1. Hyperspectral Sensors and Imaging Technologies in Phytopathology: State of the Art
- Author
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Gerrit Polder, Jan Behmann, Matheus Thomas Kuska, Achim Walter, and Anne-Katrin Mahlein
- Subjects
0106 biological sciences ,0301 basic medicine ,phenotyping ,Context (language use) ,Plant Science ,Biology ,01 natural sciences ,03 medical and health sciences ,noninvasive ,Visual assessment ,Plant Diseases ,digital technologies ,precision agriculture ,Hyperspectral imaging ,Plant Pathology ,Plant phenotyping ,Data science ,Plant disease ,030104 developmental biology ,machine learning ,Remote Sensing Technology ,GTB Tuinbouw Technologie ,plant disease detection ,Precision agriculture ,State (computer science) ,010606 plant biology & botany - Abstract
Plant disease detection represents a tremendous challenge for research and practical applications. Visual assessment by human raters is time-consuming, expensive, and error prone. Disease rating and plant protection need new and innovative techniques to address forthcoming challenges and trends in agricultural production that require more precision than ever before. Within this context, hyperspectral sensors and imaging techniques—intrinsically tied to efficient data analysis approaches—have shown an enormous potential to provide new insights into plant-pathogen interactions and for the detection of plant diseases. This article provides an overview of hyperspectral sensors and imaging technologies for assessing compatible and incompatible plant-pathogen interactions. Within the progress of digital technologies, the vision, which is increasingly discussed in the society and industry, includes smart and intuitive solutions for assessing plant features in plant phenotyping or for making decisions on plant protection measures in the context of precision agriculture.
- Published
- 2018