New case study: Developing an early warning system for infectious sea lice

A team of Scottish researchers is developing a breakthrough early-warning system to detect the tiny, harmful sea lice larvae before they can damage fish farms.

Sea lice pose one of the most persistent challenges in modern aquaculture, particularly in Atlantic salmon farming. Using holographic 3D cameras along with AI, this project explored innovative new detection methods for identifying sea lice larvae.

Sea lice, primarily Lepeophtheirus salmonis and Caligus spp., attach to the skin of farmed and wild fish, harming the fish and leading to higher production costs due to the need for treatments, lost livestock, and regulatory restrictions.

Being able to detect sea lice early enables proactive management, improving fish welfare and environmental sustainability while reducing the risk of infections.

Current detection methods involve collecting water, sending it to a lab, and painstakingly looking through samples under a microscope to identify sea lice larvae. By contrast, the new holographic system captures a three-dimensional snapshot of water containing thousands of particles in one go, which is then analysed by AI, providing automatic real-time detection of lice at the larval stage, so farms can act early.

This collaborative research project included the University of Aberdeen (experts in engineering and digital holography), the Scottish Association for Marine Science (SAMS), electronics firm Hi‑Z 3D, Mowi, SEPA, and the Scottish Government’s Marine Directorate.

Read the full case study