Stuart A. Bagley
Low-cost automated vectors and modular environmental sensors for plant phenotyping
Bagley, Stuart A.; Atkinson, Jonathan A.; Hunt, Henry; Wilson, Michael H.; Pridmore, Tony P.; Wells, Darren M.
Authors
JONATHAN ATKINSON JONATHAN.ATKINSON@NOTTINGHAM.AC.UK
Assistant Professor
Henry Hunt
MICHAEL WILSON MICHAEL.WILSON@NOTTINGHAM.AC.UK
Technical Manager
TONY PRIDMORE tony.pridmore@nottingham.ac.uk
Professor of Computer Science
DARREN WELLS DARREN.WELLS@NOTTINGHAM.AC.UK
Principal Research Fellow
Abstract
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. High-throughput plant phenotyping in controlled environments (growth chambers and glasshouses) is often delivered via large, expensive installations, leading to limited access and the increased relevance of “affordable phenotyping” solutions. We present two robot vectors for automated plant phenotyping under controlled conditions. Using 3D-printed components and readily-available hardware and electronic components, these designs are inexpensive, flexible and easily modified to multiple tasks. We present a design for a thermal imaging robot for high-precision time-lapse imaging of canopies and a Plate Imager for high-throughput phenotyping of roots and shoots of plants grown on media plates. Phenotyping in controlled conditions requires multi-position spatial and temporal monitoring of environmental conditions. We also present a low-cost sensor platform for environmental monitoring based on inexpensive sensors, microcontrollers and internet-of-things (IoT) protocols.
Citation
Bagley, S. A., Atkinson, J. A., Hunt, H., Wilson, M. H., Pridmore, T. P., & Wells, D. M. (2020). Low-cost automated vectors and modular environmental sensors for plant phenotyping. Sensors, 20(11), https://doi.org/10.3390/s20113319
Journal Article Type | Article |
---|---|
Acceptance Date | Jun 9, 2020 |
Online Publication Date | Jun 11, 2020 |
Publication Date | Jun 1, 2020 |
Deposit Date | Jun 21, 2020 |
Publicly Available Date | Jun 22, 2020 |
Journal | Sensors |
Print ISSN | 1424-8220 |
Electronic ISSN | 1424-8220 |
Publisher | MDPI |
Peer Reviewed | Peer Reviewed |
Volume | 20 |
Issue | 11 |
Article Number | 3319 |
DOI | https://doi.org/10.3390/s20113319 |
Public URL | https://nottingham-repository.worktribe.com/output/4693070 |
Publisher URL | https://www.mdpi.com/1424-8220/20/11/3319 |
Files
Low-Cost Automated Vectors
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PDF
Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
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