New spraying systems embedded with different technologies have been developed for pesticide application in 3D crops. However, while applied to specific tree crops, the potential spray drift mitigation for advanced spraying systems needs to be classified due to the great variability of spray equipment and canopy structure. Here a precision spraying system was developed and compared with two typical spraying systems (conventional system, optimized system following the best management practices) for the applied volume/pesticide and spray drift in an apple orchard at two growth stages following the ISO22866-2005 protocol. Compared to the conventional system, the other two advanced systems significantly reduced the amount of ground drift (> 60%) at most of the sampling distances at the growth stage BBCH 72, while the precision system demonstrated the best drift mitigation (57.3% reduction) at the stage BBCH 99. For the airborne drift, a remarkable drift reduction was also achieved with the two advanced systems. Specifically, the optimized spraying system exhibited a drift reduction by approximately 80% at the first growth stage, and the precision application demonstrated its considerable advantages in minimizing drift loss for the sparse canopy at the stage BBCH 99. Moreover, the saving of applied volume/pesticide was achieved by 12% with the optimized system and 43% with the precision system. This study revealed the necessity and prospect of the advanced spraying systems to reduce the environmental contamination and health risk from pesticide applications in fruit tree production.

Although many different designed air-assisted sprayers can be used for pesticide application in apple orchards, the lack of adequate adjustments according to specific crop characteristics leads to application inefficiencies and failures. To evaluate the spray coverage and biological efficacy of different application techniques combined with an alternative dosage adjustment based on tree row volume (TRV), field tests with five different techniques were carried out at three crop stages on a commercial apple orchard. The results showed that conventional mist-blower with a high application volume (800 L ha^-1) exhibited an excessive coverage with a high risk of contamination at the early crop stage (BBCH19), whereas other treatments using different application techniques, with a reduced volume rate and pesticide dose of 75%, were equivalent with good uniformity, revealing the great importance of suitable adjustment for the sprayers. For the middle and late stages (BBCH64 and 75), the orchard sprayer equipped with vertical booms provided the maximum coverage, and the pneumatic sprayer achieved significantly higher impacts density, which revealed their advantages and high efficiency for dense apple trees. The newly developed multi-fan sprayer and pneumatic sprayer achieved consistent coverage during the entire crop stage, independent of the changes in canopy structure (TRV). This indicates that a suitable setting and adjustment of the sprayer can contribute to a consistent spray quality. In general, benefiting from these new spraying technologies, an average reduction of 60.7% in pesticide dose and volume rate were achieved within the entire season, maintaining the same threshold of pest and disease control as that of the higher reference dose normally applied. These results demonstrate the importance of an alternative dose adjustment method to meet the requirements of the Farm to Fork strategy.

During air-assisted spraying operations in orchards, the interaction between the droplets and the target leaves has a decisive influence on the retention of the droplets on the leaves and the final deposition state. Based on the observation of the final deposition effect of the droplets in the spray test, the retention state of the droplets on the leaves is divided into three categories: uniform distribution (hereinafter referred to as uniform), accumulation, and loss. During the initial interaction between the droplets and the leaves, the adhesion or sliding state of the droplets has an important influence on the final deposition state of the droplets, which is determined by the target leaf adhesion work in this paper. Based on obtaining the characteristic parameters of the leaf surface, a theoretical model of adhesion work related to parameters such as the contact angle, rough factor, and initial tilt angle of the leaf is established. Afterward, through the connection of the droplet coverage on the macro level, the establishment of the deposition state model of the droplet group on the leaf is completed. By conducting the experiment test based on the Box-Behnken design of response surface methodology (RSM), the droplet deposition states under the influence of the spray distance, fan outlet wind speed and droplet size were studied and compared with the predicted values. The test results show that the prediction accuracies of the three states of uniform, accumulation, and loss were 87.5%, 80%, and 100%, respectively. The results of the study indicate that the established prediction model can effectively predict the deposition states of droplets on leaves and provide a reference for the selection of spray operation parameters.

The high moisture content of wheat grains in extreme weather, such as continuous rain, can easily cause mildew, and we lack accurate discrete element parameters when conducting a simulation analysis of the rapid dehumidification of high-moisture grains. Based on the material characteristics of wheat grains with a moisture content ranging from 10.41% to 32.51%, the key parameters of discrete element simulation were calibrated. Firstly, the stacking angle under different moisture contents was determined by a physical experiment, and the regression equation was established as R² = 0.9981. Subsequently, three significant parameters, namely, the static friction coefficient between the grains and steel plates, the static friction coefficient between grains, and the rolling friction coefficient, were selected from nine parameters using the Plackett–Burman test and the steepest climbing test. Furthermore, the stacking angle–discrete element parameter model was established using the Box–Behnken test as R² = 0.98, with a relative error of less than or equal to 3.28%. Finally, the moisture content–discrete element parameter model was derived and constructed based on the moisture content–stacking angle model and the stacking angle–discrete element parameter model, with a relative error of less than or equal to 3.92%. The results indicate that the discrete element simulation parameters of wheat grains can be directly predicted by the moisture content and used for the discrete element simulation testing of high-moisture wheat grains. This universal calibration method not only provides convenient and reliable technical support for optimizing the emergency rapid dehumidification process for high-moisture wheat grains but also provides a reference method for the calibration of other grains.

Highlights An orchard sprayer was equipped with a spray controller to monitor and manage the working conditions. Foliar deposits and losses of the optimized and conventional sprayer were tested on two different sized pear trees. No significant differences in leaf deposits were found between canopy positions with the optimized sprayer. Ground losses with the optimized sprayer in the target rows were 45% lower compared to the conventional sprayer. Abstract. Currently, mistblowers are the most common sprayer type used for pesticide application in orchards. However, maximizing canopy deposition with high application efficiency remained a challenge due to the intricate canopy structure. This study compares the performance of two air-conveyor sprayers on pear trees: a conventional sprayer and an optimized sprayer. The optimized sprayer was equipped with a spray controller that displays its operational conditions (forward speed, spraying pressure, etc.) during application through a user interface of the device. In addition, the controller was capable of recommending spray volume for an orchard with the operator’s inputs based on the Tree Row Volume (TRV) method. Two experimental blocks in two pear orchards, with different tree sizes referred to as 'small trees' and 'large trees', were designated to evaluate the foliage deposition and off-target losses of the two sprayers. The conventional sprayer applied a spray volume of 1160 L ha^-1 on both orchards following the farmers' conventional procedure. In contrast, the spray volumes of the optimized sprayer were determined by the controller based on the TRV model, resulting in a reduction of 29% and 55% for the large and small pear trees, respectively. The foliar deposition of each block was sampled from five randomly selected trees in a central row, with leaves collected from nine different canopy positions for small trees and twelve positions for large trees. Petri dishes were placed on the ground to assess the ground losses. Poles with nylon threads were mounted at various positions to evaluate airborne drift. The results showed that the mean normalized foliar depositions of the optimized sprayer were 1.57 and 1.81 µg cm^-2 / kg^-1 tracer ha^-1 for large and small trees, respectively, whereas with the conventional sprayer, the depositions were 0.85 and 2.11 µg cm^-2 / kg^-1 tracer ha^-1 for large and small trees, respectively. The optimized sprayer achieved a more uniform deposition distribution throughout the canopy compared to the conventional sprayer, as no significant differences in foliage deposition were detected between positions with the optimized sprayer. The optimized sprayer was capable of providing higher normalized deposits than the conventional sprayer for the large trees with less application volume. In addition, the optimized sprayer reduced spray losses in the air by 10% and 64% compared to the conventional sprayer for small and large trees, respectively, whereas ground losses were diminished by 45% and 50%, respectively. The results of this study suggest that controlling sprayer parameters, along with the spray volume adjustment based on canopy characteristics, may increase foliar deposition and could reduce pesticide use, although its influences on off-target loss reduction were insignificant. Keywords: Air conveyor, Constant-rate application, Digital control, Off-target losses, Pear fruit, Pesticide spraying, Tree row volume.