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Detection of Soilborne Disease Utilizing Sensor Technologies: Lessons Learned from Studies on Stem Rot of Peanut

PLANT HEALTH PROGRESS(2021)

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Abstract
Soilborne plant diseases are a major constraint to crop production worldwide. Effective and economical management of these diseases is dependent on the ability to accurately detect and diagnose their signs and/or symptoms prior to widespread development in a crop. Sensor-based technologies are promising tools for automated crop disease detection, but research is still needed to optimize and validate methods for the detection of specific plant diseases. The overarching goal of our research is to use the peanut-stemrot plant disease system to identify and evaluate sensor-based technologies that can be utilized for the detection of soilborne plant diseases. Here we summarize the current state of sensor-based technologies for plant disease detection and provide examples from our own research that illustrate the advantages and limitations of different sensor-based methods for detecting soilborne diseases. In addition, the potential to adapt different sensor-based technologies to practical use in the field is discussed.
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Key words
optical sensors, spectral reflectance, thermal imaging, volatile organic compounds, machine learning, random forest, hyperspectral, Athelia rolfsii, Arachis hypogaea
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