Evaluating Equations for Predicting Enteric Methane Emissions in Dairy Cattle

Area of Science:

• Animal Science
• Environmental Science
• Agricultural Science

Background:

• Dairy cattle enteric methane emissions (EMEs) are a significant environmental concern.
• Existing prediction equations for EMEs show considerable variability, hindering comparisons and emission reduction efforts.
• Inconsistencies in EME measurements complicate farm-to-farm comparisons and progress towards Net Zero goals.

Purpose of the Study:

• To evaluate the variability of existing dairy cattle enteric methane emission (EME) prediction equations.
• To develop a unified EME prediction equation by averaging existing models.
• To create a more accurate and consistent method for predicting EMEs based on key dietary components.

Main Methods:

• Gathered and analyzed 32 existing EME prediction equations.
• Evaluated twelve dietary variable combinations using a mixed-effects model.
• Selected an equation based on metabolised energy (ME) and neutral detergent fibre (NDF) for its predictive accuracy and significance.

Main Results:

• Existing equations yielded a wide range of EME predictions (12.49 to 34.27 g CH4/kg DM) for example diets.
• The developed combined equation (CH4 = 0.33 × ME + 0.31 × NDF + 3.47) demonstrated a low prediction error (RMSE = 1.47 g CH4/kg DM).
• The chosen equation accounted for significant predictor variables and residual variation.

Conclusions:

• A combined EME prediction equation using ME and NDF provides a more consistent and reliable estimate.
• This new equation can serve as a valuable tool for comparing EMEs across different studies and farms.
• The findings contribute to more accurate EME assessments, supporting efforts to reduce greenhouse gas emissions in dairy farming.