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Alternative approaches to predicting methane emissions from dairy cows.
J A N Mills1, E Kebreab, C M Yates
1The University of Reading, School of Agriculture, Policy and Development, Earley Gate, Reading RG6 6AR, United Kingdom. j.a.n.mills@reading.ac.uk
Journal of Animal Science
|December 18, 2003
Summary
Statistical models for predicting methane production in dairy systems showed limitations. Nonlinear Mitscherlich models, particularly those considering starch-to-ADF ratio, offered superior adaptability and accuracy across diverse diets and intake levels compared to linear regressions.
Area of Science:
- Agricultural Science
- Animal Nutrition
- Environmental Science
Background:
- Statistical models correlating nutrient intake with methane production have limited predictive value outside their construction parameters.
- Dynamic mechanistic models are suitable for extrapolation but are computationally expensive and impractical for routine use.
- There is a need for adaptable and accurate models for predicting methane emissions in dairy systems.
Purpose of the Study:
- To develop statistical models for methane production specific to United Kingdom dairy systems.
- To evaluate existing and newly developed models using United Kingdom and North American datasets.
- To explore nonlinear models, specifically modified Mitscherlich forms, as alternatives to linear regressions.
Main Methods:
- Conventional techniques were used to generate linear statistical models for methane production.
- Three nonlinear models of modified Mitscherlich (monomolecular) form were developed using United Kingdom calorimetry data.
- Models were evaluated using independent United Kingdom and North American datasets, assessing prediction error (root mean square prediction error).
Main Results:
- A literature-based linear equation showed the most reliability among tested linear models (RMSPE = 21.3%).
- Mitscherlich models demonstrated superior adaptability across different diet types and intake levels.
- A modified Mitscherlich equation incorporating the dietary starch-to-ADF ratio achieved the highest accuracy on independent data (RMSPE = 20.6%).
- Simpler Mitscherlich forms relating dry matter or metabolizable energy intake to methane production outperformed linear models when specific dietary data was unavailable.
Conclusions:
- Nonlinear Mitscherlich models offer significant advantages over conventional linear regressions for predicting methane production in dairy cattle.
- Incorporating dietary components like the starch-to-ADF ratio into Mitscherlich models enhances predictive accuracy.
- Simpler Mitscherlich models provide a practical and reliable alternative to linear models for estimating methane emissions when detailed dietary information is limited.