NSF Convergence Accelerator Track E: Empowering Stakeholders from Ship to Store--Solving Fishery Management Challenges with Use-Inspired Genomic and Artificial Intelligence Tools

NSF 融合加速器轨道 E：为从船舶到商店的利益相关者提供支持——利用受使用启发的基因组和人工智能工具解决渔业管理挑战

• 批准号: 2137766
• 负责人: Mariah Meek
• 金额: $ 74.93万
• 依托单位: Michigan State 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 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2137766&HistoricalAwards=false
• 关键词: NSF; Convergence; Accelerator; Track; Empowering

Title: NSF Convergence Accelerator Track E: Empowering stakeholders from ship to store-- solving fishery management challenges with use-inspired genomic and artificial intelligence tools The seafood sector is playing a rapidly expanding role in global food security. However, in the last 30 years the proportion of global fish stocks experiencing sustainable levels of harvest has dropped from 90% to 66%. Illegal, unreported, and unregulated fishing is a major roadblock to sustainable seafood harvest. In particular, effectively monitoring fisheries practices and enforcing existing regulations hinges on the ability to accurately identify species, but many species share similar morphological characteristics and can be difficult to distinguish. The focus of this Convergence Accelerator project is to harness the power of genomics to develop low-cost, rapid, field-deployable species identification test kits that can be implemented throughout seafood supply chains to genetically verify seafood products that are difficult to visually identify, including whole fish, fillets, and fins. These genetic identification test kits will be integrated with cutting-edge artificial intelligence capabilities via a smartphone app to drastically increase the speed and accuracy of testing and enable real-time monitoring of fisheries production. To ensure widespread implementation and use-inspired design focused on practical applications, the research team comprises a network of end users representing federal and state agencies, non-governmental organizations, and private industry to test prototypes, provide feedback for improvement, and integrate tools into fisheries and seafood sectors. The research team will also work alongside organizations to promote sustainably sourced seafood by providing a simple method to label and market catch, thus empowering local communities and small-scale fisheries to better compete in the marketplace. Additionally, to engage the public in sustainable seafood practices, high school and undergraduate students will be directly involved in developing and testing genomic and artificial intelligence tools. Further, self-contained teaching and laboratory modules will be developed and made broadly available to teachers, specifically targeting schools in underserved and fishing communities. The simplicity of the genomic test kits and smartphone app integration will make information on fisheries practices and seafood supply chains accessible to the general public, equipping consumers to make informed decisions about seafood consumption. These public education efforts will be furthered by collaborations with prominent U.S. aquariums for educational outreach in dedicated exhibitions.The ability to confidently identify species is of fundamental importance to the study of biology. However, confirming species identity in organisms with conserved morphologies, or in specimens where diagnostic morphological features have been removed, often requires specialized equipment and expertise. This not only complicates biological and ecological studies but also creates major roadblocks for the sustainable use of natural resources. Difficulty distinguishing species is a particular problem in fisheries management, where accurate species identification is crucial to quantify and monitor levels of harvest, identify illegal harvest, and determine and monitor species’ conservation status. In particular, accurate determination of species identity is central to implementing effective strategies to counteract illegal, unreported, and unregulated fishing practices and tracing seafood products throughout complex seafood supply chains to enforce regulations. This Convergence Accelerator project combines cutting-edge genomics (the CRISPR-Cas13a Specific High-sensitivity Enzymatic Reporter unLOCKing system) and artificial intelligence capabilities to develop low-cost, rapid, field-deployable species identification tools. During Phase I of this project, the research team will prototype CRISPR-Cas13a assays paired with a visual and contextual artificial intelligence smartphone app for three species pairs to develop an efficient workflow for tool design and implementation. This combined technology has the potential for widespread application, for example, in seafood supply chains where the species identity of seafood products is difficult to visually determine, including for whole fish, fillets, and fins. Concurrently, the research team will establish a multidisciplinary network of partnerships and end users to support a convergence research approach that inspires product development, customization, and implementation by bringing together members of academia, state and federal agencies, private industry, and non-governmental organizations. During Phase I, this network will be built to ensure that tool development is tailored to the needs of end users for maximum efficiency and ease of use to pioneer breakthroughs in combating illegal, unreported, and unregulated fishing. Additionally, this project will increase the public understanding of genomics, artificial intelligence, and sustainable use of ocean resources by engaging citizens through newly developed outreach programs at prominent U.S. aquariums. Finally, this research will contribute to training a diverse workforce by directly involving high school and undergraduate students from traditionally underserved communities. The project team will also develop self-contained teaching and laboratory modules that will be made broadly available to teachers, specifically targeting schools in underserved and fishing communities.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.

标题：NSF融合加速器轨道E：从船舶到商店赋予利益相关者权力--利用受使用启发的基因组和人工智能工具解决渔业管理挑战海鲜行业在全球食品安全中发挥着迅速扩大的作用。然而，在过去30年中，全球鱼类种群经历可持续捕捞水平的比例从90%下降到66%。非法、未报告和无管制的捕捞是海产品可持续收获的主要障碍。特别是，有效监测渔业做法和执行现有法规取决于准确识别物种的能力，但许多物种具有相似的形态特征，可能很难区分。这一融合加速器项目的重点是利用基因组学的力量开发低成本、快速、可现场部署的物种鉴定检测试剂盒，该试剂盒可在整个海产品供应链中实施，以对难以肉眼识别的海产品进行基因验证，包括整条鱼、鱼片和鳍。这些遗传鉴定检测试剂盒将通过智能手机应用程序与尖端的人工智能能力相集成，以大幅提高检测的速度和准确性，并实现对渔业生产的实时监测。为了确保注重实际应用的广泛实施和以使用为灵感的设计，研究团队由代表联邦和州机构、非政府组织和私营行业的最终用户网络组成，以测试原型，提供改进反馈，并将工具整合到渔业和海鲜部门。研究小组还将与各组织合作，通过提供一种简单的方法来标记和销售渔获物，从而促进可持续来源的海鲜，从而使当地社区和小型渔业能够更好地在市场上竞争。此外，为了让公众参与可持续的海鲜实践，高中生和本科生将直接参与开发和测试基因组和人工智能工具。此外，将开发自给自足的教学和实验室单元，并向教师广泛提供，特别是针对服务不足和渔业社区的学校。基因组检测试剂盒的简单性和智能手机应用程序的集成将使公众能够获得有关渔业做法和海鲜供应链的信息，使消费者能够在知情的情况下做出关于海鲜消费的决定。这些公共教育工作将通过与著名的美国水族馆合作，在专门的展览中进行教育推广来进一步推进。自信地识别物种的能力对生物学研究至关重要。然而，在具有保守形态的生物体中或在已去除诊断形态特征的标本中确认物种特性，往往需要专门的设备和专业知识。这不仅使生物学和生态学研究复杂化，而且为自然资源的可持续利用制造了重大障碍。难以区分物种是渔业管理中的一个特殊问题，准确的物种识别对于量化和监测捕捞水平、识别非法捕捞以及确定和监测物种的养护状态至关重要。特别是，准确确定物种身份是实施有效战略的核心，以打击非法、未报告和无管制的捕捞做法，并在复杂的海产品供应链中追踪海产品，以执行法规。这一融合加速器项目结合了尖端基因组学(CRISPR-Cas13a特定高灵敏度酶报告解锁系统)和人工智能能力，以开发低成本、快速、可现场部署的物种识别工具。在该项目的第一阶段，研究团队将针对三个物种对将CRISPR-Cas13a分析与视觉和上下文人工智能智能应用程序配对，以开发高效的工具设计和实施工作流程。这一结合技术具有广泛应用的潜力，例如，在海产品供应链中，很难用肉眼确定海产品的物种身份，包括整条鱼、鱼片和鳍。同时，研究团队将建立一个由伙伴关系和最终用户组成的多学科网络，以支持融合研究方法，通过将学术界、州和联邦机构、私营行业和非政府组织的成员聚集在一起，激励产品开发、定制和实施。在第一阶段，将建立这个网络，以确保工具的开发符合最终用户对最大效率和易用性的需求，以率先在打击非法、未报告和无管制的捕捞活动方面取得突破。此外，该项目将通过在美国著名水族馆新开发的外展项目吸引公民参与，从而增加公众对基因组学、人工智能和海洋资源可持续利用的理解。最后，这项研究将通过直接让来自传统上缺乏服务的社区的高中生和本科生参与进来，为培训多样化的劳动力做出贡献。该项目团队还将开发独立的教学和实验室模块，将广泛提供给教师，特别是针对服务不足和渔业社区的学校。这一奖项反映了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。