What can the quantitative and qualitative behavioural assessment of videos of sheep moving through an autonomous data capture system tell us about welfare?
•Behavioural assessments on remotely captured videos from walk-over-weigh setup.•Qualitative and quantitative measures were complementary.•Assessments provided insight into sheep behaviour related to presumed welfare state. Sheep can be exposed to a variety of challenges and failure to adapt to thes...
Saved in:
| Published in: | Applied animal behaviour science 2018-11, Vol.208, p.31-39 |
|---|---|
| Main Authors: | , , , , , , |
| Format: | Article |
| Language: | eng |
| Subjects: | |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | •Behavioural assessments on remotely captured videos from walk-over-weigh setup.•Qualitative and quantitative measures were complementary.•Assessments provided insight into sheep behaviour related to presumed welfare state.
Sheep can be exposed to a variety of challenges and failure to adapt to these challenges can compromise their health and wellbeing. Regular monitoring of stock on large-scale or extensive systems may not always be possible, although recent technological advancements in automated data capture, such as walk-over-weighing (WoW), can make monitoring easier. The potential benefit of including behavioural assessment in such a system has yet to be tested. We investigated whether quantitative and qualitative behavioural assessment (QBA) methods could be applied to short video footage collected automatically within a WoW setup, to differentiate between sheep that were, presumably, in different (positive and negative) welfare states. Video footage was collected from 36 Merino sheep within the four treatment groups; Control (n = 12), Habituated to the WoW setup and human interaction (n = 8), Lame (n = 8) and Inappetent (n = 8). Habituated sheep were exposed to a low-stress handling regimen for six consecutive days prior to filming. At the same time, feeding behaviour was recorded by means of radio-frequency identification (RFID) technology to identify sheep suffering inappetence. Lame sheep were identified using a 6-point scoring system, and Control animals were selected ensuring that they were not Lame, Inappetent or Habituated. For QBA, the footage was presented, in a random order, to 18 observers. There was a significant (P |
|---|---|
| ISSN: | 0168-1591 1872-9045 |