Abstract #232
Section: ADSA-SAD Original Research ORAL Competition
Session: SAD Undergraduate Original Research Paper
Format: Oral
Day/Time: Monday 2:45 PM–3:00 PM
Location: Room 200 B
Session: SAD Undergraduate Original Research Paper
Format: Oral
Day/Time: Monday 2:45 PM–3:00 PM
Location: Room 200 B
# 232
Use of tail movement to predict calving time in dairy cattle: Validation of a calving detection technology in dairy cattle.
Sarah E. Mac*1, Carissa M. Truman1, Joao H. C. Costa1, 1University of Kentucky, Lexington, KY.
Key Words: calving, tail behavior, precision technology
Use of tail movement to predict calving time in dairy cattle: Validation of a calving detection technology in dairy cattle.
Sarah E. Mac*1, Carissa M. Truman1, Joao H. C. Costa1, 1University of Kentucky, Lexington, KY.
Early detection of calving allows the farmer to manage the parturient cow, to be present during calving if necessary and to monitor cases of dystocia in dairy cattle. Dystocia, when not assisted, has the potential to increase calf mortality, decrease milk yield, lower conception rate, and increase uterine disorders. The objective of this study was to evaluate the ability of a precision technology, Moocall (Moocall, Dublin, Ireland), to detect the onset of calving in dairy cattle. Data from 73 cows were collected from September 2016 to January 2017 at the University of Kentucky Coldstream Dairy. The calving detection device was attached to the tail 4 ± 3 d (mean ± SD) before expected due date, and video was recorded for behavior analysis. The tail-mounted technology sends 2 SMS alerts per calving, one at 2 h and the second at 1 h before calving. Accuracy of the calving device was evaluated by comparing the alerts times to the actual time of calving. Tail behavior was monitored and analyzed for frequency and duration of tail lifts 2 h before the first alert (baseline period), the h before the first alert, and the h before the second alert. All analysis was through SAS 9.3. PROC TTEST was used to analyze the alert data. A lower one-sided analysis for significance of the difference in means was performed, with the average difference between alert 1 and alert 2 as 150 and 90 min, respectively. The average time interval between the first alert and calving was 107 ± 10 min (mean ± SEM, P < 0.01) and the average time interval between second alert and calving was 71 ± 10 min (P < 0.01). Video was evaluated for the frequency and duration of tail lifts during the control period, h before the first alert, and the h before the second alert. Mean frequencies were 3.37, 7.95, and 8.47 (lifts/h), respectively. Mean durations of tail lifts were 55, 124, and 134 s, respectively. The calving detection device has the potential to alert farmers approximately 2 h before calving. The farmer being present during birth can reduce dystocia problems and increasing timely delivery of colostrum, improving cow and calf health.
Key Words: calving, tail behavior, precision technology