Applications of Drone for Crop Disease Detection and Monitoring: A Review

Abstract

Crop diseases are one of the major threats to global food production. The different crop diseases result in significant yield losses, where their effective monitoring and accurate early identification techniques are considered crucial to ensure stable and reliable crop productivity and food security. Restricting and managing the disease's spread and lowering the cost of pesticides require effective plant pathogen monitoring and detection. If not used in the early stages of pathogenesis, traditional techniques such as molecular and serological methods—which are frequently employed for plant disease detection—are frequently ineffective. Conversely, drone-based remote sensing methods are highly successful in quickly detecting plant diseases in their early stages. Recent advances in remote sensing technology and data processing have propelled unmanned aerial vehicles (UAVs) into valuable tools for obtaining detailed data on plant diseases with high spatial, temporal, and spectral resolution. Drones have many potential uses in agriculture, including reducing manual labor and increasing productivity. Recent advances in drones and deep learning-based computer vision algorithms to identify crop diseases, providing early warning thereby allowing farmers to prevent costly crop failures and improve food production.