A Case Study Using Accelerometers to Identify Illness in Ewes following Unintentional Exposure to Mold-Contaminated Feed

SIMPLE SUMMARY: Observing the health and wellness of livestock is time consuming and costly. Sensor technologies can identify changes in animal activity, providing the potential to remotely monitor livestock health status and welfare. As part of another study, 10 ewes in a pen setting were monitored with near real-time accelerometers manufactured by Herddogg. Ewes were inadvertently fed moldy corn silage. The moldy feed was removed the following day and ewes displaying symptoms, such as reduced intake and difficulty walking, were treated under the direction of a veterinarian. Accelerometers showed a distinct decrease in activity for 4 days after the ewes were exposed to moldy feed. Accelerometers also showed an increase in activity of symptomatic ewes after treatment. Real-time and near real-time accelerometers have the potential to remotely detect changes in sheep activity that occur when animals become ill from mold contaminated feed and perhaps other illnesses, which could help producers monitor livestock health and provide a more timely response when they become ill. ABSTRACT: Sensor technologies can identify modified animal activity indicating changes in health status. This study investigated sheep behavior before and after illness caused by mold-contaminated feed using tri-axial accelerometers. Ten ewes were fitted with HerdDogg biometric accelerometers. Five ewes were concurrently fitted with Axivity AX3 accelerometers. The flock was exposed to mold-contaminated feed following an unexpected ration change, and observed symptomatic ewes were treated with a veterinarian-directed protocol. Accelerometer data were evaluated 4 days before exposure (d −4 to −1); the day of ration change (d 0); and 4 days post exposure (d 1 to 4). Herddogg activity index correlated to the variability of minimum and standard deviation of motion intensity monitored by the Axivity accelerometer. Herddogg activity index was lower (p < 0.05) during the mornings (0800 to 1100 h) of days 2 to 4 and the evening of day 1 than days −4 to 0. Symptomatic ewes had lower activity levels in the morning and higher levels at night. After accounting for symptoms, activity levels during days 1 to 4 were lower (p < 0.05) than days −4 to 0 the morning after exposure. Results suggest real-time or near-real time accelerometers have potential to detect illness in ewes.