A meta-analysis establishes bromoform dose and forage-based models to evaluate the antimethanogenic effects of Asparagopsis spp. feed additive

Asparagopsis spp., two red macroalgae, have been widely studied as antimethanogenic feed additives due to their production of bromoform (CHBr3) and other bioactive compounds, reducing methane (CH4) emissions in ruminants by up to 99%. As their integration into livestock systems expands, predictive models are needed to estimate CH4 reduction as an alternative to resource-intensive in situ methods. Existing models often omit the CHBr3 concentration or lack consistent dose-response data across diets and animal types. This meta-analysis aims to address these gaps by incorporating individual animal-level bovine data to examine the relationships between CHBr3 dose (mg/kg dry matter intake DMI) and enteric CH4 yield (g/kg DMI), stratifying analyses by animal type, identifying a CHBr3 threshold associated with diminishing mitigation returns, and assessing the influence of dietary composition and CH4 detection technology on model outcomes. A CHBr3 threshold of 49.81 mg/kg DMI was identified as a point of diminishing returns, beyond which reductions plateaued and risks of overestimation increased. Significant associations were revealed between CHBr3 dose, crude protein (CP), neutral detergent fiber (NDF), and CH4 yield reduction. Significant differences were observed by animal type (p = 0.022), prompting eight stratified linear mixed-effects models, and CH4 detection technology (p < 0.001), highlighting the need for improved accuracy. The models estimate that in beef cattle, an average CHBr3 dose of 14.95 mg/kg DMI reduces the CH4 yield by 34.8%, with a maximum dose of 35.70 mg/kg resulting in an 83.6% reduction. In dairy cows, an average dose of 11.25 mg/kg DMI led to a 16.9% reduction, whereas the maximum dose of 27.40 mg/kg resulted in a 43.1% reduction. Including CP and NDF marginally improved model performance, particularly for beef, with CP also improving predictions in dairy cows, reducing reliance on in vivo feed composition trials. Robust predictive models accounting for CHBr3 concentration, dietary covariates, and animal type provide valuable tools to maximize the impact of Asparagopsis while awaiting advances in CH4 detection technology. Identifying a dose threshold at diminishing returns is crucial for animal safety and efficacy. Future research should expand dairy datasets and assess dietary fat as a predictor variable. Not applicable.