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Original Article



Prediction of tannins as a phytogenic additive effect on in vitro enteric methane emissions in ruminants: A meta-analysis

Ana Karen Frutis-Moto, Gregorio Álvarez-Fuentes, Mendoza D. German, César Arturo Ilizaliturri-Hernández, Luis Octavio Negrete-Sanchez, Alfonso Chay-Canul, Héctor Aarón Lee-Rangel.



Abstract
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Objectives: This study aimed to quantify the effects of dietary tannins on in vitro methane emissions and to develop substrate-specific predictive equations for methane estimation in ruminants.
Materials and Methods: A systematic review was conducted following PRISMA guidelines, including studies published between 2010 and 2024 in Scopus, Web of Science, PubMed, and ScienceDirect. A total of 32 studies (213 observations) met the inclusion criteria and were classified into foliage (n = 130) and forage (n = 83) datasets. Pearson correlations and stepwise regression models were developed using 75% of the data and validated with the remaining 25%.
Results: Tannin concentrations showed high variability (0.40–391.00 gm/kg DM). In foliage, methane emissions were negatively correlated with condensed tannins (r = −0.40; p < 0.001), whereas in forages, total tannins showed a positive correlation (r = 0.27; p < 0.05). Predictive models demonstrated moderate accuracy, with higher performance in forage (R² = 54.61%; RMSEP = 0.13) compared to foliage (R² = 28.45%; RMSEP = 0.53). These contrasting responses highlight a strong substrate-dependent effect of tannins on methanogenesis.
Conclusions: Methane mitigation is influenced not only by tannin concentration, particularly condensed tannins, but also by substrate type and chemical composition. This study provides a novel substrate-specific predictive framework integrating tannin fractions and bromatological variables, offering a practical tool for rapid screening of antimethanogenic feed resources. However, model accuracy could be improved by incorporating physiological and fermentation-related variables.

Key words: Condensed tannins; in vitro methane emissions; meta-analysis; prediction equation; ruminal fermentation; ruminal digestibility







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