ArticlePlant methods2019
Assessing plant performance in the Enviratron.
Article in Plant methods, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Effects of Atmospheric COPlant, cell & environment · 2026Article
- Phenotypic dynamics and temporal heritability of tomato architectural traits using an unmanned ground vehicle-based plant phenotyping system.Horticulture research · 2025Article
- MADI: A multispectral automated dynamic imager to monitor plant health.Plant phenomics (Washington, D.C.) · 2025Article
- Elevated COThe New phytologist · 2025Article
- High-fidelity wheat plant reconstruction using 3D Gaussian splatting and neural radiance fields.GigaScience · 2025Article
- Opportunities and limits of controlled-environment plant phenotyping for climate response traits.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Review
- Daily temperature cycles promote alternative splicing of RNAs encoding SR45a, a splicing regulator in maize.Plant physiology · 2021Article
- Robotic Technologies for High-Throughput Plant Phenotyping: Contemporary Reviews and Future Perspectives.Frontiers in plant science · 2021Review
- The Transcription Factor bZIP60 Links the Unfolded Protein Response to the Heat Stress Response in Maize.The Plant cell · 2020Article
Corrections and comments
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Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAssessing 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.
resultsThe 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.
conclusionsThe 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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