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Assessing plant performance in the Enviratron

BACKGROUND: Assessing the impact of the environment on plant performance requires growing plants under controlled environmental conditions. Plant phenotypes are a product of genotype × environment (G × E), and the Enviratron at Iowa State University is a facility for testing under controlled conditi...

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Autores principales: Bao, Yin, Zarecor, Scott, Shah, Dylan, Tuel, Taylor, Campbell, Darwin A., Chapman, Antony V. E., Imberti, David, Kiekhaefer, Daniel, Imberti, Henry, Lübberstedt, Thomas, Yin, Yanhai, Nettleton, Dan, Lawrence-Dill, Carolyn J., Whitham, Steven A., Tang, Lie, Howell, Stephen H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6806530/
https://www.ncbi.nlm.nih.gov/pubmed/31660060
http://dx.doi.org/10.1186/s13007-019-0504-y
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author Bao, Yin
Zarecor, Scott
Shah, Dylan
Tuel, Taylor
Campbell, Darwin A.
Chapman, Antony V. E.
Imberti, David
Kiekhaefer, Daniel
Imberti, Henry
Lübberstedt, Thomas
Yin, Yanhai
Nettleton, Dan
Lawrence-Dill, Carolyn J.
Whitham, Steven A.
Tang, Lie
Howell, Stephen H.
author_facet Bao, Yin
Zarecor, Scott
Shah, Dylan
Tuel, Taylor
Campbell, Darwin A.
Chapman, Antony V. E.
Imberti, David
Kiekhaefer, Daniel
Imberti, Henry
Lübberstedt, Thomas
Yin, Yanhai
Nettleton, Dan
Lawrence-Dill, Carolyn J.
Whitham, Steven A.
Tang, Lie
Howell, Stephen H.
author_sort Bao, Yin
collection PubMed
description BACKGROUND: Assessing the impact of the environment on plant performance requires growing plants under controlled environmental conditions. Plant phenotypes are a product of genotype × environment (G × E), and the Enviratron at Iowa State University is a facility for testing under controlled conditions the effects of the environment on plant growth and development. Crop plants (including maize) can be grown to maturity in the Enviratron, and the performance of plants under different environmental conditions can be monitored 24 h per day, 7 days per week throughout the growth cycle. RESULTS: The Enviratron is an array of custom-designed plant growth chambers that simulate different environmental conditions coupled with precise sensor-based phenotypic measurements carried out by a robotic rover. The rover has workflow instructions to periodically visit plants growing in the different chambers where it measures various growth and physiological parameters. The rover consists of an unmanned ground vehicle, an industrial robotic arm and an array of sensors including RGB, visible and near infrared (VNIR) hyperspectral, thermal, and time-of-flight (ToF) cameras, laser profilometer and pulse-amplitude modulated (PAM) fluorometer. The sensors are autonomously positioned for detecting leaves in the plant canopy, collecting various physiological measurements based on computer vision algorithms and planning motion via “eye-in-hand” movement control of the robotic arm. In particular, the automated leaf probing function that allows the precise placement of sensor probes on leaf surfaces presents a unique advantage of the Enviratron system over other types of plant phenotyping systems. CONCLUSIONS: The Enviratron offers a new level of control over plant growth parameters and optimizes positioning and timing of sensor-based phenotypic measurements. Plant phenotypes in the Enviratron are measured in situ—in that the rover takes sensors to the plants rather than moving plants to the sensors.
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spelling pubmed-68065302019-10-28 Assessing plant performance in the Enviratron Bao, Yin Zarecor, Scott Shah, Dylan Tuel, Taylor Campbell, Darwin A. Chapman, Antony V. E. Imberti, David Kiekhaefer, Daniel Imberti, Henry Lübberstedt, Thomas Yin, Yanhai Nettleton, Dan Lawrence-Dill, Carolyn J. Whitham, Steven A. Tang, Lie Howell, Stephen H. Plant Methods Research BACKGROUND: Assessing the impact of the environment on plant performance requires growing plants under controlled environmental conditions. Plant phenotypes are a product of genotype × environment (G × E), and the Enviratron at Iowa State University is a facility for testing under controlled conditions the effects of the environment on plant growth and development. Crop plants (including maize) can be grown to maturity in the Enviratron, and the performance of plants under different environmental conditions can be monitored 24 h per day, 7 days per week throughout the growth cycle. RESULTS: The Enviratron is an array of custom-designed plant growth chambers that simulate different environmental conditions coupled with precise sensor-based phenotypic measurements carried out by a robotic rover. The rover has workflow instructions to periodically visit plants growing in the different chambers where it measures various growth and physiological parameters. The rover consists of an unmanned ground vehicle, an industrial robotic arm and an array of sensors including RGB, visible and near infrared (VNIR) hyperspectral, thermal, and time-of-flight (ToF) cameras, laser profilometer and pulse-amplitude modulated (PAM) fluorometer. The sensors are autonomously positioned for detecting leaves in the plant canopy, collecting various physiological measurements based on computer vision algorithms and planning motion via “eye-in-hand” movement control of the robotic arm. In particular, the automated leaf probing function that allows the precise placement of sensor probes on leaf surfaces presents a unique advantage of the Enviratron system over other types of plant phenotyping systems. CONCLUSIONS: The Enviratron offers a new level of control over plant growth parameters and optimizes positioning and timing of sensor-based phenotypic measurements. Plant phenotypes in the Enviratron are measured in situ—in that the rover takes sensors to the plants rather than moving plants to the sensors. BioMed Central 2019-10-23 /pmc/articles/PMC6806530/ /pubmed/31660060 http://dx.doi.org/10.1186/s13007-019-0504-y Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Bao, Yin
Zarecor, Scott
Shah, Dylan
Tuel, Taylor
Campbell, Darwin A.
Chapman, Antony V. E.
Imberti, David
Kiekhaefer, Daniel
Imberti, Henry
Lübberstedt, Thomas
Yin, Yanhai
Nettleton, Dan
Lawrence-Dill, Carolyn J.
Whitham, Steven A.
Tang, Lie
Howell, Stephen H.
Assessing plant performance in the Enviratron
title Assessing plant performance in the Enviratron
title_full Assessing plant performance in the Enviratron
title_fullStr Assessing plant performance in the Enviratron
title_full_unstemmed Assessing plant performance in the Enviratron
title_short Assessing plant performance in the Enviratron
title_sort assessing plant performance in the enviratron
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6806530/
https://www.ncbi.nlm.nih.gov/pubmed/31660060
http://dx.doi.org/10.1186/s13007-019-0504-y
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