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Prediction of enteric methane production, yield and intensity in dairy cattle using an intercontinental database


Mutian Niu

Ermias Kebreab

Alexander N. Hristov

Joonpyo Oh

Claudia Arndt


Ali R. Bayat


Tommy Boland

David Casper

Les A. Crompton

Jan Dijkstra

Maguy A.

Md Najmul Haque

Anne L. F. Hellwing

Pekka Huhtanen

Michael Kreuzer

Bjoern Kuhla

Peter Lund



Shelby C. McClelland

Mark McGee

Peter J. Moate

Stefan Muetzel



Nico Peiren

Christopher K. Reynolds

Angela Schwarm

Kevin J. Shingfield

Tonje M. Storlien

Martin R. Weisbjerg

David R.

Zhongtang Yu


Enteric methane (CH?) production from cattle contributes to global greenhouse gas emissions. Measurement of enteric CH? is complex, expensive and impractical at large scales; therefore, models are commonly used to predict CH? 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 CH? production from individual lactating dairy cattle; (2) determine the availability of key variables for predicting enteric CH? production (g/d 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 CH? prediction accuracy. The intercontinental database covered Europe (EU), the US (US), Chile (CL), Australia (AU), and New Zealand (NZ). 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, 14.4, and 19.8% for intercontinental, EU, and US regions, respectively. Less complex models requiring only DMI had predictive ability comparable to complex models. Enteric CH? 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 CH? emission conversion factors for specific regions are required to improve CH? production estimates in national inventories. In conclusion, information on DMI is required for good prediction, and other factors such as dietary NDF concentration, improve the prediction. For enteric CH? yield and intensity prediction, information on milk yield and composition is required for better estimation.


Niu, M., Kebreab, E., Hristov, A. N., Oh, J., Arndt, C., Bannink, A., …Yu, Z. (2018). Prediction of enteric methane production, yield and intensity in dairy cattle using an intercontinental database. Global Change Biology, 24(8),

Journal Article Type Article
Acceptance Date Jan 29, 2018
Online Publication Date Mar 8, 2018
Publication Date Aug 30, 2018
Deposit Date Feb 15, 2018
Publicly Available Date Mar 8, 2018
Journal Global Change Biology
Print ISSN 1354-1013
Electronic ISSN 1365-2486
Publisher Wiley
Peer Reviewed Peer Reviewed
Volume 24
Issue 8
Keywords Dairy cows; Enteric methane emissions; Prediction models; Dry matter intake; Methane yield; Methane intensity
Public URL
Publisher URL


Niu_et_al-2018-Global_Change_Biology.pdf (1.2 Mb)

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