Design and Experiment of a Prescription-Map-Based Variable-Rate Spraying System for Soybean–Maize Strip Intercropping
Year: 2026
Type: article
Abstract: To meet the requirements of differentiated pesticide application between soybean and maize strips in soybean–maize strip intercropping systems, this study developed a strip-specific variable-rate spraying system based on real-time prescription map interpretation and spatiotemporal nozzle matching with delay compensation. A simulated prescription map with predefined application-rate levels was generated using ArcMap and converted into a binary data structure suitable for embedded-controller access. Based on high-precision RTK-BDS positioning information, a local field coordinate transformation model was established and combined with SRAM-based memory preloading to achieve rapid prescription matrix addressing. To reduce boundary misalignment caused by positioning offset, actuator response lag, and hydraulic delay during dynamic field operations, a nozzle spatial position prediction model and a forward delay-compensation control algorithm were developed. Results from the strip-specific variable-rate spraying tests based on the simulated prescription map showed that, under the tested conditions, the mean boundary offset decreased from 0.69 m to 0.29 m after delay compensation. The mean flow-rate control accuracy for both soybean and maize strips exceeded 95% across different application-rate levels, while the coefficients of variation of flow rate were below 6%. These results indicate that, under the tested conditions, the developed system was able to perform real-time prescription map interpretation, target application-rate matching, and strip-specific variable-rate control, demonstrating its technical feasibility for variable-rate spraying in soybean–maize strip intercropping.
Source: Agriculture
Institutions: Jiangsu University, Ministry of Agriculture and Rural Affairs
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $3,137
Award: G66720820
OpenAlex ID: W7203825357