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  • 1
    Publication Date: 2021-06-16
    Description: By bringing concepts of precision farming to intensive aquaculturem fish production can be optimized to be more sustainable while focusing on fish welfare criteria. This means to shift from mass to smart production which requires to consider each fish as an individual instead of viewing on the total stock of fish. Therefore it is required to be able to identify each fish in a tank or sea cage. In this paper, we prove the feasibility of fish identification using the iris as biometric characteristic. For this purpose, a new database was captured which enables us to consider the basic feasibility as well as to prove the permanence of the iris pattern of Atlantic salmon in terms of ageing. Results show that the iris pattern of Atlantic salmon is suited for biometric identification, but the pattern changes significantly in short periods.
    Language: English
    Type: info:eu-repo/semantics/article
    Format: application/pdf
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  • 2
    Publication Date: 2021-09-16
    Description: Precision fish farming is an emerging concept in aquaculture research and industry, which combines new technologies and data processing methods to enable data-based decision making in fish farming. The concept is based on the automated monitoring of fish, infrastructure, and the environment ideally by contactless methods. The identification of individual fish of the same species within the cultivated group is critical for individualized treatment, biomass estimation and fish state determination. A few studies have shown that fish body patterns can be used for individual identification, but no system for the automation of this exists. We introduced a methodology for fully automatic Atlantic salmon (Salmo salar) individual identification according to the dot patterns on the skin. The method was tested for 328 individuals, with identification accuracy of 100%. We also studied the long-term stability of the patterns (aging) for individual identification over a period of 6 months. The identification accuracy was 100% for 30 fish (out of water images). The methodology can be adapted to any fish species with dot skin patterns. We proved that the methodology can be used as a non-invasive substitute for invasive fish tagging. The non-invasive fish identification opens new posiblities to maintain the fish individually and not as a fish school which is impossible with current invasive fish tagging.
    Language: English
    Type: info:eu-repo/semantics/article
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