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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | Tric Robotics Llc |
| Country | United States |
| Start Date | Jan 01, 2021 |
| End Date | Sep 30, 2021 |
| Duration | 272 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2036455 |
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to accelerate the transition from chemical pesticides to non-chemical alternatives by providing farmers with a sustainable, long-term solution for managing plant diseases (e.g., fungus), while reducing agricultural impacts on human health and the environment. Organic farms lack effective fungicide treatment methods resulting in high labor costs and increased risk of yield loss.
This project will develop a system for using ultraviolet light as an efficient and effective alternative for chemical treatments, by providing farmers with a healthier and more environmentally-conscious method for treating crops. The solution may eliminate chemical applications, reduce labor requirements, and increase profitability for farmers. Additionally, technologies developed as part of this project will minimize human exposure to chemical fungicides and greatly reduce the ecological damage caused by existing agricultural treatment practices.
This Small Business Innovation Research (SBIR) Phase I project seeks to understand how environmental and physical variabilities affect dosing of ultraviolet light in open-field strawberry production. Ultraviolet light has been shown to effectively treat pathogens including gray mold, for which there is no organically accepted treatment other than picking by hand.
Ultraviolet light can be used as a non-chemical alternative for treating pathogens but is not commercially feasible due to environmental and physical variabilities that affect treatment dosing. Excessive dosing damages plants and reduces yield, while insufficient dosing is ineffective. This project will advance agricultural best practices by developing the equipment and predictive software necessary for reliably applying ultraviolet treatment on commercial farms.
The project team will establish an experimental process for measuring multi-dimensional irradiance profiles as a function of physical and environmental factors, then use empirical data to establish functional relationships between variables and irradiance. Using real-time sensor feedback, the treatment system can automatically modulate exposure time and achieve desirable treatment dosing in open fields.
By developing the ability of maintaining ultraviolet treatment dosages, food can be grown reliably without dangerous and costly chemical applications.
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.
Tric Robotics Llc
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