Author: Jason Deveau

  • Assessing wheat head coverage from Defy 3D and 3D Ninety nozzles

    Assessing wheat head coverage from Defy 3D and 3D Ninety nozzles

    We’ve been here before, haven’t we? I could rehash the explanation of why wheat head coverage is important, and define the variables involved, but perhaps you’re already in-the-know. Instead, new readers (and those requiring a refresh) can go give this article and this article a quick read and then come back. I’ll wait.

    Why perform another wheat head nozzle assessment? Primarily we do it so you don’t have to, but in this case there’s a specific problem we’re trying to solve and a “new” nozzle to explore.

    The problem (and some history)

    Let’s digress a little and use the historical experience shared by Clean Field Services (CFS) in Drayton, Ontario (cooperators in this study), to explain the problem and our objective.

    As broadacre sprayers evolve, nozzle technology has been lagging. Consider a basic field sprayer equipped with a centrifugal pump. Its performance curve exhibits a direct relationship between flow rate and pressure. In this case, the operator relies on a rate controller to bypass flow to maintain a target application rate across a range of travel speeds.

    However, bypassing changes system pressure, which inadvertently changes the average droplet size. Basically, increasing travel speed reduces droplet size and vice versa. This was the manner of sprayer used in Ontario more than 20 years ago when researchers demonstrated that TeeJet Turbo FloodJets, alternated front-to-back, provided excellent coverage of wheat heads at the T3 timing. This is what Clean Field Services used.

    However, some booms have obstructions that interfere with the aggressive spray angles produced by wide-pattern nozzles such as the Turbo FloodJet. CFS experienced this when they got a RoGator in 2012 and later an R-series Deere in 2017. At one point they tried using extensions to clear the obstruction, but this proved to be a nuisance and interfered with folding. They settled on GreenLeaf Technologies’ TurboDrop Asymmetric DualFan (TADF), which worked great, until the sprayer changed again.

    A visual history of wheat nozzles at Clean Field Services.

    Pulse Width Modulation

    Sprayer plumbing and control systems have evolved. The introduction of pulse width modulation (PWM) technology changed the way rate control is achieved. Rather than regulating flow by altering pressure, PWM intermittently interrupts flow at the nozzle. This decouples flow rate from pressure, preserving droplet size across a range of travel speeds. Most air induction (AI) nozzles, such as the TADF are not approved for use with PWM systems.

    John Deere’s ExactApply PWM system became available in 2017, and CFS got one in 2018. Operators could mount two nozzles in each position, creating opportunities for interesting new configurations. One of the recommended nozzles was the Defy 3D, which features a 38° angle and was developed by Hypro in collaboration with Syngenta to help control blackgrass in the UK. It performed well in drift-reduction studies relative to conventional flat-fan nozzles.

    Welcome to Canada

    CFS mounted a single Defy 3D ’08 in each nozzle body, and had problems. Canadian sprayer operators, on average, drive faster than their UK cousins. Even with PWM, the largest Defy 3D tip (the ’08) required a flow rate that increased system pressure, which in turn led to a drifty experience. Bad in itself, but also not ideal for angled applications, because finer spray deposits with the wind rather than ballistically.

    They tried throttling back, slowing down and/or adjusting water volumes, but felt they never really dialed it in. They settled on a Defy 3D ’08 in the B (rear) position, and an ’05 in the A (front) position at 21 km/h (13 mph) to apply 156 L/ha (16.67 gpa).

    Exploring a solution

    Wouldn’t it be nice to have your cake and eat it too? Drive faster, apply higher volumes and still mitigate drift? Enter the 3D Ninety, with claims of good fungicide utility while producing a significantly coarser droplet than the Defy. They came out in 2021, and yet they are still difficult to find in North America. This study establishes baseline panoramic coverage from the Defy 3D, then benchmarks it against the 3D Ninety and a hybrid configuration at a faster travel speed.

    Experimental design

    The trial took place in a mature wheat field in Drayton, Ontario on July 22, 2026. Temperature was 15°C, and while generally windy, we operated in an area protected by a windbreak, reducing windspeed from an ambient 18 km/h to an average 8 km/h at boom height.

    Sprayer settings

    A John Deere See and Spray Premium (410R) was used in the study. For each condition, we isolated a section of seven nozzles in the middle of the left and right booms (as far as possible from boom tip and chassis). Nozzles were on 50 cm (20″) spacing, so this spanned 2.7 m. The sprayer was set to a 70% D.C., and the boom was 50 cm (20″) above the wheat heads. The treatment conditions were as follows:

    TreatmentForward NozzleRear NozzlePressure (psi)Travel speed (mph)
    1’05 Defy 3D’08 Defy 3D2513
    2’05 3D Ninety’08 3D Ninety4016
    3’05 Defy 3D’08 3D Ninety4016
    Operational settings and nozzles for each treatment.
    In all treatments the ’05 faced forward and the ’08 faced back.

    Samplers

    A series of four posts were positioned in the wheat, spaced 0.5 m apart and centred on the corresponding section of nozzles. The samplers were SpotOn water sensitive papers (WSP) mounted in custom holders to orient four papers at 90° to the sprayer: Advance (facing the sprayer), Left, Retreat (facing away from the sprayer) and Right.

    A series of samplers positioned at wheat head height, 50 cm apart, centred on the swath produced by the section of seven trial nozzles.

    A parallel tramline approximately 1 m from the samplers provided access. The sprayer began spraying 15 m (50 feet) before the samplers and continued spraying the same distance beyond them. Once the spray settled, the samplers were retrieved. A single pass represented a repetition and there were three passes per treatment.

    Papers were digitized using a DropScope (SprayX) and the analysis was performed in R (v. 4.6.0), leveraging the rpy2 library for integration with Python within the Colab environment.

    What we saw

    The following image shows a typical coverage pattern for each treatment. While WSP is not able to determine droplet size accurately, it can certainly reveal relative differences. It was clear that the Defy 3D produced smaller droplets than the 3D Ninety, and that there were far more of them. The hybrid condition shows a more heterogeneous coverage pattern, which would be expected given it represents a greater span of droplet sizes than either nozzle design used alone.

    Typical coverage pattern from each treament.

    Defy 3D

    3D Ninety

    Hybrid Defy 3D and 3D Ninety

    Continuing with general observations, we can average the coverage measured on each plane, on each sampler, for each treatment. When spoiled samplers were removed from the study (it happens), coverage can be described as either the area covered, or the number of deposits per area. With no exploration of variability, we see that the Defy 3D resulted in the greatest average coverage as represented by either metric.

    TreatmentnMean Area Covered (%)Mean Deposits/cm²
    Defy 3D463.73126.35
    3D Combo443.2287.64
    3D Ninety473.0293.77

    We can drill down and explore coverage by WSP orientation as well, this time including some measure of variability (standard deviation). As a matter of housekeeping, there was no evidence that repetition or post position had any meaningful bearing on coverage results (Pearson p of 0.422 and 0.455 and Spearman p of 0.267 and 0.217). We see the highest average number of deposits on the retreat side (facing the wind) in all treatments. Similarly, and excepting the combination treatment, we see the greatest average area covered on the same plane.

    TreatmentOrientationnMean Deposits/cm²SDMean Area Covered (%)SD
    3D ComboAdvance1183.0053.584.982.80
    3D ComboLeft1163.3638.071.671.24
    3D ComboRetreat10138.2058.384.121.93
    3D ComboRight1272.0063.842.291.93
    3D NinetyAdvance1167.8252.923.413.38
    3D NinetyLeft1242.2549.831.961.61
    3D NinetyRetreat12191.1754.204.892.07
    3D NinetyRight1271.6750.301.871.46
    Defy 3DAdvance12124.9265.484.192.64
    Defy 3DLeft1280.7549.752.481.74
    Defy 3DRetreat10207.70115.845.553.45
    Defy 3DRight12105.5875.922.982.83

    We can illustrate this using box and whisker plots, which show all the data as well as the relative span of each treatment. This makes it easier to compare the treatments and determine if any differences in average coverage were significant or not.

    We can illustrate coverage in an even more intuitive manner using a rosette-style graph. Here we see the average deposit density or the percent area covered for each treatment on each plane. Note that the discrepancy between the Advance (shadowed by wind) and Retreat (wind-facing) side is far greater when the coverage is represented by droplet counts rather than area covered.

    Average coverage on each plane for each treatment, as represented by deposit density.
    Average coverage on each plane for each treatment, as represented by percent area.

    Interpretation and discussion

    Deposits/cm² and percent area covered were strongly positively associated (r = 0.75), indicating that higher deposit counts generally corresponded to greater percent coverage. The relationship wasn’t perfect, suggesting that other factors also influenced coverage and leaving room for interpretation.

    The Defy 3D produced the highest overall coverage, as reflected in total deposit counts. This is consistent with the fact that it emits a higher proportion of finer droplets relative to the 3D Ninety. While finer droplets can improve coverage, they are also more prone to drift and tend to deposit on the downwind face of vertical targets. We have evidence of this in all treatments, which showed more deposits on the Retreat (windward) face than on the Advance face, which was sheltered from the wind.

    This deposition pattern is likely influenced by the rear-facing nozzle configuration (an ‘08), which delivers a higher application rate than the forward-facing nozzle (an ‘05). With higher boom heights or stronger wind conditions, this configuration may be less effective, as reported in previous studies. In this comparison, the Defy 3D also exhibited the greatest variability, suggesting greater sensitivity to such conditions.

    The 3D Ninety and hybrid treatments were difficult to separate based on overall coverage. There was no significant difference in the magnitude of coverage between them, although the hybrid condition showed a more balanced distribution of deposits between the Advance and Retreat faces. In contrast, the 3D Ninety would be expected to produce a coarser spray that is less susceptible to deflection, assuming boom height is sufficiently low to maintain droplet trajectory. Despite this, it recorded more deposits on the Retreat face than the hybrid condition. We have no explanation.

    The hybrid configuration was designed to improve deposition balance by combining complementary spray characteristics. The forward-facing nozzle produced finer droplets, which can be carried along by the sprayer’s forward momentum to enhance forward deposition. The rear-facing nozzle produced coarser droplets at a higher application rate, compensating for lower droplet numbers while counteracting forward momentum to improve retreat-side coverage.

    Although the hybrid treatment appeared to provide a more even distribution of deposits between the Advance and Retreat faces, it is uncertain whether this would translate into improved biological efficacy. Further trials would be needed to evaluate whether this deposition balance leads to measurable yield gains.

    It is also important to note that both the 3D Ninety and hybrid treatments were applied at 25.7 km/h (16 mph), nearly 20% faster than the Defy 3D treatments. This indicates potential for higher productivity. Given the relatively balanced deposition observed, a combination of a forward-facing Defy 3D nozzle and a rear 3D Ninety nozzle may offer improved resilience to changes in boom height and wind speed while maintaining adequate coverage at higher travel speeds.

    Thanks to Clean Field Services for their participation in this study, thanks to Agflow Canada (Hypro / Shurflo) for donating the 3D Ninety’s, and thanks to Cesar Cappa, OMAFA weed specialist in horticulture for patiently explaining how to use R more effectively.

  • Comparing Water Sensitive Paper Brands

    Comparing Water Sensitive Paper Brands

    Introduction

    Spray coverage describes the degree of contact between spray droplets and the target surface area. This metric can be used to predict the success of an application. One of the easiest methods for visualizing coverage is to use water sensitive paper (WSP), which is a passive, artificial collector that turns from yellow to blue when contacted by water.

    WSP is often used to evaluate iterative changes to a spray program. Placed strategically throughout a target canopy, or directly on the ground, achieving uniform, threshold coverage translates into improved efficacy, reduced waste, reduced off-target contamination and reduced risk of pesticide resistance development. WSP were also used to develop a system that measures the area covered by the effective radial distance in an attempt to relate the area covered by a stain to a larger area where sufficient pesticide activity is taking place.

    WSP tends to underestimate the spreading effect that can occur on plant surfaces (especially when surfactants are used), but they are effective as a relative index.

    A brief history of WSP

    In 1970, a journal article described a new method for sampling and assessing spray droplets. Photographic paper treated with bromoethyl blue created a yellow surface that changed colour when it encountered moisture. The pH-based reaction was fast and irreversible, leaving a distinct blue stain to mark the deposition.

    Ciba-Geigy Ltd. made water sensitive paper commercially available in 1985 (later as Novartis in 1996 and as Syngenta since 2000). It is produced in several formats, but aluminum foil packages of 50, 76 x 22 mm (1 x 3 in.) papers are the most popular. Odds are if you’ve ever used water sensitive paper, it originated from Syngenta in Switzerland. In 2023 I noticed that the papers now say “made in Germany.”

    Change of manufacturing location?

    In recent years, two new options have been made commercially available: Innoquest’s SpotOn Paper (United States) and WSPaper (Brazil). At the time of writing, there has been no impartial comparative evaluation of these three products.

    Once dry, the blue stains on WSP are irreversible and papers can be stored for long periods of time. However unstained portions will continue to react to moisture from humidity, dew, or fingerprints, so care must be taken in their handling and storage.

    Comparing WSP brands

    The three commercially-available brands of WSP were subjected to a series of comparisons. The intention was not to rank these products, but to determine if they performed in a similar fashion and to alert users to any significant differences.

    Packaging and Appearance

    Each package was donated for the study. The SpotOn (SO) papers had a “sell-by” date of November 2023, the Syngenta (SY) papers (provided via Spraying Systems Co.) were dated February 2021 and the WSPaper (WS) was their newest formulation (white package, not silver), received June 2021. The comparison was performed on July 5, 2021.

    WSP packages.

    Each product was a foil or plasticized bag of 50, 26 x 76 mm papers. SO and WS had a re-sealing feature similar to that of a sandwich bag. SO also included a package of silica gel desiccant to capture moisture and a pair of plastic forceps to facilitate handling.

    Users are encouraged to label papers to ensure they know their relative position and sprayer pass for later analysis. It was possible to write in ink on the faces of the SY and SO papers, but not WS. It was possible to write on the back of all brands.

    The three papers were different shades of yellow. Further, in the author’s experience, the colour can be visibly different between batches of the same brand. In the case of larger experiments where more than 50 papers are required, it would be prudent to ensure papers are not only from the same manufacturer, but the same production batch. This would not be an issue when subjectively comparing papers, but when using software that employs colour thresholding to identify deposits, it could create artifacts. Presently, only Syngenta has a batch number (found on a sticker on the back of the bag).

    Bleed-through

    WSP is often placed in foliar canopies which are subject to dew and transpiration that can cause the papers to react prematurely. This can be particularly limiting when moisture soaks through the backs of papers. Each brand of paper was placed face-up on a drop of water to see if the water would bleed through.

    Three brands were placed on a single drop of water. Within five minutes, WSPaper and Syngenta brands wicked the water through, causing a colour reaction. SpotOn did not, although the yellow surface darkened. When a drop of water was applied to the face, the SpotOn paper still produced a blue stain.

    WS quickly curled as the water wicked in from the edges. Within five minutes the water soaked through from the back as well. Within five minutes SY also curled, but the colour reaction was entirely due to water soaking through and not wicking along the edges of the paper. SO did not curl and there was no colour reaction save a minor wicking reaction at one edge. It did however produce a dark yellow patch. In order to see if a colour reaction was still possible, a single drop of water was placed on the face and the colour reaction was distinct and instantaneous.

    Note: Others have since replicated this experiment and reported that the response depends on the amount of water used and how long you leave it. We repeated our experiment with higher volumes and longer wait times (see image below). Ultimately, no brand of WSP is water proof from the back. Nevertheless, with small volumes of water (such as from dew) the original assessment of each brand is still valid.

    A replication of the bleed-through experiment with the same batch of papers was performed with higher water volumes and a longer duration. Eventually, all three brands bled through. (SpotOn left, WSPaper middle, Syngenta right).

    Deformation and drying time

    Users of water sensitive paper may be familiar with its occasional tendency to curl when one side is sprayed. In extreme cases, this movement could create smears if the paper contacted other wetted surfaces in dense foliage. The degree of curling was significantly different by brand, with SY becoming convex when wet and then flexing back into a concave form once dry. WS deformed as well, but only to a minor degree. SO did not appear to deform at all. Syngenta has noted that the degree to which their papers curl depends on the batch. Their manufacturing process has changed over the years in response to regulatory requirements and minor adjustments are still occasionally made.

    Once dry, each brand of WSP tended to curl to different degrees. Syngenta curled the most and SpotOn the least if at all.

    There was no appreciable difference in the time it took for any brand to dry. This is based on attempts to smear papers every 30 seconds. All were dry in under five minutes.

    Experimental design

    While there is considerable variability inherent to spraying, every effort was made to maintain consistent conditions. Papers were sprayed in a closed room with no appreciable air currents (21.5 °C and 64% RH). Papers were paired randomly, side-by-side on a plastic sled. The sled was pulled at 2.5 kmh (~1.5 mph) through the centre of a spray swath produced by a TeeJet XR80015 positioned 50 cm (20 in.) above the targets. The nozzle operated at 2.75 bar (40 psi) to produce ~270 L/ha (~29 gpa) with Fine spray quality. Six passes were made, producing four sprayed papers for each brand.

    All papers were dry to the touch after two minutes. They were removed to a cooler, low humidity space and were digitized and analyzed using the SprayX DropScope (v.2.3.0) within an hour of spraying. We noted that while WS and SO fit easily into the DropScope port, the SY papers were sometimes slightly wider and had to be forced. Learn more about how to digitize and analyze WSP in this series of articles.

    Screen capture from DropScope’s smartphone app.

    The “ground” option was selected, and each brand of paper was processed using its specific spread factor. DropScope has a detection threshold of 35 µm. This is appropriate as the smallest droplet diameter that can be resolved by any brand of WSP is ~30 µm (Syngenta, Innoquest, SprayX – Personal Communication).

    Percent surface covered

    The average percent surface covered was calculated with standard error of the mean for each paper. WS and SO produced similar values between 30 and 35%. While all three brands exhibited similar variability, SY approached saturation at approximately 80% coverage. Therefore, WSPaper exhibited a slightly higher degree of spread than SpotOn, while the Syngenta paper exhibited a significantly higher degree of spread.

    For reference, it can be difficult to determine if a stain represents a single deposit or is the result of multiple overlapping deposits. This becomes a problem when the surface of the WSP exceeds 20% total coverage. Further, it becomes increasingly difficult to distinguish a stain from the background, unstained surface when papers exceed 50% total coverage.

    Average percent surface coverage by brand.
    DropScope-digitized images of three brands of WSP. The Syngenta and SpotOn papers were sprayed simultaneously while the WSPaper was sprayed in a subsequent pass. WSPaper exhibited a slightly higher degree of spread than SpotOn, while the Syngenta paper exhibited a significantly higher degree of spread.

    Deposit density

    The average deposit density is a count of discrete objects (i.e. stains) per cm2. WS appeared to resolve the highest count, followed by SY and then SO. The process for determining what is a discrete object, and not the result of anomalies such as overlapping deposits, elliptical deposits or imperfections in the paper itself is complicated and computationally heavy. The algorithms employed by DropScope treated each paper consistently. So, while some differences are attributed to variations in spraying, they also reflect the paper’s innate ability to resolve individual deposits.

    Average deposit density was highest for WSPaper, then Syngenta, then SpotOn. Variability was similar in all cases.

    Droplet diameter

    It is not the intent of this article to determine if WSP should be used to extrapolate the original droplet size. The many assumptions and inconsistencies inherent to this process are well known. Nevertheless, some researchers do use WSP in this manner, so a comparison was warranted.

    DropScope bins deposit diameters by size to produce histograms of deposit size by count. These stain diameters are used to extrapolate DV0.1, DV0.5 (VMD), DV0.9 and NMD, which describe the population of droplets that produced the stains. DV0.5 is the Volume Median Diameter, or the droplet diameter where half the volume is composed of finer droplets and the other half by coarser droplets. Number Median Diameter (NMD) is the droplet diameter where half the total droplets are finer, and half the total droplets are coarser.

    Each brand of WSP will permit a certain degree of spread when a droplet of water contacts the surface. This spread factor is specific to the brand of paper. Further, the spread factor is not constant for all droplet sizes; Finer droplets will spread less than coarser droplets.

    When processing data using DropScope, selecting the appropriate spread factor makes a significant difference to the output. For example, here are the same four SY papers processed using the Syngenta-specific spread factor as well as the spread factors intended for SpotOn and WSPaper.

    The same four Syngenta papers were processed by DropScope using the Syngenta-specific spread factor as well as the SpotOn and WSPaper spread factors. The resulting VMD and NMD were very different.

    Therefore, each brand of water sensitive paper was analyzed using its brand-specific spread factor (according to DropScope), to produce the following graph.

    Three brands of WSP processed by DropScope using their specific spread factors. VMD differed by as much as 30%.

    SY produced a VMD higher than that of WS, and both were higher than SO. There was less variability in the NMD, but this was expected given the high droplet count on the finer side of a hydraulic nozzle’s droplet size spectrum.

    Conclusion

    Water sensitive paper has immeasurable value in agricultural spraying. It is far more important to encourage its use than to quibble over brands. However, when these tools are used for more rigorous evaluations of spray coverage, brand-specific variability must be addressed.

    The differences in how each brand responds to moisture (i.e. discolouration and deformation) may factor into which brand is most appropriate for a given situation. Further, there appear to be significant differences in how each brand resolves coverage. Once again, this may be irrelevant for those spray operators who occasionally use WSP to inform their spraying practices, but for consultants and researchers it is suggested that they use a single brand for an experiment, with papers produced in the same batch run.

    Syngenta, Spraying Systems Co., SprayX, WSPaper and Innoquest are gratefully acknowledged for their contribution of materials and time informing this article.

    2026 Update

    If there’s one thing that stays the same, it’s that nothing stays the same. Formulations and manufacturing processes change. According to SprayX, manufacturers of the DropScope, all three of the papers described in this article (written in 2021) have changed in recent years. Some have improved and others can create potential errors in digitizing coverage. The following points may require a deeper understanding of how WSP is digitized and analyzed. Refer to this series of three articles.

    Be aware of the following best practices when using WSP:

    • Be aware of package expiration dates. Expired paper will work differently from new paper, creating an artifact in analysis.
    • Papers with bright, reflective surfaces can cause an underestimation of deposit counts (specifically the smallest deposits).
    • Best results are obtained when using water for testing. Adjuvants and pesticide co-formulants have minor impacts on spread, but can also change the how the paper changes colour, making thresholding difficult.
    • Beware papers that create stains with bright borders and faint (hollow) centres (see image below). This can lead to an underestimation of volume median diameter. If your camera or scanner permits, examine the coverage in binary (e.g. black and white) for more accurate results.
    • Do not sample the edge of the WSP (leave at least a mm) to avoid edge effects such as wicking and partial impacts. Some scanners have a setting, or you can select the area manually.
    • Note the physical shape of the paper itself. Inconsistencies in the length and width (cutting errors) can make papers difficult to use in certain scanners, and curled papers cause changes in perspective and focal distance that can lead to errors.
    • When not using a sealed camera or scanner (e.g. DropScope or flatbed), changes in the camera angle, shadows, lighting conditions, and make/model of cellphone camera will affect the results. Be consistent.
    Stains with faint centers may not register correctly with some software. This could be due to adjuvants in the liquid, or issues with the coating itself. Other issues might include inconsistent coatings that are either too thick or to thin affecting the reaction to water.
  • Wind and Flight Speed Shape Drone Spray Coverage: Lessons from 3D Deposition Mapping in Wheat

    Wind and Flight Speed Shape Drone Spray Coverage: Lessons from 3D Deposition Mapping in Wheat

    In this study, 3D sampling of drone spray applications in wheat demonstrates that coverage is strongly influenced by the interaction between drone downwash, flight speed, and wind conditions. These factors collectively determine where droplets land, how evenly they are distributed, and how reliable coverage is from pass to pass. In 2025 we characterized wheat head coverage from a DJI Agras T50. In this study, we explore the larger, faster DJI Agras T100, and relate the observations to what we’ve seen in previous studies.

    Materials and Methods

    Site and crop

    The experiment was conducted at 45939 John Wise Line, St. Thomas, Ontario (42°43’57.0″N, 81°05’49.8″W) on June 3, 2025. Wheat was seeded at 1.8 million seeds/ac on 19 cm spacing and was at the T3 stage (~0.7 m height) at application.

    Design

    Twenty-one poles spaced at 1 m intervals held 3D-printed mounts with 1×3″ water-sensitive papers oriented in four directions relative to the drone flight path: advance, retreat, left, and right. A tramline behind the array preserved canopy structure while allowing access to the samplers (Figure 1).

    Figure 1 – Volunteers retrieving and replacing samplers between passes.

    Drone Operational Settings

    The primary objective of the study was to explore the effect of flight speed on coverage. Speed was increased from 6, to 10, to 14 m/s with the following operational settings:

    • 4 LX07550SX (sprinkler) nozzles
    • 50 L/ha application volume
    • 350 µm droplet size
    • 4 m flight altitude
    • 7 m programmed swath width
    • Tank volume maintained at ~50 L

    The drone began spraying 50 m before and continued 20 m after the samplers, flown on full auto over pole 10 and 11 (the middle of the 21 poles). The spray liquid was municipal water with 0.5% v/v of MasterLock (Winfield United).

    The secondary objective was to compare coverage from the drone spraying 5 gpa (6 m/s) to a 10 gpa (7 m/s) condition.

    Weather

    Weather data was collected using a Kestrel 3550AG weather meter (Kestrel Instruments) in a vane mount positioned roughly 2 m below drone altitude. Data was logged as the drone passed the samplers (Table 1).

    Table 1 – Weather conditions for each spray pass.

    Flights were conducted under a prevailing tailwind (rather than the preferred headwind) due to field constraints. Wind conditions during application varied by treatment. The 6 m/s treatment experienced higher and more variable wind speeds (avg. 6.6 km/h, SD 3.7 km/h, 177°), predominantly from the north (tailwind). The 10 m/s treatment occurred under moderate and stable winds (avg. 4.8 km/h, SD 1.1 km/h, 136°) with a slight right-to-left crosswind component. The 14 m/s treatment experienced low and variable wind speeds (avg. 1.6 km/h, SD 2.0 km/h, 198°) including periods of calm .

    Results

    Deposition Magnitude and Orientation

    Papers were analyzed using a DropScope™ (SprayX, São Carlos, Brazil). Deposition differed strongly by collector orientation (Table 2). Some repetitions were removed if wind pushed spray beyond the collectors. This left a minimum 2 repetitions per condition.

    SpeedDirectionMean (deposits/cm2)Std DevMinMax
    6 m/sAdvance45.7067.031.3210.7
     Left40.0666.190.0211.8
     Retreat20.1020.250.071.0
     Right45.4773.550.0208.9
    10 m/sAdvance52.0763.050.1189.3
     Left31.9543.650.0136.0
     Retreat5.129.190.037.6
     Right37.2270.180.0202.1
    14 m/sAdvance39.0237.510.5115.3
     Left26.8943.910.0130.9
     Retreat0.431.270.05.7
     Right11.0322.530.071.2
    Table 2 – Average deposition by sampler orientation for each speed.

    Forward-facing collectors (advance) consistently recorded the highest deposition across all speeds, followed by lateral orientations. Reverse-facing collectors (retreat) recorded substantially lower deposition. Variability was high for advance and lateral orientations, whereas retreat collectors showed consistently low variability (Table 3).

    DirectionMean (deposits/cm2)Std DevMinMax
    Advance39.0237.510.5115.3
    Left26.8943.910.0130.9
    Retreat0.431.270.05.7
    Right11.0322.530.071.2
    Table 3 – Average deposition by sampler orientation for all passes.

    Directional Bias (Anisotropy)

    Anisotropy refers to the property of having different values when measured in different directions. We can quantify this by dividing the average coverage on one plane by the opposite plane; The resulting indices show the relative direction of deposition.

    For the lateral plane (left-to-right), we divide the average coverage on the left-facing orientation by the right. On the sagittal plane (advance-to-retreat), we divide the average coverage on the advance-facing orientation by the retreat (Table 4).

    SpeedLateral (L÷R)Sagittal (A÷R)
    6 m/s0.88 (slight right-dominant)2.27 (moderate advance-dominant)
    10 m/s0.86 (slight right-dominant)10.17 (strong advance-dominant)
    14 m/s2.44 (strong left-dominant)90.05 (almost entirely advance-dominant)
    Table 4 – Relative coverage indices for lateral and sagittal planes.

    Bias in the lateral index was relatively weak, with a subtle shift with the wind (wind-facing is left) at higher speeds. The sagittal index (advance-to-retreat) increased from a 2x between 6 m/s and 10 m/s to 5x between 10 m/s and 14 m/s, demonstrating strong forward bias with flight and wind direction despite the down-and-back vector created by the downwash.

    Spatial Distribution

    Peak deposition consistently occurred 1 to 5 m downwind of the flight line, rather than directly beneath it. A cross-tail wind shifted deposition laterally, while forward motion (inertia) and wind reinforced deposition in the advance direction. This can be illustrated by isolating the average coverage for each orientation, for all three speeds (Figures 2 to 5).

    Figure 2- Advance Orientation (Facing tailwind). Bars = SE
    Figure 3 – Retreat Orientation (facing away from tailwind). Bars = SE
    Figure 4 – Right Orientation (Facing cross wind). Bars = SE
    Figure 5 – Left Orientation (facing away from cross wind). Bars = SE

    By combining and plotting average coverage on all orientations in a top-down heatmap, we can clearly see the lateral shift to the left of the flight pass (with the light crosswind), the higher relative coverage on the advance face, and indications of bi-modal coverage that likely corresponds to the position of the rotary atomizers(Figure 6).

    Figure 6 – Coverage heatmap created by smoothing the average deposition data for each speed (σ ≈ 1.1 – 1.2 m) over a 300 x 300 grid to illustrate deposition gradients. The colour scale supports a direct comparison of deposition intensity. The 21 samplers are indicated by black dots spaced at 1 m intervals, and the drone flight path appears as a black arrow between posts 10 and 11. Average wind speed and direction appears as an inset white arrow (vector).

    Effect of flight speed on swath width

    Swath width was determined by averaging all deposition on each post for each speed and using our online swath width calculator. The range of flight speeds used in this study did not significantly affect swath width.

    • 6 m/s: 8 m swath width (16.3 % C.V.).
    • 10 m/s: 7.5 m swath width (22.5 % C.V.)
    • 14 m/s: 7.5 m swath width (22.3 % C.V.)

    These widths are 15-20% wider than the widths calculated in the same manner during the 2025 study with the T50.

    Averaging swath widths can mask variability

    This method of calculating and comparing average swath widths is convenient, but it hides any variability in the amount of spray deposited within the swath. Consider that an 8 m swath with 10 deposits/cm2 every meter would have the same C.V. as an 8 m swath with 100 deposits/cm2. Deposit variability can be illustrated by plotting the average coverage along the swath with standard error (figure 7). We see that flight speed significantly influenced the degree of deposition, where higher speeds reduced the average droplet density (counts) as well as the variability (standard deviation).

    Figure 7 – Average coverage, all orientations, for each speed. Bars = SE

    Think of each repetition as a randomly-selected cross section of the swath from somewhere along a spray pass. Calculating swath width from averaged coverage data can hide shifts in the relative position along the flight path, making the composite value greater than that of any single replicate. This variability and the potential for inadvertent smoothing can be exposed by plotting each repetition. (Figure 8).

    Figure 7 – Average coverage (all orientations) from each pole plotted by speed and repetition.

    Therefore, the order of operations matters. When swath width is calculated for each repetition, and then averaged, we would expect the widths to be somewhat smaller. They are presented here in table form next to the previous values for comparison (Table 5).

    Speed (m/s)(A) Deposition averaged, then swath calculated (m)(B) Swaths calculated, then average (m)Difference (A-B) (m)
    68 (16.3% C.V.)6 (29.6% C.V.)-2
    107.5 (22.5% C.V.)6 (33.5% C.V.)-1.5
    157.5 (22.3% C.V.)7.5 (30.5% C.V.)0
    Table 5. Average swath widths generated by two methods.

    Statistical Analysis

    No matter the method, we can draw conclusions from the swath widths calculated here.

    • 6 m/s: highest deposition but greatest variability.
    • 10 m/s: best balance of deposition, uniformity, and swath width.
    • 14 m/s: lowest deposition and most directional bias.

    A two-way analysis of variance (ANOVA) was conducted to evaluate the effects of flight speed and collector orientation on spray deposition. Deposition differed significantly between Advance, Left, Right, and Retreat collectors (F = 6.1, p = 0.0005). Flight speed had a statistically significant effect on deposition, where deposition was reduced with speed (F = 3.03, p = 0.05). The effect of orientation did not significantly depend on speed (F = 0.46, p = 0.83), suggesting that the pattern of deposition was consistent across speeds.

    Effect of volume on deposition

    In a secondary investigation, the drone was flown at 7 m/s, applying 10 gpa to compare coverage to the 6 m/s, 5 gpa condition (Figure 8).

    Figure 8 – Average coverage as deposit counts, all orientations, for 5 gpa and 10 gpa. n=2 for each condition . Bars = SE

    Surprisingly, there was no significant increase in total deposition within the swath when volumes were increased. In fact, the 5 gpa condition is ~8% higher when all deposits are summed or when area under the curve is calculated. The relative shape of the curve was notably different with 5 gpa producing a sharper, higher-intensity central peak, while 10 gpa produced a broader and more uniform deposition profile.

    It was expected that higher volumes would result in higher counts. One theory for the absence of this result was that overlapping depositions in the high volume treatment might have underestimated counts when the papers were digitized. Therefore, the percent surface area was also analyzed (Figure 9). Once again, there was no significant difference in the total percent area or a comparison of area under the curves.

    Figure 9 – Average coverage as area covered, all orientations, for 5 gpa and 10 gpa. n=2 for each condition . Bars = SE

    When swath widths were calculated for each repetition, then averaged for each speed, we arrived at (5 m + 7 m) ÷ 2 = 6 m for the 5 gpa condition, and (5.5 m + 6.5 m) ÷ 2 = 6 m for the 10 gpa condition. We have no explanation for why there was no volume-related difference.

    Discussion

    Wind direction strongly influenced deposition, overriding the down-and-back pattern seen in previous studies. A tail-cross wind likely drove deposition (likely occurring after the drone passed the sampling location), explaining why retreat-facing collectors captured minimal deposition, and peak deposition was accordingly displaced from the flight line.

    Overall, results confirm that wind conditions fundamentally reshape spray distribution. The implication is that wind direction must be accounted for alongside swath width when developing flight path spacing to minimize the potential for overlaps and gaps between passes.

    Further, previous studies have demonstrated a direct and positive relationship between flight speed and swath width up to 8-10 m/s with no further response after ~8 m/s. This study supports the hypothesis that rotary-wing drone speed and swath width share an asymptotic relationship that inflects at ~8-10 m/s (variability makes it difficult to determine an exact value). Flight speed also has a direct and inverse impact on the degree of spray deposition and deposit variability within the swath.

    Finally, caution is advised when interpreting average swath widths. There may be no indication of the degree of coverage within the swath (affecting efficacy), or the lateral variability along the flight path (affecting fieldwide uniformity).

    Related video

    Thanks to Adam Pfeffer and Bayer Canada for in kind and financial support, and thanks to volunteers Erin Jewson (OMAFA Engineer), Halle Barton and Nikki Intranuovo (Bayer Summer Students) for their help with the field work.

    Author’s Note: These results were adjusted in July to exclude outliers and include the results of the spray volume comparison.

  • Airblast Nozzles – Distributing Flow

    Airblast Nozzles – Distributing Flow

    There’s a certain deer-in-headlights expression that creeps onto a sprayer operator’s face when we discuss nozzle selection. We sympathize with our field sprayer clients given the variety of brands, styles, flow rates and spray qualities they must choose from. And PWM has made the process even more complex. However, airblast operators face an additional challenge; Unlike horizontal booms, vertical booms often distribute the flow unevenly to reflect relative differences in the distance-to-target and the density of the corresponding portion of target canopy. We discuss the broader, iterative process of nozzling an airblast boom here, but in this article we focus on the topic of flow distribution.

    An overwhelmed operator trying to nozzle a boom.

    The question of “which rate goes where” is still debated. It’s led to diagnostic devices called Vertical Patternators which show the profile of the spray. Operators can use these to visualize their distribution… but they are few and far between. For the rest of us, deciding on the best distribution begins with understanding how the practice evolved.

    The AAMS vertical patternator. The mast moves back and forth across the swath of a parked sprayer. Each black collector intercepts the spray at different heights. The fractions collect in the tubes at the bottom to show relative volume.
    A blurry shot of an OMAFA-built vertical patternator. The sprayer parks in front of the screens, which intercept spray. It’s collected in troughs and runs into columns that show relative volume.

    1950s

    In the 1950s, the mantra was to blow as much as you could, as hard as you could, and hope something stuck. At the time, John Bean promoted a method called “The 70% Rule” whereby operators used full-cone, high volume disc-core nozzles to emit the vast majority of the spray from the top boom positions. John Bean provided a slide-rule calculator to help operators configure booms to align the top nozzles with the deepest, densest portion of the 20-25 foot standard trees they were trying to protect. Back then, most airblast sprayers were engine-driven low-profile radial monsters capable of blowing to the tops of those trees. The practice persisted into the 60s and was encouraged by Cornell University (Brann, J.L. Jr. 1965. Factors affecting the thoroughness of spray application. N.Y. State. Arg. Exp. Sta. J. paper no. 1429).

    The profile of the spray would have looked something like the following graph:

    1970s

    In the 70s, extension specialists began advising operators to tailor the distribution to match the orchard spacing, tree architecture, canopy density and weather conditions. we reached deep into our archives for the Ontario Ministry of Agriculture and Food’s 1976 publication entitled “Orchard Sprayers” to see what we used to tell airblast operators.

    The 1976 update of Ontario’s 1971 “Orchard Sprayers” guide. A trove of hard-earned knowledge that still has relevance today. I love that the Minister’s name, and not the author’s, is on the cover. Let’s set the record straight: R. W. Fisher, D. R. Menzies and A. Hikichi, based in Vineland and Simcoe, Ontario.

    Here’s a synopsis of what was advised:

    1. Choose a tree size and shape that is typical of your orchard and park the sprayer at the normal spraying distance from it.
    2. Find one or two middle nozzle position(s) and air deflector or vane settings that direct the spray up through the top-inside of the tree. This is called the “middle volume zone”.
    3. Find rates that will give a large output in this middle volume zone, and smaller outputs for positions above and below.
    4. The total output must still add up to the target volume.

    It seemed operators were getting away from high rates in the top positions and instead shifting the distribution to match the canopy shape and density. If we were to follow these recommendations, the spray profile would look something like this:

    Later, Agriculture Canada’s 1977 publication entitled “Air-Blast Orchard Sprayers – A Operation and Maintenance Manual” had similar advice. Here we find the “2/3 boom rule” as the authors state: “To ensure good distribution through the trees, about two-thirds of the spray should be emitted from the upper half of the manifold.”

    1980s

    Operators followed this approach well into the 80s, as they endeavored to aim the majority of the spray into the densest part of the canopy. Many can relate to the following illustration that divides the boom, which I modified from an array of period factsheets. The fractions represent the portion of the available boom. The percentages indicate the relative volume. Of course, it matters how large and how far away the target is for either the 2/3-boom or 70% rule to make sense (the middle volume zone is shown receiving 65-70% in the silhouette).

    1990s-2000s

    The 2/3 or 70% rules still work for standard nut and citrus trees, and perhaps for large cherry trees, but pome and tender fruit orchard architecture is densifying at this point in time. In the 90s and 00s we started transitioning from semi-dwarf into trellised, high density orchards.

    Leaping to 2005, Ohio’s Dr. Heping Zhu et al., found that a high density orchard is effectively sprayed by the same rate in each nozzle position. They wrote: “[Historical] recommendations are to use a larger nozzle at the top of each side, with the capacity of the top nozzle at least three times greater than other individual nozzles. However, results in this study with three different spray techniques showed that spray deposit was uniform across the tree canopy from top to bottom with the equal capacity nozzles on the air blast sprayer.”

    What a pleasant surprise to simplify our lives! If we can use an even distribution for dense, nearby trees, it follows that any vertical crop with the same width and density located close to the sprayer (e.g. cane fruit, trellised vines, etc.) would benefit from even distribution:

    Today (2020s)

    So, how do we do it today? There is still no simple answer; Conditions change, not all sprayers are the same, and not all applications have the same target. Let’s build on what history has taught us and establish a process to achieve better coverage uniformity and reduce waste.

    No matter the crop, the operator must first adjust air settings. Air volume and direction play the most critical role in transporting a droplet to (and into) a target canopy. Too high an air speed will cause spray to blow through the target, rather than allowing it to deposit within. Aim the air just over, and just under, the average canopy. Ensure there’s enough air to overcome ambient wind and to push the spray just past the middle of the target canopy.

    It should be noted that we assume the operator is spraying every row. With certain exceptions, alternate row middle spraying is not generally recommended. Not only can it compromise coverage on the far side of the target, it makes it far harder to match the nozzling on a single-row sprayer and is a sure-fire way to increase drift.

    Next, determine which nozzles are not needed (e.g. spraying the ground or excessively higher than the top of the canopy). Remember: hollow cones overlap very close to the boom and spread as much as 80°. Airblast sprayers rarely if ever need the lowest positions and unless spraying overhead trellises they may not need the highest either. Turning off the highest, and most drift-prone, nozzle positions in high density orchards is illustrated in the logo I was asked to create for Washington’s short-lived Pound the Plume awareness campaign in 2017.

    Then, finally, we decide on distribution. If the crop is nearby and relatively narrow, you can try even distribution. If you elect to distribute the spray unevenly to better match the variable-width target, or compensate for distance, aim half the overall output at the densest part of the canopy (the middle volume zone). Consider how the following factors might influence your choices:

    1. High humidity means more spray will reach the target, and vice versa. This is because all droplets are prone to evaporation. We have heard it said in hot, dry conditions (described by Delta T), a droplet can lose ½ its diameter every 10 feet. As they evaporate they get lighter, meaning they are less subject to their original vector and the pull of gravity, and more subject to deflection by wind. The use or coarser droplets, and/or humectants, can help, but higher volumes can help too – they increase the odds of some droplets hitting the target and actually humidify the air to slow evaporation.
    2. Windspeed increases with elevation, so spray is most likely to deflect at the top of canopies where they have already lost size (and momentum and direction). Early in the season when there is little if any foliage, wind speeds are higher overall. This is why we advise adjusting air settings using a ribbon test before considering boom distribution – you need enough air volume, aimed correctly, to get the spray to the top.
    3. The denser and deeper a canopy, the more spray is filtered and unavailable for coverage. This is why you will always achieve more coverage on the adjacent, outer portion of a canopy versus the interior. In semi dwarf apple orchards we have seen the coverage drop by half for every meter of canopy. Finer spray can penetrate more deeply because there are more droplets and they move erratically, whereas coarser droplets move in straight lines and impact on the first thing they encounter. Higher volumes will improve penetration and overall coverage, but there is a diminishing return and runoff will occur more quickly leading to more waste.
    4. Further to the last point, remember that it’s the air that propels the spray, not the pressure. Higher liquid pressure can propel coarser droplets further, but has little effect on finer droplets. imagine throwing a golf ball and a ping pong ball into a light headwind and envision how they fly. Plus, the higher the pressure, the finer the mean droplet diameter.

    Confirm Your Work

    To know how all these factors play out, you must use water sensitive paper (or some other form of coverage indicator) to diagnose the results. Remember, the goal is uniform coverage and for most foliar products, we want to achieve a minimum coverage threshold of 10-15% and a droplet density of 85 deposits per cm2 on at least 80% of the targets.

    Taking the time to match your output to the target has the potential to greatly improve coverage and reduce waste. Nozzle body flips and quick-change nozzle caps make the process of switching nozzles between blocks fast and easy. It’s worth it.

    Grateful thanks to Mark Ledebuhr, Gail Amos and Heping Zhu who edited, corrected and contributed to this article.

  • How Higher Speeds Affect Drone Swath Width

    How Higher Speeds Affect Drone Swath Width

    Speed Study

    Swath width is a fundamental parameter in spray drone mission planning. It facilitates the uniform application of broadacre pesticides at the target rate. Pilots adjust the swath width via operational settings such as droplet size, flight speed and altitude to produce the most effective and efficient application.

    Rapid advances in drone design, however, may warrant a re-evaluation of how operational settings affect swath width. For example, the most recent generation of drones are now capable of speeds up to 20 m/s (72 km/h), which is twice that of the previous generation.

    In late 2025 we conducted a series of comparative herbicide applications using the DJI Agras T50 and T100. For both drones, swath width increased with speed up to ~10 m/s, as expected. However, between ~10 m/s and 18.5 m/s, swath width from the T100 did not seem to increase further. Similar observations have been reported by researchers at AgroEfetiva (São Paulo, Brazil; personal communication).

    These results suggest that the relationship between speed and swath width is positive and direct at lower speeds, but reaches a saturation point beyond which any further increase in speed no longer affects swath width. This is an asymptotic relationship. To test this hypothesis, we conducted a deposition study where swath width was measured at flight speeds that increased incrementally from 8 m/s to 20 m/s.

    Configuration Study

    The standard T100 configuration uses two rotary atomizers (“sprinkler” nozzles; LX07550SX) with a reported maximum combined flow rate of 30 L/min. The alternate orchard configuration incorporates a boom that supports two additional “mister” nozzles (LX09550SX), increasing the reported maximum flow rate to 40 L/min.

    To improve productivity in broadacre applications, some operators have adopted a hybrid configuration. In this setup, the orchard boom is retained, but the reputedly drift-prone mister nozzles are replaced with a second set of sprinklers. This approach is intended to achieve a higher flow rate than the standard two nozzle configuration while maintaining a larger mean droplet size.

    A secondary objective of this study was to compare the Hybrid configuration with the Orchard configuration (Figure 1).

    Figure 1 – Left: DJI Sprinkler Nozzle (LX07550SX). Four such nozzles comprised the “Hybrid” configuration. Right: DJI Mister nozzle (LX09550SX). Four such nozzles comprised the “Orchard” configuration.

    Materials and Methods

    Location and Layout

    The study was conducted at Ontario’s Simcoe Research Station on May 12, 2026. The site (42.857414, -80.271759) was a flat, recently tilled sand/loam field with no vegetation present. A DJI Agris T100 drone was used to perform the spray applications, supported by the D-RTK 3 relay station and flown on full auto.

    The spray mix was 0.2% v/v Super Signal Blue (Precision Laboratories) and 0.125% v/v Activate Plus NIS (Winfield United) in municipal water, pre-mixed to ensure consistency. A volume of 40 L – 60 L was maintained throughout the trial to minimize the effect of a changing payload.

    The sampler was a flat, horizontal, continuous bond paper strip measuring 7.5 cm wide and 30 m long (secured in Speed Tracks™, Application Insight LLC). The sampler was oriented perpendicular to the prevailing wind, with the intention of flying the drone with a headwind across the 15 m mark (the centre) (Figure 2). Test passes determined that the T100 required 210 m to reach 20 m/s while half-full.

    Figure 2 – T100 spraying indicator dye across the 30 m continuous sampler.

    Before the swathing runs began, the prevailing wind shifted direction slightly.  It was decided to fly the drone 5 m upwind (at the 20 m mark along the 30 m sampler) to ensure any downwind displacement was captured on the sampler (Figure 3).

    Figure 3 – Trial layout and prevailing wind conditions.

    Drone Settings and Swathing Order

    The primary objective of the study was to explore the effect of flight speed on swath width. Speed was increased from 8 m/s to the maximum 20 m/s by 2 m/s increments. Trial and error with the controller indicated that we could achieve these speeds by balancing an application volume of 30 L/ha and a programmed swath width of 7 m.

    Altitude was set to 4 m which is lower than the 5 m minimum recommended by DJI for high-speed flight. This was a compromise above the preferred 3.5 m altitude we have historically used with the T50. It was felt that higher altitudes would create unacceptable potential for swath displacement.

    Rotary atomizer design is not standardized, and as a result, the droplet size selected on the controller did not necessarily produce the desired results. The Hybrid configuration was programmed to emit 350 µm droplets, selected as a compromise between drift mitigation and coverage potential. To offset the Mister nozzles’ reputation for producing a finer spray, the Orchard configuration was set to the maximum 500 µm. Operations settings are noted in Table 1.

    ConfigurationNozzleDroplet size (µm)Speed (m/s)Altitude (m)Programmed Swath Width (m)Application Volume (L/ha)
    Hybrid4 Sprinklers3508, 10, 12, 14, 16, 18, 204730
    Orchard2 Misters, 2 Sprinklers5008, 10, 12, 14, 16, 18, 204730
    Table 1 – Operational settings for trials.

    Three repetitions of seven speeds were flown for each configuration. Anticipating an increase in temperature and wind speed throughout the day, it was decided move through all seven speeds (a single repetition) before resetting and doing so two more times. The intent was to preclude confounding weather effects. Ideally, we should have alternated between configurations as well, but this proved impractical. As a result, we flew the Hybrid configuration first and the Orchard configuration last.

    Weather

    Weather data was collected using a Kestrel 3550AG weather meter (Kestrel Instruments) in a vane mount positioned 2.5 m above ground. Temperature and relative humidity were comparable throughout the ~3 hours of data collection, but as anticipated, wind speed was higher for the later Orchard configuration passes.

    As previously indicated, wind direction shifted from an ideal headwind situation just before trials began, and was somewhat changeable, but the average wind direction for the two configurations was comparable (Figure 4 and Table 2).

    Figure 4 – Weather conditions recorded at roughly 10-minute intervals, corresponding to the drone passing over the sampler.
    TimeConfiguration FlownAverage Temperature (°C)Average Relative Humidity (%)Average Wind Speed (km/h ± SD)Average Direction (° ± SD)
    11:55 am – 1:16 pmHybrid11.759.98.4 ± 3.5323 ± 46
    1:43 pm – 2:52 pmOrchard12.951.611.9 ± 2.5316 ± 48
    Table 2 – Average weather conditions for the Hybrid configuration passes and for the Orchard configuration passes.

    Collector analysis

    Bond paper digitization

    Bond papers were scanned using a Swath Gobbler™ (Application Insight LLC). The software measured deposition as both percent area covered (% area) and deposit density (deposits/cm2) every 100 mm, with a thresholded Hue of 23-280, a Saturation of 5-120 and a Value of 156-255.

    Effective swath width calculation

    The large data set produced by each pass was reduced in size by averaging the deposition for every 50 cm. This data was entered into our Excel-based swath width calculator, which assumes a racetrack pattern and sums deposits from adjacent swaths. The resulting swath width for each pass was the maximum width that minimized over- and under-dosing as well as the coefficient of variation (CV).

    Analysis

    The average swath width derived from deposit density data was wider than that derived from percent area covered (Table 3).

    Table 3 – Group means and standard deviation for average swath widths derived from deposit density data and percent coverage data. The average CV was between 29 and 32%.

    A two-way ANOVA (Analysis of Variance; α = 0.05) was performed to determine any significant effect of speed or configuration on swath width (Table 4). Flight speed had no significant effect on swath width, no matter how it was derived (% area covered or deposit density), for either configuration (Hybrid or Orchard). However, the average swath width derived from deposit density was significantly wider for the Orchard configuration compared to the Hybrid and presented higher variability.

    Table 4 – Results of two-way ANOVA, exploring interactions between speed, swath width and configuration (95% confidence interval).

    Orchard configuration was prone to displacement in a side wind. Shifting the flight path 5 m upwind improved the downwind capture, but for some flights it did trim a small portion of the upwind deposition. Deposit density gives greater resolution and exposes more variability than percent area covered. Figure 5 shows the average deposition by speed based on deposit density. Figure 6 shows the average deposition by speed based on percent area covered.

    Figure 5 – Average deposition by speed based on deposit density. Arrow indicates flight path.
    Figure 6 – Average deposition by speed based on percent area covered. Arrow indicates flight path.

    Figure 7 shows the average deposition by configuration based on deposit density. Figure 8 shows the average deposition by configuration, based on percent area covered. Based on deposit density, there were 55% more deposits on the downwind side of the sampler for Orchard configuration set to set to 500 microns compared to the Modified configuration set to 350 microns.

    Figure 6 – Average deposition by configuration based on deposit density. Arrow indicates flight path.
    Figure 8 – Average deposition by configuration based on percent area covered. Arrow indicates flight path.

    The average swath widths calculated from deposit density (Figure 9) and percent area covered (Figure 10) are shown with standard deviation. While it appears the swath width is less around 14 m/s, it is statistically insignificant and the response to speed is essentially flat. As with prior studies, swath widths calculated from deposit density are larger than those calculated from percent area covered.

    Figure 9 – Average swath widths for each speed, derived from deposit density data. SD shown. n=3 for each speed, while n=2 for Hybrid configuration at 12 m/s and 14 m/s.
    Figure 10 – Average swath widths for each speed, derived from percent coverage data. SD shown. n=3 for each speed, while n=2 for Hybrid configuration at 12 m/s and 14 m/s.

    Observations

    Previous studies demonstrated a direct and positive relationship between drone speed and swath width up to 8-10 m/s. Here, we see no further response after ~8 m/s. This supports the hypothesis that rotary-wing drone speed and swath width share an asymptotic relationship that inflects at ~8-10 m/s. Variability makes it difficult to determine an exact value.

    Despite increasing the programmed droplet size to the maximum 500 microns for the Orchard condition, there was 55% more downwind deposition compared to the Hybrid condition, which was set to 350 microns. This supports the claim that the Mister nozzle produces a span of droplet sizes that include far more fines than the Sprinkler nozzle, and underpins the need for a better understanding of the spray quality produced by rotary atomizers.

    Spraying at high speeds is not an advisable practice. While swath width is no longer affected after ~8 m/s, there are other considerations. Note that it required 200 m for the drone to reach the highest speed, and in a related study we have seen swath width taper during initial acceleration and final deceleration, leaving gaps in coverage.

    Further, the minimum 5 m altitude advised by DJI ensures a safe margin for the drone to respond to obstacles and topography during high speed flight, but is not conducive to spraying. The author is aware of a situation where flying the T100 at 4 m altitude and 18 m/s over a canola field with rolling hills caused it to perform an emergency landing.

    An ideal speed is one that maintains the most consistent swath width at a reasonable altitude.

    Thanks to Drone Spray Canada and Bayer Canada for in kind and financial support, and thanks to Cesar Cappa, OMAFA horticulture weed specialist for his participation in the study.