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Hyperspectral and Chlorophyll Fluorescence Imaging for Early Detection of Plant Diseases, with Special Reference to Fusarium spec. Infections on Wheat

Author

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  • Elke Bauriegel

    (Leibniz Institut für Agrartechnik Potsdam-Bornim, Max-Eyth-Allee 100, D-14469 Potsdam, Germany)

  • Werner B. Herppich

    (Leibniz Institut für Agrartechnik Potsdam-Bornim, Max-Eyth-Allee 100, D-14469 Potsdam, Germany)

Abstract

In recent years, market pressures have reinforced the demand to solve the problem of an increased occurrence of Fusarium head blight (FHB) in cereal production, especially in wheat. The symptoms of this disease are clearly detectable by means of image analysis. This technique can therefore be used to map occurrence and extent of Fusarium infections. From this perspective, a separate harvest in the field can be taken into consideration. Based on the application of chlorophyll fluorescence and hyperspectral imaging, characteristics, requirements and limitations of Fusarium detection on wheat, both in the field and in the laboratory, are discussed. While the modification of spectral signatures due to fungal infection allows its detection by hyperspectral imaging, the decreased physiological activity of tissues resulting from Fusarium impacts provides the base for CFI analyses. In addition, the two methods are compared in view of their usability for the detection of Fusarium , and different approaches for data analysis are presented.

Suggested Citation

  • Elke Bauriegel & Werner B. Herppich, 2014. "Hyperspectral and Chlorophyll Fluorescence Imaging for Early Detection of Plant Diseases, with Special Reference to Fusarium spec. Infections on Wheat," Agriculture, MDPI, vol. 4(1), pages 1-26, March.
    • Handle: RePEc:gam:jagris:v:4:y:2014:i:1:p:32-57:d:34384
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    Citations

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    Cited by:

    1. Chunfeng Gao & Xingjie Ji & Qiang He & Zheng Gong & Heguang Sun & Tiantian Wen & Wei Guo, 2023. "Monitoring of Wheat Fusarium Head Blight on Spectral and Textural Analysis of UAV Multispectral Imagery," Agriculture, MDPI, vol. 13(2), pages 1-16, January.
    2. Maksim N. Moskovskiy & Mikhail V. Belyakov & Alexey S. Dorokhov & Andrey A. Boyko & Sergey V. Belousov & Oleg V. Noy & Anatoly A. Gulyaev & Sergey I. Akulov & Anastasia Povolotskaya & Igor Yu. Efremen, 2023. "Design of Device for Optical Luminescent Diagnostic of the Seeds Infected by Fusarium," Agriculture, MDPI, vol. 13(3), pages 1-11, March.
    3. Gerassimos G. Peteinatos & Audun Korsaeth & Therese W. Berge & Roland Gerhards, 2016. "Using Optical Sensors to Identify Water Deprivation, Nitrogen Shortage, Weed Presence and Fungal Infection in Wheat," Agriculture, MDPI, vol. 6(2), pages 1-21, May.
    4. Wenjing Zhu & Zhankang Feng & Shiyuan Dai & Pingping Zhang & Xinhua Wei, 2022. "Using UAV Multispectral Remote Sensing with Appropriate Spatial Resolution and Machine Learning to Monitor Wheat Scab," Agriculture, MDPI, vol. 12(11), pages 1-16, October.

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