Prediction of enteric methane production, yield, and intensity in dairy cattle using an intercontinental database.
Enteric methane (CH4 ) production from cattle contributes to global greenhouse gas emissions. Measurement of enteric CH4 is complex, expensive, and impractical at large scales; therefore, models are commonly used to predict CH4 production. However, building robust prediction models requires extensive data from animals under different management systems worldwide. The objectives of this study were to (1) collate a global database of enteric CH4 production from individual lactating dairy cattle; (2) determine the availability of key variables for predicting enteric CH4 production (g/day per cow), yield [g/kg dry matter intake (DMI)], and intensity (g/kg energy corrected milk) and their respective relationships; (3) develop intercontinental and regional models and cross-validate their performance; and (4) assess the trade-off between availability of on-farm inputs and CH4 prediction accuracy. The intercontinental database covered Europe (EU), the United States (US), and Australia (AU). A sequential approach was taken by incrementally adding key variables to develop models with increasing complexity. Methane emissions were predicted by fitting linear mixed models. Within model categories, an intercontinental model with the most available independent variables performed best with root mean square prediction error (RMSPE) as a percentage of mean observed value of 16.6%, 14.7%, and 19.8% for intercontinental, EU, and United States regions, respectively. Less complex models requiring only DMI had predictive ability comparable to complex models. Enteric CH4 production, yield, and intensity prediction models developed on an intercontinental basis had similar performance across regions, however, intercepts and slopes were different with implications for prediction. Revised CH4 emission conversion factors for specific regions are required to improve CH4 production estimates in national inventories. In conclusion, information on DMI is required for good prediction, and other factors such as dietary neutral detergent fiber (NDF) concentration, improve the prediction. For enteric CH4 yield and intensity prediction, information on milk yield and composition is required for better estimation.
['Niu|Mutian|M|', 'Kebreab|Ermias|E|0000-0002-0833-1352', 'Hristov|Alexander N|AN|', 'Oh|Joonpyo|J|', 'Arndt|Claudia|C|', 'Bannink|André|A|', 'Bayat|Ali R|AR|', 'Brito|André F|AF|', 'Boland|Tommy|T|', 'Casper|David|D|', 'Crompton|Les A|LA|', 'Dijkstra|Jan|J|', 'Eugène|Maguy A|MA|', 'Garnsworthy|Phil C|PC|', 'Haque|Md Najmul|MN|', 'Hellwing|Anne L F|ALF|', 'Huhtanen|Pekka|P|', 'Kreuzer|Michael|M|', 'Kuhla|Bjoern|B|', 'Lund|Peter|P|', 'Madsen|Jørgen|J|', 'Martin|Cécile|C|', 'McClelland|Shelby C|SC|', 'McGee|Mark|M|', 'Moate|Peter J|PJ|', 'Muetzel|Stefan|S|', 'Muñoz|Camila|C|', "O'Kiely|Padraig|P|", 'Peiren|Nico|N|', 'Reynolds|Christopher K|CK|', 'Schwarm|Angela|A|', 'Shingfield|Kevin J|KJ|', 'Storlien|Tonje M|TM|', 'Weisbjerg|Martin R|MR|', 'Yáñez-Ruiz|David R|DR|', 'Yu|Zhongtang|Z|']
D000383:Agriculture D000818:Animals D001315:Australia D002417:Cattle D016208:Databases, Factual D004435:Eating D005060:Europe D005062:European Union D005260:Female D007774:Lactation D008697:Methane D008892:Milk D008962:Models, Theoretical D014481:United States
prediction models dry matter intake dairy cows enteric methane emissions methane intensity methane yield