Animal activity, in combination with physiological factors, can be used for early disease detection in dairy cattle. An initial study determined the impact of flunixin meglumine (FM), a non-steroidal anti-inflammatory drug, on activity measures, dry matter intake (DMI) and milk production during experimentally induced Escherichia coli mastitis. A total of 24 primiparous and multiparous lactating dairy cows were challenged with E.coli 727 in one quarter. Of the 24 E.coli challenged animals, 12 were administered FM at 0.002 µg/45.5kg of body weight at the onset of clinical mastitis signs. The remaining 12 cows were untreated. An additional 11 cows were infused with 1 mL of sterile phosphate-buffered saline, and served as the control group. Activity measures were collected through the use of the Afi PedometerPlus© and HOBO® data loggers. E.coli mastitis altered animal activity and improvement in DMI and milk production of animals given FM was observed, thus providing evidence for the use of an NSAID as supportive therapy for mastitis. Additionally, activity and blood metabolites concentrations were collected and analyzed from periparturient dairy cows at the Virginia Tech Dairy Center to determine the likelihood of disease occurrence. Primiparous and multiparous Holstein, Jersey, and Crossbred dairy cows were monitored for daily rest bouts, rest duration, and rest time throughout the pre and postpartum periods. Activity measurements were collected using Afi PedometerPlus© pedometers. It was concluded that evaluation of activity changes, and comparison of deviations from healthy herdmates, could allow producers to utilize activity monitoring to proactively manage dairy herd health. / Master of Science

A study was conducted to examine the correlation between a novel behavior monitoring system and a validated data logger. We concluded that the behavior monitoring system was valid for tracking daily rest time in dairy cows (R=0.96); however the correlation values for rest bouts and rest duration were relatively low, (R=0.64) (R=0.47), respectively. Daily monitoring of animal activity and milk components can be used to detect mastitis prior to clinical onset. Data from 268 cases with clinical mastitis and respective controls (n=268) from Virginia Tech and the University of Florida dairy herds were examined. Variables collected included daily milk yield, electrical conductivity, milk fat, protein, and lactose percent, as well as activity measurements including daily rest time, daily rest duration, daily rest bouts, and daily steps taken. Variables were collected for case and control cows in the 14 d prior to and after clinical diagnosis, for a total 29 d monitoring period. A milk sample was aseptically collected upon detection of clinical signs as observed by milker's at both farms. A statistical method (candisc discriminant analysis) was used to combine all measurements and sensitivity and specificity was calculated. Virginia Tech cows on d -1 (sensitivity=95%, specificity=95%), Virginia Tech and University of Florida cows on d -1 (sensitivity=88%, specificity=90). Overall, daily monitoring of animal activity and milk components can detect mastitis prior to onset of clinical signs of disease. This may allow producers to intervene and make proactive management decisions regarding herd health prior to clinical diagnosis. / Master of Science