Flight Parameters for Spray Deposition Efficiency of Unmanned Aerial Application Systems (UAASs)

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Flight Parameters for Spray Deposition Efficiency of Un- manned Aerial Application Systems (UAAS)

Review 

The manuscript presents the results of a study evaluating the effects of flight parameters on spray deposition efficiency of drones. Different flight speeds, droplet sizes, and application volumes were evaluated.

The manuscript is well written, the diagrams mostly clear, the results clearly communicated, and the limitations of the study presented. It should make an interesting addition to the readership of Drones.

The authors should consider these comments to help with improving the clarity and context of the manuscript:

Page 2: Lines 93 to 94: “While various sprayer drones have been evaluated in diverse fields and environmental conditions, there is still limited information on optimizing flight parameters for sprayer drones equipped with centrifugal nozzles.”

Some studies have been carried out in this area. It is recommended that the authors give a bit more background on the previous work in this area and clearly show what value their contribution is adding compared to the previously published work in this area.

Page 5: Lines 187 to 191: “Scanned images were processed using the AccuStain software (Version 0.32, developed by Matt Gill, University of Illinois at Urbana-Champaign) following the user manual to assess spray deposition patterns and droplet spectra parameters.”

One cannot find any references or online links to this software, how to access it and or the manual. The two references alluding to it [references 32, and 33] do not contain any information on these, as well. Please provide appropriate references and or links. This is important because AccuStain is essential to the analysis presented in this study.

Page 7: Line 259: “ns, *, and **: nonsignificant or significant at p ≤ 0.05 or 0.01, respectively.

This is unclear. Perhaps this is clearer? – “ns = nonsignificant; * = significant at p ≤ 0.05; ** = significant at p ≤ 0.01.”

Nomenclature section: The authors should consider this as necessary and add one. There are a lot of acronyms [even though they have been defined in the text] and it is difficult and distractive to keep on checking their meanings in the text each time one encounters them.

Author Response

The manuscript presents the results of a study evaluating the effects of flight parameters on spray deposition efficiency of drones. Different flight speeds, droplet sizes, and application volumes were evaluated. The manuscript is well written, the diagrams mostly clear, the results clearly communicated, and the limitations of the study presented. It should make an interesting addition to the readership of Drones. The authors should consider these comments to help with improving the clarity and context of the manuscript:

Comment: Page 2: Lines 93 to 94: “While various sprayer drones have been evaluated in diverse fields and environmental conditions, there is still limited information on optimizing flight parameters for sprayer drones equipped with centrifugal nozzles.” Some studies have been carried out in this area. It is recommended that the authors give a bit more background on the previous work in this area and clearly show what value their contribution is adding compared to the previously published work in this area.

Response: Authors reviewed the paragraph and improved clarity, giving more emphasizes to the specific research gap addressed by our study. We are being more specific giving more focuses on individual parameters than the general performance, despite few studies in the literature have systematically evaluated the combined effects of flight speed, droplet size, and application volume using a factorial design. The clarification strengthens the rationale of our study and highlights its novel contribution, particularly in the context of centrifugal nozzles and specialty crop applications. Changes were made in the manuscript lines 94-104.

Comment: Page 7: Line 259: “ns, *, and **: nonsignificant or significant at p ≤ 0.05 or 0.01, respectively. This is unclear. Perhaps this is clearer? – “ns = nonsignificant; * = significant at p ≤ 0.05; ** = significant at p ≤ 0.01.”

Response: Item corrected.

Comment: Nomenclature section: The authors should consider this as necessary and add one. There are a lot of acronyms [even though they have been defined in the text] and it is difficult and distractive to keep on checking their meanings in the text each time one encounters them.

Response: Authors appreciate the reviewer suggestion to include a nomenclature section. However, according to the journal's guidelines, acronyms and abbreviations should be defined at their first appearance in the abstract, main text, and first figure or table. We have carefully followed these instructions and ensured that all abbreviations are defined upon first use in each relevant section. While we understand that a nomenclature section may improve readability for some readers, we have chosen to adhere to the journal’s formatting policy to maintain consistency. Please refer to the journal’s instructions for authors: Drones | Instructions for Authors, section “Manuscript Preparation”, subsection “Acronyms/Abbreviations/Initialisms”.

Reviewer 2 Report

Comments and Suggestions for Authors

Overview:
This manuscript evaluates the influence of flight speed, droplet size, and application volume on spray deposition efficiency using the DJI AGRAS T40 (quarddrone) unmanned aerial application system (UAAS) for precision pesticide application in specialty crops. The study's main contributions include a comprehensive field-based analysis of spray coverage, droplet density, and effective swath width under various flight configurations, providing practical guidelines to optimize UAAS operations. Strengths of the work lie in its robust experimental design, detailed droplet spectrum analysis, and relevance to sustainable agriculture. However, gaps remain in the limited environmental conditions tested, the lack of economic or comparative analysis with other spraying technologies, and the absence of long-term performance validation across diverse crop systems.
Abstract:
In lines 22-23, what was the droplet size when maximum coverage and droplet density were achieved for specialty crops? 
In the Materials and Methods section, it is stated that this UAV was tested at a turfgrass field; therefore, how are the treatments mentioned correlated with specialty crops?
In line 24, a flight speed of 7.93 m/s was not in the treatment; explain how this was calculated/adopted?
Introduction:
In lines 60-61, how were the spraying effectiveness parameters (flight speed, droplet size, and application volumes) of UAAS identified?  
For improved spray parameter optimization, consider reviewing “Testing and Calibration of the Air Blast Citrus Orchard Sprayer”.
Materials and Methods:
In lines 117–118, I noticed that the reference cited “[22]” for the DJI AGRAS T40 technical specifications seems incorrect. I recommend citing the official DJI user manual or technical datasheet to accurately support the UAV’s specifications.
In lines 133–135 and 149–152, kindly explain the treatment level selection criteria for flight speed (m/s) more clearly, with appropriate source/citation, for better clarity of the readers.
In lines 165–171, please specify the size and specifications of the Kromekote white paper (KWP) cards. Additionally, clarify how they were placed/attached on the wooden board, with or without using adhesive tape/glue? Was the wooden board fully/partially covered with cards, and why?
Kindly also report the interval between flights for each treatment and its replications.
The use of AccuStain software for image analysis is appropriate; however, I suggest briefly discussing its accuracy, limitations, or validation.
Results:
In line 259, clearly define the meaning/representation of “*” and “**” and the level of significance, whether alpha is 0.05 or 0.01 in Table 3.  
In line 341, as per the quadratic model, effective swath increases with flight speed up to 8.07 m/s; update the value.   
Label Figure 2 with the letters A and B as written in the caption of the figure in line 290. 
To improve practical adoption, please include concise UAAS parameter recommendations (e.g., flight speed, droplet size, and application volume) for pre/post-emergence herbicide, insecticide, and fungicide applications. A summary table or flowchart would help farmers optimize spray efficiency and minimize drift. Briefly address cost-benefit comparisons to ground spraying for wider relevance.

Author Response

This manuscript evaluates the influence of flight speed, droplet size, and application volume on spray deposition efficiency using the DJI AGRAS T40 (quarddrone) unmanned aerial application system (UAAS) for precision pesticide application in specialty crops. The study's main contributions include a comprehensive field-based analysis of spray coverage, droplet density, and effective swath width under various flight configurations, providing practical guidelines to optimize UAAS operations. Strengths of the work lie in its robust experimental design, detailed droplet spectrum analysis, and relevance to sustainable agriculture. However, gaps remain in the limited environmental conditions tested, the lack of economic or comparative analysis with other spraying technologies, and the absence of long-term performance validation across diverse crop systems.
Abstract:
Comment: In lines 22-23, what was the droplet size when maximum coverage and droplet density were achieved for specialty crops?  In the Materials and Methods section, it is stated that this UAV was tested at a turfgrass field; therefore, how are the treatments mentioned correlated with specialty crops?
Response: Authors appreciate the reviewer's observations as they are important points of the manuscript. For the first question, our results highlight that spray coverage was significantly influenced by the interaction between flight speed and application volume, whereas droplet density was affected by the main effects of flight speed and droplet size only. Specifically, the maximum coverage was measured at a flight speed of 4 m/s and an application volume of 28.1 L/ha, independent of the droplet size. In contrast, droplet density was highest when using the finest droplet size (150 µm) and the slowest flight speed (4 m/s), regardless of the application volume. Nevertheless, authors have revised the manuscript accordingly to clarify these results, and also added such information in the abstract (lines 22-24).

            For the second question, the UAV was tested over a turfgrass field not to assess any crop-specific biological response, but rather to simulate a bare-ground scenario under uniform and controlled surface conditions. This approach aimed to evaluate spray pattern, droplet deposition, and effective swath width across different operational parameters. Our choice is consistent with established protocols in the literature. For instance, Martin and Latheef (2022) and Fritz and Martin (2020) conducted similar tests on unplanted fields, including turfgrass and gravel surfaces, to isolate the effects of UAV operational parameters without crop canopy interference. These studies have shown that using non-crop surfaces is a valid and effective method to measure spray uniformity and effective swath width in early-stage evaluations of spray technology. Ultimately, as explained in the "Experimental Design" section (Lines 141–176), our goal was to assess the spray distribution performance of various combinations of flight speed, droplet size, and application volume, parameters commonly used in unmanned aerial applications for specialty crops, which classify our study as the preliminary screening for specialty crops, allowing us to identify the most promising treatment combinations for subsequent validation in actual crop environments.

Comment: In line 24, a flight speed of 7.93 m/s was not in the treatment; explain how this was calculated/adopted?
Response: The flight speed of 7.93 m/s was not a specific speed tested during the field trial. Instead, this value was derived through a second-order polynomial regression model using the RSREG (Response Surface Regression) procedure in SAS. The model was applied to the response variable "effective swath width" as a function of flight speed for each droplet size.

For the 350 µm droplet size, the analysis identified a stationary point, in which the predicted swath width was maximized at 7.93 m/s. This was determined from the canonical analysis output of the RSREG procedure. Particularly, the estimated optimum speed was derived from the fitted quadratic model:

Swath = β₀ + β₁ · Speed + β₂ · Speed² 

The optimal speed corresponds to the critical point of this curve was calculated as:

Optimal Speed = –β₁ / (2 · β₂)

Substituting the estimated coefficients from the model:

Optimal Speed = –4.6841 / (2 · –0.2951) ≈ 7.93 m/s

This regression-based estimation provides a statistically robust prediction of the speed at which the maximum effective swath occurs for that droplet size, even though it was not a directly tested treatment level. This method is standard in response surface analysis for identifying optimal operating conditions within the studied range.

Introduction:
Comment: In lines 60-61, how were the spraying effectiveness parameters (flight speed, droplet size, and application volumes) of UAAS identified?  For improved spray parameter optimization, consider reviewing “Testing and Calibration of the Air Blast Citrus Orchard Sprayer”.
Response: The selection of flight speeds, droplet sizes, and application volumes was detailed in the Experimental Design subsection (Lines 141–176). These parameters were based on the DJI AGRAS T40 operator’s manual, the ASABE S572.1 standard for aerial application droplet classification, and common label recommendations for aerial application of insecticides and fungicides in specialty crops. While the suggested document on air blast sprayer calibration focuses on a different application system, we agree that parallels in spray optimization approaches can be useful and have considered that perspective when structuring the experimental design.

Materials and Methods:
Comment: In lines 117–118, I noticed that the reference cited “[22]” for the DJI AGRAS T40 technical specifications seems incorrect. I recommend citing the official DJI user manual or technical datasheet to accurately support the UAV’s specifications.
Response: Item corrected.

Comment: In lines 133–135 and 149–152, kindly explain the treatment level selection criteria for flight speed (m/s) more clearly, with appropriate source/citation, for better clarity of the readers.

Response: Authors added the requested clarification, which is now in lines 158-167.

Comment: In lines 165–171, please specify the size and specifications of the Kromekote white paper (KWP) cards. Additionally, clarify how they were placed/attached on the wooden board, with or without using adhesive tape/glue? Was the wooden board fully/partially covered with cards, and why?
Kindly also report the interval between flights for each treatment and its replications.
The use of AccuStain software for image analysis is appropriate; however, I suggest briefly discussing its accuracy, limitations, or validation.

Response: Authors have added the specifications of the Kromekote White Paper (KWP) cards used in this study as requested. Also, regarding the placement of the KWP, alligator clips were fixed onto the wooden board using dual-sided tape. The KWP cards were then inserted into these clips at 1-meter intervals. The board was therefore partially covered, not fully. This spacing allowed us to capture representative spray deposition across the swath while avoiding interference or oversaturation between adjacent cards. A close-up of this arrangement is shown Figure 1A.

           Regarding the intervals between applications, there was no fixed time interval between flights for each treatment and replication. Instead, flights were conducted only when wind conditions met the ASAE S386.2 standard. Specifically, wind speed below 2 m/s and within 15° of the desired direction, as specified in lines 122-123 in the manuscript. This ensured minimal drift and consistent application conditions. To reduce variability, we conducted all treatments over two days within the same week (April 19 and April 25, 2024), spraying only in the mornings and under closely matched meteorological conditions.

            Finally, we have revised the manuscript to briefly address the accuracy and limitations of AccuStain software. The new text now acknowledges the scope and reliability of the software, as described in its documentation (lines 215-225)

Results:
Comment: In line 259, clearly define the meaning/representation of “*” and “**” and the level of significance, whether alpha is 0.05 or 0.01 in Table 3.  
Response: Item corrected. Changes have been added to the manuscript on line 297.

Comment: In line 341, as per the quadratic model, effective swath increases with flight speed up to 8.07 m/s; update the value.   
Response: Authors would like to clarify that the value of 7.93 m/s was derived directly from our second-order polynomial regression model using the RSREG procedure in SAS, as previously explained. This value represents the stationary point (maximum) of the fitted quadratic curve for the 350 µm droplet size, confirmed by the negative eigenvalue from the canonical analysis.

The optimal flight speed was calculated using the equation for the stationary point of a quadratic function:

Optimal Speed = –β₁ / (2 × β₂)

Substituting the estimated coefficients from the regression model:

Optimal Speed = –4.6841 / (2 × –0.2951) ≈ 7.93 m/s

Given this, we respectfully suggest that you kindly double-check the value of 8.07 m/s, as it may have resulted from a different parameter set or rounding discrepancy. We have retained the 7.93 m/s value in the manuscript, consistent with our statistical analysis output.

Comment: Label Figure 2 with the letters A and B as written in the caption of the figure in line 290. 
Response: Authors decided to remove letters A and B from the caption to maintain consistency with Figure 3, since they clearly represent distinct main effects. The modification is highlighted in the manuscript (lines 328-330).

Comment: To improve practical adoption, please include concise UAAS parameter recommendations (e.g., flight speed, droplet size, and application volume) for pre/post-emergence herbicide, insecticide, and fungicide applications. A summary table or flowchart would help farmers optimize spray efficiency and minimize drift. Briefly address cost-benefit comparisons to ground spraying for wider relevance.

Response: Authors appreciate the reviewer suggestion regarding practical recommendations. However, we respectfully clarify that this study was designed as an initial step in a broader research framework. Our focus was on evaluating spray pattern and deposition under bare-ground conditions using different UAAS parameters. This preliminary phase was intended to generate foundational knowledge about spray distribution, prior to conducting crop-specific studies with actual pesticide applications. As such, direct recommendations of flight speed, droplet size, and application volume for specific pesticide types or crops would be premature at this stage.

             Authors agree that cost-benefit comparisons to ground spraying are highly relevant for practical adoption. Such analysis still would go beyond the scope of this study and require a separate investigation considering economic, agronomic, and operational variables.

                Ultimately, to provide some practical context without overstepping the scope of our findings, authors have included general recommendations from previous literature regarding target droplet densities for different pesticide classes in the discussion section. These values may assist applicators in evaluating their spray quality objectives when using UAAS.

Reviewer 3 Report

Comments and Suggestions for Authors

This paper systematically investigates the impact of flight parameters (speed, droplet size, application rate) of unmanned aerial application systems (UAAS) on spray deposition efficiency. The experimental design is rigorous, the data is comprehensive, and the conclusions hold practical significance for optimizing agricultural drone applications. However, certain details require further refinement to enhance scientific rigor and clarity of expression.

1. The paper should clearly specify the concrete parameters in the conclusions (such as the optimal flight speed of 7.93 m/s and droplet size of 350 μm) to enhance the information density of the abstract. For example: "The optimal spray swath uniformity (effective swath width of 9.50 m) peaks at a flight speed of 7.93 m/s and droplet size of 350 μm."
2. It is recommended to supplement the research gaps on centrifugal nozzle optimization in existing literature, emphasizing that this paper fills this gap. For example: "Although centrifugal nozzles are widely used in UAV spraying, there is a lack of systematic research on their parameter optimization, especially regarding the dynamic interactions in complex environments which remain unclear."
3. The assumptions of "instantaneous switching" and "no spray dynamic effect" in the text need further discussion. Recommendation: Analyze the impact of nozzle delay on coverage effectiveness (such as local under-spraying caused by transient spraying). Cite actual spray dynamic studies (such as assessments of spray drift) to support the rationality of the assumptions.
4. The paper requires supplementation of the specific sources (such as manufacturer manuals, industry standards, or preliminary test data) for flight speeds (4, 7, 10 m/s) and droplet sizes (150, 250, 350 μm). For example: "The flight speed range is based on the typical operational interval recommended in the DJI AGRAS T40 operation manual."
5. The papershould clearly specify whether the selection of a 3 m flight altitude and 10 m spray swath aligns with ASABE S386.2 or other standards, or cite relevant literature to support the choice.
6. It is necessary to indicate whether the data conform to a normal distribution. If non-normality exists, it is recommended to supplement with robustness tests (such as Box-Cox transformation) or employ generalized linear models (e.g., Gamma distribution).
7. In Table 3, the interaction effect of "flight speed × droplet size" on Dv0.9 is marked as significant (**), but Section 3.1.3 of the main text does not sufficiently explain this result, requiring supplementary discussion.
8. The paper should thoroughly discuss the reasons for maintaining uniform deposition of 350 μm droplets at high speeds (10 m/s). For instance: "Does the rotational speed of the centrifugal nozzle suppress secondary breakup of droplets? Or does the inertia of large droplets make them more resistant to turbulent disturbances?"
9. The paper should compare the research findings with other models (such as the DJI T30) to highlight the unique advantages of centrifugal nozzles. For example: "Compared to hydraulic nozzles, centrifugal nozzles can maintain droplet integrity even at high speeds, but their atomization efficiency requires careful consideration."
10. The discussion should be supplemented with the potential influence of variables such as wind speed and humidity on deposition.
11. Grammar errors in the paper should be corrected, and the reference format should be standardized.

Author Response

This paper systematically investigates the impact of flight parameters (speed, droplet size, application rate) of unmanned aerial application systems (UAAS) on spray deposition efficiency. The experimental design is rigorous, the data is comprehensive, and the conclusions hold practical significance for optimizing agricultural drone applications. However, certain details require further refinement to enhance scientific rigor and clarity of expression.

Comment: The paper should clearly specify the concrete parameters in the conclusions (such as the optimal flight speed of 7.93 m/s and droplet size of 350 μm) to enhance the information density of the abstract. For example: "The optimal spray swath uniformity (effective swath width of 9.50 m) peaks at a flight speed of 7.93 m/s and droplet size of 350 μm."

Response: Authors appreciate the reviewer comment and would like to clarify that parameter, specifically the optimal flight speed of 7.93 m/s, droplet size of 350 µm, and corresponding effective swath width of 9.50 m, are already stated in both the Abstract (Lines 24-26) and Conclusions (Lines 541-542) sections of the manuscript. We believe this information is currently presented with appropriate clarity and emphasis.

Comment: It is recommended to supplement the research gaps on centrifugal nozzle optimization in existing literature, emphasizing that this paper fills this gap. For example: "Although centrifugal nozzles are widely used in UAV spraying, there is a lack of systematic research on their parameter optimization, especially regarding the dynamic interactions in complex environments which remain unclear."

Response: Authors have reviewed the introduction section giving a better emphasis to the lack of research on the optimization of centrifugal nozzles in UAAS applications.

Comment: The assumptions of "instantaneous switching" and "no spray dynamic effect" in the text need further discussion. Recommendation: Analyze the impact of nozzle delay on coverage effectiveness (such as local under-spraying caused by transient spraying). Cite actual spray dynamic studies (such as assessments of spray drift) to support the rationality of the assumptions.

Response: The present study adopted a single pass testing method under steady flight conditions, and the potential effects of nozzle activation delay or transient spray dynamics (e.g., during turning, acceleration, or deceleration) were not directly modeled or measured. These assumptions were made to simplify interpretation of the spray pattern under controlled conditions. However, we agree that nozzle delay and dynamic spraying effects may influence coverage near the edges of a pass, especially at higher speeds, and this is a relevant consideration for future studies. Authors have added a brief discussion acknowledging these factors and referenced prior studies addressing spray drift and system response time to contextualize the limitations of this assumption (Lines 432-441).

 Comment: The paper requires supplementation of the specific sources (such as manufacturer manuals, industry standards, or preliminary test data) for flight speeds (4, 7, 10 m/s) and droplet sizes (150, 250, 350 μm). For example: "The flight speed range is based on the typical operational interval recommended in the DJI AGRAS T40 operation manual."

 Response: Authors would like to clarify that the selection of flight speeds, droplet sizes, and application volumes is already detailed in the Experimental Design subsection of the Material and methods (Lines 141–176), with appropriate citations. Specifically, flight speeds of 4, 7, and 10 m/s were selected based on operational recommendations in the DJI AGRAS T40 operator’s manual and supported by previous UAV spray studies, including Martin and Latheef (2022) and Fritz and Martin (2020). The mid-level speed of 7 m/s reflects the manufacturer's optimal condition for maximum effective swath width, while 10 m/s represents the maximum rated speed of the drone, and 4 m/s corresponds to the lower speed range commonly evaluated in UAAS research. The droplet size classifications (150, 250, and 350 µm) were chosen following the ASABE S572.1 standard, which outlines common droplet spectra used in agricultural aerial spraying. Application volumes of 18.75 and 28.10 L/ha were selected based on commercial product labels for commonly used insecticides and fungicides. For example, labels for methoxyfenozide and acetamiprid recommend a minimum aerial application volume of 18.75 L/ha to ensure effective canopy penetration in crops such as tomatoes and peppers, while fungicides containing azoxystrobin and the fluopyram + trifloxystrobin combination similarly recommend 18.75 L/ha for high-density specialty crops. These label-based recommendations are also aligned with U.S. EPA guidance under PR Notice 93-2. Ultimately, authors believe this section of the manuscript addresses the reviewer concern by providing both practical and regulatory justification for the selected parameters.

Comment: The paper should clearly specify whether the selection of a 3 m flight altitude and 10 m spray swath aligns with ASABE S386.2 or other standards, or cite relevant literature to support the choice.

 Response: The 3 m flight altitude and 10 m swath width used in this study were selected based on a combination of the DJI AGRAS T40 operational manual and prior research on UAAS spray deposition patterns. While the ASABE S386.2 provides general guidance for swath characterization and sampling layout in aerial applications, it was originally developed for manned systems and does not prescribe specific operational parameters for UAV-based applications. Therefore, our implementation aligns with studies that applied the ASABE S386.2 sampling protocols to UAV research but selected operational heights and widths based on UAV manufacturer specifications and effective coverage observed in preliminary trials. Specifically, Houston et al. (2020) and other UAV-focused studies suggest that a 3 m flight height allows sufficient time for droplet dispersion while minimizing rotor-induced turbulence, thus improving spray pattern uniformity. Likewise, a 10 m swath width is consistent with manufacturer-reported optimal operational width for the T40 under standard conditions and is a practical choice for single-pass evaluation methods recommended in ASAE S386.2. Ultimately, authors have clarified this justification in the Materials and Methods section (Lines 171-176).

Comment: It is necessary to indicate whether the data conform to a normal distribution. If non-normality exists, it is recommended to supplement with robustness tests (such as Box-Cox transformation) or employ generalized linear models (e.g., Gamma distribution).

Response: Authors appreciate the reviewer comment, but we have evaluated the distribution of the data, conducting a Shapiro–Wilk test for each treatment combination. The data were considered to meet the assumption of normality, and no data transformation or alternative modeling approach was or is necessary. This information has been added to the Statistical Analysis subsection of the Materials and Methods section for clarity (Lines 276-279).

Comment: In Table 3, the interaction effect of "flight speed × droplet size" on Dv0.9 is marked as significant (**), but Section 3.1.3 of the main text does not sufficiently explain this result, requiring supplementary discussion.

Response: While Section 3.1.3 objectively presents the result, we agree that the significant interaction between flight speed and droplet size on Dv0.9 warrants further explanation. We have now expanded the discussion section to address this interaction effect, clarifying how the combined influence of flight speed and droplet size affects the upper bound of droplet distribution (Lines 483-487).

Comment: The paper should thoroughly discuss the reasons for maintaining uniform deposition of 350 μm droplets at high speeds (10 m/s). For instance: "Does the rotational speed of the centrifugal nozzle suppress secondary breakup of droplets? Or does the inertia of large droplets make them more resistant to turbulent disturbances?" 

Response: We have expanded the discussion to explain why 350 µm droplets maintained spray uniformity at higher flight speeds. A new paragraph was added addressing how the greater inertial momentum of larger droplets helps them resist aerodynamic disturbance and maintain trajectory, reducing the risk of breakup or drift. Additionally, we discuss the role of centrifugal nozzles in generating uniform droplet sizes and minimizing secondary droplet breakup, even under increased rotor-induced turbulence (Lines 487-493).

Comment: The paper should compare the research findings with other models (such as the DJI T30) to highlight the unique advantages of centrifugal nozzles. For example: "Compared to hydraulic nozzles, centrifugal nozzles can maintain droplet integrity even at high speeds, but their atomization efficiency requires careful consideration."

Response: A brief comparative discussion has been added to the manuscript, highlighting the differences between centrifugal and hydraulic nozzles. Specifically, the new paragraph explains that centrifugal nozzles, such as those used in the DJI T40, maintain more stable droplet sizes at higher speeds due to their rotation-based atomization mechanism. In contrast, hydraulic nozzles (e.g., those on the DJI T30) are more prone to droplet size variability under UAAS-induced airflow conditions. This explanation is now supported by findings from Martin and Latheef (2022), who noted that centrifugal atomizers produced consistent droplet spectra across speed ranges and were less affected by rotor turbulence (Lines 455-461).

Comment: The discussion should be supplemented with the potential influence of variables such as wind speed and humidity on deposition.

Response: Authors have added a paragraph to the discussion section acknowledging the potential impact of wind speed and humidity on droplet deposition. These environmental variables are important factors in real-world applications and will be considered in future studies to expand the applicability of our findings (Lines 526-531).

Comment: Grammar errors in the paper should be corrected, and the reference format should be standardized.

Response: Authors have carefully incorporated all reviewers’ comments and reviewed the manuscript for grammar errors. The reference format was also standardized according to the journal guidelines.

 

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Page 5: Lines 187 to 191 of original manuscript: “Scanned images were processed using the AccuStain software (Version 0.32, developed by Matt Gill, University of Illinois at Urbana-Champaign) following the user manual to assess spray deposition patterns and drop- let spectra parameters.” One cannot find any references or online links to this software, how to access it and or the manual. The two references alluding to it [references 32, and 33] do not contain any information on these, as well. Please provide appropriate references and or links. This is important because AccuStain is essential to the analysis presented in this study.

The authors have not addressed this issue. The reference they put up for Matt Gill is not accessible and cannot be found.

Author Response

Comment 1: Page 5: Lines 187 to 191 of original manuscript: “Scanned images were processed using the AccuStain software (Version 0.32, developed by Matt Gill, University of Illinois at Urbana-Champaign) following the user manual to assess spray deposition patterns and drop- let spectra parameters.” One cannot find any references or online links to this software, how to access it and or the manual. The two references alluding to it [references 32, and 33] do not contain any information on these, as well. Please provide appropriate references and or links. This is important because AccuStain is essential to the analysis presented in this study.

Response: Authors appreciate the reviewer's comment and understand the reference's importance; however, the AccuStain manual can only be accessed as a PDF document from the folder of the software after it has been installed. Therefore, a reference or link cannot be added. Because the AccuStain software was properly cited (references 32 and 33) as mentioned by the reviewer, authors see no necessity to add another reference. In addition, adding a reference is not possible as aforementioned. We have attached the AccuStain manual to this response in case the reviewer would like to have access to it, but also to prove its existence. 

Author Response File: Author Response.pdf