Optimising the selection of welfare indicators in farm animals
The enhanced algorithm was able to move beyond the selection of iceberg indicators, by incorporating multiple selection criteria to inform welfare indicator choice. The enhanced algorithm is data-agnostic and enables users to optimise indicator selection with diverse datasets spanning research, industry, and policy contexts. Its flexibility supports the development of tailored applications for different stakeholders. Future work should explore processes to determine weighting values, scenario testing, robustness, and stakeholder engagement to maximise both relevance and practicality.
Authors
- Guro Vasdal (ORCID: https://orcid.org/0000-0001-5825-9275)
- J. E. L. Day (ORCID: https://orcid.org/0000-0003-1686-4885)
- Heleen van de Weerd (ORCID: https://orcid.org/0000-0002-5254-5868)
- Mohamed Ben Haddou
- Rita Kylling
Institutions
- University of Chichester (GB)
- Brain Physiology Lab (FR)
- EAT (NO)
- Centre hospitalier Etterbeek-Ixelles (BE)
- Animalia (Norway) (NO)
Publication Details
- Journal
- Frontiers in Veterinary Science
- Published
- 2025-10-28
- DOI
- https://doi.org/10.3389/fvets.2025.1661470
- Citations
- 1
- Primary Topic
- Animal Behavior and Welfare Studies
- Type
- article
- Field-Weighted Citation Impact
- 2.35