Understanding the relationship between weather variables and intake in beef steers

Author:

Yusuf Mustapha1,Swanson Kendall C1ORCID,Hulsman Hanna Lauren L1,Bauer Marc L1ORCID

Affiliation:

1. Department of Animal Sciences, North Dakota State University , Fargo, ND 58108 , USA

Abstract

Abstract The relationship between weather variables and dry matter intake (DMI) in beef steers was examined using daily intake data from 790 beef steers collected through a computer-controlled feeding system in nonsummer months. Daily data were condensed into weekly averages (N = 13,895 steer-weeks). The variables considered to predict DMI (2.50 to 23.60 kg/d) were body weight (197 to 796 kg), dietary net energy for maintenance (NEm; 0.79 to 2.97 Mcal/kg), ambient temperature (−23.73 °C to 21.40 °C), range of temperature (2.79 °C to 19.43 °C), dew point (−27.84 °C to 14.34 °C), wind speed (2.08 to 6.49 m/s), solar radiation (30.8 to 297.1 W/m2), and 2-wk lag (average of previous 2 wk’s values) and monthly lag (average of previous 4 wk’s values) of each weather variable. Toeplitz variance-covariance structure for repeated measures was used to determine the model to predict DMI, while accounting for the effects of body weight, dietary NEm, and other variables in the model. Two-week lag of ambient temperature interacted (P ≤ 0.005) with 2-wk lag of range of temperature, monthly lag of wind speed, 2-wk lag of solar radiation, and dew point to predict DMI. Interactions (P = 0.0001) between 2-wk lag of range of temperature vs. dew point and monthly lag of wind speed vs. 2-wk lag of solar radiation were also detected. This study reports important weather variables associated with differences in DMI of growing and finishing steers and will help improve the accuracy of DMI prediction equations for beef cattle. Improvements in the accuracy of predicting DMI should give producers better tools to plan and execute efficient feeding management programs. The R2 of the overall model was 0.8891.

Publisher

Oxford University Press (OUP)

Subject

Genetics,Animal Science and Zoology,General Medicine,Food Science

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