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

Award ID: 2335238

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 projects 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.

NSF Program Director: Rajesh Mehta