NSF Convergence Accelerator Track J Phase 2: Cultivate IQ - Empowering Regional Food Systems

NSF 融合加速器轨道 J 第 2 阶段：培养智商 - 增强区域粮食系统能力

• 批准号: 2345176
• 负责人: Meredith Adkins
• 金额: $ 499.88万
• 依托单位: University of Arkansas
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-12-15 至 2026-11-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2345176&HistoricalAwards=false
• 关键词: NSF; Convergence; Accelerator; Track; Phase

Disruptions in food supply linked to the global pandemic, conflict, and climate change have exposed vulnerabilities in the globalized agricultural-food supply chain resulting in an increased focus on the risks to domestic food and nutrition security. This project will advance the practice of use-inspired convergence research and novel data-driven techniques to address the resiliency of local and regional food systems. Findings from this research will extend understanding of barriers to wholesale and institutional procurement of local food and how technological solutions can be employed. This project will democratize access to data insights by harnessing the capabilities of advanced Artificial Intelligence and Machine Learning (AI/ML) techniques, ensuring usability by historically excluded groups, including farmers of color and indigenous communities. The technology developed will support rural development and the economic livelihoods of small farmers and food businesses. Furthermore, enhanced knowledge of consumer insights and market channels will reduce food losses and enhance crop diversification, supporting climate-smart resiliency in agricultural value chains. More broadly, the technology will increase the availability of safe and nutritious local food, supporting integrative health in American communities.The first phase of this use-inspired research project entailed extensive investigation of user needs and low-fidelity prototype development of Cultivate IQ, a data-driven technology platform that will strengthen the resiliency of regional food systems. In the second phase, we will build the platform components, including refinement of the computational models leveraging AI/ML to forecast market prices and demand, and deliver other production and consumer data insights to food distributors, such as food hubs, and small and mid-sized farmers. The project team includes academic and industry partners and key collaborators from the public and private sector who will deploy a technology solution at a scale that has significant implications for the grand challenge of food and nutrition security. The project aims to support producers’ access to cost of production profitability analysis, as well as user-friendly dashboards for geographically relevant and actionable data insights across key decision points in the food supply chain, such as price and consumer demand forecasting for specialty crops (fruits, vegetables, and nuts), regionally grown and processed meat, and value-added products. This key data will inform small food and farm business decisions by utilizing AI/ML techniques such as predictive models for future food demand. Additionally, the technology will leverage advances in AI/ML computer vision, alongside geospatial technologies and imagery, to analyze crops, including the identification of crop types and anomalies, vegetation index, and the estimation of cropland sizes across a region. Cultivate IQ’s market insights will create regional supply efficiencies and support production planning to meet the growing demand for local and sustainable products.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.

与全球大流行，冲突和气候变化有关的粮食供应中断，在全球化的农业食品供应链中暴露了脆弱性，从而增加关注家庭食品和营养安全的风险。该项目将推进使用启发的融合研究和新型数据驱动技术的实践，以解决本地和区域食品系统的弹性。这项研究的发现将扩展对当地食品批发和机构采购的障碍以及如何采用技术解决方案的理解。该项目将通过利用高级人工智能和机器学习（AI/ML）技术的能力来使对数据见解的访问权限，从而确保了历史上排除的群体（包括有色和土著社区的农民）的可用性。开发的技术将支持小型农民和食品企业的粗暴发展和经济生计。此外，对消费者见解和市场渠道的增强知识将减少粮食损失并增强作物多样性，从而支持农业价值链的攀登弹性弹性。从更广泛的角度来看，该技术将增加安全和营养的当地食品的可用性，从而支持美国社区的综合健康。该用途启发的研究项目的第一阶段是对用户需求的广泛投资和低保真原型培养智商的开发，这是一个数据驱动的技术平台，可以增强区域食品系统的弹性。在第二阶段，我们将构建平台组件，包括利用AI/ML预测市场价格和需求的计算模型，并将其他生产和消费者数据见解提供给食品分销商，例如食品枢纽，以及中小型中型农民。该项目团队包括公共和私营部门的学术和行业合作伙伴以及主要合作者，他们将以对食品和营养安全的巨大挑战具有重要意义的技术解决方案。该项目旨在支持生产商访问生产成本的润肤优雅分析，以及用户友好的仪表板，以跨食品供应链中的关键决策点在地理上相关且可操作的数据见解，例如价格和消费者需求预测特种作物（水果，蔬菜和坚果），区域性和加工的肉类和加工的肉类和价值的产品。这些关键数据将通过使用AI/ML技术（例如预测模型来满足未来的食品需求）来为小食品和农场业务决策提供信息。此外，该技术将利用AI/ML计算机视觉的进步以及地理空间技术和图像，分析农作物，包括鉴定作物类型和异常，植被指数以及整个地区的农作物规模的估计。培养智商的市场见解将创造区域供应效率并支持生产计划，以满足对本地和可持续产品的不断增长的需求。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响审查标准，认为通过评估来获得珍贵的支持。