The University of Aberdeen will develop and field-test a prototype tool for identification of sea lice infections, thus providing an early-warning system for aquaculture farms and reducing the risk posed by sea lice to farmed fish as well as to wild populations.
Sea lice infestations are a major barrier to sustainable expansion of salmon farming, causing significant welfare issues, reduced production, mortality, and impacts on wild salmonids close to sea pens. Adult sea lice are large mobile external parasites, releasing larvae directly into the water column where they are dispersed by water currents. Detecting and quantifying the abundance of these larval stages in the water would provide a powerful early warning of infection pressures on both wild and farmed salmonids. However, identifying and quantifying sea lice larvae in the water has proven extremely difficult despite more than a decade of research, and there is an urgent need to develop new technologies for early warning of sea lice infection, both for industry to develop sustainable practices of parasite control, as well as for regulators to monitor and develop sustainable policy for wild salmonid conservation and improved fish welfare.
This project will address this challenge by developing a novel method, combining holographic 3D imaging with artificial intelligence-based image recognition to identify and enumerate sea lice in-situ. A prototype will be field demonstrated. Such a tool can also provide a method for reliable data collection of sea lice larvae that is essential for validation and optimisation of sea lice dispersal modelling, which some salmon companies are adopting for sea lice management, and which lies at the heart of the proposed sea lice regulatory risk assessment framework being developed by the Scottish Environmental Protection Agency.
University of Aberdeen