This model integrates factors affecting VFA profiles and methane emissions in dairy cattle, suggesting improved management strategies.
ABSTRACT Adequate quantification of enteric methane (CH₄) emissions from dairy cattle is essential for mitigating their contribution to global warming. The capacity of mechanistic models to explain variability of CH₄ emissions better than empirical models depends on their ability to quantify the volatile fatty acid (VFA) profile and associated net hydrogen (H₂) production. Stoichiometry of VFA production has previously been modeled considering either the type of nutrient being fermented, H₂ and redox cofactors (RC), or rumen environmental conditions (in particular pH), but not in an integrated manner within the same mathematical framework. Our aim was to represent rumen VFA production based on nutrient type, RC status, and rumen pH, enabling the prediction of the VFA profile while simultaneously predicting methanogenic activity and enteric CH₄ emissions. The model represents the daily production of acetate, propionate, butyrate, and other minor VFA, resulting from the fermentation of 5 nutrient types: soluble carbohydrates, starch, cellulose, hemicellulose, and protein. Reduction and oxidation of RC (NADH and ferredoxin) were represented based on the simulated VFA and H₂ production. Feedback mechanisms of RC and rumen pH were incorporated in the stoichiometric coefficients of VFA production. The model includes pools of H₂ and methanogens, and methanogenesis was represented using a Michaelis-Menten equation dependent on H₂ concentration. The model was calibrated using data on VFA molar proportions (n = 219) and CH₄ emissions (n = 46), and was evaluated using an independent data set (n = 72). Fermentation of cellulose and hemicellulose produced more acetate and less propionate than soluble carbohydrates and starch. Increasing the reduced state of RC increased butyrate production during fermentation of soluble carbohydrates, increased both propionate and other minor VFA production during fermentation of starch, and inhibited acetate production with both substrates. Stoichiometric coefficients in fermentation of hemicellulose, cellulose and protein were not influenced by RC state. During fermentation of starch, low rumen pH decreased acetate formation and increased propionate production, whereas during fermentation of soluble carbohydrates, low pH inhibited both acetate and butyrate formation and increased propionate formation. The simulated profile of VFA and the dynamics of H₂ production controlled the rate of methanogenesis. The model explained variability in the VFA molar proportions and CH₄ production of independent data, with an RMSE of 5.5% and 12.0% of the observed mean acetate and propionate molar proportions, respectively, and an RMSE of 12.6% and 12.1% of the observed mean CH₄ production (g/d) and yield (g/kg DMI), respectively. The model advances previous approaches by mechanistically linking fermentation patterns with emissions of CH₄ and H₂. This integration of causal factors controlling VFA production enables to explain variability in VFA profiles and CH₄ emissions under diverse feeding conditions, improving understanding of rumen fermentation and supporting tools to quantify and mitigate enteric CH₄ emissions in dairy systems.
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Vivares et al. (2026) studied this question.
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