MODEL-BASED ON WEATHER VARIABLES TO PREDICT SEROCONVERSION TO BLUETONGUE VIRUS IN ALABAMA CATTLE

A model for the prediction of bluetongue virus seroconversion was deve loped using weather variables and results from serum samples collected from a research herd of Hereford, Angus, Holstein and mixed breed bee f cows at 12 different times over 2 years. The six weather variables a nalyzed were: mean daily air temperature; mean daily soil temperature at a depth of 10 cm; mean daily hours of wet vegetation; total days of rainfall greater-than-or-equal-to 0.13 cm; total rainfall for each 7 day period; mean daily solar energy (W m-2). A maximum R2 multiple lin ear regression technique was applied to meteorological data collected during the four weekly intervals prior to each sample collection date (48 sets of weekly meteorological data). The best predictors for seroc onversion were mean daily hours of wet vegetation and total rain days during the second weekly period prior to sample collection. The blueto ngue virus seroconversion was related to mean daily hours of wet veget ation, total rain days, and total precipitation as expressed by the eq uation: Seroconversion = 7.1 + 4.0 (mean daily hours of wet vegetation ) - 1.3(total precipitation) (R2 = 0.62, P < 0.0001).