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Benefits of hyperspectral imaging for plant disease detection and plant protection: a technical perspective

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Abstract

The detection and identification of plant diseases is crucial for an appropriate and targeted application of plant protection measures in crop production. Recently, intensive research has been conducted to develop innovative and technology-based optical methods for plant disease detection. In contrast to common visual rating and detection methods, optical sensors are able to measure pathogen-induced changes in the plant physiology non-invasively and objectively. Several studies showed that especially hyperspectral sensors are valuable tools for disease detection, identification and quantification on different scales from the tissue to the canopy level. This review describes the basic principles of hyperspectral measurements and different types of available hyperspectral sensors. Possible applications of hyperspectral sensors on different scales for disease detection and plant protection are discussed and evaluated. The advantages and disadvantages on each particular scale, as well as the impact of external factors, such as: light, wind, viewing angle, for measurements in laboratories, greenhouses and fields, are critically assessed in order to support researchers and agriculture technicians. Additionally, a comprehensive literature review about the use of hyperspectral sensors on these different scales for plant disease detection reflects the possibilities of non-invasive measurement systems. This highlights advantages of hyperspectral sensors when investigating plant–pathogen interactions through multiple examples. By some approaches, detection before visible symptoms appear is feasible. The potential of hyperspectral sensors as a tool for disease identification and quantification, based on disease characteristic changes in the plants spectral signature, is discussed as well. The review is concluded with an overview on different data analysis methods, which are required to extract key information from gathered hyperspectral datasets.

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Acknowledgements

Funding was provided by the German Federal Ministry of Education and Research (BMBF) within the scope of the competitive grants program “Networks of excellence in agricultural and nutrition research—CROP.SENSe.net” (Funding code: 0315529), junior research group “Hyperspectral phenotyping of resistance reactions of barley” and by the Daimler and Benz foundation. The authors are furthermore thankful to Bayer CropScience for funding.

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Authors and Affiliations

  1. INRES-Plant Diseases and Plant Protection, University of Bonn, Bonn, Germany

    Stefan Thomas, Matheus Thomas Kuska, David Bohnenkamp, Anna Brugger, Elias Alisaac, Jan Behmann & Anne-Katrin Mahlein

  2. IBG2: Plant Sciences, Forschungszentrum Jülich GMBH, Jülich, Germany

    Stefan Thomas

  3. Bayer AG, Digital Farming, CropScience, Langenfeld, Germany

    Mirwaes Wahabzada

  4. Institute of Sugar Beet Research (IfZ), Göttingen, Germany

    Anne-Katrin Mahlein

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Thomas, S., Kuska, M.T., Bohnenkamp, D. et al. Benefits of hyperspectral imaging for plant disease detection and plant protection: a technical perspective. J Plant Dis Prot 125, 5–20 (2018). https://doi.org/10.1007/s41348-017-0124-6

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