Low-Cost Automated Vectors and Modular Environmental Sensors for Plant Phenotyping
1
Integrated Phenomics Group, School of Biosciences, University of Nottingham, Sutton Bonington Campus, Sutton Bonington LE12 5RD, UK
2
Future Food Beacon, School of Biosciences, University of Nottingham, Sutton Bonington Campus, Sutton Bonington LE12 5RD, UK
3
School of Computer Science, University of Nottingham, Nottingham NG8 1BB, UK
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(11), 3319; https://doi.org/10.3390/s20113319
Received: 9 May 2020
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Revised: 5 June 2020
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Accepted: 9 June 2020
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Published: 11 June 2020
(This article belongs to the Special Issue Low-Cost Sensors and Vectors for Plant Phenotyping)
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.
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Keywords:
phenotyping robots; 3D printing; phenomics vectors; IoT sensors
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MDPI and ACS Style
Bagley, S.A.; Atkinson, J.A.; Hunt, H.; Wilson, M.H.; Pridmore, T.P.; Wells, D.M. Low-Cost Automated Vectors and Modular Environmental Sensors for Plant Phenotyping. Sensors 2020, 20, 3319. https://doi.org/10.3390/s20113319
AMA Style
Bagley SA, Atkinson JA, Hunt H, Wilson MH, Pridmore TP, Wells DM. Low-Cost Automated Vectors and Modular Environmental Sensors for Plant Phenotyping. Sensors. 2020; 20(11):3319. https://doi.org/10.3390/s20113319
Chicago/Turabian StyleBagley, Stuart A., Jonathan A. Atkinson, Henry Hunt, Michael H. Wilson, Tony P. Pridmore, and Darren M. Wells. 2020. "Low-Cost Automated Vectors and Modular Environmental Sensors for Plant Phenotyping" Sensors 20, no. 11: 3319. https://doi.org/10.3390/s20113319
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