Funding providers: Swansea University's Faculty of Science and Engineering and VisiFish Ltd.
Subject areas: Fish Welfare, Machine Vision
Project start date:
- 1 July 2023 (Enrolment open from mid-June)
- 1 October 2023 (Enrolment open from mid-September)
Supervisors:
- Professor Carlos Garcia de Leaniz (Swansea University, Welfare in Aquaculture)
- Professor Sofia Consuegra (Swansea University, Fish Genomics and Domestication)
- Professor Christos Ioannou (Bristol Universty, Behavioural Ecology)
- Dr Andrew Dowsey (Bristol Universty, One Health and Artificial Intelligence)
Aligned programme of study: PhD in Biological Sciences
Mode of study: Full-time
Project description:
Fish welfare is central for the sustainable growth of aquaculture but, because fish domestication is very recent compared to mammals and birds, knowledge and protocols for assessing welfare in aquaculture is limited. Changes in behaviour (aggression and cognition) are common effects of fish farming but their importance for fish welfare are unknown. Lower cognitive abilities seem related to the less complex farming environment compared to natural fish habitats. The ballan wrasse (Labrus bergylta) and the lumpfish (Cyclopterus lumpus) are currently used as cleanerfish (a biological alternative for parasite control) in the Atlantic salmon (Atlantic salmon) farming industry. These species do not coexist in the wild but are reared together in salmon cages, raising concerns about their health and welfare, but also potentially creating a more complex, richer environment than in mono-culture.
These is a collaborative PhD project between Swansea University and Bristol University, and a commercial sponsor VisiFish that aims to improve the welfare and delousing efficacy of cleaner fish used in salmon farming. We aim to assess the behavioural traits associated with delousing behaviour and to develop camera-based behavioural metrics that can be used to assess welfare. It is expected that the findings of this project will help to improve fish welfare and inform the artificial selection of better, more efficient elite lines of cleaner fish. We will use a combination of behavioural assays and machine vision and deep-learning algorithms to develop and optimise tools to assess and improve the welfare of cleanerfish in an industrial environment.
The project will comprise the following phases:
1. Baseline testing of the effect of fish interactions on delousing behaviour at the facilities in CSAR
2. Development of methods to assess, maintain and optimise cleanerfish welfare through machine learning
3. Validation in industry
The project is best suited for a student interested on behavioural studies combined with AI and deep learning. Close collaboration with two other projects on genomics of cleaner fish and SWBio on machine learning and fish behaviour is expected and training will be provided both by the academic supervisors and the industrial partners.
Eligibility
Candidates must normally hold an undergraduate degree at 2.1 level in Biosciences or a related subject, or a master’s degree with a minimum overall grade at ‘Merit’ (or Non-UK equivalent as defined by Swansea University).
English Language requirements: If applicable – IELTS 6.5 overall (with at least 6.0 in each individual component) or Swansea recognised equivalent.
Due to funding restrictions, this scholarship is open to applicants eligible to pay tuition fees at the UK rate only, as defined by UKCISA regulations.
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