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.

与全球大流行病、冲突和气候变化有关的粮食供应中断暴露了全球化农业粮食供应链的脆弱性，导致人们更加关注国内粮食和营养安全面临的风险。该项目将推进以用途为灵感的融合研究和新型数据驱动技术的实践，以解决地方和区域粮食系统的弹性问题。这项研究的结果将扩大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。该项目将通过利用先进的人工智能和机器学习（AI/ML）技术的能力，使数据洞察的访问民主化，确保历史上被排斥的群体（包括有色人种农民和土著社区）的可用性。所开发的技术将支持农村发展以及小农和食品企业的经济生计。此外，加强对消费者见解和市场渠道的了解将减少粮食损失，促进作物多样化，支持农业价值链的气候智慧型抵御能力。更广泛地说，这项技术将增加安全、营养的当地食品的供应，支持美国社区的综合健康。这个以使用为灵感的研究项目的第一阶段需要对用户需求进行广泛调查，并开发低保真度的“培养IQ”原型，这是一个数据驱动的技术平台，将加强区域粮食系统的弹性。在第二阶段，我们将构建平台组件，包括改进利用AI/ML预测市场价格和需求的计算模型，并向食品分销商（如食品中心）和中小型农民提供其他生产和消费者数据见解。项目团队包括学术和行业合作伙伴以及来自公共和私营部门的主要合作者，他们将大规模部署技术解决方案，对粮食和营养安全的重大挑战产生重大影响。该项目旨在支持生产者获得生产成本盈利能力分析，以及用户友好的仪表板，以便在食品供应链的关键决策点上获得与地理相关且可操作的数据见解，例如特种作物（水果、蔬菜和坚果）、区域种植和加工肉类以及增值产品的价格和消费者需求预测。这些关键数据将通过利用人工智能/机器学习技术（如未来食品需求的预测模型）为小型食品和农场的商业决策提供信息。此外，该技术将利用人工智能/机器学习计算机视觉的进步，以及地理空间技术和图像，来分析作物，包括识别作物类型和异常、植被指数，以及估计整个地区的农田面积。培养IQ的市场洞察力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不断增长的需求。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。