Abstract
The demand for improved animal welfare has lead to technological developments to effectively monitor and evaluate animal welfare. Measuring behaviour as an indicator of animal welfare has potential, but tracking and identifying animals remains technically challenging. Computer-readable markers called ArUco markers provide a solution to track and identify individual animals in a group from a single data source (video). To examine the technical performance of this technology, we equipped pullets from two commercial laying hen hybrids housed in small groups with lightweight ArUco marker backpacks. The laminated paper backpacks with the printed marker on the middle of the back of the animals were tracked with top down view cameras. The fit of the backpacks differed between the layer hybrids, with feathers obstructing view being a limitation. For the hybrid with the most optimal fit, we were able to identify 94.0% of the individuals and track them 75.6% of the time they were manually labelled visible. By applying a threshold (65%) on the minimum percentage of time tracked, ArUco position data could be used as a stand-alone application as well, for the ArUco data was comparable to the data from manually tracked pullets. For research and semi-commercial settings, ArUco markers could provide a powerful method to identify and track hens.
| Original language | English |
|---|---|
| Article number | 100703 |
| Journal | Smart Agricultural Technology |
| Volume | 10 |
| DOIs | |
| Publication status | Published - Mar 2025 |
Bibliographical note
Publisher Copyright:© 2024
Keywords
- Activity pattern
- Computer vision
- Genetics
- Group behaviour
- Individual marker