Orchard variable-rate spraying method integrating GNSS and wind-excited audio-conducted leaf area density

Conventional air-assisted sprayers used in orchards often suffer from excessive pesticide waste, high residue levels, and uneven droplet distribution on fruit tree canopies. Precision spraying technologies have emerged to address these limitations by enabling dynamic regulation of spray parameters according to canopy characteristics. Among these, leaf area density is a key indicator for describing canopy sparseness. However, accurate and automated measurement of canopy leaf area density remains challenging due to leaf shading effects. As a result, few fully functional variable-rate spraying systems have been developed based on this parameter.

This study presents a variable-rate spraying method that integrates global navigation satellite system (GNSS) positioning with wind-excited audio-conducted estimation of canopy leaf area density. A self-propelled orchard spraying platform was developed to acquire real-time GNSS positioning and audio-conducted canopy leaf area density data. Based on this, a method was established for generating prescription maps that integrate spatial positioning and canopy density information. A variable-rate spray control model and algorithm were then constructed to regulate spray flow according to the spatial distribution of leaf area density across the orchard.

Field experiments demonstrated that the system achieved a mean relative error of only 5.52% in spray flow rate regulation. Compared with conventional constant-rate spraying, the variable-rate mode reduced the longitudinal coefficient of variation (CV) of droplet deposition by 55.75% on adaxial leaf surfaces and by 33.22% on abaxial surfaces, with a maximum reduction of 62.32% in transverse CV. Ground runoff of spray solution was reduced by 62.29%, and droplet deposition density on leaf surfaces exceeded 25 droplets/cm², meeting the standard for low-volume insecticide application.

The integration of GNSS and wind-excited audio sensing for real-time canopy density assessment enables more precise and efficient pesticide application in orchards. This system significantly improves droplet deposition uniformity while reducing environmental losses, offering a promising technical solution for the development of intelligent and sustainable plant protection equipment.