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Tristan Boureau - One of the best experts on this subject based on the ideXlab platform.

  • Phenoplant: a web resource for the exploration of large Chlorophyll Fluorescence image datasets
    Plant methods, 2015
    Co-Authors: Céline Rousseau, Gilles Hunault, Sylvain Gaillard, Julie Bourbeillon, Gregory Montiel, Philippe Simier, Claire Campion, Marie-agnès Jacques, Etienne Belin, Tristan Boureau
    Abstract:

    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.

  • Phenoplant: a web resource for the exploration of large Chlorophyll Fluorescence image datasets
    Plant Methods, 2015
    Co-Authors: Céline Rousseau, Gilles Hunault, Sylvain Gaillard, Julie Bourbeillon, Gregory Montiel, Philippe Simier, Claire Campion, Marie-agnès Jacques, Etienne Belin, Tristan Boureau
    Abstract:

    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.

A. Wagué - One of the best experts on this subject based on the ideXlab platform.

Céline Rousseau - One of the best experts on this subject based on the ideXlab platform.

  • Phenoplant: a web resource for the exploration of large Chlorophyll Fluorescence image datasets
    Plant methods, 2015
    Co-Authors: Céline Rousseau, Gilles Hunault, Sylvain Gaillard, Julie Bourbeillon, Gregory Montiel, Philippe Simier, Claire Campion, Marie-agnès Jacques, Etienne Belin, Tristan Boureau
    Abstract:

    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.

  • Phenoplant: a web resource for the exploration of large Chlorophyll Fluorescence image datasets
    Plant Methods, 2015
    Co-Authors: Céline Rousseau, Gilles Hunault, Sylvain Gaillard, Julie Bourbeillon, Gregory Montiel, Philippe Simier, Claire Campion, Marie-agnès Jacques, Etienne Belin, Tristan Boureau
    Abstract:

    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.

Timothy D. Perkins - One of the best experts on this subject based on the ideXlab platform.

  • Assessing cold tolerance in Picea using Chlorophyll Fluorescence
    Environmental and Experimental Botany, 1993
    Co-Authors: Gregory T. Adams, Timothy D. Perkins
    Abstract:

    Chlorophyll Fluorescence measurements were performed on field-collected red spruce foliage exposed to controlled freezing temperatures to determine the utility of Chlorophyll Fluorescence kinetics in assessing low temperature tolerance. No significant decreases in Fluorescence relative to unfrozen control foliage were observed at progressively lower temperatures until a critical temperature was reached, whereupon rapid, irreversible decreases in Fluorescence occurred. Weekly comparisons between cold tolerance estimates derived using Chlorophyll Fluorescence inflection point temperatures and foliar visual lt20 (temperature at which 20% of foliage exhibited necrosis) estimates were also made throughout the winter of 1991–1992. No significant differences in weekly cold tolerance estimates between the two methods were evident. The weekly absolute difference in mean cold tolerance using the two methods was 3.0°C. These results indicate that Chlorophyll Fluorescence is a rapid, consistent, and reproducible method of determining low temperature tolerance of spruce foliage.

A S Ndao - One of the best experts on this subject based on the ideXlab platform.