| Autor: |
Sara C. Gurule, Victor V. Flores, Kylee K. Forrest, Craig A. Gifford, John C. Wenzel, Colin T. Tobin, Derek W. Bailey, Jennifer A. Hernandez Gifford |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Animals, Vol 12, Iss 3, p 266 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2076-2615 |
| DOI: |
10.3390/ani12030266 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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