A Meta-Analysis of Dietary Inhibitors for Reducing Methane Emissions via Modulating Rumen Microbiota in Ruminants
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Updated: Jun 4, 2025

The Use of an Automated System GreenFeed to Monitor Enteric Methane and Carbon Dioxide Emissions from Ruminant Animals
Published on: September 7, 2015
Guiling Ma1, Wei Jin2, Yu Zhang2
1Institute of Ensiling and Processing of Grass, College of Agro-grassland Science, Nanjing Agricultural University, Nanjing, China; National Center for International Research on Animal Gut Nutrition, Jingsu Key Laboratory of Gastrointestinal Nutrition and Animal Health, Nanjing Agricultural University, Nanjing, China; College of Animal Science & Technology, Nanjing Agricultural University, Nanjing, China.
Background:
Rumen methane emissions (RMEs) significantly contribute to global greenhouse gas emissions, underscoring the essentials to identify effective inhibitors for RME mitigation. Despite various inhibitors shown potential in reducing RME by modulating rumen microbes, their impacts include considerable variations and inconsistency.
Objectives:
We aimed to quantitatively assess the impacts of various methane inhibitors on RME, rumen microbial abundance, and fermentation in ruminants. Additionally, the relationships between microbial abundance and RME were examined through meta-regressions.
Methods:
Meta-analysis and meta-regression were conducted to assess the impacts of methane inhibitions, including 3-nitrooxypropanol, ionophores, nitrate, triglycerides, phytochemicals, and co-inhibitors, on RME and rumen microbiota in beef, dairy cattle, and sheep.
Results:
Analyses of 922 datasets from 274 experiments revealed that inhibitors, except ionophores (P = 0.43), significantly reduced RME, with co-inhibitors displaying the highest efficacy (standardized mean difference -2.1, P < 0.01). Inhibitors' effects were more pronounced in sheep relative to beef and dairy cattle. Inhibitors decreased the abundance of ciliates and methanogens, with positive correlations observed between Dasytrichidae (P = 0.05), Entodinomorphs (P ≤ 0.001), Methanobacteriale (P = 0.001), and fungi (P < 0.01) with RME. Among inhibitors, triglycerides exhibited simultaneous reduction in methanogen, ciliate, and fungal abundances. 3-Nitrooxypropanol and triglycerides increased H2 in the rumen whereas reducing the acetate-propionate ratio, especially in beef. The H2 emission was negatively correlated (P < 0.01) and acetate-to-propionate ratio was positively correlated (P < 0.001) with RME.
Conclusions:
Microbes, including Dasytrichidae, Entodinomorphs, Methanobacteriale, and fungi, significantly attribute to RME, and co-inhibitors have the highest efficacy in limiting RME and reducing microbial abundances. This study underscores the roles of both host and microbiota in modulating the inhibitor efficacy in RME, informing the refinement of rumen additives to mitigate RME from meat and milk production.
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