Recent Developments and Applications of Crop Disease Detection, Prediction, and Early Warning: A review

• Research status of crop disease monitoring in agriculture is summarized. • The existing sensors, systems and methods are analyzed. • The available crop disease monitoring schemes are summarized in detail. • The potential challenges and future trends of disease monitoring are reported. Crop diseases represent a significant threat to global agricultural productivity and food security. The advancement of non-invasive and efficient crop health monitoring technologies is critical for sustainable crop protection and yield stability. The continuous progress of sensing systems and computational methodologies offers promising avenues for developing intelligent agricultural disease monitoring systems. This review systematically evaluates existing research from three dimensions: sensors and systems, methods and algorithms, and applications. It provides an in-depth analysis of the roles of different sensors and systems, discusses key methods and techniques, prediction, and early warning, and explores their applications in real-world agricultural scenarios. Furthermore, this paper identifies the main challenges in agricultural disease surveillance research, particularly in the development of real-time detection techniques, the construction of early-warning models, and the promotion of data sharing and collaboration. Finally, innovative directions and application prospects are explored for integrating crop disease monitoring with big data, artificial intelligence (AI), and the Internet of Things (IoT). These research advances are expected to open new avenues for theoretical innovation and practical applications in crop disease monitoring.