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Plant Screen Mobile: an open-source mobile device app for plant trait analysis
BACKGROUND: The development of leaf area is one of the fundamental variables to quantify plant growth and physiological function and is therefore widely used to characterize genotypes and their interaction with the environment. To date, analysis of leaf area often requires elaborate and destructive...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6329080/ https://www.ncbi.nlm.nih.gov/pubmed/30651749 http://dx.doi.org/10.1186/s13007-019-0386-z |
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author | Müller-Linow, Mark Wilhelm, Jens Briese, Christoph Wojciechowski, Tobias Schurr, Ulrich Fiorani, Fabio |
author_facet | Müller-Linow, Mark Wilhelm, Jens Briese, Christoph Wojciechowski, Tobias Schurr, Ulrich Fiorani, Fabio |
author_sort | Müller-Linow, Mark |
collection | PubMed |
description | BACKGROUND: The development of leaf area is one of the fundamental variables to quantify plant growth and physiological function and is therefore widely used to characterize genotypes and their interaction with the environment. To date, analysis of leaf area often requires elaborate and destructive measurements or imaging-based methods accompanied by automation that may result in costly solutions. Consequently in recent years there is an increasing trend towards simple and affordable sensor solutions and methodologies. A major focus is currently on harnessing the potential of applications developed for smartphones that provide access to analysis tools to a wide user basis. However, most existing applications entail significant manual effort during data acquisition and analysis. RESULTS: With the development of Plant Screen Mobile we provide a suitable smartphone solution for estimating digital proxies of leaf area and biomass in various imaging scenarios in the lab, greenhouse and in the field. To distinguish between plant tissue and background the core of the application comprises different classification approaches that can be parametrized by users delivering results on-the-fly. We demonstrate the practical applications of computing projected leaf area based on two case studies with Eragrostis and Musa plants. These studies showed highly significant correlations with destructive measurements of leaf area and biomass from both ground truth measurements and estimations from well-established screening systems. CONCLUSIONS: We show that a smartphone together with our analysis tool Plant Screen Mobile is a suitable platform for rapid quantification of leaf and shoot development of various plant architectures. Beyond the estimation of projected leaf area the app can also be used to quantify color and shape parameters of other plant material including seeds and flowers. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13007-019-0386-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6329080 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63290802019-01-16 Plant Screen Mobile: an open-source mobile device app for plant trait analysis Müller-Linow, Mark Wilhelm, Jens Briese, Christoph Wojciechowski, Tobias Schurr, Ulrich Fiorani, Fabio Plant Methods Software BACKGROUND: The development of leaf area is one of the fundamental variables to quantify plant growth and physiological function and is therefore widely used to characterize genotypes and their interaction with the environment. To date, analysis of leaf area often requires elaborate and destructive measurements or imaging-based methods accompanied by automation that may result in costly solutions. Consequently in recent years there is an increasing trend towards simple and affordable sensor solutions and methodologies. A major focus is currently on harnessing the potential of applications developed for smartphones that provide access to analysis tools to a wide user basis. However, most existing applications entail significant manual effort during data acquisition and analysis. RESULTS: With the development of Plant Screen Mobile we provide a suitable smartphone solution for estimating digital proxies of leaf area and biomass in various imaging scenarios in the lab, greenhouse and in the field. To distinguish between plant tissue and background the core of the application comprises different classification approaches that can be parametrized by users delivering results on-the-fly. We demonstrate the practical applications of computing projected leaf area based on two case studies with Eragrostis and Musa plants. These studies showed highly significant correlations with destructive measurements of leaf area and biomass from both ground truth measurements and estimations from well-established screening systems. CONCLUSIONS: We show that a smartphone together with our analysis tool Plant Screen Mobile is a suitable platform for rapid quantification of leaf and shoot development of various plant architectures. Beyond the estimation of projected leaf area the app can also be used to quantify color and shape parameters of other plant material including seeds and flowers. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13007-019-0386-z) contains supplementary material, which is available to authorized users. BioMed Central 2019-01-11 /pmc/articles/PMC6329080/ /pubmed/30651749 http://dx.doi.org/10.1186/s13007-019-0386-z 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 | Software Müller-Linow, Mark Wilhelm, Jens Briese, Christoph Wojciechowski, Tobias Schurr, Ulrich Fiorani, Fabio Plant Screen Mobile: an open-source mobile device app for plant trait analysis |
title | Plant Screen Mobile: an open-source mobile device app for plant trait analysis |
title_full | Plant Screen Mobile: an open-source mobile device app for plant trait analysis |
title_fullStr | Plant Screen Mobile: an open-source mobile device app for plant trait analysis |
title_full_unstemmed | Plant Screen Mobile: an open-source mobile device app for plant trait analysis |
title_short | Plant Screen Mobile: an open-source mobile device app for plant trait analysis |
title_sort | plant screen mobile: an open-source mobile device app for plant trait analysis |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6329080/ https://www.ncbi.nlm.nih.gov/pubmed/30651749 http://dx.doi.org/10.1186/s13007-019-0386-z |
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