Development and evaluation of a model for prediction of fecal and urinary nitrogen excretions in cattle

H. Hirooka, J. B. Liang, F. Terada

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

The reduction of nitrogen (N) excretion in animal production is crucial in intensive farming systems particularly in the developed countries. In this study, a model to predict N excretion in cattle was developed based on existing feeding standards and evaluated using independent N balance experiments for Holstein steers and lactating cows and Japanese Black (JB) steers. Although model predictions for fecal and urinary N excretions appeared to be close to observed values in plot figures, statistical analysis showed that the model tended to over-predict both fecal and urinary N excretions, especially in Holstein lactating cows. This was because body weight changes of cows during lactation period were not considered in the model due to the lack of information (i.e., body weight gain or loss) available in the experimental data for evaluation. There were large mean bias and small line bias for urinary N prediction, but reverse results were obtained for fecal N prediction. The largest mean square prediction errors for both N excretions were due to random variation in all cases. When all data were pooled (combined), the accuracy for predictions for fecal N excretion was considerably high (r2 = 0.94), indicating that the model may predict fecal N excretion beyond breeds, sexes and physiological states (growing and lactating). More information and accumulated data will be required to predict urinary N excretion under a wide range of genotype and environmental situation.

Original languageEnglish
Pages (from-to)282-288
Number of pages7
JournalLivestock Science
Volume107
Issue number2-3
DOIs
Publication statusPublished - 2007 Apr
Externally publishedYes

Keywords

  • Cattle
  • Excretion
  • Model
  • Nitrogen
  • Prediction

ASJC Scopus subject areas

  • Animal Science and Zoology
  • veterinary(all)

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