Abstract
Previous attempts to apply statistical
models, which correlate nutrient intake with methane
production, have been of limited value where predictions
are obtained for nutrient intakes and diet types
outside those used in model construction. Dynamic
mechanistic models have proved more suitable for extrapolation,
but they remain computationally expensive
and are not applied easily in practical situations.
The first objective of this research focused on employing
conventional techniques to generate statistical models
of methane production appropriate to United Kingdom
dairy systems. The second objective was to evaluate
these models and a model published previously using
both United Kingdom and North American data sets.
Thirdly, nonlinear models were considered as alternatives
to the conventional linear regressions. The United Kingdom calorimetry data used to construct the linear
models also were used to develop the three nonlinear
alternatives that were all of modified Mitscherlich
(monomolecular) form. Of the linear models tested, an
equation from the literature proved most reliable across
the full range of evaluation data (root mean square
prediction error = 21.3%). However, the Mitscherlich
models demonstrated the greatest degree of adaptability
across diet types and intake level. The most successful
model for simulating the independent data was a
modified Mitscherlich equation with the steepness parameter
set to represent dietary starch-to-ADF ratio
(root mean square prediction error = 20.6%). However,
when such data were unavailable, simpler Mitscherlich
forms relating dry matter or metabolizable energy intake
to methane production remained better alternatives
relative to their linear counterparts.
Original language | English |
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Pages (from-to) | 3141-3150 |
Number of pages | 10 |
Journal | Journal of Dairy Science |
Volume | 81 |
Issue number | 12 |
Publication status | Published - 2003 |
Keywords
- dairy cows
- methane
- modeling