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Enteric methane (CH4) emissions from sheep contribute to global greenhouse gas emissions from livestock. However, as already available for dairy and beef cattle, empirical models are needed to predict CH4 emissions from sheep for accounting purposes. The objectives of this study were to:1) collate an intercontinental database of enteric CH4 emissions from individual sheep; 2) identify the key variables for predicting enteric sheep CH4 absolute production (g/d per animal) and yield [g/kg dry matter intake (DMI)] and their respective relationships; and 3) develop and cross-validate global equations as well as the potential need for age-, diet-, or climatic region-specific equations. The refined intercontinental database included 2,135 individual animal data from 13 countries. Linear CH4 prediction models were developed by incrementally adding variables. A universal CH4 production equation using only DMI led to a root mean square prediction error (RMSPE, % of observed mean) of 25.4% and an RMSPE-standard deviation ratio (RSR) of 0.69. Universal equations that, in addition to DMI, also included body weight (DMI + BW), and organic matter digestibility (DMI + OMD + BW) improved the prediction performance further (RSR, 0.62 and 0.60), whereas diet composition variables had negligible effects. These universal equations had lower prediction error than the extant IPCC 2019 equations. Developing age-specific models for adult sheep (>1-year-old) including DMI alone (RSR = 0.66) or in combination with rumen propionate molar proportion (for research of more refined purposes) substantially improved prediction performance (RSR = 0.57) on a smaller dataset. On the contrary, for young sheep (

BELANCHE, A. , HRISTOV, A. , VAN LINGEN, H. , DENMAN, S. E. , KEBREAB, E. , SCHWARM, A. , KREUZER, M. , NIU, M. , EUGÈNE, M. , NIDERKORN, V. , MARTIN, C. , ARCHIMÈDE, H. , MCGEE, M. , REYNOLDS, C. K. , CROMPTON, L. A. , BAYAT, A. R. , YU, Z. , BANNINK, A. , DIJKSTRA, J. , CHAVES, A. V. , CLARK, H. , MUETZEL, S. , LIND, V. , MOORBY, J. M. , ROOKE, J. A. , AUBRY, A. , ANTEZANA, W. , WANG, M. , HEGARTY, R. , HUTTON O. V. , HILL, J. , VERCOE, P. E. , SAVIAN, J.V. , ABDALLA, A. L. , SOLTAN, Y. A. , GOMES MONTEIRO, A. L. , KU-VERA, J. C. , JAURENA, G. , GÓMEZ-BRAVO, C. A. , MAYORGA, O. L. , CONGIO, G. F. S. , YÁÑEZ-RUIZ, D. R.
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Journal of Cleaner Production, 15 January 2023, Volume 384, 135523. OPEN ACCESS. doi:https://doi.org/10.1016/j.jclepro.2022.135523
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