Practical Approach for Estimating Enteric Methane in Smallholder Cattle Systems in Southwestern Vietnam

Danh Mo

Background and Objective: Accurate estimation of Methane (CH₄) emissions is vital for developing effective mitigation strategies and for national reporting under international climate agreements. The IPCC default emission factors may not account for the characteristics of tropical cattle raised in smallholder systems. This study aimed to evaluate and calibrate empirical models to estimate dry matter intake (DMI) and enteric CH₄ emissions in crossbred Sindhi cattle (Bos indicus) under smallholder conditions in the Mekong Delta, Vietnam. Materials and Methods: Data were collected from 150 smallholder farms between March, 2024 and March, 2025. Morphometric (heart girth, HG; body length, BL) data, live weight (W), weight gain (G), DMI and energy content (GE, DE, ME, NEm) were recorded. Predicted DMI and CH₄ emission models were assessed using the coefficient of determination (R²), residual standard deviation (RSD) and t-tests. Results: The developed model in Brazil demonstrated the best fit with (R² = 0.68, RSD = 0.43, p<0.05) and was insignificantly (p>0.05) different from the actual DMI, followed by a new model (DMI = - 0.297+0.06911×W^0.75+0.867×C, R² = 0.68, RSD = 0.47, p<0.05) developed from local data, in which W = 89.325×HG²×BL (R² = 0.98, RSD = 23.4 and p<0.05). The CH₄ estimation models based on tropical/subtropical cattle (Japan and Kaewpila and Sommart) produced significantly (p<0.05) higher CH₄ conversion factor (Ym, GEI (%)) values (7.33-7.74%) than the IPCC default (6.5%). Under lipid-supplemented diets, the developed model in Japan more accurately tracked emission reductions than the IPCC. Conclusion: The default IPCC parameters tend to underestimate CH₄ emissions in tropical cattle farming systems. The model of the study is suitable for GHG inventories as the IPCC Tier 2 method and, once combined with the developed model in Japan, holds promise for the Tier 3. Further work should incorporate the effects of dietary additives into emission modeling frameworks.

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