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食品供应链的脆弱性，导致人们更加关注国内粮食和营养安全的风险。启发融合研究和新颖的数据驱动技术来解决当地和区域粮食系统的弹性问题。这项研究的结果将加深对当地粮食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。该项目将使获取民主化。到数据通过利用先进的人工智能和机器学习（AI/ML）技术的能力来获得洞察力，通过历史上确保包括有色人种农民和土著社区在内的受排斥群体的可用性来支持农村发展以及小农和粮食的经济生计。此外，增强对消费者洞察和市场渠道的了解将减少粮食损失并增强作物多样化，支持农业价值链的气候智能型弹性，更广泛地说，该技术将增加安全和营养丰富的当地食品的供应，支持综合健康。在美国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 Cultivate IQ 的低保真原型，这是一个数据驱动的技术平台，将增强区域粮食系统的弹性。该项目将构建平台组件，包括利用人工智能/机器学习改进计算模型来预测市场价格和需求，并向食品分销商（例如食品中心）和中小型农民提供其他生产和消费者数据见解。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将部署对粮食和营养安全这一重大挑战具有重大影响的技术解决方案，该项目旨在支持生产者获得盈利生产成本分析以及用户。 - 友好的仪表板，可提供食品供应链中关键决策点的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告知小型食品和农场。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情况。 Cultivate IQ 的植被指数以及对整个地区农田面积的估算将提高区域供应效率并支持生产规划，以满足对当地和可持续产品不断增长的需求。该奖项反映了 NSF 的法定使命，并被认为值得支持。通过使用基金会的智力价值和更广泛的影响审查标准进行评估。