; Inseto; Praga; Sistema de Produção; Solo. |
Thesaurus NAL: |
botany; celery; climate; cropping systems; farming systems; liming; planting date; soil. |
Categoria do assunto: |
-- |
Marc: |
LEADER 01272naa a2200493 a 4500 001 1772653 005 2002-12-04 008 1987 bl uuuu u00u1 u #d 100 1 $aMAKISHIMA, N. 245 $aCultivo do aipo$bApium graveolens L. 260 $c1987 520 $aBotânica, Cultivares e épocas de plantio; Clima e solo; Calagem e adubação; Plantio; Tratos culturais e fitossanitários; Colheita. 650 $abotany 650 $acelery 650 $aclimate 650 $acropping systems 650 $afarming systems 650 $aliming 650 $aplanting date 650 $asoil 650 $aAdubação 650 $aAipo 650 $aApium Graveolens 650 $aBotânica 650 $aCalagem 650 $aClima 650 $aColheita 650 $aComercialização 650 $aConsumo 650 $aDoença 650 $aÉpoca de Plantio 650 $aInseto 650 $aPraga 650 $aSistema de Produção 650 $aSolo 653 $aAipum graveolens 653 $aControl 653 $aControle 653 $aDiseases 653 $aFertilization 653 $aHarvest 653 $aPest insects 653 $aSalsão 773 $tHortinforme, Brasília, DF$gn. 2, p. 10, jan./mar. 1987.
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