SPOT: Scanning plant IoT facility for high-throughput plant phenotyping

Stephen Lantin; Kelli McCourt; Nicholas Butcher; Varun Puri; Martha Esposito; Sasha Sanchez; Francisco Ramirez-Loza; Eric McLamore; Melanie Correll; Aditya Singh

doi:10.1016/j.ohx.2023.e00468

SPOT: Scanning plant IoT facility for high-throughput plant phenotyping

HardwareX. 2023 Aug 26:15:e00468. doi: 10.1016/j.ohx.2023.e00468. eCollection 2023 Sep.

Authors

Affiliations

¹ Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA.
² Department of Environmental Engineering and Earth Science, Clemson University, SC 29634, USA.
³ Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL 32611, USA.
⁴ Department of Computer and Information Sciences and Engineering, University of Florida, Gainesville, FL 32611, USA.
⁵ Department of Agricultural Sciences, Clemson University, SC 29634, USA.

Abstract

Many plant phenotyping platforms have been kept out of the reach of smaller labs and institutions due to high cost and proprietary software. The Scanning Plant IoT (SPOT) Facility, located at the University of Florida, is a mobile, laboratory-based platform that facilitates open-source collection of high-quality, interoperable plant phenotypic data. It consists of three main sensors: a hyperspectral sensor, a thermal camera, and a LiDAR camera. Real-time data from the sensors can be collected in its 10 ft. × 10 ft. scanning region. The mobility of the device allows its use in large growth chambers, environmentally controlled rooms, or greenhouses. Sensors are oriented nadir and positioned via computer numerical control of stepper motors. In a preliminary experiment, data gathered from SPOT was used to autonomously and nondestructively differentiate between cultivars.

Keywords: Hyperspectral imaging; Plant breeding; Plant phenotyping; Remote sensing; Thermal imaging.