104 research outputs found

    Evaluation of the deposition and distribution of spray droplets in citrus orchards by plant protection drones

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    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

    Experimental evaluation of UAV spraying for peach trees of different shapes: effects of operational parameters on droplet distribution

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    Small-scale plant protection Unmanned Aerial Vehicles (UAVs) are finding a wide range of applications in modern agriculture management (including aerial spraying) due to their high efficiency and flexibility, low labour/water requirement and no damage to crops and soils, which substantially increase agricultural productivity and sustainability. UAV operational parameters, however, have remarkable effects on droplet distribution in UAV spraying, which significantly affect pesticide utilization rate and treatment effectiveness. Therefore, this work aimed to evaluate the effects of UAV operational parameters on droplet distribution for orchard trees. In particular, peach, an important orchard tree worldwide, is investigated in this study, and two typical tree shapes were considered including Y-shape and Central Leader (CL)-shape. Specifically, UAV spraying experiments were performed in Shandong Institute of Pomology, Shandong Province, China, and gas powered helicopter 3WQF120-12 was chosen as the spraying platform. The UAV operational parameters under consideration include flight route (intra-row, inter-row), flight velocity (four levels: 2, 3, 4, 5 m/s), number of spray times (1 vs 2) and nozzle flow rate. Droplet coverage rate at different positions and layers, obtained by water sensitive papers, was chosen as the metric to evaluate spraying performance. Experimental results show that: (1) the spraying uniformity is different between Y-shape and CL-shape peach tree, where Y-shape exhibits uniformity for positions at inner or outer layers. CL-shape results in a higher droplet coverage at top layer while with uniformity at lower three layers; (2) for Y-shape peach, intra-row route obtained a higher droplet coverage rate; while for CL-shape peach inter-row not only saved spraying volume but also results in a higher droplet coverage rate; (3) for both tree shapes, the increase in flight velocity (2--5 m/s) significantly decreased the droplet coverage rate; (4) for Y-shape peach with doubling the number of spraying times decreased the spraying performance for unit area. (5) for CL-shape peach with intra-row route, increasing the nozzle flow rate from 1.8 to 2.2 Lmin1L\cdot min^{-1} can significantly improve the droplet coverage rate at top and bottom two layers. It is envisioned that this study can provide some fundamental guidance of the operation of small UAVs for the aerial spraying of peach trees and similar orchards

    UAV spraying on citrus crop: impact of tank-mix adjuvant on the contact angle and droplet distribution

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    Adding tank-mix adjuvants into the spray mixture is a common practice to improve droplet distribution for field crops (e.g., rice, wheat, corn, etc.) when using Unmanned Aerial Vehicle (UAV) sprayers. However, the effectiveness of tank-mix adjuvant for UAV spraying in orchard crops is still an open problem, considering their special canopy structure and leaf features. This study aims to evaluate the effects of a typical tank-mix adjuvant concentrations (i.e., Nong Jian Fei (NJF)) on Contact Angle (CA) and droplet distribution in the citrus tree canopy. Three commonly used parameters, namely dynamic CA, droplet coverage, and Volume Median Diameter (VMD), are adopted for performance evaluation. The dynamic CAs on the adaxial surface of citrus leaves, for water-only and NJF-presence sprays, respectively, are measured with five concentration levels, where three replications are performed for each concentration. The sprays with 0.5‰ NJF are adopted in the field experiment for evaluating droplet distributions, where Water Sensitive Papers (WSPs) are used as collectors. Two multi-rotor UAVs (DJI T20 and T30) which consist of different sizes of pesticide tanks and rotor diameters are used as the spraying platforms. Both water-only and NJF-presence treatments are conducted for the two UAVs, respectively. The results of the CA experiment show that NJF addition can significantly reduce the CAs of the sprays. The sprays with 0.5‰ NJF obtain the lowest CA within the observing time, suggesting a better spread ability on solid surface (e.g., WSPs or/and leaves). With respect to the effects of NJF addition on individual UAVs, the field trial results indicate that NJF addition can remarkably increase both the droplet coverage and VMD at three canopy layers, except for T30 droplet coverage of the inside and bottom layers. Comparing the difference of droplet coverage between two UAVs, while significant difference is found in the same layer before NJF addition, there is no notable difference appearing in the outside and bottom layers after NJF addition. The difference of VMD in the same layer between two UAVs is not affected by NJF addition except for the bottom layer. These results imply that the differences of droplet coverage among different UAVs might be mitigated, thus the droplet distribution of some UAVs could be improved by adding a tank-mix adjuvant into the sprays. This hypothesis is verified by investigating the droplet penetration and the correlation coefficient (CC) of droplet coverage and VMD. After NJF addition, the total percentage of T20 droplet coverage in the bottom and inside layers is increased by 5%. For both UAVs, the CCs indicate that both droplet coverage and VMD increase at the same time in most cases after NJF addition. In conclusion, the addition of a tank-mix adjuvant with the ability to reduce CA of the sprays, can effectively improve droplet distribution using UAV spraying in the citrus canopy by increasing droplet coverage and VMD

    UAV-spray application in vineyards: Flight modes and spray system adjustment effects on canopy deposit, coverage, and off-target losses

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    Improvements in the spray application of plant protection products enhance agricultural sustainability by reducing environmental contamination, but by increasing food quality and human safety. Currently, Unmanned Aerial Vehicles (UAVs) are raising interest in spray applications in 3D crops. However, operational configurations of UAV-spray systems need further investigation to maximise the deposition in the canopy and minimise the off-target losses. Our experimental research focused on investigating the effects on the canopy spray deposition and coverage due to different UAV-spray system configurations. Twelve configurations were tested under field conditions in an experimental vineyard (cv. Barbera), derived from the combination of different UAV flight modes (band and broadcast spray applications), nozzle types (conventional and air inclusion), and UAV cruise speeds (1 and 3 m s-1). Also, the best treatment, among those tested, by using the UAV-spray system and a traditional airblast sprayer were compared. The data was analysed by testing the effects of the three operational parameters and their two- and three-way interactions by means of linear mixed models. The results indicated that the flight mode deeply affects spray application efficiency. Compared to the broadcast spray modes, the band spray mode was able to increase the average canopy deposition from 0.052 to 0.161 μL cm-2 (+ 309 %) and reduce the average ground losses from 0.544 to 0.246 μL cm-2 (- 54 %). The conventional airblast sprayer, operated at a low spray application rate, showed higher canopy coverage and lower ground losses in comparison to the best UAV-spray system configuration

    Research on a UAV spray system combined with grid atomized droplets

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    BackgroundsUAVs for crop protection hold significant potential for application in mountainous orchard areas in China. However, certain issues pertaining to UAV spraying need to be addressed for further technological advancement, aimed at enhancing crop protection efficiency and reducing pesticide usage. These challenges include the potential for droplet drift, limited capacity for pesticide solution. Consequently, efforts are required to overcome these limitations and optimize UAV spraying technology.MethodsIn order to balance high deposition and low drift in plant protection UAV spraying, this study proposes a plant protection UAV spraying method. In order to study the operational effects of this spraying method, this study conducted a UAV spray and grid impact test to investigate the effects of different operational parameters on droplet deposition and drift. Meanwhile, a spray model was constructed using machine learning techniques to predict the spraying effect of this method.Results and discussionThis study investigated the droplet deposition rate and downwind drift rate on three types of citrus trees: traditional densely planted trees, dwarf trees, and hedged trees, considering different particle sizes and UAV flight altitudes. Analyzing the effect of increasing the grid on droplet coverage and deposition density for different tree forms. The findings demonstrated a significantly improved droplet deposition rate on dwarf and hedged citrus trees compared to traditional densely planted trees and adopting a fixed-height grid increased droplet coverage and deposition density for both the densely planted and trellised citrus trees, but had the opposite effect on dwarfed citrus trees. When using the grid system. Among the factors examined, the height of the sampling point exhibited the greatest influence on the droplet deposition rate, whereas UAV flight height and droplet particle size had no significant impact. The distance in relation to wind direction had the most substantial effect on droplet drift rate. In terms of predicting droplet drift rate, the BP neural network performed inadequately with a coefficient of determination of 0.88. Conversely, REGRESS, ELM, and RBFNN yielded similar and notably superior results with a coefficient of determination greater than 0.95. Notably, ELM demonstrated the smallest root mean square error

    Fluorescence tracer method for analysis of droplet deposition pattern characteristics of the sprays applied via unmanned aerial vehicle

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    With the development of agricultural aviation technologies and their application in agricultural production, plant protection unmanned aerial vehicle (UAV) has been widely used to control pests and diseases of crops. The high speed rotation of the rotor in the UAV produces a powerful downwash affecting the distribution of pesticide droplets on the ground. Understanding spatial distribution of these droplets on the ground is important to evaluate application quality of the pesticides and plays an important role in improving the spray system in UAV and optimizing its operating parameters. Current methods for measuring the droplet deposition distributions use a number of collectors placed regularly on the ground to receive the droplets and measured their sizes; it is difficult for them to effectively obtain the deposition of all droplets resultdue to the downwash of UAV. This paper presents a new method to resolve this problem by improving accuracy and spatial continuity of pesticide droplets measurement applied by an unmanned helicopter. The flying parameters of a 3WQF–80–10 unmanned helicopter used to spray pesticides were obtained from the high–precision Beidou navigation system, and the RQT–C–3 fluorescent whitening tracer with mass fraction of 1.0% was used as the proxy for the pesticides. Two droplet collection methods: one used continuous strip paper and the other one used individual water sensitive paper, were used to measure the droplets deposition distribution. We divided the experimental field into three areas, with Areas 1 and 2 spaced 3 m apart, and Areas 2 and 3 spaced 1m apart. A metal bracket 8 m log and 0.5 m away from the ground was placed in each area. Prior to the experiment, a paper tape was fixed on the surface of the bracket and the water–sensitive paper cards were placed evenly in the area 0.5 m away from the paper tape. There were one paper tape and 15 water sensitive papers in each area, and a total of six spray tests were performed based on pro–designed flight parameters. The combinations of flight speed and flight height were: 2 m/s and 3 m, 2 m/s and 6 m, 2 m/s and 9 m, 3 m/s and 3 m, 3 m/s and 6 m, and 4 m/s and 9 m. The paper tape was detected by fluorescence spectroscopy analysis, and the water sensitive papers were scanned using an image processing software to obtain droplet deposition coverage rate. The results showed that distribution curves of the coverage rate obtained by the paper tape method coupled with the fluorescence spectrum tracer were consistent with that obtained from the images of the water sensitive paper method, with the R2 being 0.88~0.96. Because not all fine droplets fell on the water sensitive papers due to the effect of the high speed rotating rotor, the coverage rate curve measured by the continuous fluorescence method had multiple peaks and the value of its coverage rate was higher than that measured from the water sensitive paper method. When the unmanned helicopter flew at speed of 2 m/s and height of 3 m, the coverage ratio obtained from the continuous fluorescence method was up 16.92% compared to that sampled from the individual water–sensitive paper method, while when the flight speed was 4 m/s at height of 9 m, the coverage ratio in the latter was 97.77% higher than in the former. In terms of the impacts of unmanned helicopter operating conditions on coverage rate, when the helicopter flew at 2 m/ s and height of 3 m, the coverage rate of the droplets obtained from the two methods were the highest, being 8.34% for the continuous fluorescence method and 7.14% for the individual paper method. With the flight height and speed increasing, the spatial coverage rate of the droplets decreased. In summary, the high–speed rotor of UAV generates a downwash, making the droplets of pesticides move in different directions and resulting in a large spatial difference in their deposition on the ground. Therefore, the continuous sampling method is more adequate to evaluate the spatial distribution of the droplets. This study has implication for study on detecting deposition of pesticides and other agrochemicals applied by UAV

    Advancements of Spraying Technology in Agriculture

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    Plant protection activities are most important practices during crop production. Application of maximum pesticide products with the sprayer. The application of fungicides, herbicides, and insecticides is one of the most recurrent and significant tasks in agriculture. Conventional agricultural spraying techniques have made the inconsistency between economic growth and environmental protection in agricultural production. Spraying techniques continuously developed in recent decades. For pesticide application, it is not the only sprayer that is essential, but all the parameters like the type and area of the plant canopy, area of a plant leaf, height of the crop, and volume of plants related to plant protection product applications are very important for obtaining better results. From this point of view, the advancement in agriculture sprayer has been started in last few decades. Robotics and automatic spraying technologies like variable rate sprayers, UAV sprayers, and electrostatic sprayers are growing to Increase the utilization rate of pesticides, reduce pesticide residues, real-time, cost-saving, high compatibility of plant protection products application. These technologies are under the “umbrella” of precision agriculture. The mechanized spraying system, usually implemented by highly precise equipment or mobile robots, which, makes possible the selective targeting of pesticide application on desire time and place. These advanced spraying technologies not only reduces the labour cost but also effective in environmental protection. Researchers are conducting experimental studies on the design, development and testing of precision spraying technologies for crops and orchards

    Review on Automatic Variable-Rate Spraying Systems Based on Orchard Canopy Characterization

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    Pesticide consumption and environmental pollution in orchards can be greatly decreased by combining variable-rate spray treatments with proportional control systems. Nowadays, farmers can use variable-rate canopy spraying to apply weed killers only where they are required which provides environmental friendly and cost-effective crop protection chemicals. Moreover, restricting the use of pesticides as Plant Protection Products (PPP) while maintaining appropriate canopy deposition is a serious challenge. Additionally, automatic sprayers that adjust their application rates to the size and shape of orchard plantations has indicated a significant potential for reducing the use of pesticides. For the automatic spraying, the existing research used an Artificial Intelligence and Machine Learning. Also, spraying efficiency can be increased by lowering spray losses from ground deposition and off-target drift. Therefore, this study involves a thorough examination of the existing variable-rate spraying techniques in orchards. In addition to providing examples of their predictions and briefly addressing the influences on spraying parameters, it also presents various alternatives to avoiding pesticide overuse and explores their advantages and disadvantages

    Field Evaluation of Commercially Available Small Unmanned Aircraft Crop Spray Systems

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    Agricultural research and development on small unmanned aircraft systems (UAS) has been directed toward UAS enabled sensing to detect features of interest. While compelling, there is an immediate need to increase the breadth and depth of UAS-based research, to move beyond sensing, and explore active intervention in agricultural production systems. This paper is focused on the concept of crop protection through ultra-precise, unmanned aerial application systems, and seeks to initiate research discussion in this important area of opportunity. Toward this end, two different, commercially available, small Unmanned Aerial Application Systems (sUAAS - defined as less than 55 lbs. maximum take-off weight) were evaluated for operational techniques and application system efficacy under dynamic field conditions. The performance of the factory supplied spray equipment systems are documented using traditional aerial spray testing methods that have been modified for UAS enabled application systems, referred to as small Unmanned Aerial Application Systems (sUAAS). Results from initial testing protocols indicate that the factory supplied systems are quite different in design and implementation, with spray test results that reflect this difference in design, in both deposition and spray swath. Further, it is apparent that with the advent of unmanned aerial application systems, and the unique characteristics of the integrated aircraft and application systems, there is a very real need for the development of standardized sUAAS testing procedures

    Testing a multi-rotor unmanned aerial vehicle for spray application in high slope terraced vineyard

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    Unmanned aerial vehicles (UAVs) are being increasingly used for the spraying of pesticides for crop protection in complex geographic terrains that are not easily accessible by operators. This experiment was conducted to investigate the sprayer performance of a commercial UAV, equipped with different types of nozzles, and compare this new technology with the sprayers usually used on small size mountain vineyards (i.e. a knapsack sprayer and a sprayer gun). Field tests were conducted in a small high slope terraced vineyard. The operative parameters of the sprayers were calculated. Data on droplet coverage, density and size were collected by using water sensitive papers attached with clips to the leaves and analysed. The results showed that the working capacity of the UAV was 2-fold that of the sprayer gun 1.6-fold that of the knapsack sprayer. Droplet coverage, density and size were variable and affected by the position of the targets (water sensitive papers) and the type of sprayer used
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