Abstract
The production potential of Atlantic salmon in Norway is influenced by a large number of variables that may best be controlled if it is possible to follow representative samples, collected randomly from fish that are still alive inside the production plant. The most optimal or objective way to follow stress or well-being of a fish is to be able to analyze in-vitro, different molecular changes within representative samples automatically. The first generation of automated fish sample collection system was developed to combine with refining technology from the partner in the CtrlAQUA center (www.ctrlaqua.no) in order to give a high analytical sensitivity, a low enough number of false negatives and positives. Result of the experiments illustrates that non-clogging separation and high concentration ratio can be achieved.
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Acknowledgements
The Research Council of Norway is acknowledged for the support through the Personal Post-doctoral Research Fellowships (HAVBRUK 2) [grant number 254862].
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Tran-Minh, N., Haug, B., Terjesen, B.F., Karlsen, F. (2022). Internet of Things Application for Online Surveillance and Control of Attacks by Sea Lice. In: Van Toi, V., Nguyen, TH., Long, V.B., Huong, H.T.T. (eds) 8th International Conference on the Development of Biomedical Engineering in Vietnam. BME 2020. IFMBE Proceedings, vol 85. Springer, Cham. https://doi.org/10.1007/978-3-030-75506-5_20
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