77 Evaluation of Models Used to Predict Dry Matter Intake in Forage-Based Diets

Abstract

Abstract Data from experiments conducted at the University of Nebraska-Lincoln were pooled to compare predicted and observed dry matter intake (DMI) of growing cattle consuming foraged-based diets (corn silage, grass, alfalfa, or sorghum-hay) to determine the accuracy of current modeling systems. Experiments (n = 22) were a minimum of 84 days and included individually fed calves using the Calan gate system with 8 to 12 calves per treatment mean or pen-fed calves with 8 to 12 head per pen. Average body weight (BW) of calves ranged from 235 to 397 kg with average daily gain (ADG) between 0.16 and 1.65 kg. Cattle were fed ad libitum and mid-point BW and ADG were entered into the Beef Cattle Nutrient Requirements Model (2016) to determine predicted DMI. Simple regression was used to compare predicted and observed DMI to determine the accuracy of the prediction model. Ninety-three treatment means were evaluated and were separated into three categories: hay-based diets (n = 24), hay-based diets with distillers grains (n = 31), and corn silage-based diets (n =38). The model for observed versus predicted DMI was significant (P < 0.05; R2 = 0.09) when comparing all means but had a poor R2. The model was the best at predicting DMI for forage-based diets (P < 0.08; R2 = 0.22). Observed and predicted DMI were regressed along TDN values, calculated using book values and digestion studies. As TDN increased, observed DMI increased linearly (P < 0.01) and predicted DMI had a quadratic response (P < 0.01), increasing up to 63% and then decreasing with increasing TDN. The model over predicted DMI intake for TDN < 63% and under predicted DMI in forage-based diets greater than 63% TDN. Further development of the current modeling system through addition of intake data from forage fed growing cattle is needed