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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

Stuart A. Bagley

JONATHAN ATKINSON JONATHAN.ATKINSON@NOTTINGHAM.AC.UK
Future Food Beacon:Technologist in Phenomics

Henry Hunt

MICHAEL WILSON MICHAEL.WILSON@NOTTINGHAM.AC.UK
Future Food Beacon:Technologist in Bioinformatics/Computational Biology

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

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Low-Cost Automated Vectors (9.1 Mb)
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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/





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