Novel AI to improve quality control and reduce food waste in seafood supply chains

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Seafood is in increasing short supply, with overfishing and supply chain waste causing depletion of global seafood stocks. According to research by Seafood.org, 57% seafood spoils between catch and service and is completely avoidable. The environmental impact is not always obvious: trawlers are overfishing to account for demand, incorporating spoilage into their quotas. By reducing spoilage, we have the potential to prevent overfishing. It also creates carbon emissions and reduces producer profitability. Qtrace ("Quality Trace") is building a quality control tool that utilises AI, image recognition and machine learning to assess the quality of seafood at each stage of the cold chain. Qtrace generates actionable data to support informed and real-time decision-making for seafood producers and buyers, reducing food and plastic packaging waste from rejections. Our vision is to increase product traceability and process transparency and in time make recommendations to seafood producers who regularly deliver sub-standard seafood. We want to increase supply chain optics on origin, quality and sustainability practices in the incumbent fishing industry. In this project Qtrace will improve its technology to make it more usable for quality checks and achieve waste and emissions reductions. The outcome of this phase of development is a new supply chain QC system powered by a data-driven product grading system.