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

HardwareX (Sep 2023)

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

Affiliations

Stephen Lantin: Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA; Corresponding author.
Kelli McCourt: Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA; Department of Environmental Engineering and Earth Science, Clemson University, SC 29634, USA
Nicholas Butcher: Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL 32611, USA
Varun Puri: Department of Computer and Information Sciences and Engineering, University of Florida, Gainesville, FL 32611, USA
Martha Esposito: Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA
Sasha Sanchez: Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA
Francisco Ramirez-Loza: Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA
Eric McLamore: Department of Agricultural Sciences, Clemson University, SC 29634, USA
Melanie Correll: Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA
Aditya Singh: Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA

Journal volume & issue: Vol. 15
p. e00468

Abstract

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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.

Published in HardwareX

ISSN: 2468-0672 (Online)
Publisher: Elsevier
Country of publisher: Netherlands
LCC subjects: Science: Science (General)
Website: https://www.journals.elsevier.com/hardwarex/

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