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

这个小型企业创新研究(SBIR)第一阶段项目利用一个创新的技术平台将农民和买家联系起来，促进农场级食物垃圾的上行循环。在美国每年产生的超过1亿吨的食物垃圾中，估计有20%是由于过剩或因为产品不符合严格的审美销售标准而在农场层面浪费的新鲜水果和蔬菜。这个项目将农民与其他与美学无关的买家联系起来，为他们提供更低成本的材料，并创建一个循环供应链。减少进入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，垃圾填埋场周围的社区也将产生积极的环境影响。随着审美上不完美和过剩的水果和蔬菜进入食品供应链，将获得更多负担得起的食品，打击粮食不安全，促进社会公平。这个SBIR第一阶段项目将人工智能和强大的规范分析引擎结合在一起，构建了一个减少农场级食物浪费的创新解决方案。该项目的主要创新是创建一个材料计价数据库，供客户访问食物垃圾的已知和新的替代用途。验证可销售的产品图像将保护客户责任并提高材料可追溯性。新颖的定制分解优化将考虑到产品老化、存储参数、发货计划和整合以及运输物流，以应对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。除了这些功能外，还将解决高客户流量造成的服务中断和神经网络潜在性能较差等障碍。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一个强大而重要的工具。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.