Plant Disease Identification Using the Unmanned Aerial Vehicle Images

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Mrs. K. Anitha Devi, et. al.


Important factors in plant development and the elimination of both qualitative and quantitative declines in crop yield are early and effective identification and evaluation of plant illnesses. Optical techniques such as RGB imaging, multi- and hyperspectral sensors, thermography, or chlorophyll fluorescence have shown their ability for early outbreak detection and quantification of plant diseases in automated, objective, and reproducible detection systems. Recently, as an optical inspection that offers additional information on crop plant vitality, 3D scanning has also been introduced. Different platforms from proximal to remote sensing are available for multiscale monitoring of single crop organs or entire fields. Accurate and accurate disease detection is enabled by highly sophisticated and advanced data analysis methods that lead to new sensor data insights for complex plant-pathogen systems.Non-destructive, sensor-based techniques help and extend the detection of plant diseases through visual and/or molecular approaches. Precision agriculture and plant phenotyping are the most important fields of use of sensor-based analyses. We suggest UAV base imaging for plant disease detection in this article.


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How to Cite
et. al., M. K. A. D. . (2021). Plant Disease Identification Using the Unmanned Aerial Vehicle Images. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(10), 2396–2399. Retrieved from
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