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Journal of Animal Science, Vol 80, Issue 1 248-259, Copyright © 2002 by American Society of Animal Science
JOURNAL ARTICLE |
E. Kebreab, J. France, J. A. Mills, R. Allison and J. Dijkstra
The University of Reading, Department of Agriculture, Reading, United Kingdom. E.Kebreab@reading.ac.uk
Improving N utilization in dairy cows and especially reducing N output in excreta is desirable due to global concerns of agricultural contribution of N to environmental pollution, particularly as ammonia. Data from five N balance experiments were used to develop a dynamic model that was evaluated with independent data. Model predictions of feces, urine, and milk outputs were close to observed values. Statistical analysis showed that 96% of mean square prediction error for feces and urine N output predictions was due to random variation. However, the model tends to overpredict milk N output, especially at higher N intake levels. Evaluation of model predictions for independent experimental observations from Agricultural Development Advisory Service at Bridgets (U.K.) showed good agreement between predicted and observed urine N output (95% due to random variation). However, there was a slight underprediction for fecal N output (14% mean square prediction error due to bias) and overprediction of milk N output (22% of mean square prediction error due to bias). The model predictions of N outputs in excreta were sensitive to changes in energy concentration of the diet. Dietary protein degradability had only a small influence on predicted fecal N output. However, the model was sensitive in its predictions of urine N when protein degradability was varied. Application of the model to assess reduction in ammonia emissions from dairy cows showed that increasing the energy concentration could potentially reduce ammonia emissions by up to 25% per cow. Similarly, reducing CP concentration in the diet to about 16% could reduce ammonia production by 20% and lower degradability of CP to match microbial requirement by 19% per cow. The model is a first step toward a mechanistic approach of nutrient modeling, and it is a valuable method for predicting N excretions and estimating N emissions from dairy systems.
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