Unmanned Aerial Vehicle Spraying Research Articles

Study on droplet deposition characteristics and application of small and medium crown garden plants sprayed by UAV sprayer

The Unmanned Aerial Vehicle (UAV) sprayer has the advantages of high work efficiency, simple operation, and high safety factor, and has broad application prospects UAV sprayer are widely used in the agricultural field, and the application of UAV sprayer spraying technology in agriculture has provided convenience and increased profits for farmers, and has also become a research hotspot in the field of agriculture. In recent years, although research has been conducted on the feasibility and application effects of UAV sprayer spraying crown shaped plants, there have been no experiments or studies in the field of garden plants. This experiment conducted a droplet deposition experiment of UAV sprayer spraying garden plants, exploring the droplet deposition effect of UAV sprayer in the field of garden plants, and conducting experiments on the influence of spray volume and nozzle type on droplet deposition. The experimental results showed that the canopy performance of small and medium-sized garden plants was better at a flight altitude of 1.5m, a spray volume of 180L/hm2, and a flight speed of 2m/s. Reducing flight altitude, increasing spray volume, and reducing flight speed can improve the distribution of droplets in the canopy. This experiment lays the foundation for the application of UAV sprayer for the prevention and control of pests and diseases in garden plants, as well as for the application of growth regulators, and provides a basis for further innovative research in the field of garden plant application technology.

Increased outlet design of flat-fan nozzle improves octocopter unmanned aerial vehicle sprayer's efficiency

Increased interest in unmanned aerial vehicle (UAV) sprayers leads to identifying the factors affecting their efficiency. This study aimed to check and introduce a factor that has not been considered so far – the outlet design of a flat-fan nozzle. In a field experiment, spray drift potential and chemical weed control efficacy (sulfosulfuron against spontaneous barley) from an octocopter UAV sprayer was evaluated as a two-factor randomized complete block design including nozzle type (standard, anti-drift, and air induction) and nozzle outlet design (single, twin, and triplet-orifice). When averaged over nozzle outlet design, 22.9, 31.0, and 39.6% in-swath spray deposition and 66.0, 73.6, and 93.5% spontaneous barley control were obtained for standard, anti-drift, and air induction nozzles, respectively. Also, a similar trend from out-swath spray coverage was observed up to 8 m. In the standard, anti-drift, and air induction nozzles, an outlet design change from single-to triplet-orifice changed in-swath spray coverage by −30.8, +16.4, and +39.4% and herbicide efficacy by −27.1, +27.7, and +19.3%, respectively. The results showed that the outlet design of flat-fan nozzles had a significant interaction effect with the nozzle type. It was suitable with the anti-drift and air induction nozzles but unsuitable with the standard nozzle.

Tank-mix adjuvants improved spray performance and biological efficacy in rice insecticide application with unmanned aerial vehicle sprayer.

The use of unmanned aerial vehicles (UAVs) for the application of plant protection products (PPPs) in paddy fields is becoming increasingly prevalent worldwide. Despite its growing usage, UAV spraying for rice pest control faces practical challenges, including limited canopy penetration, uneven deposition, and significant spray drift. This study investigated the impact of two tank-mix adjuvants, Wonderful Rosin (Adjuvant-1) and Tiandun (Adjuvant-2), at six volume concentrations, on the spray liquid's physicochemical properties, spray drift, plant deposition, and the biological efficacy of rice insecticides using a quadrotor UAV sprayer. The physicochemical characteristics of the spray liquid influenced spray performance and biological efficacy. Incorporating Adjuvant-1 and Adjuvant-2 led to a decrease in surface tension and contact angle while increasing the viscosity of the spray solution. These alterations in surface tension and viscosity contributed to an optimized droplet size distribution, reduced spray drift, enhanced deposition uniformity and penetration, and improved control efficacy against the rice planthopper in UAV applications. The highest control efficacy was observed at a concentration of 0.5%, showing an improvement of 35.12% (Adjuvant-1) and 20.23% (Adjuvant-2) over applications without tank-mix adjuvant 7 days after treatment. The judicious selection of tank-mix adjuvants for UAV PPP applications can significantly enhance spray performance and biological efficacy in controlling rice insects. This study's findings offer valuable insights for integrating tank-mix adjuvants into UAV spraying applications. © 2024 Society of Chemical Industry.

Reducing environmental exposure to PPPs in super-high density olive orchards using UAV sprayers.

The increasing demand for optimizing the use of agricultural resources will require the adoption of cutting-edge technologies and precision farming management. Unmanned Aerial Vehicle (UAV) sprayers seem promising due to their potential to perform precision or spot spraying, particularly in woody crop environments where total surface spraying is unnecessary. However, incorporating this technology is limited by the lack of scientific knowledge about the environmental risks associated with UAV sprayers and the strict legal framework. Nonetheless, these spraying systems' characteristic downwash airflow and the limited swath width can potentially mitigate drift in hedgerow crops. During our study we performed comparative studies aimed to compare the airborne drift, soil, and crop depositions between a conventional orchard sprayer and a UAV sprayer in a commercial superhigh-density orchard in the South Iberian Peninsula in 2022. Our findings reveal that, in superhigh-density olive orchards, the UAV sprayer presents a substantial reduction in airborne drift, while soil depositions showed no significant differences compared to those of a conventional terrestrial orchard sprayer. Crop depositions were significantly lower when utilizing the UAV sprayer. These results suggest that introducing UAV spraying technology in Mediterranean agricultural systems, under specific scenarios, can effectively reduce the environmental impact of crop spraying and encourage the responsible use of plant protection products (PPPs).

Back pressure generated by downwash and crosswind on spatial atomization characteristics during UAV spraying: CFD analysis and verification.

During unmanned aerial vehicles (UAVs) spraying, downwash and crosswind generate back pressure in comprehensive, which changes in spatial atomization characteristics of spraying droplets. However, the process of such atomization characteristics needs to be clarified. This study focuses on the effect of rotor speed and crosswind speed on spatial atomization characteristics. The computational fluid dynamics (CFD) models of the distributions of airflow, back pressure and atomization characteristics were established, and verification was conducted by developing a validation platform. The CFD results indicated that small droplets of 65-130 μm atomized by negative pressure would be coalesced near the nozzle, while large droplets of 390-520 μm atomized by positive pressure would be aggregated further away. Crosswind caused atomization stratification with droplet sizes of approximately 90 μm, 320 μm and 390 μm. When crosswind speed increased from 3 m/s to 6 m/s, the spraying drifted from 0.5 m to 1 m. When rotor speed increased from 2000 RPM to 3000 RPM, droplet distribution was expanded and droplet particle size was more uniform. Verification results demonstrated that the spraying distribution and the droplet size variation were consistent with the CFD. Spatial atomization characteristics were highly correlated with airflow and back pressure. Moreover, as crosswind generated droplet drift and atomization stratification and downwash could improve the uniformity of droplet distribution, spraying performance was superior by enhancing downwash to restrain the adverse effect of crosswind in real applications. © 2023 Society of Chemical Industry.

How tank-mix adjuvant type and concentration influence the contact angle on wheat leaf surface.

Currently, the utilization of unmanned aerial vehicles (UAVs) for spraying pesticides is a prevalent issue in Asian countries. Improving the pesticide efficiency of UAV spraying is a major challenge for researchers. One of the factors that affect the efficiency is the wetting property of the spraying solutions on crop leaves. Tank-mix adjuvants, which can modify the wetting ability of the solutions, are often used for foliar application. However, different types and concentrations of tank-mix adjuvants may have different impacts on the wetting properties of droplets. In this article, we investigated the effects of four tank-mix adjuvants, Beidatong (BDT), Velezia Pro (VP), Nongjianfei (NJF), and Lieying (LY), on the dynamic contact angle (CA) values of droplets on the adaxial surface of wheat leaves. We measured the dynamic CA values of various concentrations of each adjuvant solution and determined the optimal concentrations based on the CA values, droplet spreading time, and cost. The results showed that adding any of the four adjuvants decreased the CA values, but the patterns of decrease varied among them. The CAs of BDT and VP solutions decreased slowly during the observation time (0-8.13 s), while those of NJF and LY solutions decreased rapidly throughout the observation period. According to the dynamic CA values of different concentrations, the optimal concentrations of BDT, VP, NJF, and LY for wheat field application were 12%, 16%, 6‰, and 0.3‰, respectively. Alkoxy-modified polytrisiloxane adjuvant (LY) could be recommended as an appropriate tank-mix adjuvant for wheat field application, considering spreading efficiency and cost. This study provides theoretical and practical guidance for selecting and optimizing tank-mix adjuvants for UAV spraying.

CFD analysis and RBFNN-based optimization of spraying system for a six-rotor unmanned aerial vehicle (UAV) sprayer

To reduce pesticide waste caused by low spray droplet coverage on target surface, the spraying system parameters of a six-rotor UAV sprayer are optimized. Computational Fluid Dynamics (CFD) is employed to simulate the downwash airflow distribution and droplet deposition for the UAV sprayer. Latin hypercube sampling method is used to obtain 15 sample points to train the surrogate model with CFD results. The validated CFD model is coupled with radial basis function neural networks (RBFNN) and genetic algorithm (GA) to optimize the spraying system parameters, including numbers of nozzles, horizontal position of nozzles and vertical position of nozzles. The overall correlation coefficient (R) of this RBFNN model is about 0.949, indicating good fitting performance. The optimal nozzles number of a six-rotor UAV sprayer is 4. The spraying droplet coverage is increased by 16.27%, 23.25% and 18.24% at a rotor height of 1 m, 2 m and 3 m above from the target surface, respectively, compared with the original six-rotor UAV spraying system structure. The spraying droplet coverage and pesticide utilization of the six-rotor UAV sprayer are improved through optimizing the mounting number and mounting positions of the nozzles in the spraying system. The research results provide a theoretical basis for further design and optimization of the multi-rotor UAV sprayers.

Efficacy of Two Tank-Mix Adjuvants to Control Mango Thrips Using a UAV Sprayer

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.

Challenges and opportunities of unmanned aerial vehicles as a new tool for crop pest control.

The application of pesticides is not simply delivering chemicals to the target area. It also involves considering the negative aspects and developing strategies to deal with them during the application process, to ensure the maximization of pesticides use efficiency and the maintenance of the ecosystem. Unmanned aerial vehicle (UAV) sprayers demonstrate unique advantages compared to traditional ground sprayers, particularly in terms of maneuverability and labor intensity reduction, showed great potential for chemical application in pest control. It is undeniable that there exist challenges in the practice of UAV spraying, such as higher potential risks of pesticide drift or pathogen transmission, uncertainty canopy deposition for different crops, and unexpected leaf breakage induced by downwash flow. Maximizing the utilization of downwash flow while avoiding lateral air movement outside the intended target crop area is a major issue for chemical application with UAV sprayers, particularly in light of the increasingly apparent consensus on the need for enhanced environmental protection during the chemical application process. It must be considered that the operation strategy in different scenarios and for different crop targets is not the same, unique requirements should be given on nozzle atomization, flight parameters, adjuvants and aircraft types in specific working situations. In future, the implementation of spray drift prediction, technical procedures development, and other solutions aimed at reducing pesticide drift and improving deposition quality, is expected to promote the adoption of UAV sprayers by more farmers. © 2023 Society of Chemical Industry.

Evaluation of the droplet deposition and control effect of a special adjuvant for unmanned aerial vehicle (UAV) sprayers.

Unmanned aerial vehicle (UAV) sprayers have been widely used in agriculture. With the goals of using pesticides efficiently and reducing their dosage, we evaluated the effects of adding and not adding special adjuvants to UAV sprayers on droplet deposition and the control effect of leaf folder insects. The deposition quantity and coverage area of UAV sprayers with the Kao Adjuvant A-200® on rice leaves were better than those without the Kao Adjuvant A-200®. Regarding the control effect on rice leaf rollers, UAV sprayers with the Kao Adjuvant A-200® were also better, and they also met the pesticide residue limit for brown rice. Kao Adjuvant A-200® can improve the UAV sprayer's droplet deposition and pest control effect. When the pesticide dosage was reduced by 30%, UAV sprayers with Kao Adjuvant A-200® can achieve a good control effect, which is very helpful in reducing the pesticide dosage.

Environmental impact of agricultural sprayers used in Japanese rice farming

ABSTRACTRice production in Japan faces severe labour shortage; hence, cutting-edge technologies, such as agricultural unmanned aerial vehicle (UAV) sprayers, are being actively considered and tested for installation in agricultural settings by the government. However, the environmental impacts of agricultural UAV sprayers remain unclear. Here, we aimed to assess the environmental performance of agricultural UAV sprayers in pest control during rice production in Japan, by comparing the environmental impact during pest control by using UAV, power, and boom spraying. We performed life cycle analysis with SimaPro 8 using the ReCiPe 2016 Midpoint (H) methodology and carried out sensitivity analyses to estimate the influence of input variables on emissions as a function of operational area. UAV spraying exhibited a lower environmental impact than did boom- and power spraying – attributed to the weight and fuel consumption of boom and power spraying, which increase the environmental impact associated with material production and energy consumption. Pesticide input remained constant, while the required water volumes for pesticide dilution differed among the sprayers. These results suggest the use of lighter and energy-saving machinery to mitigate the environmental impact of pest control in rice production; UAV spraying was found to be a good alternative to conventional methods.

Influence of Different Liquid Spray Pollination Parameters on Pollen Activity of Fruit Trees—Pear Liquid Spray Pollination as an Example

Liquid spray pollination (LSP) is widely used in fruit tree pollination. However, the LSP parameters that affect the pollen activity are still unclear. In this study, three LSP parameters that mainly affect the pollen activity were studied: storage time of pollen suspensions, sprayer parameters and unmanned aerial vehicle sprayer (UAVS) downwash airflow. In addition, sprayer parameters include the recirculation device, pump type, spraying pressure, nozzle size and revolutions per minute (rpm) of the rotary atomizer (RA). The results showed that, with the exception of nozzle size and UAVS downwash airflow, the pollen activity was significantly influenced by LSP parameters. The mean pollen activity decreased by 20.20% when the pollen suspension was stored for 30 min compared to 0 min. The activity of pollen in the tank was dramatically reduced using the recirculation device. The mean pollen activity decreases as the pump production maximum pressure increases. The mean pollen activity decreased from 40.7% to 29.02% when the spraying pressure increased from 0.3 MPa to 2.5 MPa. Additionally, the mean pollen activity decreased from 44.25% to 14.14% as the rpm of RA increased from 3000 rpm to 14,000 rpm. Our study demonstrated that pollen activity would be ensured by appropriate LSP parameters. This study provides a reliable theoretical basis for optimizing and advancing pear LSP technology.

CFD-based pesticide selection for a nozzle used in a six-rotor UAV in hover mode for tea spraying.

A key challenge for unmanned aerial vehicle (UAV) spraying sometimes used in tea plantations is the downwash flow structure there stronger than in crops. In addition, the UAV spray is affected by the relationship between the nozzle design and the pesticide. However, there is little current research on this aspect. As a preliminary step this study focuses on the most appropriate pesticide for a designated nozzle in a six-rotor UAV according to the nozzle-pesticide relationship using a three-dimensional computational fluid dynamics model. This model considers the downwash flow structure effect and nozzle spray performance in hover. Nozzle FVP110-02, widely used in six-rotor UAVs, is used as a representative nozzle and bifenthrin and tea saponin water, commonly used in tea plantations, are used as the pesticides. The downwash flow structure of the six-rotor UAV in hover was conveniently controlled by the flight height and rotational speed, thereby causing the turbulence to be more stable. For nozzle FVP110-02, bifenthrin was more appropriate than tea saponin water at the same concentration, whilst bifenthrin and tea saponin water at a concentration of 1:1000 showed the best performance under identical working conditions. The numerical model developed here was shown to be effective for investigating the relationship between nozzle and pesticide. Our findings will help to not only improve UAV spraying for tea cultivation but also provide guidelines for pesticide selection in crops. Further work will address the comparison of the rigorous qualification of the numerical simulations with the measurements by the field test. © 2023 Society of Chemical Industry.

Optimization-Design and Atomization-Performance Study of Aerial Dual-Atomization Centrifugal Atomizer

The aerial atomizer is the most essential component of the plant protection UAV (unmanned aerial vehicle). However, the structural optimization of existing aerial atomizers lacks comprehensive consideration of spray parameters and structural parameters, and there is a shortage of available atomizer spray models, resulting in the unstable effect of UAV application. In our previous work, an aerial dual-atomization centrifugal atomizer was developed. In order to obtain an aerial atomizer with good atomization effect and its atomization model, structural optimization at different rotation speeds and flow rates of the atomizer, and its atomization performance, are studied in this paper. Firstly, with the droplet volume median diameter (VMD) and spectral width (SRW) as the evaluation index, through the single-factor, Plackett–Burman and Box–Behnken tests, the influence of rotation speed, flow rate, tooth number and tooth shape were studied. The regression models of the droplet VMD and SRW were established using multiple quadratic regression fitting of the test data. Secondly, in order to achieve the lowest droplet VMD and SRW, the response surface method and post-hoc multiple comparison method were used to obtain the optimized structure of the atomizer’s rotation ring at different rotation speeds (600–7000 r/min) and flow rates (500–1000 mL/min). Lastly, with the effective swath width (ESW) of the optimized atomizer as the evaluation index, through the Box–Behnken test, the influence of rotation speed, flow rate and spray height were studied. The multiple quadratic regression model of ESW was established with the test data. The test results indicated that rotation speed, flow rate and tooth number had a significant effect on droplet VMD and SRW; tooth shape had no significant effect on the droplet VMD and SRW, however, the square tooth shape had the best atomization effect; and rotation speed, flow rate and spray height had a significant effect on ESW. The optimized structural parameters were tooth shape: square, and tooth number: 20. The determination coefficient R2 of the regression model of VMD, SRW and ESW were 0.9976, 0.9770 and 0.9974, respectively, which indicates that the model was accurate, and can evaluate and predict the spray effect. This paper provides an optimized dual-atomization centrifugal atomizer, and its regression models of VMD, SRW and ESW for UAV applications can provide a reference for efficient UAV spraying.

Design and validation of a multi-objective waypoint planning algorithm for UAV spraying in orchards based on improved ant colony algorithm.

Current aerial plant protection with Unmanned Aerial Vehicles (UAV) usually applies full coverage route planning, which is challenging for plant protection operations in the orchards in South China. Because the fruit planting has the characteristics of dispersal and irregularity, full-coverage route spraying causes re-application as well as missed application, resulting in environmental pollution. Therefore, it is of great significance to plan an efficient, low-consumption and accurate plant protection route considering the flight characteristics of UAVs and orchard planting characteristics. This study proposes a plant protection route planning algorithm to solve the waypoint planning problem of UAV multi-objective tasks in orchard scenes. By improving the heuristic function in Ant Colony Optimization (ACO), the algorithm combines corner cost and distance cost for multi-objective node optimization. At the same time, a sorting optimization mechanism was introduced to speed up the iteration speed of the algorithm and avoid the influence of inferior paths on the optimal results. Finally, Multi-source Ant Colony Optimization (MS-ACO) was proposed after cleaning the nodes of the solution path. The simulation results of the three test fields show that compared with ACO, the path length optimization rate of MS-ACO are 3.89%, 4.6% and 2.86%, respectively, the optimization rate of total path angles are 21.94%, 45.06% and 55.94%, respectively, and the optimization rate of node numbers are 61.05%, 74.84% and 75.47%, respectively. MS-ACO can effectively reduce the corner cost and the number of nodes. The results of field experiments show that for each test field, MS-ACO has a significant optimization effect compared with ACO, with an optimization rate of energy consumption per meter of more than 30%, the optimization rate of flight time are 46.67%, 56% and 59.01%, respectively, and the optimization rate of corner angle are 50.76%, 61.78% and 71.1%, respectively. The feasibility and effectiveness of the algorithm were further verified. The algorithm proposed in this study can optimize the spraying path according to the position of each fruit tree and the flight characteristics of UAV, effectively reduce the energy consumption of UAV flight, improve the operating efficiency, and provide technical reference for the waypoint planning of plant protection UAV in the orchard scene.

Effects of spray adjuvants and operation modes on droplet deposition and elm aphid control using an unmanned aerial vehicle

A conventional spraying mode and a fully autonomous fruit tree operation mode using a model DJ T30 unmanned aerial vehicle (UAV) were used to control aphids control on elm trees and to clarify the distribution of droplets in elm trees sprayed by an UAV. The effects of six aviation spray adjuvants on elm canopy droplet deposition and aphid control were evaluated. ImageJ software was used to analyze and measure the droplet density and deposition of water sensitive paper in two modes; this was done to calculate the droplet uniformity, depositional penetration and droplet penetration, and to verify the aphid control effect. The results showed that the droplet density increased by 79.7%-100.7% in the upper canopy and 0-394.1% in the lower canopy without adjuvants in the fully autonomous fruit tree operation mode. The upper canopy deposits increased by 65.7%-179.3%, and the lower canopy increased by 0-152.8%. When adjuvants were added, the droplet density in the upper canopy increased by 49.7-56.1% using Jiexiaofeng (JXF), and the lower canopy increased by 138.2%-177.8% using JXF, 45.8%-141.3% using Beidatong (BDT), 45.5%-92.9% using Gongbei (GB), 0-93.5% using Maisi (MS), and 0-95.2% using Manniu (MN). The deposits of the upper canopy increased by 888.1-1154.2% using JXF, 0-1298.3% using MN, 0-343.9% using BDT, 0-422.5% using GB, 0-580.3% using MS. The lower canopy increased by 746.4%-1426.0% using JXF, 226.2%-231.0% using BDT, 435.8%-644.0% using GB, 255.0%-322.4% using MS, and 249.3%-360.0% using MN. When JXF was added, the droplet uniformity, droplet penetration and depositional penetration were better than when using other adjuvants. The effects of JXF, BDT and GB in controlling aphids was significantly better than other adjuvants (p<0.05). The following control effects were observed; 94.1% with JXF, 93.1% with BDT, and 93.3% with GB after 3 d of application, and 97.9% with JXF, 95.6% with BDT, and 97.1% with GB after 7 d of application. At the same time, the application of the fully autonomous fruit tree operation mode and JXF can effectively improve the density and deposits, which will produce a superposition optimization effect. Our study focuses on the prevention and control of elm aphid infestations based on the operation mode of a UAV and aviation spray adjuvants, which can provide a baseline for the control of diseases and insect pests using UAVs in agriculture and forestry. Keywords: adjuvants, UAV, operation mode, droplet deposition, aphid DOI: 10.25165/j.ijabe.20231602.7424 Citation: Dou Z C, Fang Z H, Han X Q, Zeeshan M, Liu Y P, Lan Y B. Effects of spray adjuvants and operation modes on droplet deposition and elm aphid control using an unmanned aerial vehicle. Int J Agric & Biol Eng, 2023; 16(2): -.

Study on Spray Deposition and Drift Characteristics of UAV Agricultural Sprayer for Application of Insecticide in Redgram Crop (Cajanus cajan L. Millsp.)

Insecticide applications are typically being carried out with traditional manual spraying equipment in redgram, which leads to inadequate control of insects due to higher crop height. The modern deployment of tractor-drawn spray machines causes serious damage to the crop. In this connection, unmanned aerial vehicle (UAV) spray technology has great potential for precise insecticide application in redgram crops. One of the important machine parameters influencing droplet deposition and drift characteristics in UAV sprayers is downwash airflow generated by a multi-rotor propeller. A field experiment was carried out at the redgram research field (N11.01, E76.92), Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, during 2021–2022 to study the spray drift and deposition characteristics of an autonomous UAV sprayer. The Imidacloprid (a.i. 17.8SL) insecticide mixed with water in a ratio of 1 mL per liter was sprayed with a UAV sprayer. Water-sensitive paper samples were kept at upper, middle, and bottom positions on the leaves, and data were analyzed for the spray droplet size, deposition rate, droplet density, and area coverage both in target and non-target areas using Spray Deposit Scanner software. UAV spray droplet deposition rate (2.93 ± 0.17, 2.01 ± 0.08, and 2.21 ± 0.162.38 μL cm−2), droplet density (47 ± 4.04, 53 ± 3.61, and 52 ± 8.74 droplets cm−2), and area coverage (15.72 ± 0.39, 16.60 ± 0.71, and 14.99 ± 0.39%) were highest in the upper layer as compared to the middle layer (droplet deposition rate: 1.21 ± 0.08, 1.07 ± 0.03, and 0.77 ± 0.02 μL cm−2; droplet density: 42 ± 2.52, 43 ± 8.50, and 38 ± 2.52 droplets cm−2; area coverage: 10.95 ± 0.81, 11.22 ± 0.56, and 8.57 ± 0.44%) and bottom layer (droplet deposition rate: 0.41 ± 0.06, 0.35 ± 0.03, and 0.33 ± 0.03 μL cm−2; droplet density: 22 ± 4.36, 17 ± 3.51, and 19 ± 4.51 droplets cm−2; area coverage: 2.78 ± 0.29, 2.95 ± 0.45, and 2.46 ± 0.20%, respectively). In the spray drift test, there was a higher droplet deposition rate (1.63 ± 0.09, 1.93 ± 0.05, and 1.82 ± 0.06 μL cm−2), area coverage (14.40 ± 0.07, 17.54 ± 0.36, and 16.42 ± 0.30%), and droplet density (46 ± 3.61, 54 ± 2.08, and 45 ± 3.21 No’s cm−2) in the target area as compared to the non-target area (droplet deposition rate: 0.88 ± 0.02, 0.46 ± 0.03, 0.22 ± 0.05, and 0.00 μL cm−2; droplet density: 23 ± 1.53, 11 ± 2.08, 6 ± 1.53, and 0.00 droplets cm−2; area coverage: 7.58 ± 0.34, 4.41 ± 0.19, 2.16 ± 0.05, and 0.00%, respectively), which may have been due to the downwash airflow produced by the multi-rotor propeller of the UAV sprayer. Finally, the UAV-based spraying technology results showed that the downwash air produced by the six-rotor propeller improved the penetrability of insecticide to crop leaves and led to a higher droplet deposition rate, droplet density, area coverage, and droplet penetrability on the upper layer, middle layer, and bottom layer of the plants.

Impacto da altura de voo de drone pulverizador no espectro de gotas em café de montanha

ABSTRACT Weather conditions and sprayer operating parameters influence spray quality. Unmanned aerial vehicles are considered a modern, useful, and very efficient technological tool in the application of pesticides, as they carry out punctual spraying, and reduce environmental and public health problems. The objective of this study was to characterize the spraying quality carried out with an unmanned aerial vehicle as a function of flight height and target position in a coffee plantation in a mountainous region. Three flight heights (2.5, 3.0, and 4.0 m) were used, and the targets were placed at the top and bottom of the plant. For each plant, six water sensitive papers were placed on top of the plant and six were placed at the bottom. CIR 1.5 software was applied to determine the coverage percentage, drop density, volume median diameter, volumetric diameter corresponding to 10 and 90%, numerical median diameter, and relative amplitude. The results showed that the flight height only influenced the parameters of the volumetric diameter corresponding to 10% of the volume, numerical median diameter, and coverage percentage. The target position on the canopy influenced all the evaluated spraying parameters. In mountainous coffee plantations, the spraying system using unmanned aerial vehicle spraying is more efficient for the lower part of the plant.

Effect of flight velocity on droplet deposition and drift of combined pesticides sprayed using an unmanned aerial vehicle sprayer in a peach orchard

Extensive research has been conducted on plant protection unmanned aerial vehicle (UAV) chemical application technology in recent years owing to its importance as a means of pest and disease control. UAV spraying in orchards faces the drawback of drift risk and can be hazardous to non-targeted crops, humans, and the environment. A detailed and systematic analysis must be performed to determine the uniformity and drift risk of plant UAV sprays. In this study, a peach orchard is sprayed with a plant-protection UAV at three different flight velocities and we evaluate the combined pesticide deposition performance of the canopy, ground loss, downwind ground drift, and airborne drift. Additionally, the droplet size and coverage rate in the canopy are calculated by using water-sensitive paper. The results demonstrate that there is significant difference in the droplet size at flight velocities of 1–3 m/s. The droplet size in the lower canopy is slightly smaller than those in the middle and upper parts. Increasing the flight velocity helps the pesticide droplets to spread and penetrate the canopy. However, it also causes a non-uniform pesticide deposition, reduced effective coverage ratio and effective density ratio. Among the three pesticides used in the experiment, imidacloprid exhibits the best deposition efficiency. The deposition amount and normalized deposition amount in the canopy were the highest at a flight velocity of 2 m/s, accompanied by a lower ground loss under the canopy. The highest near-field ground drift is observed at a velocity of 1 m/s, and the far-field airborne drift is highest at 3 m/s. Lastly, this study provides a reference for the commercial application of plant-protection UAVs.

Evaluation of UAV spraying quality based on 1D-CNN model and wireless multi-sensors system

The droplet deposition is a key index to evaluate the quality of unmanned aerial vehicle (UAV) spraying. The detection of the droplet deposition is time-consuming and costly, therefore, it is difficult to achieve large-scale and rapid acquisition in the field. To solve the above problems, a droplet deposition acquisition system (DDAS) was developed. It was composed of the multiple sensors, processing units, remote server database and Android-based software. A droplet deposition prediction model based on field experimental data was established by using a one-dimensional convolutional neural network (1D-CNN) algorithm, and the effects of different inputs on the prediction ability of the model were analyzed. The results showed that adding temperature and humidity data to the inputs can achieve higher prediction accuracy than only using UAV spraying operation parameters and wind speed data as the inputs to the model. In addition, the prediction accuracy of the 1D-CNN model was the highest when compared with other models such as back propagation neural network, multiple correlation vector machine, and multiple linear regression. The 1D-CNN model was embedded into the DDAS, and the evaluation experiments were carried out in the field. The correlation analysis was conducted between two datasets of the droplet deposition obtained by the DDAS and water sensitive paper (WSP), respectively. The R2 was 0.924, and the RMSE was 0.026 μL/cm2. It is proved that the droplet deposition values obtained by the DDAS and WSP have high consistency, and the DDAS developed can provide an auxiliary solution for the intelligent evaluation of UAV spraying quality.