MyFishCheck: A Model to Assess Fish Welfare in Aquaculture.

animal welfare assessment aquaculture fish welfare ontology semantic data model

Journal

Animals : an open access journal from MDPI
ISSN: 2076-2615
Titre abrégé: Animals (Basel)
Pays: Switzerland
ID NLM: 101635614

Informations de publication

Date de publication:
11 Jan 2021
Historique:
received: 26 11 2020
accepted: 06 01 2021
entrez: 14 1 2021
pubmed: 15 1 2021
medline: 15 1 2021
Statut: epublish

Résumé

Welfare in animal husbandry includes considerations of biology, ethics, ecology, law and economics. These diverse aspects must be translated into common quantifiable parameters and applicable methods to objectively assess welfare in animals. To assist this process in the field of aquaculture, where such methods are largely missing, we developed a model to assess fish welfare. A network of information was created to link needs, i.e., fundamental requirements for welfare, with parameters, i.e., quantifiable aspects of welfare. From this ontology, 80 parameters that are relevant for welfare, have practicable assessment methods and deliver reliable results were selected and incorporated into a model. The model, named MyFishCheck, allows the evaluation of welfare in five distinct modules: farm management, water quality, fish group behaviour, fish external and fish internal appearance, thereby yielding five individual grades categorising welfare ranging from critical, to poor, to acceptable, and good. To facilitate the use of the model, a software application was written. With its adaptability to different fish species, farming systems, regulations and purposes as well as its user-friendly digital version, MyFishCheck is a next step towards improved fish welfare assessment and provides a basis for ongoing positive developments for the industry, the farmers and the fish.

Identifiants

pubmed: 33440704
pii: ani11010145
doi: 10.3390/ani11010145
pmc: PMC7826897
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Bundesamt für Lebensmittelsicherheit und Veterinärwesen
ID : ARAMIS-Nr. 502 2.16.09.

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Auteurs

Linda Tschirren (L)

Research Group for Aquaculture Systems, Institute of Natural Resource Sciences, Zurich University of Applied Sciences, 8820 Wädenswil, Switzerland.
Centre for Fish and Wildlife Health, University of Berne, 3012 Bern, Switzerland.

David Bachmann (D)

Research Group for Aquaculture Systems, Institute of Natural Resource Sciences, Zurich University of Applied Sciences, 8820 Wädenswil, Switzerland.

Ali Cem Güler (AC)

Research Group for Aquaculture Systems, Institute of Natural Resource Sciences, Zurich University of Applied Sciences, 8820 Wädenswil, Switzerland.

Oliver Blaser (O)

Research Group for Aquaculture Systems, Institute of Natural Resource Sciences, Zurich University of Applied Sciences, 8820 Wädenswil, Switzerland.

Nicola Rhyner (N)

Research Group for Environmental Genomics and Systems Biology, Institute of Natural Resource Sciences, Zurich University of Applied Sciences, 8820 Wädenswil, Switzerland.

Andreas Seitz (A)

Research Group for Aquaculture Systems, Institute of Natural Resource Sciences, Zurich University of Applied Sciences, 8820 Wädenswil, Switzerland.

Erich Zbinden (E)

Research Group for Knowledge Engineering, Institute of Applied Simulation, Zurich University of Applied Sciences, 8820 Wädenswil, Switzerland.

Thomas Wahli (T)

Centre for Fish and Wildlife Health, University of Berne, 3012 Bern, Switzerland.

Helmut Segner (H)

Centre for Fish and Wildlife Health, University of Berne, 3012 Bern, Switzerland.

Dominik Refardt (D)

Research Group for Aquaculture Systems, Institute of Natural Resource Sciences, Zurich University of Applied Sciences, 8820 Wädenswil, Switzerland.

Classifications MeSH