Precision pesticide application is a key focus in orchard management, with targeted spraying serving as a core technology to optimize pesticide delivery and reduce environmental pollution. However, its accurate implementation relies on high-precision environmental sensing technologies to enable the precise identification of target objects and dynamic regulation of spraying strategies. This paper systematically reviews the application of orchard environmental sensing technologies in targeted spraying. It first focuses on key sensors used in environmental sensing, providing an in-depth analysis of their operational mechanisms and advantages in orchard environmental perception. Subsequently, this paper discusses the role of multi-source data fusion and artificial intelligence analysis techniques in improving the accuracy and stability of orchard environmental sensing, supporting crown structure modeling, pest and disease monitoring, and weed recognition. Additionally, this paper reviews the practical paths of environmental sensing-driven targeted spraying technologies, including variable spraying strategies based on canopy structure perception, precise pesticide application methods combined with intelligent pest and disease recognition, and targeted weed control technologies relying on weed and non-target area detection. Finally, this paper summarizes the challenges faced by multi-source sensing and targeted spraying technologies in light of current research progress and industry needs, and explores potential future developments in low-cost sensors, real-time data processing, intelligent decision making, and unmanned agricultural machinery.

With the ongoing advancement of global agricultural modernization, intelligent technologies have gained significant attention in agricultural production—particularly in the field of intelligent orchard sprayers, where notable progress has been achieved. Intelligent orchard sprayers, equipped with precise sensing and control systems, enable targeted spraying. This enhances the efficiency of crop health management, reduces pesticide usage, minimizes environmental pollution, and supports the development of precision agriculture. This review focuses on three core modules of intelligent sprayer technology: perception and intelligent control, spray deposition and drift control, and autonomous navigation with system integration. By addressing key areas such as sensor technologies, object detection algorithms, and real-time control strategies, this review explores current challenges and future directions for intelligent orchard sprayer technology. It also discusses existing technical bottlenecks and obstacles to large-scale adoption. Finally, this review highlights the pivotal role of intelligent orchard sprayer technology in enhancing crop management efficiency, improving environmental sustainability, and facilitating the transformation of agricultural production systems.

This paper presents an air-assisted sprayer for vineyard pesticide application. The spraying unit was designed with two symmetrically arranged ports. The airflow velocity distribution of the sprayer was investigated using a combination of experimental validation and a computational fluid dynamics (CFD) model. The results of both the simulation and the experiment showed good agreement in airflow velocity, and the distribution was uniform. Both unilateral and bilateral spraying field experiments were conducted in this study. The unilateral spraying experiment showed that higher spray pressure and lower sprayer speed increased both total deposition coverage and spray penetration (SP), while shorter spray distances improved SP but decreased total deposition coverage. The optimal operational conditions for the sprayer were determined as follows: spray pressure of 0.40 MPa, sprayer speed of 0.83 m/s, and spray distance of 1.00 m. The results of the bilateral spraying field experiment indicated that the coefficient of variation (CV) for deposition coverage in Columns A, B, and C were 16.20%, 8.10%, and 15.47%, respectively. The CVs in Layers a, b, and c were 6.14%, 12.62%, and 6.74%, respectively. This result demonstrated that the deposition coverage distribution in the canopy was relatively uniform, and the air-assisted sprayer exhibited good spray penetration performance. This study demonstrates the effectiveness and potential of the air-assisted sprayer for vineyard pesticide application.

The multiscale interactive system composed of wind, leaves, and droplets serves as a critical dynamic unit in precision orchard spraying. Its coupling mechanisms fundamentally influence pesticide transport pathways, deposition patterns, and drift behavior within crop canopies, forming the foundational basis for achieving intelligent and site-specific spraying operations. This review systematically examines the synergistic dynamics across three hierarchical scales: Droplet–leaf surface wetting and adhesion at the microscale; leaf cluster motion responses at the mesoscale; and the modulation of airflow and spray plume diffusion by canopy architecture at the macroscale. Key variables affecting spray performance—such as wind speed and turbulence structure, leaf biomechanical properties, droplet size and electrostatic characteristics, and spatial canopy heterogeneity—are identified and analyzed. Furthermore, current advances in multiscale modeling approaches and their corresponding experimental validation techniques are critically evaluated, along with their practical boundaries of applicability. Results indicate that while substantial progress has been made at individual scales, significant bottlenecks remain in the integration of cross-scale models, real-time acquisition of critical parameters, and the establishment of high-fidelity experimental platforms. Future research should prioritize the development of unified coupling frameworks, the integration of physics-based and data-driven modeling strategies, and the deployment of multimodal sensing technologies for real-time intelligent spray decision-making. These efforts are expected to provide both theoretical foundations and technological support for advancing precision and intelligent orchard spraying systems.

This study evaluates the performance of a novel high-clearance air-assisted electrostatic sprayer designed for vineyards and investigates the impact of applied voltage on droplet deposition. This sprayer, which uses a new type of air-assisted electrostatic spray nozzle, could spray three rows of grapes at the same time, significantly improving work efficiency. Field test results show that the middle row of the high-clearance air-assisted electrostatic sprayer deposition effect was better than the left and right rows, and the minimum droplet deposition density inside the grape canopy was 26.4 deposits/cm². The droplet deposition effects of electrostatic spraying were effectively improved, and the average droplet deposition density of the canopy increased by 15.72%. Electrostatic spraying improves the deposition on the outer canopy but reduces deposition on the inner canopy, so electrostatic spraying reduces the penetration of droplets into the canopy. The sprayer’s design proves effective for large-scale operations, offering insights into electrostatic spray technology’s role in precision agriculture.

This study experimentally investigates the breakup mechanisms and atomization characteristics of liquid jets in subsonic crossflows and develops a penetration depth model that incorporates the incidence angle. Experimental data show that the model fits well, with a minimum R² value of 0.924 and an average of 0.969. High-speed imaging techniques were used to systematically analyze the effects of liquid- and gas-phase Weber numbers and incidence angles on the penetration and atomization of liquid jets. The experimental results indicate the following: (1) As the liquid Weber number (We_l) increases, the penetration depth increases, while the gas Weber number (We_a) is inversely related to penetration depth. (2) A decrease in the incidence angle (ranging from 45° to 90°) significantly reduces penetration performance. (3) As We_a increases, the volume median diameter (VMD) of droplets decreases by 61.70% to 83.09%, while smaller incidence angles cause a 42.96% increase in the VMD. The VMD shows a non-linear trend with respect to We_l, reflecting the complex interaction between inertial forces and surface tension. These findings provide a theoretical basis for understanding the atomization behavior of transverse jets and the key parameters affecting penetration and droplet formation. The results are of practical significance for the structural optimization and performance enhancement of air-assisted atomizing nozzles used in precision agricultural spraying systems.