Prediction of nitrogen excretion by beef cattle: A meta-analysis.

Reliable estimates of N excretion in the urine and feces of beef cattle are essential for developing cost-effective and environmentally sound nutrient management plans. A meta-analysis dataset was compiled that included data for starting live BW, DMI, N intake, dietary CP and RDP concentrations, urine N excretion, and feces N excretion. The data were taken from 12 individual feeding trials that included N balance data, and represented a total of 47 different dietary treatments and 255 animals. Correlation analysis was used to determine the animal and dietary parameters that were most closely related to N excretion in urine and feces by beef cattle. A multivariate mixed modeling approach was used to develop empirical equations to predict excretion of urine N, feces N, and the partitioning of total N excretion between urine and feces, as a function of N intake and the concentration of dietary CP. Univariate, regression, and mean difference comparisons indicated 46 to 95% agreement between observed and predicted values for the developed equations. Evaluation of the equations with an independent dataset taken from 6 studies, and 2 random subsets of the meta-analysis dataset showed moderate agreement (P < 0.05, r(2) = 0.34 to 0.86) for urine N excretion as a function of both N intake and %CP, and the partitioning of total N excretion into urine as a function of %CP. There was less agreement between predictions and observations for feces N excretion as a function of %CP (r(2) = 0.003 to 0.14) than N intake (r(2) = 0.52 to 0.75), indicating that %CP is not a good predictor of fecal N excretion. The empirical equations provide a simple tool that, if used with caution, could predict N excretion characteristics for a wide range of dietary and animal characteristics and could improve ammonia emissions estimates by process-based models.

Citation

H M Waldrip, R W Todd, N A Cole. Prediction of nitrogen excretion by beef cattle: A meta-analysis. Journal of animal science. 2013 Sep;91(9):4290-302

PMID: 23825341

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