Quantifying H2 emissions under different nutritional mitigation strategies and its impact on improving the prediction of enteric methane emissions of ruminants
Résumé
Stoichiometric models that predict methane (CH4) production of ruminants assume that the amount of hydrogen gas (H2) produced during fermentation in the rumen equals the amount of H2 consumed by electron sinks in the rumen and thus that H2 should not be emitted into the environment. However, some studies have demonstrated that H2 emissions occur under practical conditions. In addition, the H2 emissions increase when nutritional mitigation strategies are used. Hence, this study hypothesized that considering H2 emission would improve the prediction of enteric CH4 emission, especially when using mitigation strategies that induce high variation in the H2 emission. The objective of this study was to develop and evaluate the performance of CH4 emission prediction models using H2 emission as an explanatory variable. A database of CH4 and H2 emission (mean treatment data) from ruminants (dairy cattle, growing cattle and sheeps) was built to develop mixed-effects models at three levels of complexity: level 1 -H2 production/yield, DMI, or both; level 2 -level 1 explanatory variables plus chemical composition of the diet (i.e. CP, EE, NDF, OM, or PCO); and level 3 -level 2 explanatory variables plus animal metabolic weight (BW0.75, kg). When all animal categories were grouped, including H2 production improved the performance of CH4 production prediction only in level 1 models for the electron-receptor mitigation strategy, reducing the root mean square of prediction error (RMSPE) by 18 %. For dairy cattle and sheep, dry matter intake was not a significant explanatory variable in level 1 or 2 models. For growing beef cattle, for all mitigation strategies together and the inhibitor-mitigation strategy alone, including H2 production reduced RMSPE by 13 % and 27 %, respectively. Overall, H2 production was included in 60 % of level 1 models and 100 % of level 2 and 3 models, which best predicted CH4 production. Thus, including H2 emission does improve prediction of enteric CH4 emission, especially when mitigation strategies that induce variation in the H2 are used.