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

海产品供应日益短缺，过度捕捞和供应链浪费导致全球海产品库存枯竭。根据Seafood.org的研究，57%的海鲜在捕捞和服务之间变质，完全可以避免。对环境的影响并不总是显而易见的：拖网渔船过度捕捞以满足需求，并将腐败纳入其配额。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（“Quality Trace”）正在构建一个质量控制工具，该工具利用人工智能、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，以支持海鲜生产商和买家做出明智和实时的决策，减少因拒绝而产生的食品和塑料包装浪费。我们的愿景是提高产品可追溯性和流程透明度，并及时向经常提供不合格海鲜的海鲜生产商提出建议。我们希望在现有渔业中增加供应链对原产地、质量和可持续性实践的关注。在该项目中，Qtrace将改进其技术，使其更适用于质量检查，并实现减少浪费和排放。这一开发阶段的成果是一个由数据驱动的产品分级系统驱动的新供应链QC系统。

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.