| dc.description.abstract | The current National Academies of Sciences, Engineering and Medicine (NASEM) dry matter intake (DMI) prediction models are inadequate for DMI prediction of beef cattle in the Northern Great Plains. Four studies were conducted to account for additional variation in DMI and average daily gain (ADG) caused by weather variables. Experiment 1 and 2 had 13,895 steer-weeks observations, experiment 3 had 13,739 steer-weeks observations, and experiment 4 had 2,161 cow-weeks observations, respectively. Experiment 1 examined the influence of ambient temperature and solar radiation on DMI of beef steers. In experiment 2, 3, and 4, we examined the influence of ambient temperature, range of temperature, dew point, solar radiation, wind speed and their lags (two-week lag and monthly lag) on DMI of beef steers, ADG of beef steers, and DMI of beef cows, respectively. After adjusting for week of the year, linear and quadratic relationships of predictor variables on response variables were evaluated. In experiment 1 and 2, body weight (BW) had both linear and quadratic relationship with DMI of steers. In experiment 3 and 4, BW had a linear relationship with ADG of steers and DMI of cows, respectively. Week of the year, BW, and dietary energy density (NEm) were accounted for in the base model in experiment 1, 2 and 4 while in experiment 3, DMI was also accounted for. For the models, stepwise regression procedure was utilized. In experiment 1, ambient temperature and solar radiation interacted (P = 0.0001) and accounted for additional variation in DMI of beef steers. In experiment 2, weather variables and their interactions (P = 0.0001) accounted for additional variation in DMI of beef steers. In experiment 3, weather variables (P = 0.0001) accounted for additional variation in ADG of beef steers. In experiment 4, wind speed interacted (P <0.001) with ambient temperature and range of temperature which all accounted for additional variation in DMI of beef cows. These studies show that weather variables interact and cause variation in DMI and ADG in beef cattle. This has helped in better understanding the relationship between weather variables with DMI and ADG. This will improve the accuracy of DMI and ADG prediction equations and help beef cattle producers in managing their feed resources more efficiently. | en_US |
