SBIR Phase II: Low-Power, Wireless Crop Quality Sensors for Grain Quality Preservation and Storage Automation

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The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to reduce postharvest loss due to toxins and insect damage while increasing the returns for farmers. In the US, an annual $3-5 billion dollars of crop value is lost due to toxin, insect and moisture mismanagement that could have been prevented through the introduction of affordable and accessible monitoring technology during product storage. Additionally, rising carbon dioxide levels in production agriculture create 14% of global greenhouse gas emissions. This project will validate the feasibility of low-power, wireless sensors that can detect grain storage conditions. The project will also enable buyers in the grain marketplace to ensure that the grain they are purchasing is, in fact, from fields where sustainable practices are implemented. This technology will help validate the feasibility of tracking grain across the supply chain to create trust and new business models around sustainability-verified grain. This Small Business Innovation Research (SBIR) Phase II project seeks to advance internet of things automation and wireless sensor applications as applied to production agriculture and the postharvest supply chain. There are certain manual processes of farm production that are strenuous due to time burdens and the lack of information available to make decisions. One such process is monitoring grain assets in farm bins, commercial storage, and barges, though this is important for the safety of the global food supply. This technology is focused on sensing for loss and spoilage risks and connecting and turning the data into automation opportunities. Cable-based monitoring solutions currently exist, but adoption is restricted due to physical installation limitations, electricity/power constraints, and investment costs. This project will validate the feasibility of low-power, wireless sensors that can detect grain conditions and last a full postharvest cycle (18 months). Such a device will create opportunities to track grain qualities across the agriculture value chain, advancing its current use in on-farm grain bins. By characterizing and testing smart kernel sensors this project will provide business model applications of tracking mechanisms in the grain supply chain.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.