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Modeling Diurnal Variation in Ruminal Temperature of Beef Cows
Ruminal temperature (RuT) of beef cows is an effective measure of core body temperature. Monitoring RuT may be useful for the prediction of physiological events in cattle including estrus, parturition, and health status. Daily variation in core body temperature of cattle is well documented and may influence prediction models using temperature. The objective of this experiment was to develop a method to reduce the impact of diurnal variation in RuT of beef cows. Hourly reporting temperature boluses (SmartStock, LLC) were administered to postpartum, lactating, Angus cows. The data set used for modeling contained 12,358 RuT values (58 cows; 14 d), with a daily mean of 19.3 ± 0.3 RuT readings per cow. Models were developed to generate hourly correction factors for RuT, which reduce the impact of diurnal variation. Briefly, the RuT for a cow at an hour was subtracted from the mean RuT of all cows at all hours in the experimental group (Ac), or mean RuT of an individual cow for all hours (Cc), or all RuT during a 72 h running average for an individual cow (Ra). Correction factors for each daily hour (0000 to 2300 h) were calculated as the hourly least squares mean for the hourly deviations from the means (Ac, Cc, Ra). Hourly least square means of the deviations for an hour were calculated for all cows (AM) or for individual cows (CM). Unadjusted RuT and RuT excluding drinking events (W; less than 2 x SD of mean RuT) were used for model evaluation. Ruminal temperature for each model was analyzed using PROC UNIVARIARTE, PROC REG, and PROC MIXED (SAS Inst. Inc.). All 6 correction models reduced the variation (>54%) and skewdness (>30%) of RuT. Hourly variation in RuT occurred for unadjusted RuT, W, and RaAM (P < 0.05), but was eliminated in AcAM, AcCM, CcAM, CcCM, and RaCM models. Bayesian information criterion values (goodness of fit), were least when AcCM was used to model RuT. When the AcCM model was used, variation in RuT was greatly diminished. Daily hour did not influence RuT when AcCM, CcCM, and RaCM models (P = 0.87, 0.83, 0.91, respectively) were used to adjust RuT. These results indicate models can be developed to greatly reduce diurnal variation in RuT. The usefulness of RuT can be enhanced through the use of models to reduce diurnal variation in body temperature of cows.
Keywords: beef cow, diurnal variation, ruminal temperature