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Article
Prediction of Nitrogen Use in Dairy Cattle: a Multivariate Bayesian Approach
Animal Production Science
  • K.F. Reed, University of California, Davis
  • L.E. Moraes, University of California, Davis
  • J.G. Fadel, University of California, Davis
  • David P. Casper, South Dakota State University
  • J. Dijkstra, University of Copenhagen
  • J. France, University of Guelph
  • E. Kebread, University of California, Davis
Document Type
Article
Publication Date
9-1-2014
Keywords
  • Protein nutrition,
  • modeling
Disciplines
Abstract
Quantification of dairy cattle nitrogen (N) excretion and secretion is necessary to improve the efficiency with which feed N is converted to milk N (ENU). Faecal and urinary N excretion and milk N secretion are correlated with each other and thus are more accurately described by a multivariate model that can accommodate the covariance between the three observations than by three separate univariate models. Further, by simultaneously predicting the three routes of excretion and taking advantage of the mass balance relationships between them, covariate effects on N partitioning from feed to faeces and absorbed N and from absorbed N to milk and urine N and animal ENU can be estimated. A database containing 1094 lactating dairy cow observations collated from indirect calorimetry experiments was used for model development. Dietary metabolisable energy content (ME, MJ/kg DM) increased ENU at a decreasing rate, increased the efficiency with which feed N was converted to absorbed N and decreased the efficiency with which absorbed N was converted to milk N. However, the parameter estimate of the effect of ME on post-absorption efficiency was not different from zero when the model was fitted to a data subset in which net energy and metabolisable protein were at or above requirement. This suggests the effect of ME on post-absorption N use is dependent on the energy status of the animal.
DOI of Published Version
10.1071/AN14534
Publisher
CSIRO Publishing
Rights
© 2014 CISRO Publishing
Citation Information
Reed K. F., Moraes L. E., Fadel J. G., Casper D. P., Dijkstra J., France J., Kebreab E. (2014) Prediction of nitrogen use in dairy cattle: a multivariate Bayesian approach. Animal Production Science 54, 1918–1926. http://dx.doi.org/10.1071/AN14534