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

海鲜供应日益短缺，过度捕捞和供应链浪费导致全球海鲜储备枯竭。根据Seafood.org的研究，57%的海鲜在捕获和上桌之间变质，完全可以避免。对环境的影响并不总是显而易见的：拖网渔船为了满足需求而过度捕捞，将破坏纳入他们的配额。通过减少腐败，我们有可能防止过度捕捞。它还会产生碳排放，降低生产商的盈利能力。QTRACE(质量跟踪)正在构建一种质量控制工具，利用人工智能、图像识别和机器学习来评估冷链每个阶段的海鲜质量。QTRACE生成可操作的数据，以支持海产品生产商和买家知情和实时的决策，减少食品和塑料包装垃圾的拒收。我们的愿景是提高产品可追溯性和过程透明度，并及时向经常提供不合格海鲜的海鲜生产商提出建议。我们希望增加供应链对现有渔业的产地、质量和可持续发展实践的了解。在这个项目中，QTRACE将改进其技术，使其更适用于质量检查，并实现废物和排放的减少。这一阶段开发的结果是一个新的供应链QC系统，由数据驱动的产品评级系统提供支持。

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.