Frontiers in Animal Science (Sep 2022)

Solar radiation and temperature as predictor variables for dry matter intake in beef steers

  • Mustapha Yusuf,
  • Kendall C. Swanson,
  • Lauren L. Hulsman Hanna,
  • Ronald Degges,
  • Marc L. Bauer

DOI
https://doi.org/10.3389/fanim.2022.975093
Journal volume & issue
Vol. 3

Abstract

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Solar radiation may be an important weather variable that has not been included in previous dry matter intake (DMI) prediction models. Solar radiation affects the overall effective ambient temperature, which in turn contributes to the net gain of heat in an animal’s body. This experiment examined ambient temperature and solar radiation with DMI in beef steers. Data from 790 beef steers collected between 2011 and 2018 using an Insentec feeding system was used. Daily data was condensed into weekly averages (n = 13,895 steer-weeks). The variables considered for this study were DMI (2.50 to 23.60 kg/d), body weight (197 to 796 kg), calculated dietary energy density (NEm; 0.79 to 2.97 Mcal/kg), ambient temperature (-23.73 to 21.40°C), two-week lag of ambient temperature (-20.73 to 23.56°C), monthly lag of ambient temperature (-17.95 to 22.74°C), solar radiation (30.8 to 297.1 W/m2), two-week lag of solar radiation (34.6 to 272 W/m2) and monthly lag of solar radiation (43.7 to 256.6 W/m2). Residuals of DMI fitting week of the year (fixed) and experiment (random) were used to generate scatter plots with other explanatory variables to identify if non-linear relationships existed. Body weight and NEm had both linear and quadratic relationships with DMI, while the relationship with DMI for other variables was linear. The MIXED procedure of SAS with Toeplitz variance-covariance structure was used to determine the final model of DMI. After accounting for body weight and NEm in the model, two-week lag of ambient temperature and monthly lag of solar radiation interacted together (P = 0.0001), and this accounted for 0.7790 (R2) variation in DMI and improved the model fit. Therefore, these two variables and their interactions should be considered in DMI prediction equations of beef steers.

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