SBIR Phase I: CAS: Upcycling Farm-level Food Waste to Accelerate the Transition to a Circular Economy

这个小企业创新研究（SBIR）第一阶段项目利用创新的技术平台将农民和买家联系起来，促进农场层面食物垃圾的升级循环。在美国每年产生的一亿多吨食物垃圾中，估计有20%是由新鲜水果和蔬菜组成的，这些水果和蔬菜由于过剩或由于产品不符合严格的美学销售标准而在农场浪费。该项目将农民与美学无关的其他买家联系起来，为他们提供低成本的材料，并创建一个循环供应链。减少垃圾填埋场的食物将减少垃圾填埋场的甲烷排放。通过清洁空气、减少水和土壤污染以及改善人类健康，在垃圾填埋场周围的社区也将产生积极的环境影响。随着不美观和过剩的水果和蔬菜进入食品供应链，将有更多负担得起的食品，消除粮食不安全，促进社会公平。SBIR第一阶段项目结合了人工智能和强大的规范分析引擎，为减少农场食物浪费构建了一个创新的解决方案。该项目的主要创新是为客户创建一个材料价值评估数据库，以访问食物垃圾的已知和新的替代用途。验证可销售产品图像将保护客户责任并提高材料可追溯性。新的自定义分解优化将考虑产品老化，存储参数，运输时间表和整合以及运输物流，以解决农场级供应链挑战并优化运营。每笔交易也将获得碳当量减排量。除了这些功能之外，还将解决诸如高客户流量导致的服务中断和神经网络潜在性能差等障碍。该项目将解决大规模交易在优化农场、买家和运营物流方面的复杂性，为实现循环经济提供强大而重要的工具。该奖项反映了NSF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。

This Small Business Innovation Research (SBIR) Phase I project facilitates the upcycling of farm-level food waste using an innovative technological platform to connect farmers and buyers. Of the more than one hundred million tons of U.S. food waste generated yearly, an estimated twenty percent is comprised of fresh fruits and vegetables wasted at the farm level due to surplus or because the produce does not meet stringent aesthetic sales standards. This project connects farmers to additional buyers for whom aesthetics is not relevant, providing them with lower-cost materials and creating a circular supply chain. This reduction in food going to landfills will decrease methane emissions from landfills. Positive environmental impacts will also be discernible in the communities surrounding landfills through cleaner air, lessened water and soil contamination, and improved human health. As aesthetically imperfect and surplus fruits and vegetables enter the food supply chain, more affordable food will be available, combating food insecurity and promoting social fairness. This SBIR Phase I project combines artificial intelligence and a powerful prescriptive analytics engine to build an innovative solution for mitigating farm-level food waste. The project’s primary innovation is creating a material valorization database for customers to access known and new alternative uses for food waste. Verification of saleable produce images will protect customer liability and improve material traceability. Novel custom decomposition optimization will account for produce aging, storage parameters, shipping schedules and consolidation, and transportation logistics to address farm-level supply chain challenges and optimize operations. Carbon-equivalent emissions reductions will also be available for each transaction. Beyond these features, obstacles such as service outages from high customer traffic and poor potential performance from neural networks will also be addressed. The project will address the complexity of large-scale transactions in optimizing farms, buyers, and operation logistics, providing a powerful, vital tool for achieving a circular economy.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.