NSF Convergence Accelerator Track E: Innovative Seafood Traceability Network for Sustainable Use, Improved Market Access, and Enhanced Blue Economy

NSF 融合加速器轨道 E：创新海鲜可追溯网络，实现可持续利用、改善市场准入和增强蓝色经济

• 批准号: 2137582
• 负责人: Demian Willette
• 金额: $ 74.96万
• 依托单位: Loyola Marymount University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2137582&HistoricalAwards=false
• 关键词: NSF; Convergence; Accelerator; Track; Innovative

Proposal # 2137582 NSF Convergence Accelerator Track E: Innovative seafood traceability network for sustainable use, improved market access, and enhanced blue economy Addressing the global challenge of feeding the growing human population will require a solution from the ocean. To prevent reoccurrences of overfishing and its negative ecological impacts, major fisheries require reimagined monitoring and management strategies. Leveraging leading-edge machine learning computer technology and environmental DNA (an organism’s DNA that can be detected in the water) techniques, this project builds a broad network to implement a powerful traceability tool for marine fisheries. This project focuses on octopus (known as cephalopods), a fishery currently at severe risk due to unsustainable exploitation as an animal protein source. While the United States catches a fair number of octopus to supply the domestic market, it also relies on imports from both neighboring and distant countries. Regardless of origin, octopus products on the market should meet the same requirements of other seafoods to ensure consumer protection and fishery sustainability and reduced illegal fishing practices. This project will develop and pilot reliable tools to achieve these goals for the American market and consumers. Deliverables will also help to combat the fraudulent practice of species substitution – the dishonest labeling and selling of a cheap species under the name of an expensive one. Proper, easy to deploy and affordable environmental DNA traceability techniques will help combat this practice that damages the seafood management chain. Most importantly, this project will help make these tools and techniques available and affordable for octopus-exporting countries, thus allowing for critical check points through the supply chain – from the fishing net to the dinner plate. From a development perspective, it can help small-scale octopus harvesters in developing countries access the lucrative American market without facing tariff barriers to trade. This will promote fair trade practices. Ultimately, this project applies convergence research concepts that integrate knowledge, methods, and expertise across disciplines to advance science and lay the foundation for solving the simultaneous global challenges of food security, sustainable consumption, and marine resource conservation. Cephalopods are currently undergoing accelerating misuse and mismanagement with octopus species particularly vulnerable due to their exploitation as an important animal-derived protein. This problem originates from a dearth of data on octopus recruitment and a general lack of infrastructure within the fishery. Hence, the utility of traceability methods rooted in real-time detection and reliable predictions offer promise to robustly assess stocks and their potential for exploitation in the octopus seafood supply chain. Seafood traceability methods must be easily replicable and affordable for the management of seafood to control Illegal, Unreported and Unregulated fishing. Furthermore, transparent activities between the producers and the consumers will facilitate data collection under proper regulations and, ultimately, appropriate decisions towards stock improvements. This NSF Convergence Accelerator project will: (1) Develop a dashboard prototype traceability tool that allows affordable identification of species and area of capture for wild octopus fisheries within the United States and abroad using a machine learning model “SeaTraceBlueNet” trained on legacy data of environmental metadata, species occurrence and images; (2) Develop a community-based citizen-science network (fishers, researchers, industry partners, students, etc.) to gather new data (images, metadata and environmental DNA (eDNA)), train on and test the portable eDNA kits and SeaTraceBlueNet prototype to build the collaborative capacity to establish a standardized traceability system; and, (3) Set a system in place to connect traceability, sustainability and legality to support the development of a blue economy around the octopus value chain, incorporating the best practices and existing standards from stakeholders. This project is forward-thinking in drawing upon the perspective, ideas, expertise, and skillsets of the team members that represent a diversity of backgrounds, races, ethnicities, ages, and geographic regions. Over half of the team of co-PIs and Senior Personnel are women and/or persons of color. Most of the research team and industry partners are geographically located within the United States, yet this project is further strengthened by experts based in both developed and emerging nations as seafood traceability requires a global solution. Broadly, this project promotes coordinated use of multiple new and existing fisheries knowledge and data for transformative, accurate monitoring of key marine bioresources.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

提案# 2137582NSF 融合加速器轨道 E：创新海鲜可追溯网络，以实现可持续利用、改善市场准入和增强蓝色经济 解决养活不断增长的人口的全球挑战需要从海洋中找到解决方案，以防止过度捕捞及其负面影响再次发生。为了应对生态影响，主要渔业需要利用先进的机器学习计算机技术和环境 DNA（可以在水中检测到的生物体 DNA）重新构想监测和管理策略。该项目建立了一个广泛的网络，为海洋渔业实施强大的追溯工具。该项目重点关注章鱼（称为头足类动物），这种渔业目前由于作为动物蛋白来源的不可持续开发而面临严重风险。各国捕捞相当数量的章鱼供应国内市场，同时也依赖从邻国和遥远国家进口，无论产地如何，市场上的章鱼产品都应满足其他海产品的相同要求，以确保消费者的需求。该项目将为美国市场和消费者开发和试点实现这些目标的可靠工具，还将有助于打击物种替代的欺诈行为——不诚实的标签和廉价销售。适当、易于部署且负担得起的环境 DNA 追踪技术将有助于打击这种破坏海鲜管理链的做法。最重要的是，该项目将有助于使章鱼能够使用且负担得起这些工具和技术。出口国、因此，从发展的角度来看，它可以帮助发展中国家的小规模章鱼捕捞者进入利润丰厚的美国市场，而不会面临贸易关税壁垒。最终，该项目应用融合研究概念，整合跨学科的知识、方法和专业知识，以推进科学发展，并为解决粮食安全、可持续消费和海洋资源保护等全球挑战奠定基础。目前正在加速滥用由于章鱼作为一种重要的动物源性蛋白质而被利用，因此管理不善，这一问题源于章鱼招募数据的缺乏以及渔业内普遍缺乏基础设施。 - 时间检测和可靠的预测为强有力地评估章鱼海鲜供应链中的库存及其开发潜力提供了希望。海鲜追溯方法必须易于复制且负担得起，以便海鲜管理能够控制非法、未报告和非法捕捞。此外，生产者和消费者之间的透明活动将有助于在适当的监管下收集数据，并最终为种群改进做出适当的决策：(1) 开发一个仪表板原型可追溯工具，以实现经济实惠的识别。使用机器学习模型“SeaTraceBlueNet”，根据环境元数据、物种发生和图像的遗留数据进行训练，了解美国和国外野生章鱼渔业的物种和捕捞区域（2）开发基于社区的公民科学；网络（渔民、研究人员、行业合作伙伴、学生等）收集新数据（图像、元数据和环境 DNA (eDNA)），训练和测试便携式 eDNA 套件和 SeaTraceBlueNet 原型，以建立协作能力，建立标准化可追溯性系统；(3) 建立一个将可追溯性、可持续性和合法性联系起来的系统，以支持围绕章鱼价值链的蓝色经济的发展，纳入利益相关者的最佳实践和现有标准。在借鉴代表不同背景、种族、民族、年龄和地理区域的团队成员的观点、想法、专业知识和技能，超过一半的联合 PI 和高级人员是女性和/或个人。大多数研究团队和行业合作伙伴都位于美国，但由于海鲜可追溯性需要全球解决方案，因此该项目得到了发达国家和新兴国家专家的进一步加强。多种新的和现有的渔业知识和该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。