Plant protection drone spraying technology is widely used to prevent and control crop diseases and pests due to its advantages of being unaffected by crop growth patterns and terrain restrictions, high operational efficiency, and low labor requirements. The operational parameters of plant protection drones significantly impact the distribution of spray droplets, thereby affecting pesticide utilization. In this study, a field experiment was conducted to determine the working modes of two representative plant protection drones and an electric backpack sprayer as a control to explore the characteristics of droplet deposition with different spray volumes in the citrus canopy. The results showed that the spraying volume significantly affected the number of droplets and the spray coverage. The number of droplets and the spray coverage area on the leaf surface were significantly increased by increasing the spray volume from 60 L/ha to 120 L/ha in plant protection drones. Particularly for the DJI T30, the mid-lower canopy showed a spray coverage increase of 52.5%. The droplet density demonstrated the most significant variations in the lower inner canopy, ranging from 18.7 droplets/cm² to 41.7 droplets/cm² by XAG V40. From the deposition distribution on fruit trees, the plant protection drones exhibit good penetration ability, as the droplets can achieve a relatively even distribution in different canopy layers of citrus trees. The droplet distribution uniformity inside the canopy is similar for XAG V40 and DJI T30, with a variation coefficient of approximately 50%-100%. Compared to the plant protection drones, the knapsack electric sprayer is suitable for pest and disease control in the mid-lower canopy, but they face challenges of insufficient deposition capability in the upper canopy and overall poor spray uniformity. The distribution of deposition determined in this study provides data support for the selection of spraying agents for fruit trees by plant protection drones and for the control of different pests and diseases.

The use of drones in agriculture is expanding at a brisk pace in crop production due to the superiority in precision, efficiency, and safety of their applicators. However, their potential drift risk also raises concern for users and regulatory authorities. The method of wind tunnel research can effectively evaluate the weighted influence of each drift factor, especially the drift characteristics of the nozzle and spray solution. Based on the wind tunnel test results, centrifugal nozzles have a higher drift risk than hydraulic nozzles, even with a similar DV₅₀. The cumulative drift rate of the centrifugal nozzle at 2 m downwind was 90.1% compared to the LU12001 nozzle’s 40.6% under the wind speed of 3.5 m/s. Compared with the same coding as the flat fan hydraulic nozzle, the IDK nozzle can effectively reduce the drift rate. For the tested nozzles, DV₅₀ and wind speed had a linear relationship with drift rate, and the sampling location had an exponential or logarithmic relationship with drift rate. Spray adjuvants, especially modified vegetable oils, had a significant effect on reducing the amount of drift. The results of this experiment provide a reference for the selection of nozzles and the addition of spray adjuvants. Further clarifying the spray drift characteristics of drones until a drift prediction model is available is still the focus of research.

The droplet size distribution following pesticide application practices can significantly impact droplet drift and non-target organisms (animals and plants). However, the relationship among liquid sheet breakup, drop formation, and droplet drift is an area that has been studied over the past 65 years but is still not fully understood. The objectives of this study were severalfold: to examine the liquid sheet breakup following the use of different adjuvants (sodium dodecyl sulfate, aerosol OT, and silicone at 1%) and their effects on the drift via three commonly used commercial spray nozzles (XR, AIXR, and TXVK). The spray sheet and initial droplet size spectrum for each spray was detected by a particle image velocimetry (PIV) system, and the drift for each treatment was measured in a wind tunnel. The nozzle type and the spray solution were found to significantly affect the liquid sheet breakup characteristics. AIXR produced large droplets, and TXVK with short liquid sheet length produced more small droplets. All adjuvants used in these experiments increased the formation of large droplets upon atomization while simultaneously reducing driftable fines (e.g., drops %<150 µm). The drift potential can be reduced by up to 66.1% when switching from a fine spray quality (TXVK) to a coarse spray quality (AIXR). The SDS adjuvant provided the most effective drift reduction for XR and TXVK nozzles showing reduced drift potential by 69.2% and 66.3%, respectively, while the silicone adjuvant showed the largest drift reduction for AIXR of 78.3%. The correlation between the liquid sheet length and D_V0.5 was positive for XR and TXVK nozzles, and there was a significant positive correlation between %<150 µm and drift potential for all nozzles. This work suggests that the drift can be reduced significantly by changing the nozzle type and adding pesticide adjuvant into spray solution, which provided data support for the drift reduction of plant protection drones.

The feasibility of aerial fertilization by UAV-based granular fertilizer spreaders (GFSs) has been widely accepted. Although commercial UAV-based spreaders have emerged, their performance in granular fertilizer spreading application has rarely been studied. This paper tested the performances of four existing UAV-based GFSs in the automatic controllability, range of the discharge rate and the swath width and uniformity of the distribution. An analytic hierarchy process (AHP)-based method was proposed to evaluate their comprehensive performance in spreading application. The main results are as follows: (a) GFS-A showed the maximum controllable discharge rate of 27 kg/min, and GFS-B showed the minimum (proximately 3 kg/min). The discharge rate could be changed in a stepless way by GFS-B, C and D. The relationship between the discharge rate and the rotational speed of the fluted roller of GFS-D showed a significant linear relationship ( $\text {R}^{2} = 0.9991$ ) for the operational range. (b) The distribution patterns of GFS-A and D were trapezoidal, which was the better deposition pattern for generating uniform spreading; those of the other two UAV-based GFSs were a wide triangle with obviously asymmetrical sides (GFS-B) and a typical M-shape with two peaks (GFS-C). (c) the simulation of CV-swath width illustrated that the available effective swath width (CV ≤ 20%) for these UAV-GFSs were 5.1m (CV = 14.73%), 4.8m(CV = 17.55%), 3.9m(CV = 13.02%) and 5.7m(CV = 18.36%) respectively under the given conditions. Furthermore, according to the AHP-based evaluation model, it was proved that GFS-D was able to provide superior performance in precise fertilization for a large application range, which is important for its practical application. This comparative study makes useful contribution for farmers and researchers in this field in understanding the application performance of various UAV-based GFSs.

As an effective supplement to ground machinery, UAVs play an important role in agriculture and have become indispensable intelligent equipment in the development of precision agriculture. Various types of agricultural UAV-based spreading devices, mainly disc-type and pneumatic-type, have appeared in domestic and foreign markets. UAV-based rice topdressing has gradually become a widely recognized application with great market potential. In the process of UAV-based low-altitude fertilization, due to the existence of the rotor wind field, the environment for particle air diffusion is complex, and the movement trajectory and deposition distribution of fertilizer are affected by many factors, resulting in large differences in the spreading. The flight height and speed have a great influence on particle movement and deposition, and a reasonable combination of work parameters can be used for efficient and high-quality particle deposition. In order to obtain better particle deposition distribution, this paper uses the method of a single flight line to test and analyze the characteristics of particle deposition distribution for fertilization using multi-rotor UAVs at different flight heights and speeds. The effective swath width and deposition uniformity obtained via the simulation of overlapped route superposition were used to optimized the appropriate work parameters to ensure that a reasonable and effective deposition amount can be obtained during actual application. The results show that the flight height and speed and the interaction of both have an important influence on the deposition amount and the effective width, but it is not a simple linear relationship. On the whole, as the flight height increases, the coefficient of variation decreases and the effective width increases, but it is not obvious when the speed is low. For the R20, when the flight speed is 2 m/s, the effective width first increases and then decreases with the increase in flight height, and the difference in the deposition amount at a height of 5 m is larger than that at other heights. Under the three working heights, the effective swath width is the same when the flight speed is 4 m/s and 6 m/s, and the effective swath width is also the same when the speed is 7 m and 9 m. For the T16, when the flight speed is 4 m/s, the deposition uniformity is relatively good, and the effective width increases with the increase in flight height. Therefore, the combination of 7–6 m/s and 9–4 m/s parameters will be the best operating parameters for R20 and T16. However, considering the actual dynamic meteorological environment in the field, the operating height can be appropriately lowered according to the influence of the crosswind during actual operation. The research results of this paper can provide scientific reference and suggestions for further improving the effect of UAV-based fertilization.

This paper proposes an optical tracking system to realize the clustering of multiple unmanned aerial vehicles (UAVs). The system uses a laser spot as a visual recognition target to realize cluster flight operations in a complex environment. To reduce the interference of sunlight in the optical visual navigation and obtain the optimal combination of laser receiving devices, we selected lasers in a variety of spectrum bands and filter films with different light transmittances to conduct a comprehensive test. By performing a fluid simulation of the UAVs with the related modules mounted in different positions, the optimal installation position was selected to enhance the effect of the UAV wind field. An online learning tracking framework based on the multi-feature extraction of convolutional networks was developed to realize robust long-term visual tracking. In the tracking process, the tracking algorithm could train the detector online according to the status of the target and adaptively initialize the target. Finally, to verify the practical application performance of the clustering system, a group of UAVs was tested in flight. We verified that the proposed method and device exhibit a high feasibility and reliability.