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收敛加速器轨道E：通过使用采用启发的基因组和人工智能工具来解决利益相关者从船上到商店 - 解决渔业管理挑战。海鲜部门在全球粮食安全中正在迅速扩大角色。但是，在过去的30年中，经历可持续收获水平的全球鱼类股票比例从90％下降到66％。非法，未报告和不受管制的捕鱼是可持续海鲜收获的主要障碍。特别是，有效地监测渔业实践并执行现有的法规取决于准确识别物种的能力，但是许多物种具有相似的形态特征，并且很难区分。该收敛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，可见的可替代物种鉴定测试试剂盒，这些测试试剂盒可以在整个海鲜供应链中实施，以在遗传上验证很难在视觉上识别的海鲜产品，包括全鱼，菲尔斯和鳍。这些遗传识别测试套件将通过智能手机应用程序与尖端的人工智能功能集成，以极大地提高测试的速度和准确性，并实现对渔业生产的实时监控。为了确保以实用应用为重点的宽度实施和使用启发式设计，研究团队包括代表联邦和州机构，非政府组织以及测试原型的私人行业的最终用户网络，为改进提供了反馈，并将其集成到渔业和海洋餐饮领域中。研究团队还将通过提供一种简单的标签和市场捕捞量的方法来与组织一起促进可持续采购的海鲜，从而赋予当地社区和小规模渔业，以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，将开发并为教师提供广泛的教学和实验室模块，特别是针对服务不足和捕鱼社区的学校。基因组测试套件和智能手机应用程序集成的简单性将提供有关渔业实践和海鲜供应链的信息，可供公众使用，使消费者为消费者做出有关海鲜消费的明智决定。这些公共教育工作将通过与美国著名水族馆进行专门展览中的教育外展的合作来进一步进一步，自信地识别物种的能力对于生物学研究至关重要。但是，清除了诊断形态特征的样本中，确认具有构成形态的生物体中的物种认同，通常需要专业的设备和专业知识。这不仅使生物学和生态学研究复杂化，而且为可持续使用自然资源创造了主要的障碍。难以区分物种是渔业管理中的一个特殊问题，在渔业管理中，准确的物种鉴定对于量化和监测收获水平，确定非法收获以及确定和监测物种的保护状况至关重要。特别是，对物种认同的准确确定对于实施有效的策略来抵消非法，未报告和不受管制的捕鱼实践以及在整个复杂的海鲜供应链中实施海鲜产品以执行调节的有效策略至关重要。该收敛加速器项目结合了最先进的基因组学（CRISPR-CAS13A特定的高敏化酶报告器解锁系统）和人工智能功能，以开发低成本，快速，野外剥夺的规格标识工具。在该项目的第一阶段，研究团队将原型CRISPR-CAS13A分析与三种物种对的视觉和上下文人工智能智能手机应用程序配对，以开发有效的工具设计和实现的工作流程。这种组合的技术具有宽度应用的潜力，例如，在海鲜供应链中，海鲜产品的物种标识很难在视觉上确定，包括全鱼，鱼片和鳍。同时，研究团队将建立一个多学科的合作伙伴关系网络和最终用户，以支持一种融合研究方法，通过将学术界，州和联邦机构，私营企业和非政府组织的成员汇集在一起​​，从而激发产品开发，定制和实施。在第一阶段，将建立该网络，以确保对最终用户的需求量身定制工具开发，以最大程度地效率，并易于使用非法，未报告和不受管制的捕鱼来打击突破性。此外，该项目将通过在美国著名水族馆通过新开发的外展计划吸引公民来增加公众对基因组学，人工智能和可持续使用海洋资源的理解。最后，这项研究将有助于培训从传统服务不足社区的高中和本科生的直接参与的潜水员劳动力。该项目团队还将开发独立的教学和实验室模块，这些模块将为教师提供广泛的可用，特别是针对服务不足和捕鱼社区的学校。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的影响审查标准通过评估来获得的支持。