This study aimed to expand the knowledge about the activity and mode of action of CHI on methanogenesis and rumen microbial populations in vivo. A total of 16 lactating dairy cows were distributed in two groups, one of them receiving 135 mg CHI/kg body weight daily. The effect on productive performance, milk composition, fermentation efficiency, methane emissions, microbial protein synthesis, and ruminal microbial communities was determined. Supplementation with CHI did not affect rumen microbial diversity but increased the relative abundance (RA) of the bacteria Anaeroplasma and decreased those of rumen ciliates and protozoa resulting in a shift towards a lower acetic to propionic ratio. However, no effect on milk yield or methane intensity was observed. In conclusion, supplementing 135 mg CHI/kg body weight increased the RA of Anaeroplasma and decreased those of rumen ciliates and protozoa, both being related to fiber degradation in the rumen in different ways and resulted in a shift of ruminal fermentation towards more propionate proportions, without affecting CH₄ emissions, milk yield, or milk composition. Further research with higher doses would be necessary to assess the potential use of this additive as a methane inhibitor.

Enteric methane (CH ₄ ) from ruminants is a significant contributor to agricultural greenhouse gas emissions and represents a energy loss to the animal. Accurate and scalable quantification is therefore essential for mitigation strategies, national inventory refinement, and evaluation of genetic or nutritional interventions. While individual-animal techniques (e.g. respiration chambers, GreenFeed, SF ₆ tracer) provide high precision, their application is often constrained under commercial or grazing conditions. This review critically evaluates group-based approaches that estimate CH ₄ emissions at herd-paddock-, or facility-scale, including mass balance, eddy covariance, flux gradient, inverse dispersion modelling, and tracer ratio methods. For each technique, we outline measurement principles, spatial scale, typical deployment scenarios, and dominant sources of uncertainty related to atmospheric variability, source geometry, instrumentation, and model assumptions. We propose minimum reporting standards to improve transparency and comparability across studies and discuss trade-offs between precision, scalability, cost, and logistical complexity. Integration of complementary techniques and greater methodological standardisation will enhance the robustness and policy relevance of herd- and farm-scale methane estimates.