Assessing plant performance in the Enviratron

dc.contributor.author Bao, Yin
dc.contributor.author Zarecor, Scott
dc.contributor.author Tang, Lie
dc.contributor.author Shah, Dylan
dc.contributor.author Lubberstedt, Thomas
dc.contributor.author Tuel, Taylor
dc.contributor.author Campbell, Darwin
dc.contributor.author Chapman, Antony
dc.contributor.author Imberti, David
dc.contributor.author Kiekhaefer, Daniel
dc.contributor.author Whitham, Steven
dc.contributor.author Imberti, Henry
dc.contributor.author Nettleton, Dan
dc.contributor.author Yin, Yanhai
dc.contributor.author Lawrence-Dill, Carolyn
dc.contributor.author Howell, Stephen
dc.contributor.department Plant Pathology and Microbiology
dc.contributor.department Department of Agronomy
dc.contributor.department Statistics (LAS)
dc.contributor.department Department of Genetics, Development, and Cell Biology (LAS)
dc.contributor.department Department of Agricultural and Biosystems Engineering (ENG)
dc.contributor.department Human Computer Interaction
dc.contributor.department Plant Sciences Institute
dc.date 2019-10-28T15:44:47.000
dc.date.accessioned 2020-06-29T22:36:46Z
dc.date.available 2020-06-29T22:36:46Z
dc.date.copyright Tue Jan 01 00:00:00 UTC 2019
dc.date.issued 2019-12-01
dc.description.abstract <p>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.</p> <p>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.</p> <p>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.</p>
dc.description.comments <p>This article is published as Bao, Yin, Scott Zarecor, Dylan Shah, Taylor Tuel, Darwin A. Campbell, Antony VE Chapman, David Imberti, Daniel Kiekhaefer, Henry Imberti, Thomas Lübberstedt, Yanhai Yin, Dan Nettleton, Carolyn J. Lawrence‑Dill, Steven A. Whitham, Lie Tang, and Stephen H. Howell. "Assessing plant performance in the Enviratron." <em>Plant Methods</em> 15, no. 1 (2019): 117. DOI: <a href="http://dx.doi.org/10.1186/s13007-019-0504-y" target="_blank">10.1186/s13007-019-0504-y</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/abe_eng_pubs/1088/
dc.identifier.articleid 2373
dc.identifier.contextkey 15634608
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath abe_eng_pubs/1088
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/787
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/abe_eng_pubs/1088/2019_TangLie_AssessingPlant.pdf|||Fri Jan 14 18:29:52 UTC 2022
dc.source.uri 10.1186/s13007-019-0504-y
dc.subject.disciplines Agronomy and Crop Sciences
dc.subject.disciplines Bioresource and Agricultural Engineering
dc.subject.disciplines Plant Breeding and Genetics
dc.subject.disciplines Plant Pathology
dc.subject.disciplines Statistics and Probability
dc.subject.keywords Environment
dc.subject.keywords Climate change
dc.subject.keywords Crop plants
dc.subject.keywords Growth chambers
dc.subject.keywords Robot
dc.subject.keywords Hyperspectral imaging
dc.subject.keywords PAM-fluorometry
dc.title Assessing plant performance in the Enviratron
dc.type article
dc.type.genre article
dspace.entity.type Publication
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