|
|
| 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.. |
| 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.... |
| Tipo: Artigo de periódico |
Palavras-chave: Empirical modeling; Enteric methane; GHG inventory; Prediction equations; Diet; Linear models. |
| Ano: 2022 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1146525 |
| |
