Developing models to predict feces and urine excretion in Japanese Black fattening steer by multiple regression analysis.

Abstract

The objective of this study was to develop models for predicting the amount of feces and urine excreted by Japanese Black fattening steer using a dataset of 119 digestion trials for a total of 46 animals. Correlation analysis was used to analyze the relationships between feces and urine excretion and feed intake, feed digestibility, and nitrogen balance. Multiple regression analysis was conducted to develop models for predicting the amount of feces and urine excreted using the explanatory variables selected from various animal and dietary parameters based on P-value (<0.10) and variance inflation factor (<3.0). Resultingly, dry matter intake was a primary predictor of feces excreted. The prediction equation for the amount of feces excretion as a function of body weight, dry matter intake, and calculated total digestible nutrients fits the data well (adjusted coefficient of determination [adj R2 ] = 0.519, root mean square error = 1.57). Furthermore, the nitrogen content in the urine was the primary predictor of the urine excretion amount. Thus, the prediction equation for the amount of urine excreted using the nitrogen content in urine yielded a highly accurate model (adj R2 = 0.813, root mean square error = 4.12).