Tag: wheat

  • 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, and it’s clear that the Defy 3D produced smaller droplets than the 3D Ninety, and that there 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 a 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 % area covered were strongly positively associated (0.75 correlation), suggesting higher deposit counts generally corresponded with higher percent coverage, but not entirely, giving some wiggle room for interpretation.

    The Defy 3D produced the highest coverage overall, but mainly as higher droplet counts, especially on the wind-facing Retreat side. This only indicates better delivery of finer droplets with the wind, and not necessarily the nozzle design. In the case of higher booms or higher wind speeds, we would expect coverage to skew to any prevalent downwind surface and for drift to increase.

    The 3D Ninety and the hybrid condition are difficult to separate based on this data. In either case, finer droplets would still deposit with the wind, but in the case of the 3D Ninety we would expect the coarser spray quality to resist deflection, assuming the boom was low enough to maintain the droplet direction.

    The hybrid condition was developed to place finer droplets at the fore, taking advantage of the sprayer’s momentum to lend some inertia to those smaller droplets. Likewise, the coarser droplets (and higher rate to compensate for fewer droplets) of the rear-facing nozzle was expected to counter the sprayer’s momentum and provide sufficient retreat coverage. It could be argued there was better balance between the Advance and Retreat faces in the hybrid condition, but how significantly, and whether this would lead to better efficacy is uncertain.

    However, it should be remembered that the 3D Ninety and the hybrid treatments took place at 25.7 km/h (16 mph) which is almost 20% faster than that of the Defy 3D. This represents potential for greater productivity without excessive drift. Therefore, given the arguably more-balanced deposition, the combination of a fore Defy 3D and a rear 3D Ninety might be more resilient to changes in boom height and wind speed while providing sufficient coverage at higher travel speeds.

    It would be worth running efficacy trials to see how this combination performs.

    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 for Cesar Cappa, OMAFA weed specialist in horticulture for patiently explaining how to use R more effectively.

  • 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.

  • Characterizing RPAS Coverage at Four Cardinal Points on a Vertical Plane: Practical implications for spraying wheat at T3

    Characterizing RPAS Coverage at Four Cardinal Points on a Vertical Plane: Practical implications for spraying wheat at T3

    Global research into Remotely Piloted Aerial Systems (RPAS) is producing pesticide residue, drift and efficacy data that is helping to inform federal regulatory policy. It is reasonable to assume that Canada will ultimately sanction the use of RPAS for agricultural spraying. The first registered products will likely be fungicides intended for broad acre crops such as soybean, corn, and wheat.

    Those considering RPAS for agricultural spraying have expressed interest ranging from general curiosity to high demand. Successful adoption will be contingent on expectation management, which in turn requires education on the functional differences between RPAS and conventional application technologies.

    Quadrotor RPAS design dominates the current commercial landscape, with typical models featuring four rotary atomizers and 40 L tanks. There have been improvements in recent years, but these designs continue to suffer from a low rate of productivity (by North American standards for broad acre crops). This is due, in part, to low volumetric capacity and limitations with rotary atomizer design, which result in a debatably short effective swath width. Broadly, “swath width” refers to the minimal span consistently sprayed by a single pass, while “effective” indicates a spray coverage (i.e. deposition pattern and threshold dose) sufficient to achieve the desired result.

    Our research efforts have focused on identifying and evaluating variables that influence effective swath width. These include operational settings such as altitude, travel speed, volume applied and nozzle settings. They also include environmental factors such as meteorological conditions, crop morphology, and planting architecture. Establishing a combination of settings that account for these factors will inform operator practices and optimize the balance between RPAS effectiveness and efficiency.

    Study Objective

    Fusarium head blight is a significant economic threat in wheat. Fungicide application takes place at the T3 stage of development, with the intention of providing panoramic coverage of the wheat head. RPAS is being considered to apply these fungicides.

    The pursuit of productivity tempts operators to push operational settings to the point that spray coverage is compromised. This study will use operational settings based on the results of previous work and assign flight speed as the independent variable.

    Coverage will be assessed using water sensitive paper (WSP) positioned at the top of the canopy and oriented vertically in four cardinal directions to emulate the circumference of the wheat head. Isolating the resultant coverage in each cardinal direction may provide insight into droplet behaviour within the RPAS spray cloud and perhaps better assess effective swath width.

    Coverage from a conventional field sprayer will also be characterized. This represents the current standard and it will provide a basis for comparison.

    Materials and Methods

    Site

    The experiment was conducted at 45939 John Wise Line, St Thomas, Ontario (42.7320746, -81.0879887) on June 1, 2025. Common seed wheat was planted on October 6th, 2024, at 1.8 million seeds/ac on a 19 cm (7.5 in) row spacing. At the time of spraying, wheat was at the T3 stage of development, approximately 0.7 m (2.5 ft) high.

    Holder Design

    3D-printed holders were designed in Autodesk Fusion. They feature tabs that create a pressure fit (for quick WSP loading and unloading) and a back support (to prevent WSP movement in a downwash) to vertically position 1×3” WSP facing out on four cardinal points (figure 1). 21 poles were positioned on a 1 m spacing, leaving the tops coplanar with the wheat heads for in situ swathing. The square cross-section of the poles corresponded to a square depression in the WSP holder, ensuring the samplers were correctly aligned (figure 2). The gcode file to 3D print your own holders can be downloaded here. We used PLA filament with 3 walls and a 15% rectilinear infill to print 16 holders at a time on a Bambu P1S.

    Figure 1. 3D-printed WSP holder slotted onto a pole in the wheat field.
    Figure 2. Four WSP positioned vertically, facing four cardinal points, at wheat-head depth.

    Wind direction is indicated by the direction the wind is coming from, not the direction it’s blowing to. Therefore, a wind blowing in a northern direction is referred to as a southern wind. The WSP holders were aligned east to west, perpendicular to the prevailing southern wind. We established a trampled path ~0.75 m on the downwind side. This left the wheat canopy surrounding the samplers intact while still permitting access to the WSP holders (figure 3).

    Figure 3. 21 WSP holders on 1 m spacing with access ~0.75 away.

    WSP were given unique serial numbers to identify their position, and pre-loaded into the holders. 170 loaded holders were stored on raised grids inside four shallow plastic bins, arranged in the order they would be used (figure 4). This greatly expedited placement and retrieval, allowing for more repetitions to take place while optimal weather conditions held.

    Figure 4. WSP holders arranged in sequence in a storage bin. This allowed the pre-loading of serial numbered WSP prior to the day of the experiment.

    Application Method

    A DJI Agras T50 RPAS maintained and calibrated by the cooperator was fitted with four rotary atomizers. Previous work has demonstrated that higher rates of flow can have a detrimental effect on the spray quality from rotary atomizers, so distributing the flow over four nozzles was intended to prevent this. The atomizers applied a 250 µm spray over a 7 m swath width (corresponding with route spacing), as selected on the flight controller. Altitude was 3 m above the wheat heads, and flight speed was either 6 or 10 m/s (three repetitions each). Application volume was 50 L/ha, anticipating this to be a future label requirement.

    The RPAS flew a racetrack pattern over the samplers (figure 5). It flew with a prevailing tailwind between samplers 14 and 15, and then back with a prevailing headwind between samplers 7 and 8. We employed a DJI RTK-1 base station, which claims 1 cm horizontal accuracy.

    Figure 5. Racetrack flight path relative to WSP holders and prevailing wind direction.

    The RPAS was given sufficient distance (~40 m before and after the samplers) to reach the target speed, which was confirmed with a screenshot from the flight controller. The RPAS tank (capacity 40 L) contained municipal water with 0.125% v/v of NIS (Ag-Surf II). The level of liquid in the RPAS tank was maintained at 40 L throughout the trial to eliminate the effect of a changing payload.

    The field sprayer, maintained and calibrated by the cooperator, was a New Holland SP 275s. It extended the left boom over the samplers from position 1 through to 12 and made a single pass with a prevailing tailwind (three repetitions). It traveled at 4.5 m/s (16 km/h or 10 mph) spraying 187 L/ha (20 gpa) and rough terrain caused the boom height to fluctuate between ~25 cm and ~50 cm above the wheat heads. The nozzles were Greenleaf Technologies TADF 06 (greys) on a 50 cm spacing operated at 50 psi to produce a Coarse spray quality. The tank contained municipal water with 0.125% v/v of NIS (Ag-Surf II).

    Trial Procedure

    WSP holders were placed just prior to spraying while the RPAS or field sprayer was positioned ~40 m beyond the samplers. When wind conditions were deemed appropriate, a signal was given to initiate spraying. On pass completion, one minute elapsed before initiating collection to permit complete deposition of the spray and drying of the droplets.

    Weather Data

    Weather data was collected using a Kestrel 3550AG weather meter (Kestrel Instruments) in a vane mount positioned roughly 1 m below RPAS altitude. Data was logged as the RPAS or field sprayer boom passed the samplers (table 1). In the case of the RPAS, there was very little difference between the two passes per repetition, so values were averaged.

    TimeRep and TreatmentTemperature (°C)Wind Speed (km/h)Wind Direction
    10:21:511. RPAS 6 m/s16.43.1S
    10:33:562. RPAS 6 m/s17.76.2S x SW
    10:45:503. RPAS 6 m/s18.84.0S x SW
    10:55:401. RPAS 10 m/s18.62.1SW
    11:06:242. RPAS 10 m/s20.00.5S
    11:16:003. RPAS 10 m/s19.25.8S x SW
    11:29:541. Field Sprayer21.10.0S
    11:41:122. Field Sprayer19.91.7S x SW
    11:48:313. Field Sprayer20.23.9S
    Table 1. Time and weather conditions for each repetition. Data was captured as the nozzles passed over the holders. Wind direction is indicated by the direction it is coming from.

    Digitization

    WSP (Spot-On) were scanned using a DropScopeTM (SprayX). The software reported droplet density and percent area coverage, but only deposit density is considered in this report.

    Results

    Comprehensive Observations

    When the average deposit density from each of the four WSP per holder is added, we have a measure of total panoramic coverage. The mean total panoramic coverage from three repetitions of each treatment is shown in figure 6. For the RPAS treatments, distinct coverage peaks typical of RPAS applications correspond to the flight passes through poles 14-15 and 7-8. There is a slight spray displacement due to an occasional shift to a west wind (i.e. overall coverage shifted towards pole 1). However, the entire spray swath appears to have fallen within the range of the samplers. The back-and-forth flight pattern produced higher coverage at the interface between passes (pole 10) compared the extremes (beyond poles 19 and 3) suggesting some overlap. Deposit density was higher for the slower RPAS flight speed, and RPAS produced a higher deposit density than the field sprayer. Field sprayer coverage data is included for perspective but is generally not referred to unless it has some bearing on the evaluation of the RPAS coverage.

    Figure 6. Mean sum deposit in count/cm2 for each treatment. RPAS 6 m/s deposited an average 700 drops/cm2. RPAS 10 m/s deposited an average 400 drops/cm2. The field sprayer deposited an average 280 drops/cm2. r=3. S.E. bars shown. Arrows indicate RPAS flight path and direction.

    Swath Width

    If the coverage at pole 10 represents the edge of each swath, then a swath width of ~6.0 m can be estimated based on similar coverage at poles 16-17 and 3-4. This is less than the programed value of 7.0 m.

    This inference is supported when these averaged values were entered in an Excel-based model that calculates swath width. The model sums deposits from adjacent swaths assuming a racetrack pattern. Threshold coverage is subjective but adhering to the objective of establishing a balance between over- and under-dosing with the lowest possible C.V., we calculated swaths between 5.0 and 6.5 m (table 2).

    TreatmentPole PositionThreshold Coverage (count/cm2)Under-dose (%)Over-dose (%)C.V. (%)Swath (m)
    RPAS 6 m/s21-1012010.45.018.05.5
    RPAS 6 m/s10-11205.714.126.05.0
    RPAS 10 m/s21-10809.111.425.46.0
    RPAS 10 m/s10-13517.214.143.46.5
    Table 2. Swath widths calculated from the average cumulative deposit density for each WSP holder.

    It was expected that the field sprayer would produce a somewhat trapezoidal coverage pattern, tapering up at pole 12 (boom extreme) and level to pole 1 (sprayer chassis). Instead, note the gradual increase in coverage from pole 12 to 1. This is likely the result of boom yaw, where the boom end rose higher than the point closest to the sprayer. If this degree of coverage represents the industry standard, it is notable that the average boom coverage is either on par with, or considerably less, than that of the RPAS.

    Deposit Density

    The RPAS was programmed to produce a 250 µm droplet size, while the field sprayer produced Coarse (~218-349 µm) droplets. Smaller stains were produced by the RPAS than the field sprayer (figures 7 and 8), and their circular/oval shape suggest both a smaller droplet volume and a somewhat perpendicular flight path. Droplets produced by the field sprayer left long streaks, which suggest higher droplet volumes and a more parallel flight path.

    Figure 7. Typical deposition pattern from a single WSP holder in the centre of the RPAS flight pattern. Considered from the perspective of the RPAS, WSP starting at the top and rotating clockwise are left side, retreat side, right side, and advance side.
    Figure 8. Typical deposition pattern from a single WSP holder nearer the field sprayer chassis. Considered from the perspective of the field sprayer, WSP starting at the top and rotating clockwise are left side, retreat side, right side, and advance side.

    When the overall average coverage is calculated the RPAS at 6 m/s deposited an average 700 drops/cm2 and an average 400 drops/cm2 at 10 m/s. The field sprayer deposited an average 280 drops/cm2. When volume remains constant, smaller droplet diameters produce a greater number of droplets than with larger droplet diameters, so more droplets would be expected from the RPAS. However, the RPAS applied only 50 L/ha while the field sprayer applied 182 L/ha. Therefore, the RPAS distributed a greater density of potentially higher-concentration droplets on each WSP holder compared to the field sprayer. Further, a slower flight speed deposited a higher density of stains than a faster flight speed.

    Effect of Travel Speed

    The 6 m/s treatment resulted in slightly smaller swath widths (1 m or 15% less) than the 10 m/s treatment. The positive relationship between swath width and flight speed has already been established. The positive relationship between flight speed and off target drift has also been established, which may account for the significantly fewer deposits (almost 50% fewer) in the swath at 10 m/s versus 6 m/s. When a higher deposit density is valued, such as in the case of contact fungicide application, the loss of productivity from a slightly smaller swath width is a reasonable compromise for the superior coverage within that swath.

    Coverage by Cardinal Point

    North Facing WSP

    This side of the WSP holder faced north, away from the prevailing south wind. The RPAS deposited far more on this face when traveling with the wind between poles 14-15, making this side face the RPAS retreat (figure 9). It suggests the RPAS blows down and back, even against a tail wind. This is supported when RPAS returned between poles 7-8 and deposited comparatively less on this face.

    Figure 9. Mean sum deposit in count/cm2 for each treatment on north facing WSP. r=3. S.E. bars shown. Arrows indicate RPAS flight path and direction.

    RPAS speed may have had an effect. With airblast sprayers, slower travel speeds produce greater dwell times, which increases the distance a droplet travels on a given trajectory. Logically, when flying away from the retreat face, higher speeds would impart a greater forward momentum on a droplet, cancelling out some of the backward momentum (watch a video here). If this were the case, there would be comparatively improved deposit density on the 14-15 pass for slower speeds and reduced coverage between poles 7-8 as it blew past the target. Figure 9 supports this hypothesis.

    South Facing WSP

    This side of the WSP holder faced south, into the prevailing south wind. Considering the 6 m/s treatment, we see more coverage on the 7-8 pass than the 14-15, because it represents the retreat side of the sprayer (figure 10). The differential is far less on this plane than the north facing (figure 9) because the prevailing wind likely blew spray into the WSP on the 14-15 pass. Nevertheless there is significantly more on 7-8.

    Figure 10. Mean sum deposit in count/cm2 for each treatment on south facing WSP. r=3. S.E. bars shown. Arrows indicate RPAS flight path and direction.

    This relationship is less clear for the faster 10 m/s treatment. There does tend to be higher deposit on the 14-15 pass as spray was blown into the collectors. However far more was expected on this face for the 7-8 pass as it represents both the retreat face and has the added benefit of wind. Further, there was far less coverage overall when compared to the slower flight speed. We have no explanation for the lack of coverage on the 7-8 pass and can only conclude that higher speeds left droplets airborne and were not conducive to coverage.

    West Facing WSP

    This side of the WSP holder faced west, into the slight west wind. We see coverage is almost exclusively on those WSP facing the drone (figure 11). In other words, as the RPAS passed between 14-15 and 7-8, coverage was positively skewed from this point. The skewed coverage was evident at both flight speeds, but overall coverage was higher for the slower speed. Once again, we cannot explain why there was significantly reduced coverage on the 10 m/s pass between poles 7-8 except to suggest the spray may have remained airborne.

    Figure 11. Mean sum deposit in count/cm2 for each treatment on west facing WSP. r=3. S.E. bars shown. Arrows indicate RPAS flight path and direction.

    East Facing WSP

    This side of the WSP holder faced east, away from a slight west wind. We see that coverage is almost exclusively on those WSP facing the drone in the upwind direction (figure 12). Overall coverage was slightly higher for the slower speed, but far less overall coverage compared to the west facing samplers (figure 11). This is likely because the light west wind caused spray to displace from pole 21 to pole 1, washing past the back (insensitive) sides of the WSP.

    Figure 12. Mean sum deposit in count/cm2 for each treatment on east facing WSP. r=3. S.E. bars shown. Arrows indicate RPAS flight path and direction.

    Summary

    RPAS can provide par or better panoramic wheat head coverage compared to a conventional ground rig when they are flown using reasonable operational settings in optimal environmental conditions. A moderate flight speed (~6-8 m/s), appropriate altitude (~3 m above wheat heads), and four rotary atomizers producing a Medium-Coarse (~250 um) droplet size can produce an in situ 6 m swath width at 50 L/ha. Higher flight speeds produce a marginally wider swath at the cost of reduced droplet density and increased drift potential.

    Assessing coverage using vertical WSP facing four cardinal points has provided further insight into the behaviour of spray from an RPAS. Droplets from any application technology tend to deposit with wind and gravity, but rotor downwash represents an additional variable unique to RPAS. That force, combined with a forward cant of the drone during flight, lead droplets to deposit on vertical surfaces that face the rear (retreat) of the sprayer as well as surfaces that face and intercept spray that radiates laterally from the flight path.

    Author’s note: In 2026 we conducted a similar study with the larger, faster T100. The results give additional insight that should be considered.

    Drone Spray Canada, Bayer Canada, volunteers Kurtis Pilkington and Natalie, and grower-cooperator Adam Pfeffer are gratefully acknowledged for their contributions to this study.

  • 28% UAN in Winter Wheat: Drive-Along Diaries #2

    28% UAN in Winter Wheat: Drive-Along Diaries #2

    I’d been pestering Dan Petker to let me come along as he and his father Paul applied 28% UAN to the winter wheat on their family farm in Port Rowan, Ontario.

    Me: “Today?”
    Dan: “Nope – Wheat’s not at the right stage.”
    Me: “Today?”
    Dan: “Nope – Rain in the forecast.”
    Me: “Today?”
    Dan: “We’ll see if the ground can hold a full sprayer. I’ll let you know.”

    April 26th, 8:00 am

    My first lesson was a reminder that farming requires a lot of advance planning and preparation because ultimately, it’s opportunistic. The Petkers were toeing the start line as they focused on weather forecasts, crop staging and field conditions. As soon as they determined that the wheat in the tram lines would bounce back rather than get mashed into the soil, they were ready to roll. I suppose I was opportunistic as well because as soon as I got the thumbs-up I dropped everything and raced to their farm.

    10:30 am

    When I arrived, I found Dan filling their tender wagon in the yard. All their farm inputs are stored in their chemical shed, including 27,000 gallons of 28% UAN. The wagon had two, 1,000 gallon tanks which Dan was filling from a 2” line. He said that as the season progressed, they would move up to faster fills by swapping to a 3” line. They weren’t in that kind of rush today and he didn’t want to have to lug the heavier line around if he didn’t need to. Fair enough. At that point Paul radioed from the sprayer to tell Dan he was ready for his first refill.

    As we drove to meet Paul, I learned that the goal was to spray two fields totaling 200 acres. A single, 1,000 gallon tankful would cover 20 acres. Dan noted that these soils were a loamy silt and clay mix that held nitrogen very well. On sandier soils, farmers often choose to split the application where a smaller amount is applied earlier in the season and the remainder later, but Dan said it never paid dividends on these fields. Of course, that reasoning may have been moot since it was such a wet spring; They couldn’t get out earlier even if they wanted to.

    The two fields were within a 5 km radius from the yard, so nothing was more than 10 minutes away. The county roads were narrow, but throughout they day I saw that the locals knew how to share the road with farm equipment; lots of polite waves and no one risked their necks trying to pass. Good to see.

    10:40 am

    We pulled up alongside the sprayer and Dan started filling as I greeted Paul, who’d I’d ride with for the rest of the day. We were using their John Deere R4038 equipped with Pentair Hypro six-stream fertilizer nozzles (FC-ESI-11015’s) on 15” centres. The Petkers used 06’s the year before and found they had to drive too slowly, so investing in these larger nozzles was a productivity booster.

    While filling, they both watched the sight gauge on the side of the sprayer. I asked why they didn’t use a flowmeter and they said it could be off by +/- 10 gallons, so if the sprayer was level, the sight gauge told them what they needed to know.

    10:50

    I joined Paul in the cab and we drove into the field. Paul pointed out the pink field boundary on the monitor and grimaced at the rounded corners that were established during planting. He wanted to reset the A-B lines and square off those corners. His reasoning was to ensure weeds didn’t grow in the margins and affect yield. However, he also said it looked terrible and I got the impression this was as much about pride in a job well done as it was yield.

    We backed into the corner. Paul explained that the rate controller “hunts” a little as the sprayer speeds up over the first few meters and wouldn’t apply a full or consistent rate. By temporarily disengaging it until we got up to speed, we would avoid the weed escapes common to field corners. We’d be applying a slightly higher rate than required for those first few meters, but it was the lesser of two evils.

    He set the first pass using GPS: “Got-Paul-Steering” and I watched as the breakaway section started snagging the treeline on the edge of the field. I asked if that was a problem and he replied that he was driving slowly, and it didn’t bother anything. It was important to get those margins and the trees were always growing and dropping branches, so hits were inevitable.

    Soon we were back in the hands of GPS-guided autosteer and rate control and moving at a respectable 12 mph. 20 acres later we’d sprayed the 1,000 gallons and were headed back to meet Dan for a refill. On the way we noticed a triangular area that we missed while I was distracting Paul with questions. He said we’d double back later and let sectional control take care of it. Paul loved sectional control.

    11:30

    Soon Dan was empty, and we were full, so we got right back at it. I wouldn’t describe the field as hilly, but it was far from flat. On occasions where the sprayer dipped significantly, one side of the boom would sometimes kiss the ground while the other hung precipitously in the air. We had the boom height set to about 36” but Paul was manually raising each side if the boom got too close. You can forget the fantasy of sitting back and letting the machine do all the work; It certainly wasn’t the case, here.

    Slower travel speed and a reasonably-low boom are the best practice for crop protection sprays. However, streamer nozzles don’t form droplets and overlap was maintained, so I wasn’t worried about our lively boom causing drift or coverage uniformity concerns. I was, however, increasingly focused on my lower back and teeth. The buddy-seat didn’t have the padding or air-ride suspension Paul was enjoying.

    When we hit level ground again, I began to appreciate the process of passing back and forth over a field. It was satisfying to watch the sprayer icon on the monitor filling the screen with blue as we covered ground. Like the old-school, low-res, 1980’s video games that ate all my hard-earned quarters. Then we were empty again and it was time to go beg for more quarters.

    11:46

    Dan was busy so we drove back to the yard rather than wait for tender. There was a Rogator on the road ahead of us and Paul pointed out the muck it was flinging from the tires. A quick peek behind us showed we weren’t tracking mud. Paul said it was because of their soil management practices – no-till left the fields better able to weather droughts and absorb rains. The Rogator was operating in fields that employed deep tillage and were full of standing water and now, muddy tire ruts. Paul pointed out a few such fields as we drove, and I could soon see for myself which fields were managed by the Petkers and which were not. In fact, I only saw one puddle of standing water in their fields that day when all around us were shallow swimming pools.

    12:15

    We filled, drove back to the field, and picked up where we left off. Paul noted they had to plant their wheat a little later than they would have liked because they were delayed getting the beans off. Despite that, he was very happy with the stand we were fertilizing. We were able to have this conversation because Paul (like Dan) did not listen to music or podcasts in the sprayer. He said it helped him focus and that he liked the peace. I think being alone with my thoughts all day would have driven me around the bend. And then we were empty again, so back to the yard.

    12:47

    We filled, drove back, engaged the A-B line, and started the last section of this field. I asked about sprayer sanitation. UAN is notoriously caustic and can cause compatibility issues with some products, so I wanted to know how diligent they were about rinsing or cleaning (two different things). Paul agreed that it was messy stuff and it got all over the sprayer. So, at the end of the day, they would perform a thorough rinse of the plumbing before washing the exterior out behind their equipment shop. We finished with 300 gallons left in the tank, so we elected to head over to the second field.

    1:10

    At field number two, Paul changed fields on the monitor and grumbled about the round corners on the boundary. He pointed out that the edge of this field wasn’t straight – it contoured along a wavy treeline. Paul briefly disengaged rate control, set the “A” point and started driving manually again, hugging the treeline and dipping in and out using Got-Paul-Steering until we’d cleared the trees. Now that the field boundary was straight, he erased the “A” point and set a new one before later setting the “B”. He looked over at me, anticipating my question, but I’d already guessed that Paul didn’t want to repeat that wavy line on every subsequent row. Instead, we’d now run parallel to a straight A-B line and let sectional control handle the overlaps on our twisty start. That earned me an approving smile. And to add to that feeling of pride, our tank emptied exactly at the end of that first row. Perfect.

    1:27

    Back at the yard for our refill, I thought about how long our previous fill times were compared to now. From this second field it was 10 minutes on the road, 10 minutes to fill, and 10 minutes back, so 30 minutes compared to maybe 15 for the first field. Longer than I thought it would be. At 1:48 we were back and spraying again and I was beginning to notice how technical this field was. We performed a number of three-point turns in order to back into corners while the monitor alternated between happy chirps and stern alarms as we passed over A-B lines. Then we were empty, so back we went for more.

    2:41

    To continue to video game metaphor, this field was an advanced level and the Big Boss was coming. Not only was the shape odd, but it had chain link fences, posts, more trees, a water course, and they stored some farm equipment on one part of it. Paul calmly negotiated all these obstacles with stops, starts, boom adjustments (either height changes or partial folds), and then, shockingly, asked me to drive.

    Paul: “Line up the tracks.”
    Me: “I’m trying.”
    Paul: “Do not try or you won’t get it right. Do!”
    Me: “…what!?”

    As a card-carrying Star Wars fan, I thought Paul was teasing me. His Yoda impression was perfect. I asked if he’d seen Star Wars and he replied that he was vaguely aware of it. So, he was being sincere, and I relaxed knowing I was in good hands. I even negotiated a few turns under his tutelage. But I confess I was relieved when the hydrostatic lightsaber was back in his capable hands.

    3:04

    Empty. Drive. Fill. Drive. Spray at 3:43. The last section was quick and easy and once we’d finished, we headed to their equipment shop to find Dan waiting. Dan pointed out the nitrogen all over the sprayer and reinforced Paul’s assertion that they’d rinse it out and wash the exterior off later that evening.

    He drove me back to the yard so I could retrieve my car and we said our goodbyes. As I was headed home, I happened to pass their equipment shop where I saw Paul, a man in his mid 70’s that hadn’t stopped to eat and had been spraying all day, hard at it washing off the exterior. Wow.

    Take Homes

    I’m guilty of over-emphasizing the fill-time aspect of spraying because that’s the biggest time-suck on productivity. However, some tank mixes (e.g. SC’s) don’t appreciate being rushed, and while time is always pressing, there are those occasions where it isn’t mission-critical. Fill-time never came up on this job. There were, however, other aspects that deserved attention.

    In the case of applying UAN to winter wheat on these irregularly shaped home-farm fields, it was more important to be attentive and manually adjust sprayer settings to fit the moment rather than always trust in the technology. Granted, the technology (namely rate control, boom leveling and GPS sectional control) was brilliant once we’d finished the headlands and dealt with any obstacles and topographical challenges.

    I also appreciated that this family has been farming for many years. Dan and his father had a practiced rhythm that made it look easier than it actually was. Equipment was prepared, decisions were made, and everything was in place well ahead of the application. That included how they managed their soil and knowing how their fields responded to nitrogen. They communicated well, using digital records and redundant written notes to ensure everything was coordinated and going to plan, and that good planning made for a good day.

    And it was a good day.

  • Nitrogen Application Technology in Winter Wheat

    Nitrogen Application Technology in Winter Wheat

    With an ever growing selection of options for nozzles and streamer bars, many growers are asking the question, what should I outfit my sprayer with for winter wheat liquid fertilizer applications? Well, it depends on what are you trying to accomplish.

    If the goal is to push your winter wheat management and improve yields, then the accurate and uniform application of liquid nitrogen is key. Selecting the appropriate sprayer technology can have a huge impact. Using a twitter poll, we learned that growers use many methods:

    • 3, 5, 6 or 7 hole streamer nozzles
    • Flood nozzles
    • 3 or 5 hole streamer bars

    Let’s look at some of the options and consider why you might choose one technology over another.

    Floods on a Terra-Gator. Photo courtesy of Kyle DeCorte.

    Air Induction, Conventional Flat Fan or Flood Nozzles

    Let’s get this one out of the way first. Air induction (AI), conventional flat fan and flood nozzles are a no-go when it comes to applying 28% UAN in winter wheat. Dr. Peter Sikkema (University of Guelph) demonstrated that when 28% UAN was applied with an AI nozzle there was an increase in visual crop injury (Table 1).

    He also showed that injury increased substantially when tank-mixed with herbicides and when nitrogen applications were delayed (Table 2). So, while AI nozzles are great for herbicide applications, they are not suitable for 28%. Growers should consider fall weed control to avoid the need for spring herbicide applications.

    Table 1. Potential yield loss associated with applying UAN 28% as overall broadcast treatment using FloodJet or TeeJet nozzles. 11 gallon (Imperial) = 1.2 U.S gal. Source: P. Sikkema, University of Guelph (RCAT), 2008–2013 (OMAFRA Pub 811: Agronomy Guide).

    Application CombinationVisual InjuryYield
    200 L/ha water (18 1g/ac water)0%6.4 t/ha (95 bu/ac)
    150 L/ha water + 50L/ha UAN (13.4 g/ac water +4.5 gal/acre UAN)3%6.4 t/ha (95 bu/ac)
    100 L/ha water + 100L/ha UAN (9 g/ac water +9 g/ac UAN)5%6.1 t/ha (91 bu/ac)
    50 L/ha water + 150L/ha UAN (4.5 g/ac water +13.4 g/ac UAN)7%6.1 t/ha (91 bu/ac)
    200 L/ha UAN (18 g/ac UAN)9%6.0 t/ha (89 bu/ac)

    Table 2. Crop injury (%) and yield (bu/ac) of winter wheat following an application of 28% UAN (400 L/ha) alone with air induction nozzles and with various herbicides compared to an untreated control that received the same amount of nitrogen. Source: Dr. P.H. Sikkema, 3 trials from 2008-2010, University of Guelph (Ridgetown Campus) – Additional information on tank-mixing with herbicides can be found here.

    TreatmentHerbicide rate/acInjury (%)Yield (bu/ac)
    control (unsprayed)——0105
    28% UAN alone——6105
    28% UAN + Infinity0.33 L9104
    28% UAN + Buctril M0.4 L8103
    28% UAN + Estaprop XT0.48 L9102
    28% UAN + Refine M12 g + 0.36 L1799

    Streamer Nozzles

    Streamers significantly reduce crop injury when applying UAN 28% in winter wheat. Growers in Ontario are using a range of 3, 5, 6 and 7 hole nozzles. These nozzles provide even coverage and minimize burn compared to flat-fan or flood nozzles; however, boom height can have an impact on crop injury. This is particularly important with 3 and 6 hole streamer nozzles. If there are significant variations in boom height (e.g. uneven emergence, uneven land, or a boom with excessive sway and yaw), significant crop injury can occur. This is exacerbated by hot and dry conditions.

    The damage is the result of non-uniform coverage. Streamers deliver spray in a triangular shape. If the boom is too low gaps in the spray pattern reduce coverage. If the boom is too high the crop may receive increased overlap, resulting in crop injury. Therefore, these nozzles are an excellent option for apply UAN 28% to winter wheat crop (see image below) as long as boom height can be managed effectively.

    Pro tip: 28-0-0 often has crystals so strainers are important.

    UAN 28% being applied uniformly to winter wheat using 3 hole streamer nozzles. Photo courtesy of: Jim Patton.

    Streamer Bars

    Streamer bars (see image below) may be the best choice. Streamer bars deliver liquid nitrogen to the crop vertically. This allows for even distribution across the winter wheat crop at various boom heights, often permitting great speed. Some even have a sliding orifice to permit an easy transition between rates. Research performed in Kentucky showed that streamer bars produced a 2.8 bu/ac yield advantage compared to 3 hole streamer nozzles, and a 4.9 bu/ac yield advantage over 7 hole streamer nozzles.

    Some may argue those aren’t significant yield advantages, but most Ontario growers would argue differently. Streamer bars provide uniform coverage no matter the state of emergence, boom height, topography or even wind conditions. Streamer bars can be adapted to most sprayers and are available in 15″ or 20″ spacing. The only caveat is that they can be fragile and can make folding the boom difficult.

    Chafer streamer bar. Photo courtesy of Alex Zelem.

    Other Ways to Reduce Burn

    In addition to proper nozzle selection there are a few things you can do to reduce the risk of crop injury from N applications.

    • Avoid applications of 28% when the crop is stressed or during hot and dry conditions.
    • If conditions are more conducive for crop injury, increasing water volumes or applying less N can also help reduce burn significantly.

    At the end of the day it is important to remember the end goal – maximize yield potential. If we can deliver UAN 28% as uniformly as possible to a standing winter wheat crop while minimizing crop injury, the 100+ bu/ac wheat crop will be well worth the effort.

    Here’s Peter Johnson (@WheatPete) to tell you more in this RealAgriculture Wheat School episode: