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Modeling methane production from beef cattle using linear and nonlinear approaches.

J L Ellis1, E Kebreab, N E Odongo

  • 1Centre for Nutrition Modeling, Department of Animal and Poultry Science, University of Guelph, Guelph, Ontario, N1G 2W1, Canada. jellis@uoguelph.ca

Journal of Animal Science
|December 23, 2008
PubMed
Summary
This summary is machine-generated.

Mathematical modeling helps reduce methane emissions from beef cattle. New equations predict methane production based on diet, aiding in greenhouse gas inventory and mitigation strategies for agriculture.

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Area of Science:

  • Agricultural Science
  • Environmental Science
  • Animal Science

Background:

  • Canada aims to reduce greenhouse gas emissions, targeting methane from ruminants in the agricultural sector.
  • Mathematical modeling is crucial for understanding methane production, improving emission inventories, and developing mitigation strategies.

Purpose of the Study:

  • To compile an extensive database of methane production values in beef cattle.
  • To generate and evaluate linear and nonlinear equations for predicting methane production based on dietary variables.
  • To assess the performance of existing methane prediction equations.

Main Methods:

  • Compilation of a comprehensive database of methane production measurements from beef cattle.
  • Development of linear and nonlinear regression models using dietary components (e.g., ME intake, cellulose, hemicellulose, fat, starch:ADF ratio, DMI, NFC:NDF ratio) as predictors.
  • Evaluation of model performance using Root Mean Square Prediction Error (RMSPE) and Residual Variance (RV).

Main Results:

  • Developed linear Eq. I (CH(4), MJ/d = 2.72 + 0.0937*ME intake + 4.31*Cellulose - 6.49*Hemicellulose - 7.44*Fat) with RMSPE of 26.9% and RV of 1.13.
  • Generated ratio-based Eq. P (CH(4), MJ/d = 2.50 - 0.367*(Starch:ADF) + 0.766*DMI) with RMSPE of 28.6% and RV of 1.35.
  • Nonlinear Eq. W (CH(4), MJ/d = 10.8*(1-e^(-0.141*DMI))) showed RMSPE of 29.0% and RV of 3.06; Eq. W(3) (CH(4), MJ/d = 10.8*[1-e({-[-0.034*(NFC/NDF)+0.228]*DMI})]) had RMSPE of 28.0% and RV of 3.06.
  • Existing equations performed comparably or better than newly developed ones in some cases.

Conclusions:

  • New linear and nonlinear equations were developed to predict methane production in beef cattle based on diet.
  • Equation selection should consider RMSPE, RV, available input variables, and potential deviations from a normal diet.
  • The findings contribute to improving greenhouse gas inventories and developing effective methane mitigation strategies in the beef industry.