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Abstract
Virtual fencing systems have emerged as a promising technology for managing the distribution of livestock in extensive grazing environments. This study provides comprehensive documentation of the learning process involving two conditional behavioral mechanisms and the documentation of efficient, effective, and safe animal training for virtual fence applications on nursing Brangus cows. Two hypotheses were examined: (1) animals would learn to avoid restricted zones by increasing their use of containment zones within a virtual fence polygon, and (2) animals would progressively receive fewer audio-electric cues over time and increasingly rely on auditory cues for behavioral modification. Data from GPS coordinates, behavioral metrics derived from the collar data, and cueing events were analyzed to evaluate these hypotheses. The results supported hypothesis 1, revealing that virtual fence activation significantly increased the time spent in containment zones and reduced time in restricted zones compared to when the virtual fence was deactivated. Concurrently, behavioral metrics mirrored these findings, with cows adjusting their daily travel distances, exploration area, and cumulative activity counts in response to the allocation of areas with different virtual fence configurations. Hypothesis 2 was also supported by the results, with a decrease in cueing events over time and increased reliance with animals on audio cueing to avert receiving the mild electric pulse. These outcomes underscore the rapid learning capabilities of groups of nursing cows in responding to virtual fence boundaries.
Original language | English |
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Article number | 3558 |
Number of pages | 14 |
Journal | Animals |
Volume | 13 |
Issue number | 22 |
Early online date | 17 Nov 2023 |
DOIs | |
Publication status | Print publication - Nov 2023 |
Keywords
- virtual fence; conditional behavior; animal tracking; precision livestock farming; GPS location; accelerometer and activity
- conditional behavior
- precision livestock farming
- GPS location
- animal tracking
- accelerometer and activity
- virtual fence
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RESAS 22-27: SRUC-b2-2 Breeding And Management Strategies For Sheep In The Scottish Hills And Uplands, To Meet Future Economic, Environmental And Climatic Challenges
Lambe, N. (PI), McCracken, D. (CoI), Holland, J. (CoI), Holland, J. (CoI), McCracken, D. (CoI), Livingstone, F. (CoI) & McLaren, A. (CoI)
Scottish Government: Rural & Environment Science & Analytical Services
1/04/22 → 31/03/27
Project: Research