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Journal article
Computer Vision Detects an Association Between Gross Gill Score and Ventilation Rates in Farmed Atlantic Salmon (Salmo salar)
Journal of fish diseases, Vol.First online
25/08/2025
PMID: 40855664
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Abstract
Poor gill health compromises the health and welfare of farmed Atlantic salmon (Salmo salar) by causing respiratory distress and increased ventilation frequency. Poor gill health is caused by numerous factors, including amoebic gill disease (AGD), jellyfishstings, and toxic algae, and is monitored by fish farmers by manual ‘gill scoring’. Gill scoring involves visual inspection of gillsurfaces for visible lesions, such as white mucoid patches. In commercial salmon farming, these patches are commonly associated with AGD, a major cause of poor gill health. Manual monitoring of gills is labour-intensive, costly, and stressful for fish. This study tested a non-invasive computer vision approach to detect the association between the gross gill score and fish ventilationrates in commercial farms. We hypothesised that increased ventilation rates of farmed Atlantic salmon were associated with ahigher gross gill score. The computer vision model first detected fish heads and classified their mouth states (open or closed)using a convolutional neural network, followed by a tracking-by-detection method to estimate ventilation rates by calculating the frequency with which fish opened and closed their mouths. Ventilation rates were estimated from 240 videos recorded atTasmanian salmon farms and analysed alongside gross gill score, water temperature, dissolved oxygen, and fish weight. Multiplelinear regression analysis revealed a positive association between ventilation rates and gross gill score, although the observedchange in ventilation rates was relatively small. As laboratory diagnostic methods did not confirm AGD in this study, the grossgill scores should be interpreted primarily as indicators of gill health, acknowledging that they may also reflect signs consistent with AGD. While the tested computer vision method cannot serve as a diagnostic tool, it may assist the industry in identifying health and welfare issues that require further examination. This approach provides a non-invasive way to oversee health andwelfare, enhances management practices, and guides manual health assessments.
Details
- Title
- Computer Vision Detects an Association Between Gross Gill Score and Ventilation Rates in Farmed Atlantic Salmon (Salmo salar)
- Creators
- Quynh Le Khanh Vo - Griffith University (Australia, Gold Coast)Kylie A. Pitt - Griffith University (Australia, Gold Coast)Colin Johnston - Tassal Group (Tasmania)Blair Kennedy - Tassal Group (Tasmania)Lukas Folkman - Griffith University (Australia, Gold Coast)
- Publication Details
- Journal of fish diseases, Vol.First online
- Publisher
- Wiley
- Identifiers
- 991013341085902368
- Copyright
- © 2025 The Author(s).
- Academic Unit
- Faculty of Science and Engineering
- Language
- English
- Resource Type
- Journal article