Research status and progress on key technologies of intelligent orchard

With the aging of the rural population, standardized and intelligent orchard production has become a key development direction for modern orchards. Orchard production currently faces several challenges, including labor shortages, low mechanization levels, and inefficient resource utilization. Intelligent orchard technologies offer potential solutions to these problems by improving productivity, reducing costs, and minimizing resource waste. This study systematically reviews the four key technological areas of intelligent orchards: information perception, intelligent decision-making, precision operations, and intelligent management, and analyzes their current status, future directions, and applications in modern orchards based on recent research and developments at home and abroad. First, information perception technology forms the foundation of intelligent orchard production. By integrating various sensors, drones, and Internet of Things (IoT), orchards can achieve real-time, multidimensional monitoring of their environments, crop growth, and operational equipment. Environmental perception technologies cover factors such as climate, soil moisture, and temperature. These data are collected using tools like LiDAR, remote sensing, and soil sensors, helping orchard managers better understand the microen-vironment of the orchard. Crop perception technology monitors the health, growth, and pest infestation status of trees using hyperspectral imaging, infrared technology, and other advanced sensors. This enables early interventions to prevent losses in yield or quality. Additionally, operational equipment perception technology provides real-time monitoring of the status and performance of agricultural machinery, supporting autonomous navigation and precision operations by providing crucial data for optimizing equipment use and ensuring efficient orchard management. By fusing multiple sources of information, intelligent orchards can monitor and manage their operations across the full lifecycle of the orchard, from planting to harvest. Secondly, intelligent decision-making systems are essential for achieving smart orchard production. By analyzing and processing the collected data, these systems can optimize various orchard production processes such as irrigation, fertilization, flower thinning, pesticide application, and harvesting. For example, intelligent irrigation systems analyze soil moisture levels and meteorological data to determine the best times and quantities for irrigation, ensuring efficient use of water resources. Fertilization and pesticide application systems adjust the timing and dosage based on the specific growth needs of the trees, promoting healthy growth while reducing the use of fertilizers and pesticides, thus minimizing environmental pollution. Additionally, smart harvesting systems use fruit maturity detection to schedule harvests efficiently, improving productivity while reducing fruit damage. Precision operations are a vital component of smart orchard production. Autonomous navigation technologies allow agricultural machinery to operate autonomously in the complex environments of orchards. Using LiDAR, vision-based navigation, and obstacle avoidance algorithms, machinery can complete tasks safely and efficiently. Precision operations are enhanced by real-time sensor data, which enables machinery to adjust its parameters automatically to ensure accuracy and quality. For example, precision fertilization and pesticide application systems adjust the amount applied based on the actual needs of each tree, improving resource utilization efficiency and production outcomes. In terms of system integration, intelligent orchards rely on cloud platforms to achieve unmanned and automated management. Orchard inspection robots collect real-time data on tree growth and pest status, which is uploaded to the cloud for analysis by intelligent decision-making systems. Orchard management robots carry out tasks such as fertilization, flower thinning, and pruning based on the instructions from the intelligent decision systems, executing complex operations automatically. Harvesting robots, equipped with visual recognition technology and deep learning algorithms, can assess fruit maturity and perform harvesting tasks efficiently. In multi-machine collaborative operation systems, several robots in the orchard are coordinated through cloud platforms to work together, improving overall efficiency. For example, during harvest seasons, harvesting robots and transport robots collaborate to ensure that picked fruits are swiftly transported to designated locations, reducing spoilage and enhancing workflow efficiency. Finally, this study looks forward to the future development direction of smart orchard technology and provides specific research ideas. Future smart orchard technology will place greater emphasis on multi-source information fusion, autonomous operation of agricultural machinery, and intelligent management throughout the entire process. By deeply integrating perception data from different sources, orchard managers can more accurately grasp the production dynamics of the orchard, further improving the scientificity of decision- making. The autonomous operation technology of agricultural machinery will continue to improve, achieving autonomous navigation and operation in more complex environments. The fully intelligent management system will optimize the production process, reduce operating costs, improve the overall production efficiency and fruit quality of the orchard through technologies such as big data analysis and cloud computing, in order to provide reference and guidance for the devel-opment of key technologies in standardized orchards. In conclusion, the future of intelligent orchards lies in the continuous improvement and integration of these technologies. Through the development of more advanced sensing technologies, intelligent decision-making systems, and autonomous machinery, orchards will become more efficient, sustainable, and productive, helping farmers to manage their resources better while meeting the demands of modern agriculture. This will not only enhance orchard productivity and fruit quality but also contribute to the overall sustainability and competitiveness of the agricultural sector.