UK: Using advanced underwater holographic cameras, this innovative system will allow researchers to identify the natural presence and abundance of sea lice, they say.

A team of researchers in Scotland plans to use 3D holographic imaging, machine learning and artificial intelligence (AI) to detect the presence of microscopic salmon lice larvae in the sea.

Led by engineering and digital holography experts from the University of Aberdeen, along with the Scottish Association for Marine Science (SAMS), the project, which received almost £359,000 ($408,000) from the UK Marine Products Innovation Fund (SIF) in May, has recently been held. raise other funds. and in-kind funding from partners including the Sustainable Aquaculture Innovation Center (SAIC), bringing the project value to £538,000 ($612,000).

Electronics company Hi-Z 3D, manufacturer Mowi, the Scottish Environmental Protection Agency (SEPA) and the Scottish Government’s Marine Directorate also support the initiative, which was reported in Fish Farming Expert back in May.

Using an advanced underwater holographic camera, developed at the University of Aberdeen, and automatic image identification technology based on artificial intelligence, the system will enable researchers to identify the natural presence and abundance of sea lice in the ocean, while helping fish farmers with sea lice quickly . detection and effective management on Scottish salmon farms.

Currently, the most common way to test for parasites is to collect a water sample for analysis in a laboratory under a microscope, which can take several days to get results.

Compared with standard cameras and 2D photography, digital holography has important advantages when used with microorganisms. Holographic cameras can directly record the volume of water and extract high-resolution images of various particles present in the water. Therefore, holograms can provide a data set equivalent to thousands of standard photographic images.

Identifying sea lice from other zooplankton species has previously been like looking for a needle in a haystack, so the researchers will use AI to help overcome this.

The system will be trained with thousands of holographic images of sea lice recorded in the SAMS laboratory to support the sea lice identification process when the tool is deployed.