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.
Subject(s)
Plant Diseases , Plant Pathology/instrumentation , Remote Sensing Technology/instrumentation , Plant Diseases/prevention & controlABSTRACT
Hyperspectral Imaging has long been established in other scientific disciplines than medicine (e. g. earth science) as a means for objective classification of image data information. Some 10 years ago it was first introduced into medicine. Due to its immanent advantages - non-destructive specimen, compatibility with established optical tools (microscope, endoscope), objectivity, and user-independence - several attempts have been made in order to use its potential for the treatment of cancer patients. This publication reviews which methods have been developed for analogue issues in disciplines other than medicine, how these can be transferred into medicine, and what the perspectives are for the traditional innovative field of head-and-neck-oncology.
