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Phenocave: An Automated, Standalone, and Affordable Phenotyping System for Controlled Growth Conditions

Controlled plant growth facilities provide the possibility to alter climate conditions affecting plant growth, such as humidity, temperature, and light, allowing a better understanding of plant responses to abiotic and biotic stresses. A bottleneck, however, is measuring various aspects of plant gro...

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Autores principales: Leiva, Fernanda, Vallenback, Pernilla, Ekblad, Tobias, Johansson, Eva, Chawade, Aakash
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8469120/
https://www.ncbi.nlm.nih.gov/pubmed/34579350
http://dx.doi.org/10.3390/plants10091817
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author Leiva, Fernanda
Vallenback, Pernilla
Ekblad, Tobias
Johansson, Eva
Chawade, Aakash
author_facet Leiva, Fernanda
Vallenback, Pernilla
Ekblad, Tobias
Johansson, Eva
Chawade, Aakash
author_sort Leiva, Fernanda
collection PubMed
description Controlled plant growth facilities provide the possibility to alter climate conditions affecting plant growth, such as humidity, temperature, and light, allowing a better understanding of plant responses to abiotic and biotic stresses. A bottleneck, however, is measuring various aspects of plant growth regularly and non-destructively. Although several high-throughput phenotyping facilities have been built worldwide, further development is required for smaller custom-made affordable systems for specific needs. Hence, the main objective of this study was to develop an affordable, standalone and automated phenotyping system called “Phenocave” for controlled growth facilities. The system can be equipped with consumer-grade digital cameras and multispectral cameras for imaging from the top view. The cameras are mounted on a gantry with two linear actuators enabling XY motion, thereby enabling imaging of the entire area of Phenocave. A blueprint for constructing such a system is presented and is evaluated with two case studies using wheat and sugar beet as model plants. The wheat plants were treated with different irrigation regimes or high nitrogen application at different developmental stages affecting their biomass accumulation and growth rate. A significant correlation was observed between conventional measurements and digital biomass at different time points. Post-harvest analysis of grain protein content and composition corresponded well with those of previous studies. The results from the sugar beet study revealed that seed treatment(s) before germination influences germination rates. Phenocave enables automated phenotyping of plants under controlled conditions, and the protocols and results from this study will allow others to build similar systems with dimensions suitable for their custom needs.
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spelling pubmed-84691202021-09-27 Phenocave: An Automated, Standalone, and Affordable Phenotyping System for Controlled Growth Conditions Leiva, Fernanda Vallenback, Pernilla Ekblad, Tobias Johansson, Eva Chawade, Aakash Plants (Basel) Article Controlled plant growth facilities provide the possibility to alter climate conditions affecting plant growth, such as humidity, temperature, and light, allowing a better understanding of plant responses to abiotic and biotic stresses. A bottleneck, however, is measuring various aspects of plant growth regularly and non-destructively. Although several high-throughput phenotyping facilities have been built worldwide, further development is required for smaller custom-made affordable systems for specific needs. Hence, the main objective of this study was to develop an affordable, standalone and automated phenotyping system called “Phenocave” for controlled growth facilities. The system can be equipped with consumer-grade digital cameras and multispectral cameras for imaging from the top view. The cameras are mounted on a gantry with two linear actuators enabling XY motion, thereby enabling imaging of the entire area of Phenocave. A blueprint for constructing such a system is presented and is evaluated with two case studies using wheat and sugar beet as model plants. The wheat plants were treated with different irrigation regimes or high nitrogen application at different developmental stages affecting their biomass accumulation and growth rate. A significant correlation was observed between conventional measurements and digital biomass at different time points. Post-harvest analysis of grain protein content and composition corresponded well with those of previous studies. The results from the sugar beet study revealed that seed treatment(s) before germination influences germination rates. Phenocave enables automated phenotyping of plants under controlled conditions, and the protocols and results from this study will allow others to build similar systems with dimensions suitable for their custom needs. MDPI 2021-08-31 /pmc/articles/PMC8469120/ /pubmed/34579350 http://dx.doi.org/10.3390/plants10091817 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Leiva, Fernanda
Vallenback, Pernilla
Ekblad, Tobias
Johansson, Eva
Chawade, Aakash
Phenocave: An Automated, Standalone, and Affordable Phenotyping System for Controlled Growth Conditions
title Phenocave: An Automated, Standalone, and Affordable Phenotyping System for Controlled Growth Conditions
title_full Phenocave: An Automated, Standalone, and Affordable Phenotyping System for Controlled Growth Conditions
title_fullStr Phenocave: An Automated, Standalone, and Affordable Phenotyping System for Controlled Growth Conditions
title_full_unstemmed Phenocave: An Automated, Standalone, and Affordable Phenotyping System for Controlled Growth Conditions
title_short Phenocave: An Automated, Standalone, and Affordable Phenotyping System for Controlled Growth Conditions
title_sort phenocave: an automated, standalone, and affordable phenotyping system for controlled growth conditions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8469120/
https://www.ncbi.nlm.nih.gov/pubmed/34579350
http://dx.doi.org/10.3390/plants10091817
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