49 Solar radiation as a predictor variable for dry matter intake in beef steers - Yusuf, Mustapha (J Anim Sci, 2020)
The objective of this experiment was to examine the relationship between ambient temperature and solar radiation with dry matter intake (DMI) in beef steers. Daily intake data from 790 beef steers collected from years 2011 to 2017 using an Insentec feeding system were used for this experiment. Data were condensed from daily data into weekly averages (n = 14250 steer-weeks). The variables considered for this experiment include DMI (2.50 to 23.60 kg/d), body weights (197.3 to 796.1 kg), energy density of diets (NEm; 0.7930 to 2.970 Mcal/kg), ambient temperature (-23.72 to 26.40 °C), two week lag of temperature, monthly lag of temperature, solar radiation (30.81 to 297.12 W/m(2)), two week lag of solar radiation and monthly lag of solar radiation. Residuals of DMI generated after fitting week of year as a fixed effect were used in scatter plots with explanatory variables to identify if non-linear relationships existed. Body weight and energy density were observed to have both linear and quadratic relationships, while the relationship for average temperature and solar radiation vs. DMI were observed to be linear. The MIXED procedure of SAS was used to assess the fit and regression parameters of explanatory variables as fixed covariates. Repeated measures were handled using the REPEATED statement and within-individual relationship were accounted for by autoregressive 1 covariance structure. Absolute average temperature (P = 0.0024) and monthly lag of average solar radiation (P = 0.0014) are the best predictor variables for ambient temperature and solar radiation based on p-values. An interaction (P < 0.001) between average temperature and monthly lag of solar radiation was also observed. The coefficient of determination (R(2)) for our model was 0.23. This study indicates that monthly lag of solar radiation interacts with ambient temperature in affecting DMI by beef steers and improves DMI prediction equations.