Cultivating Adoption: Evaluating the Impact of Optical Leaf Sensors on Precision Agriculture Outcomes
This proposal presents the evaluation of optical leaf sensors for precision agriculture, designed to detect plant stress earlier than current methods. These color-changing sensors developed at Penn within the Internet of Things for Precision Agriculture (IoT4Ag), a U.S. NSF Engineering Research Center can fulfill a critical need for how we proactively manage farms. We aim to provide a low-cost, biodegradable, and battery-free solution for monitoring plant health, contrasting with existing expensive sensors and reactive yield mapping techniques. By quantifying the economic and environmental benefits through sensor scale-up, deployment, and stakeholder interviews, we seek to identify high-ROI crop-specific sensor targets and address barriers to market adoption. The proposal aims to correlate sensor data with potential resource savings, and policy recommendations to facilitate their widespread use in agriculture.
This grant is made possible by the Goldsmith Research Fund, a gift from Carl H. Goldsmith (W ‘88).
Akhila Mallavarapu
Postdoctoral Researcher, Cherie R Kagan Research GroupAkhila Mallavarapu is a postdoctoral researcher with the Cherie R Kagan Research Group in the School of Engineering and Applied Science.
