Cargando…

Phenoplant: a web resource for the exploration of large chlorophyll fluorescence image datasets

BACKGROUND: Image analysis is increasingly used in plant phenotyping. Among the various imaging techniques that can be used in plant phenotyping, chlorophyll fluorescence imaging allows imaging of the impact of biotic or abiotic stresses on leaves. Numerous chlorophyll fluorescence parameters may be...

Descripción completa

Detalles Bibliográficos
Autores principales: Rousseau, Céline, Hunault, Gilles, Gaillard, Sylvain, Bourbeillon, Julie, Montiel, Gregory, Simier, Philippe, Campion, Claire, Jacques, Marie-Agnès, Belin, Etienne, Boureau, Tristan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4392743/
https://www.ncbi.nlm.nih.gov/pubmed/25866549
http://dx.doi.org/10.1186/s13007-015-0068-4
_version_ 1782366041433702400
author Rousseau, Céline
Hunault, Gilles
Gaillard, Sylvain
Bourbeillon, Julie
Montiel, Gregory
Simier, Philippe
Campion, Claire
Jacques, Marie-Agnès
Belin, Etienne
Boureau, Tristan
author_facet Rousseau, Céline
Hunault, Gilles
Gaillard, Sylvain
Bourbeillon, Julie
Montiel, Gregory
Simier, Philippe
Campion, Claire
Jacques, Marie-Agnès
Belin, Etienne
Boureau, Tristan
author_sort Rousseau, Céline
collection PubMed
description BACKGROUND: Image analysis is increasingly used in plant phenotyping. Among the various imaging techniques that can be used in plant phenotyping, chlorophyll fluorescence imaging allows imaging of the impact of biotic or abiotic stresses on leaves. Numerous chlorophyll fluorescence parameters may be measured or calculated, but only a few can produce a contrast in a given condition. Therefore, automated procedures that help screening chlorophyll fluorescence image datasets are needed, especially in the perspective of high-throughput plant phenotyping. RESULTS: We developed an automatic procedure aiming at facilitating the identification of chlorophyll fluorescence parameters impacted on leaves by a stress. First, for each chlorophyll fluorescence parameter, the procedure provides an overview of the data by automatically creating contact sheets of images and/or histograms. Such contact sheets enable a fast comparison of the impact on leaves of various treatments, or of the contrast dynamics during the experiments. Second, based on the global intensity of each chlorophyll fluorescence parameter, the procedure automatically produces radial plots and box plots allowing the user to identify chlorophyll fluorescence parameters that discriminate between treatments. Moreover, basic statistical analysis is automatically generated. Third, for each chlorophyll fluorescence parameter the procedure automatically performs a clustering analysis based on the histograms. This analysis clusters images of plants according to their health status. We applied this procedure to monitor the impact of the inoculation of the root parasitic plant Phelipanche ramosa on Arabidopsis thaliana ecotypes Col-0 and Ler. CONCLUSIONS: Using this automatic procedure, we identified eight chlorophyll fluorescence parameters discriminating between the two ecotypes of A. thaliana, and five impacted by the infection of Arabidopsis thaliana by P. ramosa. More generally, this procedure may help to identify chlorophyll fluorescence parameters impacted by various types of stresses. We implemented this procedure at http://www.phenoplant.org freely accessible to users of the plant phenotyping community. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13007-015-0068-4) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-4392743
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-43927432015-04-11 Phenoplant: a web resource for the exploration of large chlorophyll fluorescence image datasets Rousseau, Céline Hunault, Gilles Gaillard, Sylvain Bourbeillon, Julie Montiel, Gregory Simier, Philippe Campion, Claire Jacques, Marie-Agnès Belin, Etienne Boureau, Tristan Plant Methods Methodology BACKGROUND: Image analysis is increasingly used in plant phenotyping. Among the various imaging techniques that can be used in plant phenotyping, chlorophyll fluorescence imaging allows imaging of the impact of biotic or abiotic stresses on leaves. Numerous chlorophyll fluorescence parameters may be measured or calculated, but only a few can produce a contrast in a given condition. Therefore, automated procedures that help screening chlorophyll fluorescence image datasets are needed, especially in the perspective of high-throughput plant phenotyping. RESULTS: We developed an automatic procedure aiming at facilitating the identification of chlorophyll fluorescence parameters impacted on leaves by a stress. First, for each chlorophyll fluorescence parameter, the procedure provides an overview of the data by automatically creating contact sheets of images and/or histograms. Such contact sheets enable a fast comparison of the impact on leaves of various treatments, or of the contrast dynamics during the experiments. Second, based on the global intensity of each chlorophyll fluorescence parameter, the procedure automatically produces radial plots and box plots allowing the user to identify chlorophyll fluorescence parameters that discriminate between treatments. Moreover, basic statistical analysis is automatically generated. Third, for each chlorophyll fluorescence parameter the procedure automatically performs a clustering analysis based on the histograms. This analysis clusters images of plants according to their health status. We applied this procedure to monitor the impact of the inoculation of the root parasitic plant Phelipanche ramosa on Arabidopsis thaliana ecotypes Col-0 and Ler. CONCLUSIONS: Using this automatic procedure, we identified eight chlorophyll fluorescence parameters discriminating between the two ecotypes of A. thaliana, and five impacted by the infection of Arabidopsis thaliana by P. ramosa. More generally, this procedure may help to identify chlorophyll fluorescence parameters impacted by various types of stresses. We implemented this procedure at http://www.phenoplant.org freely accessible to users of the plant phenotyping community. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13007-015-0068-4) contains supplementary material, which is available to authorized users. BioMed Central 2015-04-03 /pmc/articles/PMC4392743/ /pubmed/25866549 http://dx.doi.org/10.1186/s13007-015-0068-4 Text en © Rousseau et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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 Methodology
Rousseau, Céline
Hunault, Gilles
Gaillard, Sylvain
Bourbeillon, Julie
Montiel, Gregory
Simier, Philippe
Campion, Claire
Jacques, Marie-Agnès
Belin, Etienne
Boureau, Tristan
Phenoplant: a web resource for the exploration of large chlorophyll fluorescence image datasets
title Phenoplant: a web resource for the exploration of large chlorophyll fluorescence image datasets
title_full Phenoplant: a web resource for the exploration of large chlorophyll fluorescence image datasets
title_fullStr Phenoplant: a web resource for the exploration of large chlorophyll fluorescence image datasets
title_full_unstemmed Phenoplant: a web resource for the exploration of large chlorophyll fluorescence image datasets
title_short Phenoplant: a web resource for the exploration of large chlorophyll fluorescence image datasets
title_sort phenoplant: a web resource for the exploration of large chlorophyll fluorescence image datasets
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4392743/
https://www.ncbi.nlm.nih.gov/pubmed/25866549
http://dx.doi.org/10.1186/s13007-015-0068-4
work_keys_str_mv AT rousseauceline phenoplantawebresourcefortheexplorationoflargechlorophyllfluorescenceimagedatasets
AT hunaultgilles phenoplantawebresourcefortheexplorationoflargechlorophyllfluorescenceimagedatasets
AT gaillardsylvain phenoplantawebresourcefortheexplorationoflargechlorophyllfluorescenceimagedatasets
AT bourbeillonjulie phenoplantawebresourcefortheexplorationoflargechlorophyllfluorescenceimagedatasets
AT montielgregory phenoplantawebresourcefortheexplorationoflargechlorophyllfluorescenceimagedatasets
AT simierphilippe phenoplantawebresourcefortheexplorationoflargechlorophyllfluorescenceimagedatasets
AT campionclaire phenoplantawebresourcefortheexplorationoflargechlorophyllfluorescenceimagedatasets
AT jacquesmarieagnes phenoplantawebresourcefortheexplorationoflargechlorophyllfluorescenceimagedatasets
AT belinetienne phenoplantawebresourcefortheexplorationoflargechlorophyllfluorescenceimagedatasets
AT boureautristan phenoplantawebresourcefortheexplorationoflargechlorophyllfluorescenceimagedatasets