PSII-16 Potential of sensor technology to detect changes in behavior related to health status of ewes following exposure to mold-contaminated feed. (8th October 2021) - Gurule, Sara C; Aguirre, Melissa; Forrest, Kylee; Flores, Victor V; Wenzel, John; Tobin, Colin; Bailey, Derek; Hernandez Gifford, Jennifer A
Abstract: Behavior can be a valuable indicator of an animal's health and wellness state, emphasizing the importance of monitoring changes in behavior. Sensor technologies can identify changes in animal activity, providing the potential to detect abnormal behavior associated with health status and animal welfare. The aim of this study was to investigate sheep behavior before and after illness caused by mold-contaminated feed using tri-axial accelerometers. Twenty-five ewes were fitted with HerdDogg biometric accelerometer ear tags. Thirteen ewes also had Axivity AX3 accelerometers attached on the opposite side ear tag. Tri-axial accelerometers were attached to mature ewes for the purpose of parturition evaluation, when an unexpected ration change occurred. The entire sheep flock was exposed to mold-contaminated feed, symptoms were immediately observed, and symptomatic ewes were treated with a veterinarian directed protocol. Accelerometer data were evaluated 4 days prior to exposure (d -4 to -1); on day of ration change (d 0); and 4 days post exposure (d 1 to 4). Herddogg accelerometer data from 3 ewes displaying symptoms identified a decrease in activity (P ≤ 0.03) for 2 days after feed exposure compared to the 4 days before exposure. Three days after exposure and 2 days after treatment, no difference in activity was detected (P > 0.05) between pre- and post-activity levels. Herddogg accelerometers can identify similar behavioral changes as Axivity accelerometers. The correlation of the standard deviation of movement intensity derived from the Axivity accelerometer and the Herddogg activity metric was 0.67. It is crucial to detect subtle behavioral changes at onset of illness, to allow for prompt producer intervention before animal health is compromised. These results suggest that real-time or near-real time accelerometers, such as Herddogg, have potential to detect illness in ewes in a pen setting.