AI, Machine Vision, and Navigation Technologies for Rice and Wheat Cultivation

Dear Colleagues,

Driven by artificial intelligence (AI), agricultural automation is becoming a core approach in modern agricultural transformation, aiming to enhance production efficiency and achieve sustainable resource utilization. By integrating AI technologies such as machine learning, computer vision, and agricultural robotics, agricultural production can attain unprecedented levels of precision, efficiency, and autonomy. This Special Issue focuses on cutting-edge research that leverages AI to address key challenges in crop production and management, autonomous operation of smart agricultural machinery, and agricultural environment monitoring and regulation, thereby laying the foundation for smart agriculture and unmanned production systems.

The application of AI in agriculture must be grounded in studies of agronomic mechanisms and agricultural machinery operation characteristics, combined with crop growth models and robotic motion control theories, to ensure that automation solutions align with biological, agronomic, and mechanized operational requirements. Advanced technologies such as visual navigation for agricultural robots, coordinated operation of intelligent agricultural machinery clusters, precision pesticide application robotic systems, and deep learning-based yield prediction models are critical for reducing resource waste, optimizing operational efficiency, and minimizing labor dependency. The ultimate goal is to establish a fully autonomous agricultural production system powered by AI, achieving intelligent and low-carbon agricultural production.

We invite scholars to submit original research exploring the application of AI in agricultural automation, contributing to the advancement of smart agriculture toward greater efficiency, intelligence, and sustainability.

Dr. Xiaobo Xi
Dr. Zhipeng Xing
Guest Editors

Dr. Yangjie Shi
Guest Editor Assistant

Manuscript Submission Information

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