Hyperspectral Sensors and Imaging Technologies in Phytopathology: State of the Art.

  title={Hyperspectral Sensors and Imaging Technologies in Phytopathology: State of the Art.},
  author={Anne-Katrin Mahlein and Matheus Thomas Kuska and Jan Behmann and Gerrit Polder and Arnold Walter},
  journal={Annual review of phytopathology},
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… 
A Review of Advanced Technologies and Development for Hyperspectral-Based Plant Disease Detection in the Past Three Decades
It is proposed that different pathogens’ identification, biotic and abiotic stresses discrimination, plant disease early warning, and satellite-based hyperspectral technology are the primary challenges and pave the way for a targeted response.
A review of hyperspectral image analysis techniques for plant disease detection and identif ication
  • A. F. Cheshkova
  • Environmental Science
    Vavilovskii zhurnal genetiki i selektsii
  • 2022
Plant diseases cause signif icant economic losses in agriculture around the world. Early detection, quantif ication and identif ication of plant diseases are crucial for targeted application of plant
Current State of Hyperspectral Remote Sensing for Early Plant Disease Detection: A Review
The development of hyperspectral remote sensing equipment, in recent years, has provided plant protection professionals with a new mechanism for assessing the phytosanitary state of crops.
Spatial Referencing of Hyperspectral Images for Tracing of Plant Disease Symptoms
A method to spatially reference time series of close range hyperspectral images to derive a suitable transformation model for each observation within a time series experiment to cope with the specific structure and growth processes of wheat leaves.
In-Field Detection of Yellow Rust in Wheat on the Ground Canopy and UAV Scale
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Digital plant pathology: a foundation and guide to modern agriculture
A global connection of experts and data is suggested as the basis for defining a common and goal-oriented research roadmap and high interconnectivity will likely increase the chances of swift, successful progress in research and practice.
Technical workflows for hyperspectral plant image assessment and processing on the greenhouse and laboratory scale
A general workflow for the assessment and processing of hyperspectral plant data at greenhouse and laboratory scale is shown to outline procedures and requirements to provide fully calibrated data of the highest quality, essential for differentiation of the smallest changes from hyperspectrals reflectance of plants.
Practical Recommendations for Hyperspectral and Thermal Proximal Disease Sensing in Potato and Leek Fields
An optimal measurement setup combining both sensors for disease detection in leek and potato was studied by optimising the signal-to-noise ratio (SNR) based on the height of measurement above the crop canopy, off-zenith camera angle and exposure time of the sensor.
Detection of Leek Rust Disease under Field Conditions Using Hyperspectral Proximal Sensing and Machine Learning
It can be concluded that the results in this work are an important step towards the mapping of leek rust disease, and that future research is needed to overcome certain challenges before variable rate fungicide applications can be adopted against leek Rust disease.