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Advanced Multi-Color Fluorescence Imaging System for Detection of Biotic and Abiotic Stresses in Leaves

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Author Info

  • Stefanie Konanz

    ()
    (Botanical Institute II, Karlsruhe Institute of Technology (KIT), University Sector, Fritz-Haber-Weg 4, 76131 Karlsruhe, Germany)

  • László Kocsányi

    ()
    (Department of Atomic Physics, Budapest University of Technology and Economics, Budafoki út 8, 1111 Budapest XI, Hungary)

  • Claus Buschmann

    ()
    (Botanical Institute II, Karlsruhe Institute of Technology (KIT), University Sector, Fritz-Haber-Weg 4, 76131 Karlsruhe, Germany)

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    Abstract

    The autofluorescence of a sample is a highly sensitive and selective optical property and gives the possibility to establish non-destructive techniques of the investigation of plants, like detecting the chlorophyll fluorescence related to stress phenomena. In this study, an advanced multi-color fluorescence imaging system and data analysis were presented. The advantage of an imaging system is the additional receiving of spatial information over a sample area, this is a strong improvement compared to spot measurements commonly used. The purpose was to demonstrate the possibility of the detection and characterization of stress symptoms using this system. Specific fluorescence ratios were identified to characterize the stress status over the whole leaf, here shown on barley grown under different nitrogen supply (abiotic stress). Due to the changes, it is possible to make conclusions about leaf pigments (chlorophylls and phenolics) related to stress response. The second aim was to use the shape of local symptoms (biotic stress) as a criterion. For this purpose, three structural different kinds of fungal symptoms were analyzed using shape descriptors. It shows that an additional image shape analysis can be very useful for extracting further information, in this case the successful discrimination of fungal infections.

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    File URL: http://www.mdpi.com/2077-0472/4/2/79/pdf
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    Bibliographic Info

    Article provided by MDPI, Open Access Journal in its journal Agriculture.

    Volume (Year): 4 (2014)
    Issue (Month): 2 (April)
    Pages: 79-95

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    Handle: RePEc:gam:jagris:v:4:y:2014:i:2:p:79-95:d:34799

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    Web page: http://www.mdpi.com/

    Related research

    Keywords: fluorescence image; stress detection; symptom characterization; shape analysis; ImageJ; leaf level;

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