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Can AI Aquaculture Integration Slash Salmon Prices and Sea-Lice Woes?

AI aquaculture integration

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TL;DR

  • AI-driven holographic imaging technology may revolutionize aquaculture by detecting sea-lice in salmon farms faster than traditional methods.
  • Aberdeen University and Scottish Association for Marine Science collaborate on an innovative project supported by Hi-Z 3D, Mowi, SEPA, and the Scottish Government.
  • The project, funded by over £538,000 from partners including the UK Seafood Innovation Fund and SAIC, aims to create a baseline for future analysis using images collected over the next 18 months.

In a breakthrough endeavor, researchers from Aberdeen University and the Scottish Association for Marine Science (Sams) are leveraging Artificial Intelligence (AI) and holographic imaging technology to combat a longstanding issue in aquaculture—the presence of sea-lice in salmon farms. This collaborative effort, supported by industry heavyweights and governmental bodies, holds the promise of not only enhancing fish health management but also potentially reducing the financial burden on the Scottish salmon sector, a significant portion of which is spent annually to eradicate sea-lice.

AI aquaculture integration to detect sea-lice

Artificial Intelligence, coupled with underwater holographic imaging technology, is at the forefront of a pioneering aquaculture project aimed at transforming the way sea-lice are detected in salmon farms. Spearheaded by Aberdeen University and Sams, the project has garnered support from prominent entities such as Hi-Z 3D, Mowi, SEPA, and the Scottish Government.

Thangavel Thevar of Aberdeen University’s school of engineering highlights the innovative approach, asserting that holographic imaging technology is set to be reinforced by AI and machine learning. According to him, this integration is poised to facilitate the identification process, leading to a substantial reduction in processing time. The system, expected to outpace manual water sampling and lab-based analysis, could mark a paradigm shift in fish health management.

Thangavel Thevar further elaborates on the technology, mentioning that the camera utilized was initially designed for identifying marine organisms and microparticles in the ocean. The team saw an opportunity to adapt this tool for supporting the aquaculture sector in fish health management. The integration of AI and machine learning is crucial, not only for swift identification but also for training the system to distinguish sea-lice from other species. The project, recently endowed with over £538,000 in funding, primarily from the UK Seafood Innovation Fund and Sustainable Aquaculture Innovation Centre (SAIC), aims to create a robust baseline for future analysis using images collected over the next 18 months.

Heather Jones, the Chief Executive of SAIC, conveys a positive outlook regarding the project’s potential influence on aquaculture. She highlights the excitement surrounding the prospect of new data-led techniques supporting the thriving of aquaculture. Jones envisions the developed system as a valuable tool in the industry’s arsenal, offering sustainable solutions to address the persistent challenge of sea-lice on salmon farms. Also, she anticipates the transformative impact on fish health management, foreseeing economic benefits for the sector while concurrently minimizing its environmental footprint.

A costly conundrum for salmon farms

Sea-lice, a perennial concern for the aquaculture sector, pose a substantial threat to fish health and result in significant economic losses for the Scottish salmon industry. The parasites cause stock depletion and cost millions of pounds annually for their eradication and treatment. Identifying sea-lice among zooplankton species has been likened to searching for a needle in a haystack.

The collaboration between Sams and the aquaculture project aims to address this challenge by setting up a dedicated sea-lice hatchery for research purposes. Helena Reinardy, an aquaculture researcher at Sams, emphasizes the importance of early detection, stating, “Sea-lice are a concern for the aquaculture sector and regulator. One of the first steps to managing them is to identify whether they are present in the water.”

Current methods of sea-lice identification involve labor-intensive processes, such as using zooplankton nets that require significant time and specialized expertise. The new system, integrating holographic imaging technology supported by AI, holds the promise of providing more regular and accurate monitoring. Helena Reinardy envisions the system as a game-changer, allowing for early indications of potential sea-lice risks at the larval stage. As the project progresses, the goal is to be ready for trialing the system at sea, marking a significant step toward a more efficient and sustainable approach to managing sea-lice in salmon farms.

The convergence of AI, holographic imaging technology, and aquaculture presents a promising solution to the persistent challenge of sea-lice in salmon farms. As researchers embark on an 18-month journey to gather data and create a baseline for future analysis, the industry watches with anticipation, hopeful that this technological intervention could not only enhance fish health management but also alleviate the financial strain on salmon producers. The potential for early detection and accurate monitoring could mark a turning point in addressing the sea-lice menace, offering a more sustainable and economically viable future for the Scottish salmon sector.

Disclaimer. The information provided is not trading advice. Cryptopolitan.com holds no liability for any investments made based on the information provided on this page. We strongly recommend independent research and/or consultation with a qualified professional before making any investment decisions.

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Aamir Sheikh

Amir is a media, marketing and content professional working in the digital industry. A veteran in content production Amir is now an enthusiastic cryptocurrency proponent, analyst and writer.

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