Conventional orchard spraying often suffers from a mismatch between spraying parameters and the spatial structure of fruit tree canopies, resulting in uneven spray deposition and low spray utilization efficiency. To address these issues, this study developed a canopy feature-based profile variable-rate orchard sprayer. LiDAR was used to acquire spatial information on fruit tree canopies, based on which a mapping relationship between canopy profile characteristics and profile adjustment parameters was established. A profile adjustment mechanism consisting of a lifting platform, a translation mechanism, and a five-section profile spraying arm was designed to enable adaptive adjustment of nozzle positions and spray directions according to canopy morphology. In addition, a variable-rate spraying model was developed based on the effective canopy volume to achieve dynamic matching between spray volume and canopy spatial distribution. Field experiments were conducted in a high-spindle apple orchard to evaluate the performance of the developed sprayer. The results showed that, under the canopy-adaptive spraying mode, the average droplet coverage rate on the adaxial leaf surface was 37.65%, with a vertical coefficient of variation of 2.83%. The horizontal coefficients of variation for the upper, middle, and lower canopy layers were 11.50%, 8.03%, and 5.73%, respectively. Compared with the fixed-position quantitative spraying mode, the canopy-adaptive spraying mode reduced ground spray loss by 69.47% and water consumption by 51.93%. Overall, the canopy-adaptive spraying mode improved droplet deposition uniformity, reduced ground spray loss, and decreased spray volume, demonstrating its potential for precision plant protection in orchards.
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Jiang et al. (2026) studied this question.
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