Effects of Tank-Mix Adjuvants on Spray Performance Under Downwash Airflow Fields Using an Indoor Simulated UASS Spraying Platform

Abstract

The unmanned aerial spraying system (UASS) has emerged as an advanced tool in precision agriculture for applying plant protection products (PPP). The addition of tank-mix adjuvants to PPP solutions is a common practice to enhance aerial spray performance. However, the effects of these adjuvants on spray performance under the downwash airflow fields generated by UASS rotors remain unclear. This study aimed to evaluate the impacts of adjuvant addition (AGE852B, AGE825, AGE809, and CCL846) on droplet size spectrum and spray deposition distribution with various rotor speeds and layouts, using an indoor simulated single-rotor/multi-rotor UASS spraying platform. The results showed that adding AGE809 and AGE825 made the droplet size and distribution much better in the flat fan nozzle LU110-015 under the downwash airflow field. The spray volume fractions made with droplets smaller than 100 µm (V₁₀₀) went down by 48.15% and 21.04%, respectively. Furthermore, rotor speed was found to have a significant impact on volume median diameter, relative span, and V₁₀₀ (p < 0.05). The downwash airflow field was observed to increase the vertical droplet velocity, achieving a more uniform spray distribution in the central airflow area. These results show that choosing the right adjuvants and making the most of the operational parameters can improve spray deposition, coverage uniformity, and drift reduction. This gives us useful information for making PPP applications more efficient and effective in precision agriculture.

1. Introduction

Unmanned aerial spraying systems (UASSs) or unmanned aerial vehicle (UAV) sprayers have been developed and favorably employed for the application of PPP, including pesticides, fertilizers, and plant growth regulators, to prevent and control pests and diseases in crop fields and orchards. UAV sprayers can be categorized into two types based on their structures: single-rotor UAVs or helicopters and multi-rotor UAVs or drones [1]. There are many benefits to using UASS for plant protection, such as being able to reach areas that cannot be reached by people or ground-based machinery, being able to move around easily, using low or very low volume spraying to save water and make better use of pesticides, being more efficient than manual operation, and effectively replacing human plant protection efforts. Moreover, the effectiveness of aerial spraying can be significantly influenced by various factors, including droplet size, physicochemical properties, downwash airflow field, and environmental conditions [2,3,4,5,6,7,8,9,10,11]. In several Asian countries, UAV-based PPP spraying has been employed to control pests, diseases, and weeds in various field crops, such as paddy rice, wheat, cotton, soybean, and maize, as well as fruit crops, including citrus, mango, longan, apple, pear, peach, olive, and vineyard grapes [9,12,13,14,15,16,17,18,19,20,21,22,23,24]. However, UAV sprayers equipped with conventional flat fan nozzles or centrifugal nozzles generate fine droplets that are highly susceptible to drift and evaporation. Unlike ground-based equipment, UAV rotors generate a downward airflow field, which not only provides lift for the UAV’s flight but also carries droplets downward, enabling them to penetrate and deposit within the crop canopy. Nevertheless, the mechanism by which the downwash airflow field of UASS rotors influences the atomization characteristics of sprayed droplets is not yet fully understood.

Previous studies have collectively highlighted the influence of the downwash airflow field of UAV rotor models on spray deposition patterns. Zhang et al. indicated that for a hovering single-rotor UAV, the downwash velocity initially increased from small values to larger ones, then decreased as the radial distance increases [25]. Liu et al. demonstrated that the peak of downwash airflow velocity appeared in a circular distribution below the outer edge of the rotor when the single-rotor UAV was hovering [26]. When the single-rotor UAV was in forward flight, Tang et al. revealed that the airflow speed on the right side was lower than on the left, with asymmetric flow structures demonstrated by the vorticity iso-surface. Higher application heights were found to reduce droplet expansion speed and make droplet distribution more symmetric, whereas lower heights resulted in more asymmetry and fewer droplets on the left side of the sprayer [27]. Guo et al. described that the rotor downwash airflow of multi-rotor UAVs flowed downward in a spiral pattern, exhibiting a clear contraction and expansion effect. Near the ground, the z-vertical direction velocity coverage area increased, pressure distribution became more uniform, and an upwash phenomenon occurred due to the ground effect [28]. Conventional flight operations showed that the wind vortex created a short downwash airflow field, which formed a canopy vortex patch that spread out quickly and could be recovered. This patch had little effect on the shape and yield of the rice. Furthermore, the intensity of the UAV wind vortex was found to significantly influence the penetration of pesticide droplets into the rice canopy [21,29,30,31]. Wang et al. found that the droplet vertical distributions differed because the wind distribution was generated by the different UAV structures [32]. Chyrva et al. described the impact of a multi-rotor UAV model on particulate dispersion. This resulted in a swath pattern deposited on the ground that showed peak mass deposited at the center area with one peak [33]. Wang et al. found that an eight-rotor UAV operating at flight velocities of 1.0 and 3.0 m s⁻¹ under field crosswind conditions exhibited significant positive droplet deposition under the downwash airflow field in the vertical ground direction. This finding suggested that the downwash airflow field caused more droplets to be deposited within the effective spray swath [34]. Lan et al. revealed that the downwash airflow field with the optimal flight height improved droplet deposition in the crosswind and vertical directions [35]. Yang et al. found that the inner downwash airflow field of a six-rotor UAV sprayer contained entangled droplets, with the majority of the droplets being distributed in the central area of the downwash airflow field. In contrast, larger droplet sizes were more prevalent in the outer periphery of the downwash airflow field [36]. Wongsuk et al. and Wang et al. examined the droplet size spectrum under the downwash airflow field of the UASS platform in a hovering state. They found that adding tank-mix adjuvants to the pesticide solution resulted in increased droplet sizes and decreased the proportion of fine droplets [10,37].

The incorporation of tank-mix adjuvants serves several crucial functions, including anti-drift, anti-evaporation, settlement penetration, absorption promotion, and adhesion. These functions play a pivotal role in enhancing droplet characteristics and spray distributions, especially under the influence of the downwash airflow field generated by UAVs. To tackle these challenges and improve the efficiency and effectiveness of aerial pesticide applications, the utilization of tank-mix adjuvants has garnered significant attention [38,39]. Tank-mix adjuvants are substances incorporated into pesticide formulations to augment their performance by altering their physicochemical properties [40,41]. These adjuvants can enhance the efficacy of pesticides by increasing their adherence, spreading, penetration, and overall stability [20,42,43,44,45]. In the context of aerial spraying, where uniform coverage and minimization of drift are paramount, the significance of tank-mix adjuvants becomes even more pronounced [40]. Moreover, the addition of adjuvants can achieve a favorable performance in terms of droplet distribution, droplet size, percent coverage, and drift reduction [39,40]. Other authors assessed the spray performance of a small plant protection UAV utilizing low-volume spraying. By adjusting the pesticide dosage and incorporating aerial spraying adjuvants, they enhanced the efficiency of UAV spraying [46]. Furthermore, Zhang et al. reported that the addition of tank-mix adjuvant 8860 significantly improved the physicochemical properties of tebuconazole on wheat leaves and enhanced disease control, even when the tebuconazole dosage was reduced by one-third [20].

The primary objective of this research was to investigate the effectiveness of different types of tank-mix adjuvants in modifying the spray performance of two typical models of UASS. The interaction between adjuvant ingredients and physicochemical properties was examined, and their impacts on droplet size spectrum and spray deposition distribution under the downwash airflow field were evaluated. Through a comprehensive analysis of tank-mix adjuvants in aerial spraying, this study aims to bridge the knowledge gap and provide practical recommendations for the development of UASS application technology.

2. Materials and Methods

2.1. Spray Solution

All indoor trials were conducted at the Centre for Chemical Application and Technology, China Agricultural University, Beijing, China. As presented in

Table 1. Tank-mix adjuvants used in the measurements of droplet size spectrum and spray deposition distribution.

Adjuvant	Ingredients	Contents (%)	Recommended Dosage (%V/V)
AGE852B	Ammonium sulfate	40	2
	Methylated seed oil	50
	Alkoxylated phosphate ester	10
AGE825	Natural fatty acid	71	2
	Guerbet alcohols, C10, ethoxylated NR	28.2
	Calcium dodecylbenzene sulfonate	0.8
AGE809	Soybean lecithins	50	1
	Methylated seed oil	24
	Alcohols, C11, ethoxylate (5 EO)	26
CCL846	Water	44	2
	Fatty acid methyl esters	22
	Natural fatty acid	14
	Alcohols, C16-18, and C18-unsaturated ethoxylated	9
	Starch	6
	Glycerol	5

, four aerial spraying adjuvant products were utilized in this study: AGE852B, AGE825, AGE809, and CCL846 (DE SANGOSSE Co., Ltd., Agen, France). The physiochemical properties, droplet size spectrum, and spray distribution uniformity of the spray solution were measured at the recommended dosage for each adjuvant. An indoor simulated UASS spraying platform, consisting of a single-rotor and a multi-rotor configuration, was constructed by the authors in previous studies. Utilizing this platform, measurements of droplet size and distribution uniformity were performed under various rotor speeds, spraying positions, and downwash airflow fields [10,37].

2.2. Physiochemical Properties Characterization

The contact angle (CA) of spray droplets was determined using an optical tensiometer (Attension Theta, Biolin Scientific, Gothenburg, Sweden) equipped with a telecentric camera and a 55 mm focus lens. A 5 µL droplet of each treatment was placed on a polyvinyl chloride (PVC) card (Hongsu Rubber Technology Co., Ltd., Shanghai, China) (Figure 1a). For each treatment, the CA was recorded over a 10 s duration, with three replications.

The static surface tension (SST) was measured optically through a pendant drop sharp analysis technique using an optical tensiometer (Attension Theta, manufactured by Biolin Scientific, Gothenburg, Sweden). A 5 µL droplet was released and formed a drop that hung from the needle tip, which had a diameter of 0.9 mm (Figure 1b). The hanging drop was then analyzed over a 10 s duration, with three replications for each treatment.

The dynamic surface tension (DST) was determined as a function of time using a maximum bubble pressure tensiometer (SINTERFACE BPA-2P, manufactured by Sinterface technologies, Berlin, Germany (Figure 1c)). The DST was measured by submerging the capillary tip in the liquid, then controlling the flow of gas through the capillary to form bubbles at a defined rate over a 20 min period. Three replications were performed for each treatment.

2.3. Droplet Size Spectrum Measurement

2.3.1. Single-Rotor Downwash Airflow Field

All spraying experiments were conducted at room temperature, and the spray system was required to be switched on and sprayed with water for 1 min before each test to maintain the ambient humidity within an equilibrium range. The droplet size spectrum under the single-rotor downwash airflow field was measured (Figure 2). The single-rotor platform was operated via a 1200 W power supply (SkyRC Technology Co., Ltd., Shenzhen, China). The rotor (10033/48 KV model, SZ DJI Technology Co., Ltd., Shenzhen, China) was equipped with a pair of propellers, each with a diameter of 1371.6 mm. A 55 V power supply was used for the motor, and a servo tester from DJI served as the rotor speed controller. Testing revealed that the rotor speed was positively correlated with the signal output of the servo tester. A boom with a width of 150 cm, equipped with four flat fan nozzles (LU120-015, Lechler GmbH, Metzingen, Germany), was placed below the rotor at a height of 1.75 m above the particle size analyzer. The operating pressure was set at 0.4 MPa. Droplet sizes were determined within a range of 1 µm to 1500 µm using a DP-02 laser spray particle size analyzer (OMEC Instruments Co., Ltd., Zhuhai, China) at three positions: at the center of the rotor, and at 30 cm and 75 cm away from the center. Each treatment was conducted at a pressure of 0.4 MPa with three replications. The 10th percentile diameter (D_V10), volume median diameter (VMD, D_V50), 90th percentile diameter (D_V90), relative span (RS), and spray volume fractions generated with droplets finer than 100 and 200 µm (V₁₀₀ and V₂₀₀) were recorded for further analysis. The experimental treatments are presented in

Table 2. Experimental treatment design of the single-rotor and multi-rotor UASS spraying platform.

No.	Adjuvant	Rotation Speed (rpm)
		Single-Rotor	Multi-Rotor
1	2% AGE825	0	0
2		824	2200
3		962	2400
4		1072	2600
5	2% AGE852B	0	0
6		824	2200
7		962	2400
8		1072	2600
9	1% AGE809	0	0
10		824	2200
11		962	2400
12		1072	2600
13	2% CCL846	0	0
14		824	2200
15		962	2400
16		1072	2600

.

2.3.2. Multi-Rotor Downwash Airflow Field

The measurement of the droplet size spectrum was conducted under the multi-rotor downwash airflow field (Figure 3). Four rotors (model X5212S KV:340, SUNNYSKY, Zhongshan Langyu Model Co., Ltd., Zhongshan, China), equipped with propellers of 515 mm diameter, were operated using a 1200 W power supply (SkyRC Technology Co., Ltd., Shenzhen, China). A 55 V power supply was utilized to run the motor, while a DJI servo tester served as the speed controller. The results of the tests demonstrated a positive correlation between rotor speed and the signal output of the servo tester. The study focused on four LU120-015 flat fan nozzles, operating at a pressure of 0.4 MPa. Each nozzle was positioned below its corresponding rotor at a height of 1.75 m above the particle size analyzer. The measurement operations and parameters were identical to those described in Section 2.2. Spray atomization was measured at five positions, namely the UAV center (0 cm), and at distances of 15 cm, 30 cm, 45 cm, and 60 cm from the center. Table 2 presents the experimental treatments.

2.4. Spray Distribution Uniformity Measurement

The upper part of the experimental equipment consisted of the indoor simulated UASS spraying platform described in Section 2.3.1 (single-rotor form) and Section 2.3.2 (multi-rotor form). The lower part featured a horizontal patternator positioned 2.5 m from the nozzle (Figure 4) [47]. A total of 14 grooves (10 cm in width) were placed at intervals of 8 cm. The center of the patternator was aligned with the center of the simulated UASS platform. At the lower end of each groove, a liquid bucket collector was placed to store deposited droplets from the groove. The spray deposition volumes at different horizontal positions were then measured using a cylinder.

2.5. Statistical Analyses

Data analysis was performed using SPSS 23 (SPSS Inc., an IBM Company, Chicago, IL, USA). A one-way analysis of variance (ANOVA) was applied to assess the physicochemical properties and spray distribution. To analyze the droplet size spectrum, a three-way ANOVA was conducted. The three-way ANOVA examined the factors of adjuvant, rotor speed, and measured distance position from the center of the platform. Duncan’s post hoc test (α = 0.05) was employed to compare mean values across all analyses.

3. Results

3.1. Physicochemical Properties

The CA results are presented in Figure 5. Water alone exhibited the highest contact angle at 86.18°. The addition of AGE852B and CCL846 resulted in contact angles of 69.68° and 63.08°, respectively. Conversely, the lowest contact angles were observed with the addition of AGE825 and AGE809, measuring 46.67° and 51.49°, respectively.

The SST results are depicted in Figure 6a. Water alone demonstrated the highest surface tension at 72.37 mN m⁻¹. The addition of AGE852B and AGE809 reduced the surface tension to 44.71 mN m⁻¹ and 33.60 mN m⁻¹, respectively. Further decreases were observed with the addition of AGE825 and CCL846, reaching 30.73 mN m⁻¹ and 31.41 mN m⁻¹, respectively.

The DST was measured over time using the maximum bubble pressure technique, and the results are presented in Figure 6b. Water alone exhibited a DST of 68.11 mN m⁻¹. The addition of the four adjuvants led to a decrease in DST. For AGE852B, the DST decreased to 59.72 mN m⁻¹ and further slightly decreased to 54.82 mN m⁻¹ at 1.41 s. The addition of CCL846 reduced the DST to 50.82 mN m⁻¹, with a slight decrease to 45.18 mN m⁻¹ at 5.30 s. With the addition of AGE809, the DST was 56.38 mN m⁻¹ and then sharply decreased to 38.56 mN m⁻¹ at 1.76 s. The addition of AGE825 immediately decreased the DST to 40.97 mN m⁻¹, with a slight decrease to 34.09 mN m⁻¹ at 12.78 s. These results, in conjunction with the SST findings, indicate that the addition of these four adjuvants effectively lowered the spray liquid surface tension.

3.2. Droplet Size Spectrum

3.2.1. Single-Rotor UASS Platform

A three-way ANOVA was conducted to assess the effects of rotor speed, measured distance from the center, and adjuvant product on the droplet size spectrum. The results presented in

Table 3. Significance obtained from the three-way ANOVA for droplet size as affected by rotor speed, distance from the center, and adjuvant product using the single-rotor UAV simulation base on D_V50, RS, and V₁₀₀.

Source of Variance	DV50			RS			V100
	p Value	Sig.	Correlation Coefficient	p Value	Sig.	Correlation Coefficient	p Value	Sig.	Correlation Coefficient
Rotor speed (R)	3.630 × 10−5	***, †, ‡	0.030	0.039	*, †, ‡	0.073	7.070 × 10−10	***, †, ‡	−0.133
Distance (D)	2.830 × 10−37	***	0.334 **	1.095 × 10−8	***	−0.323 **	3.540 × 10−49	***	−0.526 **
Adjuvant (A)	7.574 × 10−68	***	0.660 **	0.639	NS	0.017	1.455 × 10−48	***	−0.542 **
R × D	4.574 × 10−24	***		1.364 × 10−5	***		4.440 × 10−28	***
R × A	3.352 × 10−16	***		0.008	**		2.856 × 10−10	***
D × A	7.324 × 10−30	***		1.193 × 10−8	***		1.680 × 10−20	***
R × D × A	3.719 × 10−13	***		0.002	***		2.165 × 10−7	***

^† The statistical significance levels are denoted as follows: NS p > 0.05, * p < 0.05, ** p < 0.001, and *** p < 0.000, with ^‡ 0.000 representing a p-value lower than 1.0 × 10⁻⁶. ** The correlation is considered significant at the 0.01 level.

indicate that rotor speed and distance from the center significantly influenced D_V50, RS, and V₁₀₀ (p < 0.05). However, the addition of adjuvants had a significant effect on D_V50 (p < 0.001) but not on RS (p > 0.05). Furthermore, a strong interaction was observed among the three parameters affecting D_V50, RS, and V₁₀₀ (p < 0.001). The correlation coefficients revealed that adjuvant type had the most substantial positive influence on D_V50, followed by distance, while rotor speed had a minimal effect. Distance exerted a significant negative impact on RS, indicating a reduction in droplet span as the spraying distance increased, with rotor speed and adjuvant type exhibiting negligible effects. However, both distance and adjuvant type had notable negative impacts on V₁₀₀, suggesting a reduction in the proportion of fine droplets as these factors increased, with rotor speed showing a weaker influence.

The droplet size spectrum results are presented in Figure 7 and

Table A1. The droplet size spectrum distribution of the single-rotor UAV simulation indoor spraying.

Treatment	D * (cm)	Droplet Size (µm) in Different Rotor Speeds
		0 rpm					824 rpm					962 rpm					1072 rpm
		DV10	DV50	DV90	V100	V200	DV10	DV50	DV90	V100	V200	DV10	DV50	DV90	V100	V200	DV10	DV50	DV90	V100	V200
Water	0	84.17	126.06	192.42	27.47	67.37	82.40	124.27	201.99	30.02	66.09	78.88	113.60	175.48	35.32	78.47	80.11	112.04	179.69	36.39	77.85
	30	84.27	154.04	216.07	22.84	47.76	84.87	125.22	193.20	28.14	67.39	84.43	121.34	180.92	28.79	73.47	82.91	124.53	191.08	27.68	70.17
	75	85.95	137.31	208.09	24.79	56.60	96.79	158.46	222.56	11.53	42.75	97.17	163.05	236.01	11.24	39.41	99.58	163.18	232.19	10.26	39.15
AGE852B	0	87.68	166.83	228.07	19.70	38.24	87.09	153.30	219.94	21.19	48.17	97.44	164.46	228.03	11.18	37.45	86.77	154.09	228.90	20.36	47.35
	30	88.98	163.24	220.41	17.68	39.09	85.58	126.27	194.29	26.11	68.06	83.43	151.99	227.01	21.89	48.65	82.22	141.24	267.48	22.60	55.24
	75	87.14	157.60	224.05	20.62	44.95	94.64	161.00	214.53	13.25	39.72	102.39	176.68	235.25	10.09	29.42	107.62	180.17	238.56	9.22	26.94
AGE825	0	86.28	129.83	192.11	24.61	65.70	83.95	116.96	185.55	32.27	70.67	88.94	136.78	192.08	20.34	59.82	86.02	137.18	209.35	20.40	60.71
	30	87.27	149.52	200.46	20.23	50.45	85.87	125.06	226.99	24.12	70.38	91.70	149.68	310.49	15.73	50.54	85.30	146.97	304.38	20.50	51.58
	75	87.40	157.02	214.20	19.85	44.49	106.55	160.64	210.78	8.09	38.66	121.23	174.52	234.70	3.94	27.54	118.71	178.04	241.47	4.60	26.95
AGE809	0	88.18	170.71	230.15	19.54	44.98	92.84	176.78	279.32	13.61	36.35	88.07	162.42	260.96	16.95	42.84	91.80	194.48	323.27	14.75	34.76
	30	89.85	171.72	233.08	11.91	28.94	92.30	176.67	241.27	14.24	33.26	92.15	162.38	224.52	14.53	40.36	89.11	158.86	228.60	17.55	44.09
	75	91.94	173.97	233.70	16.18	34.98	106.27	166.60	216.44	8.24	33.17	125.64	181.25	234.24	4.59	22.13	133.01	185.20	238.33	3.33	18.89
CCL846	0	89.69	168.65	230.46	16.96	38.54	96.28	192.61	514.33	11.53	29.21	90.24	170.33	237.47	15.91	37.52	89.92	170.44	259.94	15.91	38.41
	30	123.81	198.39	268.62	5.13	18.96	106.64	184.53	241.44	9.03	24.09	94.04	176.40	233.20	13.05	30.43	91.72	179.53	239.14	14.45	30.03
	75	92.18	180.70	236.06	14.18	29.40	105.70	178.22	235.18	8.45	28.15	122.58	180.44	233.47	4.87	22.29	119.57	181.84	235.37	5.52	23.14

* D represents the measured distance from the platform center position.

. The effects of different rotor speeds and measuring positions from the center of the spray platform on droplet sizes (D_V50) were investigated. In the simulated single-rotor UASS equipped with a bracket of four LU120-015 nozzles, the results demonstrated that the LU120-015 produced very fine to fine droplets ranging from 112.04 µm to 198.39 µm, categorized based on the ASAE S572.3 droplet size classification [48]. The average measured data across three distances and four rotor speeds were examined, along with the effect of adding tank-mix adjuvants on D_V50 compared to water alone. The addition of CCL846 significantly increased the D_V50 by an average of 25%, while the addition of AGE809, AGE852B, and AGE825 led to average increases of 24.50%, 16.87%, and 8.57%, respectively. When the propeller rotor was stationary, the addition of the four adjuvants increased the D_V50 and tended to decrease the proportion of the finest droplets at the 0, 30, and 75 cm distances from the center of the spray platform. For water alone, the average finest droplet size was 139.14 µm, with V₁₀₀ at 25.03% and V₂₀₀ at 57.24%. The addition of CCL846 increased the D_V50 by an average of 31.22% to 182.58 µm and reduced V₁₀₀ to 12.09%. The addition of AGE809 increased the average D_V50 to 172.13 µm by 23.72% and reduced V₁₀₀ to 15.88%. For adjuvants with the same ingredients, AGE852B and AGE825 increased the average D_V50 to 162.56 µm (16.83%) and 145.46 µm (4.54%), respectively, and reduced V₁₀₀ to 19.33% and 21.56%, respectively.

A comparison of the average percentage of V₁₀₀ using Duncan’s post hoc tests (α = 0.05) revealed that water alone was significantly highest at 24.54%. The addition of adjuvants AGE852B and AGE825 decreased V₁₀₀ to 17.82% and 17.89%, respectively. This was followed by AGE809 at 12.95% and CCL846, which significantly decreased V₁₀₀ to 11.25% (p < 0.05).

Furthermore, the increase in rotor speed affected the D_V50. The four adjuvants varied in their effect on droplet size at different rotor speeds and distances from the center of the spray platform. The addition of the four adjuvants decreased V₁₀₀ at a distance of 75 cm from the center at each rotor speed.

The uniformity of droplet distribution was indicated by the RS. Figure 8 illustrates the results, revealing no significant difference in RS with the addition of adjuvants. However, the RS was found to vary with rotor speed and distance from the center of the spray platform. At a measured distance of 0 cm from the center, the RS of CCL846 was observed to be large at a rotor speed of 824 rpm. Conversely, the RS values of AGE852B and AGE825 were noted to be large at a distance of 30 cm from the center with rotor speeds of 962 and 1072 rpm, respectively. AGE809 exhibited the smallest RS value at a distance of 75 cm from the center, with a rotor speed of 1702 rpm.

3.2.2. Multi-Rotor UASS Platform

In the multi-rotor UASS platform, the three-way ANOVA analysis results, as shown in

Table 4. The significance obtained from the three-way ANOVA for droplet size as affected by rotor speed, distance from the center, and adjuvant product using the multi-rotor UAV simulation based on D_V50, RS, and V₁₀₀.

Source of Variance	DV50			RS			V100
	p Value	Sig.	Correlation Coefficient	p Value	Sig.	Correlation Coefficient	p Value	Sig.	Correlation Coefficient
Rotor speed (R)	2.893 × 10−6	***, †, ‡	0.070	6.321 × 10−21	***, †, ‡	−0.130 *	1.238 × 10−42	***, †, ‡	−0.209 **
Distance (D)	5.292 × 10−91	***	0.009	3.587 × 10−57	***	−0.174 **	5.443 × 10−105	***	0.056
Adjuvant (A)	4.024 × 10−104	***	0.517 **	1.673 × 10−80	***	−0.593 **	5.531 × 10−97	***	−0.393 **
R × D	2.489 × 10−63	***		1.380 × 10−23	***		8.232 × 10−56	***
R × A	4.661 × 10−18	***		1.542 × 10−6	***		5.524 × 10−19	***
D × A	1.038 × 10−41	***		2.367 × 10−50	***		1.225 × 10−47	***
R × D × A	5.101 × 10−14	***		2.450 × 10−13	***		9.860 × 10−19	***

^† The statistical significance levels are denoted as follows: * p < 0.05, ** p < 0.001, and *** p < 0.000, with ^‡ 0.000 representing a p-value lower than 1.0 × 10⁻⁶. * The correlation is considered significant at the 0.05 and 0.01 levels.

, revealed that rotor speed, distance from the center, and adjuvant type had an extremely significant influence on D_V50, RS, and V₁₀₀ (p < 0.001). Furthermore, the interaction of these three parameters exhibited a strong relationship with D_V50, RS, and V₁₀₀. The correlation coefficients indicated that adjuvant type played a significant role across all variables, demonstrating a moderate positive correlation to D_V50 and strong negative effects on RS and V₁₀₀. Rotor speed showed weak correlations, but its negative influence on RS and V₁₀₀ was notable and statistically significant. Distance had a minimal effect on D_V50 and V₁₀₀ but exhibited a weak negative correlation with RS.

The droplet size spectrum of the multi-rotor UAV simulation spraying is presented in Figure 9 and Table 2. For water alone, the average droplet size was found to be 159.55 µm. With the addition of adjuvants, the average D_V50 increased to 173.10 µm (8.49%), 168.49 µm (5.60%), 188.37 µm (18.06%), and 199.17 µm (24.83%) for AGE825, AGE852B, AGE809, and CCL846, respectively. Moreover, a decrease in the quantity of V₁₀₀ and an increase in the percentage of V₂₀₀ were observed.

When the rotor was stationary (0 rpm), the LU110-015 produced fine droplets. At the measured distances of 0 and 15 cm, droplet sizes were larger and then decreased from the 30 to 60 cm measured distances from the center for water alone. The addition of the four adjuvants tended to increase the droplet size for each measured distance, particularly the addition of AGE809 and CCL846, which increased droplet sizes from fine to medium.

Under downwash airflow field conditions, the addition of four adjuvants increased droplet sizes at every measured distance from the center compared to water alone. With increasing rotor speed, the addition of AGE852B, AGE825, and CCL846 resulted in larger droplet sizes at the center of the spray platform. In contrast, AGE809 tended to decrease droplet sizes. At measured distances from 15 to 45 cm from the center, each spray solution exhibited finer droplets compared to those at the center and increased droplet sizes at a 60 cm measured distance from the center. The addition of AGE852B and CCL846 decreased droplet size when rotor speed was increased at a measured distance of 30 cm from the center, while AGE809 decreased droplet sizes at measured distances from 0 to 45 cm from the center. Furthermore, the addition of adjuvants also decreased the percentage of V₁₀₀ and increased that of V₂₀₀.

Comparison of the average percentage of V₁₀₀ using Duncan’s post hoc tests (α = 0.05) revealed that water alone had the significantly highest V₁₀₀ value (6.75%). The addition of adjuvants resulted in AGE852B and AGE825 decreasing V₁₀₀ to 5.28% and 5.33%, respectively. Adding AGE809 and CCL846 resulted in the lowest V₁₀₀ values of 3.50% and 3.55%, respectively.

The RS results, as shown in Figure 10, indicated that the average RS value of water alone fluctuated more than with the addition of adjuvants. With increased rotor speed, the average RS value suggested a more uniform distribution under downwash airflow field conditions. According to the droplet size spectrum results, at distances from 30 to 60 cm from the center, the droplet distribution was found to be more uniform than at the center of the platform.

3.3. Spray Distribution Uniformity

3.3.1. Single-Rotor UASS Platform

The spray distribution uniformity was measured under the downwash airflow field of the simulated single-rotor UAV sprayer at rotor speeds of 0, 824, 962, and 1072 rpm, and the results are presented in Figure 11.

When the downwash airflow field was stationary, the deposition amount in the control treatment exhibited a specific pattern from the center of the spray platform (serial numbers 7–8) to the outside (serial numbers 6 to 1 and 9 to 14). Initially, the deposition amount increased, then decreased, followed by another decrease on the left side, and finally increased once more on the right side. Conversely, the deposition amount with the addition of adjuvants exhibited distinct volume distributions. The addition of CCL846, AGE852B, and AGE825 resulted in a peak in volume distribution at the center of the spray platform, followed by a decrease and subsequent increase at the outer collection positions. In contrast, the addition of AGE809 led to a peak in volume distribution at position no. 9, followed by a decrease and subsequent increase on the right side of the collection positions, while the left side exhibited a decreasing trend.

Under downwash airflow field conditions, at a rotor speed of 824 rpm, the addition of CCL846 resulted in the maximum spray distribution in the central area of the spray platform, while the other treatments shifted the maximum spray distribution to the left side. At rotor speeds of 962 and 1072 rpm, each treatment exhibited a maximum spray distribution in the central area (serial numbers 5–10) of the spray platform. This was followed by a decreasing trend toward the ends of spray atomization and a fluctuating trend on the outside (serial numbers 3 to 1 and 12 to 14).

Because the propeller in the single-rotor UAV sprayer had a large diameter, the downwash airflow field reduced the amount of deposition in the middle of the spray platform. This made the droplet volume more evenly distributed in the central area. The downwash airflow increased the velocity of the droplets in the vertical direction and shortened the movement time of the droplets in the air, particularly in the central area. Its turbulent nature caused the droplets on both outsides of the spray platform to increase the movement distance of some droplets in the horizontal direction.

3.3.2. Multi-Rotor UASS Platform

The spray distribution uniformity was measured under the downwash airflow field of the simulated multi-rotor UAV sprayer at rotor speeds of 0, 2200, 2400, and 2600 rpm (Figure 12).

When the downwash airflow field was stationary, the amount of deposition for each treatment followed a specific pattern from the center of the spray platform (serial no. 7–8) to the outside (serial no. 6 to 1 and 9 to 14). The deposition amount initially decreased, then increased, and finally decreased again at the outer positions. The maximum amount with the addition of CCL846 was lower than those of the other treatments, while there was no significant difference between AGE852B, AGE825, AGE809, and water alone.

Under downwash airflow field conditions, the airflow could wrap the finest droplets and carry them to the outside of the simulated UAV. This would reduce the amount of finer droplets in the center of the spray platform and promote a more uniform distribution of droplet volume centrally. The downwash airflow increased the movement speed of the droplets in the vertical direction, which shortened their movement time in the air, and may, therefore, reduce the movement distance of some droplets in the horizontal direction, resulting in a significant reduction in the amount of droplet deposition on both sides. At a rotor speed of 2200 rpm, the distribution trend and amount of distribution for AGE852B, AGE825, and AGE809 under the downwash airflow field conditions were not significantly different compared to water alone. However, the maximum amount with the addition of CCL846 was significantly higher than those of other treatments at the center. There was no obvious correlation between rotor speed and the uniformity of deposition distribution. At rotor speeds of 2400 and 2600 rpm, there was no significant difference in the distribution trend or amount of distribution. The center of the spray platform was slightly deviated from the middle position after the downwash airflow field was increased, while the peak of the spray distribution area was significantly shifted to the right side of the measurement. The spray distribution of each treatment tended to decrease slightly from the center to the outside. The downwash airflow field exerted a greater impact on the distribution of droplets, and the uneven distribution of the downwash airflow field shifted the center of the spray distribution area.

4. Discussion

The present study aimed to assess the droplet size spectrum and uniformity of spray distribution under downwash airflow conditions using single-rotor and multi-rotor simulated UASS platforms in an indoor environment without crosswinds. The physicochemical properties of four adjuvants were investigated and compared with water alone. The addition of AGE809 and AGE825 significantly decreased the CA by 40.26% and 45.85%, respectively, followed by AGE852B and CCL846, which decreased the CA by 19.15% and 26.81%, respectively. The SST decreased by 57.54%, 56.60%, 53.57%, and 38.22% with the addition of AGE825, CCL846, AGE809, and AGE852B, respectively. The DST also exhibited a slight decrease over time with the addition of these adjuvants. Zhang et al. reported that the LU120015 nozzle produced a fine-grade spray quality when adding different adjuvants, characterized by finer droplet sizes and improved retention on wet leaf surfaces. However, the fine droplets generated by this nozzle also increase the potential for drift [49]. The addition of tank-mix adjuvants has been shown to lower the CA, SST, and DST, thereby enhancing wetting time, spreading, spray coverage, penetration, deposition, and distribution uniformity [10,19,20,43,45,50,51,52].

The droplet size spectrum of the single-rotor and multi-rotor UASS platforms using a flat fan nozzle LU110-015 at an operating pressure of 0.4 MPa produced droplets ranging from very fine to medium across various distances and rotor speeds. For the single-rotor UAV spraying platform, the addition of CCL846 increased the D_V50 by an average of 25% compared to water alone, while AGE809, AGE852B, and AGE825 resulted in an average increase of 24.50%, 16.87%, and 8.57%, respectively. Rotor speed and distance from the center platform significantly affected both D_V50 and RS, while the addition of adjuvants had a significant effect on D_V50 and the volume of droplets smaller than V₁₀₀ but not on RS. The addition of CCL846, AGE809, AGE852B, and AGE825 reduced V₁₀₀ values by 54.16%, 47.23%, 27.38%, and 27.10%, respectively, compared to water alone. The simulated multi-rotor UAV sprayer without a downwash airflow field produced larger droplets at the 0 and 15 cm measured distances, while finer droplets were observed at various distances from the center. As the rotor speed increased, the droplet size significantly increased at various distances from the center of the spray platform, especially at 60 cm, but decreased in the central area (0–45 cm). The addition of the four adjuvants changed the D_V50 from fine droplets to medium droplets at rotor speeds of 2200, 2400, and 2600 rpm, particularly increasing droplet size in the central area of the spray platform. The addition of adjuvants, rotor speed, and distance from the center had significant effects on both D_V50 and RS. The addition of AGE809, CCL846, AGE852B, and AGE825 reduced V₁₀₀ by 48.15%, 47.41%, 21.78%, and 21.04%, respectively, compared to water alone. While rotor speed and distance from the spray platform center significantly influenced D_V50 and RS, adjuvant addition primarily impacted D_V50 and V₁₀₀, with limited effect on RS. Previous studies have also reported that the addition of methylated vegetable oil produced fine droplets when using a flat fan XR11001VS nozzle under the downwash airflow field at 0.4 MPa operating pressure [37,50]. Wang et al. indicated that the addition of vegetable oil and organosilicon adjuvants at concentrations of 0.5% and 1.0% increased D_V50 and reduced V₁₀₀ under the downwash airflow field at a rotor speed of 2200 rpm and a pressure of 0.3 MPa [10].

The spray distribution uniformity of the simulated single-rotor and multi-rotor UASS platforms was observed. The impact of the downwash airflow field on the single-rotor UASS platform when adding CCL846, AGE809, AGE852B, and AGE825 showed a maximum amount of spray distribution in the central area of the spray platform at rotor speeds of 824, 962, and 1072 rpm. All treatments resulted in a more uniform droplet spread centrally, decreasing toward the atomization end. The presence of the downwash airflow led to a more uniform spray distribution across the central area by reducing deposition concentration at the center. The downwash airflow field also increased vertical droplet velocity, decreasing airborne time, particularly centrally, while turbulence extended horizontal movement for peripheral droplets. The spray distribution uniformity of the simulated multi-rotor UASS platform exhibited similar distribution trends under downwash airflow field conditions with the addition of CCL846, AGE809, AGE852B, and AGE825. This led to a reduction in fine droplets and the promotion of a uniform distribution at the center of the spray platform. It contributed to an increase in vertical droplet velocity, resulting in a shortened duration of airborne suspension and potentially reduced horizontal movement, consequently leading to reduced deposition on both sides. After the increasing rotor speed to 2200, 2400, and 2600 rpm, the central peak shifted rightward, with the spray distribution decreasing slightly from center to outside. This could be especially useful in reducing drift for field applications where uniform pesticide distribution is critical. Similarly, Chyrva et al. demonstrated that a multi-rotor UAV produced a deposition pattern with a peak mass concentrated centrally [33]. Yang et al. observed that in a six-rotor UAV sprayer, the downwash airflow field structured spray distribution, with larger droplets predominantly at the periphery and finer droplets concentrated centrally [36]. Additionally, Lan et al. and Wang et al. emphasized that an optimal flight height can further improve droplet deposition, particularly in crosswind and vertical directions, attributed to the downwash airflow field that expanded the effective spray swath [34,35]. These findings collectively underscored the importance of rotor configurations, flight parameters, and downwash dynamics in achieving targeted and efficient droplet deposition in UAV-based aerial applications. The results indicated that the downwash airflow field increased the vertical movement speed of droplets, which shortened their airtime and affecting the droplet size and distribution. By adding tank-mix adjuvants, the atomization properties improved, which led to better spray deposition and penetration of pesticide droplets in the UAV rotor’s downwash airflow field.

5. Conclusions

This study investigated the effects of adding four different adjuvants, namely AGE809, AGE825, AGE852B, and CCL846, on the physicochemical properties, droplet size spectrum, and volume distribution uniformity under UASS downwash airflow field conditions. The addition of AGE809 and AGE825 significantly reduced CA, while all adjuvants led to a decrease in SST and DST. In single-rotor tests, the presence of adjuvants resulted in larger droplet sizes. Both rotor speed and measured distance position were found to significantly affect the D_V50 and RS. Notably, the adjuvants substantially reduced the percentage of spray volume contained in droplets smaller than V₁₀₀, without markedly influencing RS. In multi-rotor tests, the added adjuvants shifted the D_V50 from fine to medium classification at higher rotor speeds ranging from 2200 to 2600 rpm, particularly increasing droplet size in the central spray area. Higher rotor speeds caused the central peak of spray distribution to move towards larger droplet sizes, indicating larger droplets in the central area. Therefore, the combination of adjuvant addition and the downwash airflow field led to a reduction in fine droplets and enhanced the uniformity of spray distribution. This study demonstrated that selecting appropriate adjuvants and optimizing rotor speeds can improve spray performance in UAV applications targeting areas during static hovering. In particular, future research should focus on investigating the influence of forward flight and crosswind conditions on the droplet size spectrum and spray distribution.