343 The Influence of Weather Variables on Average Daily Gain of Beef Steers. (8th October 2021)

• Record Type: Journal Article
• Authors: Yusuf, Mustapha; Bauer, Marc L; Swanson, Kendall C; Hanna, Lauren L Hulsman
• Is Part Of: Journal of animal science. Volume 99(2021)Supplement 3
• Page Start: 190
• Page End: 191
• Publication Date: 2021-10-08
• Subjects: gain -- weather -- steers; Livestock -- Periodicals; Livestock; Electronic journals; Periodicals; 636.005
• DOI: 10.1093/jas/skab235.344
• Languages: English
• ISSNs: 0021-8812

Abstract

Abstract: Average daily gain is one of the most important measures producers utilize to measure productivity of beef cattle. The objective was to examine how weather variables influence ADG. Data from 790 beef steers collected using an Insentec feeding system were utilized for this study. Intake data were condensed from daily data into weekly averages (n = 13, 739 steer-weeks). The variables considered were ADG (-3.0 to 4.86 kg/d), DMI (2.50 to 21.77kg/d), BW (197.3 to 796.1 kg), dietary energy density (NEm; 1.2 to 2.5 Mcal/kg), average ambient temperature (-23.7 to 21.4 °C), range of temperature (2.8 to 19.4 °C), dew point (-27.8 to 14.3 °C), wind speed (2.08 to 6.49 km/h), solar radiation (30.8 to 297.1 W/m 2 ), and two weeks lag (average of previous two weeks values) and monthly lag (average of previous four weeks values) of each weather variable. Relationship between weather variables were considered while developing the model, including controlling for confounding variables. Residuals of ADG 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. 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 was accounted for using the Toeplitz covariance structure. Body weight and energy density had linear and quadratic relationships with ADG (Table 1). Two weeks lag of wind speed and monthly lag of solar radiation had positive and negative associations with ADG, respectively, and there were several interactions between weather variables. These data indicate that weather variables influence ADG and should be considered in ADG prediction equations.