Representing interconversions among volatile fatty acids in the Molly cow model

Area of Science:

• Rumen microbiology and nutrition
• Computational modeling in animal science

Background:

• The Molly cow model predicts volatile fatty acid (VFA) production using fixed stoichiometric coefficients.
• Previous studies indicated large errors in VFA production predictions, potentially due to unrepresented carbon exchange among VFAs.

Purpose of the Study:

• To enhance the Molly cow model by incorporating thermodynamic equations for VFA interconversions.
• To evaluate the impact of these thermodynamic additions and modified coefficient predictions on VFA prediction accuracy and precision.

Main Methods:

• Introduced thermodynamic equations to represent interconversions among acetate, propionate, and butyrate.
• Modified the model to predict VFA production coefficients based on forage-to-concentrate ratios.
• Reparameterized and evaluated both original and modified models against extensive datasets of ruminal pH and VFA data.

Main Results:

• Predictions of VFA production rates showed no significant improvement with the revised model compared to the original.
• Rederiving VFA coefficients substantially reduced prediction errors for VFA concentrations.
• Thermodynamically driven VFA interconversion equations provided minimal additional improvement in VFA concentration predictions.

Conclusions:

• Thermodynamic interconversions among VFAs may not be the primary factor limiting the accuracy of net VFA production predictions.
• Improved VFA concentration prediction accuracy was mainly attributed to rederived coefficients, not thermodynamic equations.
• Further research is needed to address potential inadequacies in representing VFA production, absorption, and ruminal digestion, or data quality issues.