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Quantifying enteric methane from ruminants: a critical review of group-based measurement approaches Cover

Quantifying enteric methane from ruminants: a critical review of group-based measurement approaches

Open Access
|Jun 2026

Abstract

Enteric methane (CH4) 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, SF6 tracer) provide high precision, their application is often constrained under commercial or grazing conditions.

This review critically evaluates group-based approaches that estimate CH4 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.

Language: English
Page range: 133 - 144
Accepted on: Feb 10, 2026
Published on: Jun 30, 2026
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2026 Jagoba Rey Gotxi, Patryk Sztandarski, Aneta Jaszczyk, Dorota Komorowska, Anna Wójcik, Marek Balcerzak, Jan Ślósarz, Danuta Siwiec, Grzegorz Pogorzelski, Joanna Marchewka, Jarosław O. Horbańczuk, published by Institute of Genetics and Animal Biotechnology of the Polish Academy of Sciences
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.