Efficient utilization is a pre-requisite for pesticide reduction, and appropriate airflow distribution pattern plays a key role in enhancing the effectiveness of pesticide application by air-assisted orchard sprayers, yet the mechanism of this is unclear. In order to clarify the specific effects of airflow velocity and direction on spraying efficacy, a series of spray tests on pear and cherry and airflow distribution tests in open areas were conducted by a multi-unit air-assisted sprayer on ten different fan settings. Several deposit indicators were analyzed and contrasted with the air distribution. The results showed that an increase in airflow velocity inside the canopy improved the abaxial side deposit coverage of both pear (from 3.33% to 11.80% in the Top canopy and from 6.26% to 11.00% in the Upper canopy) and cherry leaves (from 3.61% to 10.87% in the Top canopy, from 1.36% to 9.04% in the Middle canopy, and from 3.40% to 9.04% in the Bottom canopy), but had no significant effect on the spray penetration. The correlation between deposit indicators and airflow velocities/directions was evaluated, and the results indicated that the enhanced airflow velocities, both in the forward and horizontal direction, improved the abaxial side deposit coverage (CAB) on the outside of pear canopy (p < 0.001), but for cherry, none of the airflow indicators had a significant impact on the CAB independently. On the other hand, the increased airflow direction angle in the cross-row plane for pear, as well as the increased airflow velocities in forward and vertical direction for cherry, both showed negative effects on the adaxial side deposit coverage (p < 0.01). The findings in this study might be helpful to improve the performance of pesticide application in orchards, especially for abaxial side deposition, and could provide a reference for the further investigations about the effect of airflow on spray canopy deposition.

In recent years, with the further development of agricultural aviation technology, the plant protection UAV has been widely used, especially in some agricultural environments with limited operating conditions due to its advantages of high efficiency, environmental protection and safety guarantee. A plant protection UAV generally flies at low altitude during operation. However, the low altitude operation environment, such as farmland and mountainous areas, is relatively complex, and is faced with many types of obstacles, proposing higher requirements for obstacle avoidance and the profiling system of a plant protection UAV. In order to test the obstacle avoidance and profiling performance of the commercialized plant protection UAV at this stage and explore the performance boundary of obstacle avoidance and profiling of the UAV, EAVISION E-A2021 and XAG P80, the flagship models of the plant protection UAV manufacturer on the market, were hereby selected as the experimental test objects in the paper. Firstly, the obstacle avoidance and profiling test scheme of plant protection UAVs is designed; then, the above two UAVs are adopted for corresponding tests, and the test data are discussed based on the analysis of software and hardware technology; finally, the practical application status of different obstacle avoidance and profiling technologies of plant protection UAVs is clarified, and the shortcomings of obstacle avoidance and profiling technology of plant protection UAVs on the market are summarized, providing a reliable reference for the future development of plant protection UAVs.

Strawberry is a widely cultivated cash crop in China. In order to control pests and diseases on strawberries, there must be sufficient deposits on the abaxial surfaces of the leaves. Air-assisted technology can effectively increase the deposition on the abaxial surfaces of the leaves; however, most air-assisted equipment is not suitable for application due to the pattern of strawberry planting. Therefore, a novel air-assisted strawberry sprayer was developed, the static and dynamic wind fields were measured using a 3D anemometer, and the effectiveness of the application at different spray angles and wind speeds was evaluated. In addition, a comparison of the deposition effect in the strawberry canopy between the air-assisted strawberry sprayer, knapsack sprayer, and spray gun was conducted. The results showed that in the static wind field test, a difference between the center and edge wind fields was obtained, which was correlated with the distance and the outlet wind speed. In the dynamic wind field test, the wind field was found to be rolling backward during the movement, and an inward vortex was obtained. In the field, the data showed that a spray angle of 30° and a wind speed of 16 m·s⁻¹ had the best deposition on the abaxial surface, with a coverage of 36.5% and 38.3% in the upper canopy and 6.2% and 7.9% in the lower canopy, respectively. Moreover, the air-assisted strawberry sprayer was found to have a higher deposition efficiency on abaxial surfaces than the knapsack sprayer and spray gun at a lower spray volume, the values of which in the upper and lower canopies were 42.8% and 29.7%, respectively. In conclusion, the air-assisted strawberry sprayer has the potential for the crop protection of greenhouse strawberries, and more evaluations are needed to improve the sprayer in the future.

Thrips have become some of the most challenging pests to control in mango production due to their short developmental time, hidden locations and resistance to pesticides, in the tropical regions of China. To improve pesticides efficacy, the tank-mix adjuvants Qi Gong (QG) and the thrips attractant Lv Dian (LD) were added when using an unmanned aerial vehicle (UAV) to control thrips. The surface tension, contact angle on mango leaves, droplet size, spreading rate, and drying time of the two tank-mix adjuvants were determined. The effects of the two tank-mix adjuvants using a UAV sprayer on the droplet coverage and control efficacy against thrips on mango inflorescences were tested through field trials. The results showed that both QG and LD could reduce the surface tension of the liquid and the contact angle on mango leaves and could increase the spreading performance. The droplet coverage in the upper layer of the canopy was about 2% higher than that in the lower layer, and the coverage at the top of the panicle was 5% higher than that at the bottom. QG improved the deposition coverage of mango inflorescences by about 31.5%. The addition of QG increased the efficacy by 18.24% and 8.03%, respectively, at florescence and the young fruit stage. The addition of the LD increased the efficacy by 24.56% and 14.38%, respectively, at florescence and the young fruit stage. These test results can provide a scientific basis for the control of mango thrips with UAVs.