Propellers Spin Rate Effect of a Spraying Drone on Quality of Liquid Deposition in a Crown of Young Spruce

Abstract

The study aimed to assess the quality of spraying of ornamental conifer using a multi-rotor drone. We examined how the speed of drone movement and the propellers’ spin speed can affect the deposition quality of the sprayed liquid in the crown of blue spruce (Picea pungens Engelm.). Due to the avoidance in the future of droplet drift by air movements, an air injector atomiser for liquid spraying was used, and a low altitude of 0.6 m of the drone flying above the tree was used in the study. The drone moved at two speeds: 0.57 m·s^–1 and 0.94 m·s^–1. The propellers’ spin speeds were adjusted based on the drone’s weight with the spray liquid tank filled and empty. The propellers’ zero-spin rate was also included to compare the drone to a field sprayer. The tests were conducted in a laboratory setting. Volume and uniformity of liquid volume settled on the levels of samplers positioned on a tripod within the tree canopy were assessed. The samplers were placed in two zones of the tree: near the tree trunk and at a distance of 0.21 m from the trunk. Airstream speed generated by drone propellers was also evaluated inside the tree. The findings indicated that the rotations of propellers and air speed significantly influenced the quality of liquid deposition on samplers located away from the trunk. The results also showed that using a drone instead of a field sprayer could benefit the quality of the spray application. The weight of the multi-rotor drone, determined by the spray liquid tank’s filling level, can significantly impact the quality of spray deposition in the tree. Based on the investigations, it can be recommended that low-altitude spraying drones be adopted for studies and future strategies in precision agriculture using autonomous inspection-spraying drones.

1. Introduction

Protection against pests of ornamental tree crops is a crucial aspect of agriculture, forest nursery production, and forestry. Traditionally, crop protection treatments for young ornamental trees and forest nurseries are applied using a backpack or tractor-mounted field sprayers. However, this equipment is not always suitable for these tasks [1]. For trees in forests, pest spraying is mainly carried out using manned aircraft such as planes and helicopters [2,3]. Although treatments performed with aircraft are effective, this method is expensive due to the high cost of aviation equipment and infrastructure, as well as the cost associated with the spraying process itself. The deposition quality of the liquid droplets on trees is strongly influenced by the technical conditions of the flights, such as the aircraft type and speed, the liquid dose, the droplet size, the spray release height above the trees, as well as by the weather conditions, especially wind speed and air humidity. These factors can also cause droplet drift and evaporation [4,5,6].

Recently, unmanned aerial vehicles (UAVs), commonly known as drones, have emerged as a potential solution for protecting crops against pests [7,8,9,10]. These drones can be divided into two groups: inspection drones and work drones. Inspection drones are used to raid agricultural crops and forests to assess their development and health and even monitor the weather to evaluate pest possibility [11,12,13,14,15]. They are equipped with various types of cameras and scanners. The most popular are thermal, multispectral, or hyperspectral cameras, which allow selected spaces to be photographed in a specific wavelength of light, including colours invisible to the human eye. Working drones are used to carry out work from the air. In agriculture, they can be applied, besides spraying pesticides, as flying machines for sowing seeds, spreading and spraying chemical and organic fertilizers, and crop planting [7,9,15,16,17]. Due to the tremendous potential of drones for crop assessment and programming pesticide application rates based on inspection data, drones can be used to apply chemicals with variable rate application (VRA) [18]. Research is also being conducted into the intelligent use of drones as autonomous robots in precision agriculture, not only for crop protection but to perform other fieldwork [19,20]. Research shows that the future of drone use in precision agriculture also involves using artificial intelligence (AI) in evaluating the information obtained and steering not only individual unmanned aircraft in agricultural operations but a swarm of working drones on the field [20,21,22].

By construction, drones are divided into fixed-wing and rotor drones. Of the two types of drones, rotor drones, particularly multi-rotors with an electric power source, are most commonly used for crop protection.

Attempts have been made to compare the effects of spraying plants with drones to the effects of using ground-based sprayers, but this is not easy due to differences in the construction and conditions of use of the two types of equipment. Hence, conclusions are inconclusive [23]. A comparison of the penetration in the cotton plant canopy of liquid sprayed with a boom sprayer positioned above the plants at the height of 0.5 m with the penetration of liquid sprayed with a drone at heights of 1.5 and 2.0 m provided the result that liquid sprayed with a drone penetrates the plant canopy less than liquid sprayed with a sprayer [24].

Studies are being carried out on the effects of using unmanned aerial spraying systems (UASSs) to control pests in agricultural fields and plantations of trees in orchards [7,25,26,27,28,29]. It has been observed that the effectiveness of spray penetration, especially of the lower parts of the tree crown, is influenced by such factors as the flight height and speed of the drone above the tree crown and the shape of the tree crown.

There are also attempts to use drones for spraying trees in forests [30,31]. Compared with classic aerial treatments using human-manned aviation, the advantages of using drones in protecting forest crops have many advantages. The most important of these is the possibility of spraying at lower altitudes, smaller areas of plantations, and even individual trees, as well as lower treatment costs. Drones reduce spraying time and can perform treatments on trees of varying heights while maintaining precise control over their flight height. UAVs are also suitable for applying forest protection products to objects at different altitudes, such as mountainous areas. Drones also offer precise removal of parasites inside tree crowns [32]. They are well-suited for spraying small, limited areas and even single trees. During aerial spraying with drones, the rotors’ propellers generate airflow. This flow and external natural air movements can alter droplet trajectories and affect the deposition of liquid droplets within the tree crown and their drift [33,34]. The severe disadvantage of aerial spraying is the drift of droplets sprayed with UASS and containing very often significantly concentrated pesticides. This drift is often caused by the influence of the local climate and gusts of air in open spaces, occurring even without wind. The drift of liquid sprayed from drones is much greater than when spraying with ground-based equipment and can lead to environmental contamination [35]. Avoiding the drift of sprayed liquid is a big challenge for drone spraying [9,33,35]. The European Union has strict regulations regarding aerial plant spraying due to the potential drift of sprayed pesticides and environmental contamination. Spraying from aerial vehicles, human-manned or UAV, is permitted only in the absence of any other option. This is outlined by the European Parliament and Council 2009/128/EC of 20 October 2009 [36].

Farmers using drones for crop protection expect, in addition to the typical gains resulting from not being able to carry out treatments with ground-based sprayers, additional profit resulting from a reduction in the cost of crop protection by UASS to the costs of using sprayers. In order to increase efficiency, attempts are being made to widen the swath using very high flight altitudes above the plants, even reaching up to 10 m, high drone travel speeds of about 6.0 m·s⁻¹, and using very condensed pesticide solutions in the spray liquid and also by spraying droplets very finely [8,34,35]. Although most drone spraying treatments experiments have been carried out at heights of 1.2 to 2.5 m above trees mainly fruit trees and hazel [11,27,28], even at these spraying heights the long fall of fine droplets can lead to drift and damage the environment. There are no regulations in the European Union, and probably in many countries around the world, concerning the parameters and environmental conditions for safe UASS spraying. On the other hand, there needs to be more information and research on the cost-effectiveness of drone spraying concerning effectiveness and environmental safety.

The flight height of multi-rotor UASS when spraying plants has the most significant impact on reducing the drift of the spray. Lowering the flight height of spraying drones is recommended as a droplet drift prevention strategy [9]. In addition to the short path of the droplets from the nozzle to the plants, the strong airflow generated by the drone’s rotors being at a short distance between the rotors and the plants can further accelerate their arrival at the target and improve penetration into crop canopy [35,37]. The low flight altitude of spraying drones also means that precise spraying of individual plants, or even parts of plants, can be carried out. Low drone flight altitudes can also be recommended for inspection drones as they allow very accurate information on pests not only at the scale of the crop area but also at the scale of individual plants and trees and even at the scale of their leaves [19,20,21]. The low flight altitude also favours the effectiveness of autonomous drones with the ability to identify pests and immediately pesticide spray their location on the plant.

The weight of the multi-rotor drones used for crop spraying changes during the spraying process because the tank of liquid is emptied. At this time, the drone maintains a constant altitude. The drone’s rotors must generate enough strong thrust from the airflow to overcome the drone’s total weight and lift it above the trees when the tank is full and when the tank is nearly empty. This situation means that, at the same treatment altitude, a drone with a full tank generates greater thrust force from its rotors compared with the thrust force produced when the tank is nearly empty or empty. The thrust of a multi-rotor drone depends on the rotational speed of its rotors [38]. As the thrust force and rotational speed of the rotors decrease during the spraying time, the airflow speed affecting the droplet stream also decreases. Many studies investigating the use of drones for tree spraying overlook the disparities between a drone’s weight with a full or empty liquid tank and the outcomes. These studies predominantly focus on factors such as tree type, droplet size, drone flight parameters, and the biological effects of the treatment. In the case of multi-rotor unmanned aerial spraying systems operating at very low altitudes, such an influence can exist, and varying airflow parameters during treatment can affect the quality of liquid deposition.

Forest and ornamental trees are susceptible to many pests, including insects, nematodes, fungi, bacteria, and viruses. The effectiveness of tree protection depends not only on the specific pesticide used to control a particular pest but also on its even deposition, along with the spray of the entire tree crown, or at least its areas where pests mainly feed. Studies show that the shape of the tree crown can affect the volume of spray penetrating its various parts [39]. Studies on the deposition of fluid sprayed from drones onto plants are conducted not only in open spaces, forests, and fields but also in laboratory test beds. Laboratory tests enable the simulation of natural conditions with precise control and measurement of technical parameters during the treatments performed [40,41]. They also allow for detailed observation of the physical phenomena accompanying the spraying of plants using drones.

The research aim was determined because of the intention to reduce droplet air drift when spraying drones. For this reason, the research focused on the low height of the drone’s movement above the object being sprayed. It was assumed that the drone’s height should be comparable to the distance of the nozzles from the plants in ground sprayers.

The main aim of the research was to evaluate the influence of the drone’s rotors speed and speed of drone movement on the quality of spray deposition in the tree crown in conditions of low-altitude drone spraying. The studies were also intended to answer the question of whether the rotational speed of the propellers generating the airflow from the drone when the tank is full and when the tank is empty can significantly influence the quality of liquid deposition in the tree crown.

The research also aimed to assess the influence of the airstream generated by the drone’s propeller rotation and the degree of foliage in the tree crown zones on the quality of liquid deposition on the tree.

In addition, the study aimed to compare the droplet deposition results on the tree obtained from the spraying drone with the results from the same treatment that can be performed with a conventional field sprayer without airflow.

2. Materials and Methods

The studies were primarily focused on using drones to spray crops of young ornamental and forest trees. Therefore, a young tree of blue spruce (Picea pungens Engelm.) was selected for the research. This spruce species is commonly cultivated for gardens, parks, and Christmas tree plantations, as well as for industrial purposes in forest plantations. Blue spruce trees are susceptible to pests, particularly parasitic fungi, and small insects [42,43,44]. Protective treatments are typically required for spruce trees grown in plantations, with ground sprayers and, mainly, field sprayers commonly employed for these treatments.

2.1. Test Stands

For the experiment, a laboratory stand was prepared, which ensured precise and repeatable measurements of the drone’s movement speed, altitude above the tree, and propeller spin speeds. On the stand, the drone was affixed to a rolling cart on rails supported by fixed structures at opposite ends. The cart was then pulled by an electric motor and a rope connected to the cart. By adjusting the frequency of the current supplied to the electric motor, the researchers can control the drone’s movement speed. Studies carried out in a stable laboratory environment allowed for a more accurate analysis of the results compared with field tests. Additionally, this stationary stand prevented the impact of air gusts, which can affect the air stream’s properties and the trajectory and shape of the sprayed liquid and hinder research [33,35,45].

For the studies, a hexacopter drone with 15 × 5.2″ propellers and 500 W, 400 kV brushless electric motors powered by a LiPo 16,000 mAh, 22.2 V battery was used. The drone’s propellers were controlled using a transmitter station. An optical digital tachometer (UT-372), produced by Uni-Trend Technology Co. Ltd. (Dongguan, China), connected to a computer was employed to measure the speed of the propellers’ spin.

Manufacturers of unmanned aerial spraying systems typically equip drones with fine droplet nozzles for better crop coverage. The fine droplets produced by pressurised and rotary atomisers are highly susceptible to drift by air movement. Bearing in mind that the conditions of the study assumed not to allow droplets to drift by gusts of air for testing, the fine droplet atomiser was abandoned, and the air-injector compact nozzle (IDK 90-015) manufactured by Lechler GmbH (Metzingen, Germany), was mounted on the drone. For delivering pressurized liquid to a spray nozzle, a small ground sprayer was connected to it by a flexible pipe. The liquid pressure in the system remained constant at 0.20 MPa. According to the manufacturer’s specifications, at this pressure, the nozzle produced average droplet diameters, measured according to the ISO 25358 classification standard in the coarse droplet range [46]. A nozzle with a spray angle of 90° was used to accurately match the shape of the droplet jet to the shape of the crown of the tree sprayed so that the spray jet covered the entire volume of the crown, assuming that this was the most favourable way to spray similar trees from above. Figure 1 illustrates the positioning of the spray nozzle relative to the drone’s frame, rotors, and tree, as well as the drone’s altitude to the spruce being sprayed.

The hexacopter had a specific configuration with a single arm positioned in the front and rear in the direction of movement and two arms mounted on each side of it. The liquid spray nozzle (2) was situated under the first front arm (1), located on one side of the multi-rotor drone. The spray nozzle’s axis of symmetry aligned with the rotor’s axis directly beneath it. The nozzle outlet was located below the lower level of the rotor propellers at a distance of H₁ = 0.15 m.

In order to ensure accurate positioning, the spruce tree was placed in a pot, allowing precise alignment with the drone. The top and centre of the tree canopy were positioned along the nozzle’s symmetry axis. The tree’s height above the soil level in the pot was 0.90 m. Bearing in mind that there is a need to limit the drift of drops, the lowest possible height of the nozzle over the tree was selected [9]. The nozzle was positioned at the height of H₂ = 0.60 m above the tree’s crown. This altitude was determined based on previous tests and literature review, considering it also the lowest feasible altitude for flying the drone over spruce trees without risking a collision. This decision was suggested by the lowest flight altitude of the drone over the citrus tree described in the paper [39].

In order to evaluate the deposition of sprayed liquid in trees, samplers are used. These can be attached to branches or indirectly positioned on metal stands, artificial trees, or nets that simulate canopy space [5,39,47]. A tripod with samplers attached to its arms was employed to assess liquid deposition in this research. The stand consisted of a vertical metal rod connected to three sets of horizontally placed metal rods at three different heights. Each set comprised four rods intersecting at right angles. The vertical rod was attached to the tree trunk. The levels of sampler bars were marked with the letters “A”, “B”, and “C” from the top. In addition, in order to be able to assess the influence of the crown of the tree on the changes in the velocity of the airflow inside the spruce, a second tripod, identical to the tripod placed in the crown of the tree, was constructed to take airstream measurements without the tree. Figure 2 illustrates the tree with the tripod mounted and the tripod itself.

The distance between the first level of rods (A) and the top of the tree was 0.18 m. The gap between each level (A, B, and C) was 0.24 m. Placing the samplers on the rods ensured precise positioning relative to the drone and nozzle during the tests.

For measuring liquid deposition inside of the tree crown, plastic labels (0.02 m × 0.04 m) were used as samplers. They were glued to holders attached at the marked positions on the horizontal bars of the tripod. Each rod at every level had two types of samplers: “trunk” samplers placed 0.06 m from the trunk’s centre and “branch” samplers positioned at a distance of 0.21 m, also measured from the trunk’s centre. As there were four rods at each tripod level, so there were a total of four “trunk” samplers and four “branch” samplers (Figure 2). The “trunk” samplers were used to estimate of the amount of liquid penetrating the branches in the central part of the tree canopy near the trunk. The “branch” samplers assessed the liquid reaching the branches at a distance of approximately two-thirds of the average branch length, counting from the trunk’s centre (the vertical zone of the tree, away from the trunk).

Two speeds of moving drone, 0.57 m·s^–1 and 0.94 m·s^–1, were taken to study the influence of the drone’s linear speed over the tree on the volume of liquid reaching different parts of the spruce canopy. The speeds adopted were due to the design and capabilities of the stand.

The study also assessed how the air stream generated by the drone’s rotor thrust, depending on the drone’s weight, affected the liquid distribution inside the tree canopy. Since the drone was fixed to the cart was unable to generate an air stream, depending on the water’s weight inside the tank, in order to calculate propellers’ rotation speeds, the weight of the commercial spraying drone M4E (TTAviation) [48], similar in technical parameters to the drone used in the research, was taken. The calculations utilized a mathematical Formula (1) derived from a previous study of the same drone model [49].

F = 9·10⁻⁷·n^2.137,(1)

where F is the thrust force, and N and n is the rotors speed, rpm.

For the desired thrust force, F₁ = 72.2 N, when the tank was empty, calculated rotations were n₁ = 5000 rpm. For F₂ = 120.4 N, when the tank was full, rotations were n₂ = 6350 rpm. The ratio of the liquid weight in the tank to the total weight of the drone was determined to be 39.8%. Additionally, to assess the settling of spray in the spruce tree canopy without the influence of airflow from the drone’s rotors, the study was performed with the rotors’ speed n₀ = 0.0 rpm. This value of the propellers speed also simulated tree spraying with an above-ground sprayer.

All measurements for the designated three drone propeller speeds, the adopted two drone travel speeds, and a tripod placed inside the tree and a tripod without a tree were repeated three times. Only one tree placed under the drone was used for the tests.

Previous studies [34,41,50,51] suggest that the air stream generated by the UAV plays a crucial role in the delivery and deposition of droplets during plant spraying. In order to analyse the influence of the air stream on liquid deposition inside the spruce tree, changes in air velocity within the tree’s canopy caused by its attenuation due to branches and leaves were measured. Testo 405i anemometers were used to make the measurements. During the measurement, the drone remained stationary above the tree, with the spraying nozzle axis of symmetry aligned with the centre of the tree trunk. The anemometers were installed on a beam at a tripod at the heights corresponding to each level of the samplers: “A”, “B”, and “C.” The method of fixing the anemometers to enable them to be adjusted is shown in Figure 3.

The measurement probes of the anemometers were positioned precisely at the mounting points of the liquid samplers but only on rods positioned transverse to the direction of the drone’s movement. Once the position of the anemometer probes was established, the rods were removed from the tripod so as not to suppress airflow. The air velocity measurements were conducted on the same test stand with and without the presence of the spruce tree. During the measurements without the tree, the anemometers were in the same place where they were placed during the measurements with the tree because a second tripod was used to position their probes.

2.2. Quality of Liquid Deposition

The quality of liquid deposition sprayed from the drone was evaluated based on the volume of liquid deposited on each level of the tripod and the uniformity of liquid deposition at all levels, separately for “trunk” and “branch” samplers. Distilled water, stained with aqueous nigrosin dye at a concentration of 0.5%, was used as the liquid in the study. As the drone moved over the tree, liquid droplets were deposited on the samplers. After the liquid dried, samplers from each location and level were collected and placed in separate containers. Each measurement involving the liquid spray on the tree was repeated three times under the same technical parameters. The dye on the samplers collected in the containers was washed off with 5.0 mL of distilled water. The dyed liquid was analysed using a photo colorimeter to determine the dye concentration in parts per million (ppm). Since the volume of liquid used to wash off the dye remained constant in all containers, and the amount of dye washed off the samplers was proportional to the volume of spray liquid deposited on them, the dye concentration measured by the photo colorimeter was converted to the volume of spray liquid in µL deposited on one cm² of the sampler.

The uniformity of liquid deposition at tree levels was assessed using the coefficient CV, calculated from the results of liquid volume deposited on the samples at the tripod levels, according to the following Equation (2):

(2)$\mathrm{C}\mathrm{V}=\frac{1}{v_m}\sqrt{\frac{{\sum \left(v_i-v_m\right)}^2}{3}}$

where CV is the coefficient of uniformity of liquid deposition at three levels; v_m is an average volume of liquid deposited on samplers, µL·cm⁻²; and v_i is the volume of liquid deposited on the i-th sampler, µL·cm⁻².

The CV value was calculated using the data obtained from each repetition of the liquid deposition measurement on the samplers.

2.3. Spruce Tree Crown Evaluation

The leaf area index (LAI) was adopted to characterize the density of branches with needles at a particular level of the spruce tree crown. This index was used to examine the relationship between tree structure and airflow velocity reduction at different levels [52]. Formula (3) was employed to calculate the leaf area index:

(3)${\mathrm{L}\mathrm{A}\mathrm{I}}_{\mathrm{i}}=\frac{{\mathrm{F}}_{\mathrm{l}\mathrm{i}}}{{\mathrm{F}}_{\mathrm{s}\mathrm{i}}}$

where LAI_i is the leaf area index value for the selected tree level—i, F_li is an area of needle leaves on branches above the selected level, and F_si is the field area under the branches for the selected level.

The area of needle leaves—F_li, was calculated by adding up the lengths of branches within the space above the selected level measured, next the average number of needles per unit of branch length was determined, along with the average area of one needle. These factors were then multiplied together. To calculate the field area under the branches for the selected level—F_si, for a specific level the distance from the centre of the trunk to the end of the longest branch within the crown of the tree, placed inside or above that level, was measured. The area of a circle with a radius equal to this distance was then calculated to determine the field area under the branches.

The leaf area index for the upper part of the tree (LAI_A) was determined up to level “A” by dividing the calculated leaf area above this level (F_lA) by the circle area under this part of the tree (F_sA), which was determined using the length of the longest branch at this level as the radius. The leaf area index for the middle part of the crown (LAI_B) at level “B” was determined by dividing the combined leaf area from levels “A” and “B” (F_lB) by the corresponding field area under this part of the tree (F_sB). For level “C,” the leaf area index (LAI_C) was calculated by dividing the summed leaf area above level “C” (F_lC) by the area of the circle determined using the longest branch of the tree as the radius (F_sC).

2.4. Statistical Methods

Mean values, calculated from the measurement results, were presented in a bar chart, with the measurement error range as ±standard deviation. After analysing the data for normality of distribution (Shapiro–Wilk test), analyses of variance were performed to assess the significance of the input factors on the results obtained. Statistica 13.3 software (StatSoft) was used to perform both analyses. A value of 0.05 was taken as a limit for the calculated significance p-factor.

3. Results

3.1. Effect of Propellers Rotations on Liquid Deposition

After each tree spraying, the samplers, after drying, were disconnected from the tripod rods and subjected to further processing to assess the capacity of the deposited liquid. The average results and their corresponding standard deviations are presented in Figure 4. Separate graphs were created for the liquid deposited on the “trunk” samplers and the liquid deposited on the “branch” samplers, taking into account the varying spin rates of the propellers. Figure 4a shows the results of liquid deposition on the tripod levels obtained at the speed of 0.57 m·s^–1, and Figure 4b at the speed of 0.94 m·s^–1.

The findings presented in Figure 4a,b indicate that both the speed of the drone’s movement over the tree and the speed of its propellers impact the volume of liquid deposited on the samplers. This observation holds for both drone movement speeds of 0.57 m·s^–1 and 0.94 m·s^–1. Variance analysis was performed to evaluate the influence of the drone’s movement speed and the presence or absence of rotation of propellers on the liquid volume deposited on the samplers. Similarly, the significance of the propellers’ spin speeds, considering the drone’s weight with an empty or full tank on the liquid volume at different levels of the tree canopy was examined.

The analysis revealed that the absence or presence of the rotation of propellers at 0.0 rpm, 5000 rpm, and 6350 rpm significantly affected the volume of deposited liquid, but only for the “branch” samplers (p = 0.010456). Additionally, the effect of rotation speeds due to the drone’s weight, with an empty or full tank on liquid deposition, was found to be significant only for the “branch” samplers at the middle level (“B”) when the drone was moving at a speed of 0.57 m·s^–1 (p = 0.043965). At the other sampler levels, both “trunk” and “branch,” and at both drone travel speeds, the effect of propellers’ rotations speeds resulting from tank filling did not exhibit significance.

Variance analysis conducted on “trunk” samplers revealed a significant relationship between drone travel speed and the volume of liquid collected by these samplers (p = 0.000008). Likewise, a significant impact of drone travel speed on the volume of liquid deposited on the “branch” samplers was observed (p = 0.000002).

Additionally, the total volume of liquid deposited on 1 cm² of the sampler surface was determined when the individual volumes from repeated measurements were summed across the same drone travel speeds, rotations of propellers, and sampler types. The results of this summation are presented in Table 1.

In order to compare the effect of the relationship between the drone’s movement speeds and the volume of liquid deposited on each level of the samplers, the ratios of the volume of liquid deposited on the samplers at a drone movement speed of 0.57 m∙s⁻¹ to the volume of liquid deposited on the samplers at a speed of 0.94 m∙s⁻¹ were calculated. For this purpose, the corresponding results of the repetitions from the measurements for the same tripod levels and speed of drone propellers were divided by each other. And then, the mean values and standard deviations were determined. The ratios of the volume of liquid deposited at all tripod levels (total relations) for the same drone propellers spin rate were also calculated in a similar way. The results are shown in Table 2. The calculated ratio of higher drone speed to lower speed is 1.65.

3.2. The Influence of the Speed of Propellers on the Uniformity of Liquid Deposition

The coefficient of uniformity for liquid deposition at tree levels was calculated using Formula (2), separately for the “trunk” samplers and the “branch” samplers, considering the speed of drone propellers’ spin set to “zero” and the rotations resulting from two different weights of the multi-rotor drone. CV values were determined separately for the displacement speed of 0.57 m·s^–1 and 0.94 m·s^–1. The results are presented in Figure 5.

The variance analysis conducted on the results of liquid distribution uniformity at the sampler levels revealed the significant influence of both speed of the propellers and drone movement speed on improving the CV index, but only for the “branch” samplers. In terms of propellers rotation, the significance of its effect on the coefficient of uniformity of deposited liquid was 0.00164. Regarding the effect of the drone’s displacement speed, the significance level was 0.014855. Further analysis of the propeller speeds, which were solely influenced by the drone’s weight, showed a significant effect on improving the uniformity of liquid deposition for the “branch” samplers at a speed of 0.57 m·s^–1 (p = 0.046004). No significant effect was observed at a speed of 0.94 m·s^–1.

3.3. Leaf Area Index—LAI

Table 3 presents the calculated leaf area index using Formula (3). In the table were also presented the total area of the leaves and the measured sizes of the longest branches for the selected level, which were used as radii for the field area under the branches for the selected level calculation.

3.4. Airstream Velocity in the Crown of the Tree

The results of the velocities of the airstream measurements are presented in Figure 6a,b. Because the velocity of the airstream was measured separately on the positions of the “trunk” samplers and separately at the “branch” samplers at levels “A”, “B”, and “C,” the charts of passing it through the tree crown and without tree were shown side by side.

4. Discussion

The analysis of the results concerning the impact of the rotational speed of drone propellers on airflow velocity through the crown of the tree and the quality of the liquid deposition at the “trunk” sampler levels revealed that although the rotations of drone’s propellers, at 5000 and 6350 rpm (as shown in Figure 6a,b), generated airflow within the tree crown where the “trunk” samplers were positioned, no evidence was found indicating that this airflow increased the capacity of the liquid deposited on these samplers. The volumes of deposited liquid and the uniformity of deposition were comparable across all speeds of propellers, ranging from 0.0 to 6350 rpm (as shown in Figure 4a,b and Figure 5). This phenomenon was likely attributed to the high density of branches and coniferous leaves in that part of the tree crown and the coarse liquid droplets generated by the IDK 90-015 nozzle. These droplets were able to penetrate this part of the tree crown similarly, regardless of the presence or absence of airflow. The branches near the trunk are stiff and do not deflect under the influence of the air stream. Hence, the speed of the propellers and the resulting airflow had no effect on the volume of the deposited liquid in this zone of the tree crown.

In contrast, at the “branch” sampler levels, the effect of the drone’s speed of propellers on increased liquid deposition volume was observed on “B” and “C” tripod levels at both drone movement speeds (as depicted in Figure 4a,b). The total volume of liquid deposited on all levels of this kind of sampler also increased (Table 1). This increase occurred despite a higher leaf area index (as presented in Table 3) and lower airflow velocity through the crown compared with the “trunk” samplers (as shown in Figure 6a,b). The uniformity of liquid deposition on the “branch” sampler levels (Figure 5) improved. This phenomenon can be attributed to the narrowing of the droplet stream angle under the influence of airflow generated by the drone’s propellers rotations [40,53]. Consequently, there was an increase in liquid volume within the narrower stream width. The “branch” samplers were positioned in the region of the droplet stream where this volume increase occurred. Not only did the amount of liquid deposited on these samplers increase, but it also improved the uniformity of liquid deposition at tree levels (CV). The airflow generated by the propellers further facilitated the liquid deposition at the lower levels of the tripod on the “branch” samplers.

Analysing both the improvement in the results of liquid deposition on the “branch” samplers and the improvement in the uniformity of liquid deposition on these samplers under the influence of airflow generated by the rotation of the drone rotors in comparison with the situation when the rotors were not rotating (field sprayer), it can be concluded that when comparing the quality of spraying young spruce trees with a drone and a field sprayer, spraying with a drone provides better results of liquid deposition. The possibility of carrying out tests on a laboratory test site made it possible to compare the design of the equipment and the comparability of the conditions and parameters of the treatment, which was not possible previously [23,25].

The analysis of the drone’s speed of propellers, which varied with the weight of the drone (full tank vs. empty tank), showed the potential impact of the weight of the liquid in the drone’s tank on the quality of spray applied to the plants. A significant effect was observed at level “B” when the speed was 0.57 m·s^–1. The higher propellers rotations resulting from the increased weight of the drone also significantly improved the uniformity of liquid deposition on the “branch” samplers.

The analysis of variance confirmed the significance of the drone’s movement speed on the volume of liquid deposited on the sampler surfaces. The ratio between the two drone displacement speeds was determined to be 1.65. Comparing the ratios of total liquid volume deposited on the samplers at lower and higher speeds (as indicated in Table 2, at “Total relatios”) showed close to this value proportions. However, when examining the liquid volume ratios deposited at each sampler level, deviations from the expected relationship between velocities were observed. Specifically, deviations occurred at the “B” level of the “branch” samplers with non-rotating propellers, as well as at the “C” level of the “branch” samplers, both with rotating and non-rotating propellers. These deviations made it challenging to establish a consistent rule to describe the relationship between drone speed and liquid volume deposition in these cases. If confirmed by other studies, the aerodynamic phenomena that caused these differences may be worth explaining.

Comparing the air velocity passing through a spruce tree at sampler levels with the air velocity measured at the same places as samplers but without the presence of the tree (Figure 6a,b) revealed noteworthy observations. Firstly, the leaf area index (LAI) at each tree level strongly impacted reducing the air stream’s velocity. Secondly, the distance of the tree level from the drone also contributed to the reduction in airspeed, which is particularly evident in Figure 6a,b when measuring without a tree. Therefore, the changes in air velocity observed within the tree crown (as also depicted in Figure 6a,b) were influenced by both the distance of the measurement level from the drone and the presence of the leaf canopy, which dampened the airflow. Whereas significant is a range of changes in airstream velocity. The distance between levels “A” and “C,”, when measured without the tree, caused a decrease in speed in the range of 26%. The tree crown decreased air stream velocity about six times, dividing by each other the velocity values at point “C” in measurements without and with the tree. The reason for the reduction in air velocity in the lower part of the tree may have been due not only to the flow-dampening structure of the tree but also to a change in the direction of airflow close to the ground [50,51]. In the study, only the vertical velocity was measured; the horizontal velocity was not measured.

In general, it can be concluded that the results of studies on the quality of liquid deposition in the central part of the crown of a young spruce tree and at the levels of its canopy confirmed the results of earlier studies that the effectiveness of liquid penetration of the tree crown, is influenced by factors such as the speed of the drone above the tree crown and the shape of the tree crown [26,27,28,29,40]. After studies, it can also be sure that tree species and foliage surface and density influence liquid deposition.

Studies have shown that the low altitude above the plants of the displacement of the spraying drone makes sense. If, in the future, unmanned aerial spraying systems at low altitudes become a permanent, legislated component of precision agriculture, and in orchard and ornamental tree crops, the airflow generated by the drone rotors will support spray quality and reduce liquid drift [9,35].

5. Conclusions

Comparing the quality of spray deposition in the tree when the drone’s propellers were in operation to when they were not rotating revealed an improvement in spray deposition quality when the propellers were rotating, so the drone was flying and liquid spraying. This suggests that using a drone instead of a field sprayer may yield better results for pest control treatments on cultivations, not only conifer trees.

Low altitude above the plants of moving multi-rotor drones when spraying can not only improve the deposition of the spray on the plants but can also prevent droplets from drifting off with the wind.

Described studies indicate that using the strategy of low altitude over the plants of multirotor drones can successfully replace classic methods of plant spraying with field sprayers and increase the quality and precision of the treatments performed.

The process of emptying the drone’s tank while spraying, which leads to changes in the rotations of propellers value due to the weight difference between a full and empty tank, can potentially impact the deterioration of droplet stream deposition in the tree crown.

No significant effect of the rotational speed of the drone’s propellers and the resulting air stream on the quality of liquid deposition was observed on the samplers placed at the tree trunk. However, a noticeable effect of the rotations of drone propellers was observed on the samplers located on the branches of the tree at a considerable distance from the trunk.

Author Contributions

Conceptualization, A.P., B.B., J.C. and G.M.; methodology, J.C., G.M. and J.D.; software, J.N., J.K. and T.N.; validation, A.P., B.B., J.C. and M.M.; formal analysis, J.D. and A.K.; investigation, J.C., A.K. and J.K.; resources, J.C., G.M., J.N., T.N. and M.M.; data curation, A.P., A.K., J.K. and T.N.; writing—original draft preparation, A.P., B.B. and J.C.; writing—review and editing, J.C., J.D. and A.K.; visualization, A.P., B.B., T.N. and M.M.; supervision, J.C., J.D., A.K. and J.N.; project administration, J.C., G.M., J.K. and M.M.; funding acquisition, J.C. and J.N. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

Data available on request.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Figures and Tables

Figure 1. Position of the drone relative to the sprayed tree: 1—drone’s front arm; 2—spray nozzle, the arrow indicates the direction of the drone’s movement.

Figure 2. The tripod mounted inside the tree crown and the tripod without the tree: 1—places to mount “trunk” samplers; 2—places to mount “branch” samplers.

Figure 3. Example of the method of mounting anemometers on the tripod for placement in the tree crown.

Figure 4. Influence of the propellers speeds and drone velocity on the volume of spray deposited on the samplers at (a) 0.57 m·s–1, (b) 0.94 m·s–1.

Figure 5. Effect of the propeller speeds on the uniformity of liquid deposition in the spruce crown.

Figure 6. Comparison of changes in airflow speed down the tripod, caused by the foliage of the spruce tree crown at rotations of propellers 5000 rpm (a) and 6350 rpm (b).

Table 1

Influence of parameters for performing tree spraying on the total volume of liquid deposited on the samplers.

Conditions		Total Volume of Settled Liquid per Unit Area of Samplers, µL·cm−2
V, m·s−1	Rotations of Propellers, rpm	0	5000	6350
0.57	“Trunk” sampl.	5.07 ± 1.39	5.55 ± 0.44	5.77 ± 0.83
	“Branch” sampl.	5.59 ± 0.84	7.17 ± 0.79	7.58 ± 0.34
0.94	“Trunk” sampl.	3.63 ± 0.99	3.51 ± 0.42	3.26 ± 0.31
	“Branch” sampl.	4.54 ± 0.97	4.63 ± 024	5.26 ± 0.69

Table 2

The ratio between the volume of liquid deposited on the samplers at the drone’s movement speed of 0.57 m·s⁻¹ to the volume of liquid deposited on the samplers at 0.94 m·s⁻¹.

	“Trunk” Samplers			“Branch” Samplers
Rotations of Propellers, rpm	0	5000	6350	0	5000	6350
Level “A”	1.25 ± 0.33	1.58 ± 0.19	1.82 ± 0.55	1.71 ± 0.77	1.84 ± 0.12	1.64 ± 0.07
Level “B”	2.54 ± 1.86	1.58 ± 0.73	1.76 ± 0.61	0.80 ± 0.13	1.34 ± 0.46	1.46 ± 0.68
Level “C”	2.65 ± 2.47	2.80 ± 1.90	2.36 ± 1.52	0.92 ± 0.32	1.27 ± 0.11	1.28 ± 0.34
Total relations	1.48 ± 0.65	1.59 ± 0.22	1.77 ± 0.21	1.26 ± 0.26	1.55 ± 0.09	1.46 ± 0.27

Table 3

LAI values for different levels of the tree crown.

Total Area of the Leaves, cm2		Radius of the Area Circle, cm	LAI Value
FlA,	803.84	16.0	LAIA	0.658
FlB	3957.2	35.5	LAIB	2.071
FlC	5539.0	42.0	LAIC	4.490

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