Category: Speciality Sprayers

Main category for all sprayers that are not horizontal booms

Spray Water pH

The scuttlebut on coffee row is that acidifying a spray mixture improves its efficacy. There are also claims that pesticides break down in the sprayer tank if the pH is too high.

But it’s not that simple. Low pH has a strong impact on pesticide solubility, and that means mixing and cleanout are affected. Acidifying the mixture can have profound negative effects for many products.

It’s important to know what you’re doing.

What is pH?

pH is defined as the negative log of the molar concentration of hydrogen ions in a water-based solution. The more abundant the hydrogen, the lower the pH. It’s a log scale, so every unit of pH refers to a 10-fold change in the concentration of hydrogen ions.

Both very low (acidic) or very high (basic) pH can be caustic. But having a low or high pH doesn’t mean it will burn your skin or clothes right away, it might just be a bit unpleasant. But at the extreme ends, protection is needed.

Why is pH Important in Spray Mixtures?

In spraying, the main effect of pH is on the pesticide’s solubility. Solubility matters when mixing and becomes important during cleanout as well.

A minor effect on pH, at least for herbicides, is on chemical breakdown, usually through hydrolysis, when the pH is too high. The effect on breakdown is rarely meaningful during any given spray day, but may play a role if a spray mix is stored overnight or longer.

The Basics: Strong vs Weak Acids

Strong acids like hydrochloric acid (HCl) ionize completely in solution. When added to water, only H⁺ and Cl^– are present, there is no HCl. The water’s pH does not affect solubility of a strong acid.

But weak acids do not completely ionize. The water pH affects the degree of ionization and therefore solubility.

Most herbicides are weak acids. A weak acid is one that does not dissociate completely in solution. A typical example of a weak acid functional group is carboxylic acid (-COOH). In solution, compounds with a carboxylic moiety exist in an equilibrium, with some as -COOH (containing the hydrogen, also called “protonated”) and others as -COO^– and H⁺. In the dissociated form, the acid is more water soluble than in its protonated form due to the negative charge that makes it ionic.

Weak acids have a dissociation constant known as the pKa. When the solution is at the molecule’s pKa, the acid is 50% dissociated. When the solution has a lower pH than the pKa, there is less dissociation and the protonated forms of the molecule dominate. That has two important implications for herbicides.

the molecule becomes less water-soluble at lower pH
the molecule has fewer opportunities to interact with positively charged items

pH Dependent Solubility

Water-solubility is a two-edged sword. On the one hand, having a highly water soluble product makes it easier to dissolve in water. This pays dividends when mixing a batch or cleaning a sprayer because a product formulated as a solution will easily go into a true solution and will stay mixed. Examples are glyphosate, glufosinate, and salts of 2,4-D, MCPA, and dicamba.

On the other hand, most pesticides need to enter a plant to reach their site of action. And a plant cell, with its waxy cuticle and oily membranes, creates an effective barrier for water, and for water-loving molecules dissolved in it. As a result, a formulation that allows the water-soluble product to interact with an oily barrier is needed.

The products that can do this are surfactants. Acting like detergents, surfactants have regions in their structure that are oil-loving (lipophilic) and other regions that are water-loving (hydrophilic). Surfactants can therefore bind to both oil and water and provide a bridge for water-soluble products across oily barriers.

That’s also one of the reason that the most water-soluble products such as glyphosate and glufosinate contain a lot of surfactants in their formulation, reducing the concentration of active ingredient in the jug and possibly leading to foaming with agitation.

Pesticides have a wide range of solubilities, and for some, water pH will play an important role. Below is a table of some water solubilities of selected herbicides.

				Solubility (ppm)
Trade Name	Active Ingredient	Mode of Action Group	pH ~ 5	pH ~ 7	pH ~ 9
Select	clethodim	1	53	5,450	58,900
Ally 2	metsulfuron	2	550	2,800	313,000
Express	tribenuron	2	48	2,040	18,300
Pinnacle	thifensulfuron	2	223	2,240	8,830
Everest	flucarbazone	2	44,000	44,000	44,000
Simplicity	pyroxsulam	2	16	32,000	13,700
Frontline	florasulam	2	0.1	6	94
Varro	thiencarbazone	2	172	436	417
Raptor	imazamox	2	116,000	>626,000	>628,000
Pursuit	imazethapyr	2	2,570	12,870	7,500
2,4-D	2,4-D salt	4	29,934	44,558	43,134
dicamba	dicamba salt	4	>250,000	>250,000	>250,000
Roundup	glyphosate	9	>500,000	>500,000	>500,000
Liberty	glufosinate	10	>500,000	>500,000	>500,000
Heat	saflufenacil	14	30	2,100	>5000
Distinct	diflufenzopyr	19	63	5,900	10,550
Infinity	pyrasulfatole	27	4,200	69,100	49,000

Compare the solubility at pH 7 to that at pH 5. For most of these herbicides, water solubility is worse at lower pH. That is because they are more protonated and become more lipophilic.

I’ve placed a lot of Group 2 products in this table because those products are most often implicated in tank cleanout issues. All Group 2 products in this table, with the exception of Everest (flucarbazone-sodium) have lower solubility at pH 5 than they do at pH 7. For some, like pyroxsulam and floarsulam, it’s a big change. Those products, when acifified, are prime candidates for poor mixability and poor cleanout.

When it comes to dicamba, low pH has another side-effect. It makes the molecule more volatile, increasing danger to sensitive plants nearby. For that reason, acidification of dicamba in its Xtendimax and Engenia formulations is not permitted.

Note that the Group 4 examples, 2,4-D salt and dicamba salt, as well as glyphosate and glufosinate, are highly water-soluble and pH has very little effect on that.

Particularly for glyphosate, the claim that it becomes more oily at low pH and will therefore be taken up more easily, is not supported by these data. Considering that the most acidic pKa for glyphosate (it has four acidic groups) is 0.8, pH would need to be much lower for any noticeable impact on oilyness.

Tank Mixability

Given today’s environment of herbicide resistance, applications with multiple mode of action tank mixes are very common. Acidifying a spray mix to benefit one herbicide may create problems for its tank mix partners.

If there is a concern that spray water is too alkaline, it is recommended that the pH of the finished spray mix be measured. Since many herbicides are weak acids, they will lower the pH of the mixture by themselves. For example, the addition of glyphosate to water with pH 7.5 will drop the pH to about 5 or so, depending on the water’s buffering capacity.

As a result, glyphosate tank mix partners that are pH sensitive may suffer in the presence of glyphosate, and pH may actually need to be raised.

pH Dependent Half-life

Herbicides

There are a lot of claims that pesticides break down rapidly in alkaline spray water. And yet, in my career working primarily with herbicides, I do not recall this ever being a problem in practice.

Below is a table of herbicides for which I could find half-life information, with the help of this comprehensive list produced by Michigan State University.

Product	Active ingredient	Half Life
Atrazine	atrazine	More stable at high pH
Banvel	dicamba	Stable at pH 5 – 6
Bromoxynil	bromoxynil	pH 5 = 34 d; pH 9 = 1.7 d
Fusilade	fluazifop-p-butyl	pH 4.5 = 455 d; pH 9 = 17 d
Liberty	glufosinate-ammonium	Stable over wide range of pH
Gramoxone	paraquat	Not stable at pH above 7
Reglone	diquat	pH 5 = 178 d; pH 7 = 158 d; pH 9 = 34 d
MCPA	MCPA	pH 9 = < 5 days
Poast	sethoxydim	Stable at pH 4.0 to 10
Princep	simazine	pH 4.5 = 20 d; pH 5 = 96 d; pH 9 = 24 d
Prowl	pendimethalin	Stable over a wide range of pH values
Roundup	glyphosate	Stable over a wide range of pH values
Treflan	triflularin	Stable over a wide range of pH values
2,4-D	2,4-D	Stable at pH 4.5 to 7

Note that all of the herbicides are relatively stable. Some are a bit less stable at high pH, but none of the listed herbicides is in danger of breaking down on the day it is being applied. Only one is actually unstable at high pH – paraquat, a herbicide no longer registered in Canada and resticted in many other countries. Those with short half-lives experience them at quite high pH which are rarely seen in practice.

Insecticides

Insecticides are a different story. Several are very sensitive to pH. This table is again adapted from a comprehensive list published by Michigan State University, here.

Trade Name	Active Ingredient	Half-life
Admire	Imidacloprid	Greater than 31 days at pH 5 – 9
Agri-Mek	Avermectin	Stable at pH 5 – 9
Ambush	Permethrin	Stable at pH 6 – 8
Assail	acetamiprid	Unstable at pH below 4 and above 7
Avaunt	indoxacarb	Stable for 3 days at pH 5 – 10
Cygon/Lagon	dimethoate	pH 4 = 20 hrs; pH 6 = 12 hrs; pH 9 = 48 min
Cymbush	cypermethrin	pH 9 = 39 hours
Diazinon	phosphorothioate	pH 5 = 2 wks; pH 7 = 10 wks; pH 8 = 3 wks; pH 9 = 29 days
Dipel/Foray	b. thuringiensis	Unstable at pH above 8
Dylox	trichlorfon	pH 6 = 3.7 days; pH 7 = 6.5 hrs; pH 8 = 63 min
Endosulfan	endosulfan	70% loss after 7 days at pH 7.3 – 8
Furadan	carbofuran	pH 6 = 8 days; pH 9 = 78 hrs
Guthion	azinphos-methyl	pH 5 = 17 days; pH 7 = 10 days; pH 9 = 12 hrs
Kelthane	dicofol	pH 5 = 20 days; pH 7 = 5 days; pH 9 = 1hr
Lannate	methomyl	Stable at pH below 7
Lorsban	chlorpyrifos	pH 5 = 63 days; pH 7 = 35 days; pH 8 = 1.5 days
Malathion	dimethyl dithiophosphate	pH 6 = 8 days; pH 7 = 3 days; pH 8 = 19 hrs; pH 9 = 5 hrs
Matador	lambda-cyhalothrin	Stable at pH 5 – 9
Mavrik	tau-fluvalinate	pH 6 = 30 days; pH 9 = 1 – 2 days
Mitac	amitraz	pH 5 = 35 hrs; pH 7 = 15 hrs; pH 9 = 1.5 hrs
Omite	propargite	Effectiveness reduced at pH above 7
Orthene	acephate	pH 5 = 55 days; pH 7 = 17 days; pH 9 = 3 days
Pounce	permethrin	pH 5.7 to 7.7 is optimal
Pyramite	pyridaben	Stable at pH 4 – 9
Sevin XLR	carbaryl	pH 6 = 100 days; pH 7 = 24 days; pH 8 = 2.5 days; pH 9 = 1 day
SpinTor	spinosad	Stable at pH 5 – 7; pH 9 = 200 days
Thiodan	endosulfan	70% loss after 7 days at pH 7.3 to 8
Zolone	phosalone	Stable at pH 5 – 7; pH 9 = 9 days

Among insecticides, dimethoate, amitraz, and malathion stand out as breaking down rapidly in alkaline water. For these products in particular, it may be important to acifify the spray mix if there is any delay in spraying.

Recommendations

I’ve never been a fan of messing with solution pH unless recommended on the product label. Even when there is evidence that lower pH improves efficacy, consider the impact on tank mix partners.

We’ve seen improvements in solubility and tank cleranout of Group 2 products with raised pH, and ammonia is the most cost-effective way to achieve that. But again, following label recommendations is strongly recommended. The consequences of changes in pH, particularly acifification, can be very detrimental. To be safe, consider doing a jar test before committing to a whole tank to a pH adjustment.

April 2, 2026

How to Interpret a Water Quality Test Result
It’s common advice: Test your water before using it as a spray carrier. You dutifully sample the well or dugout and await lab results. And what comes back is a whole lot of numbers. How to make sense of it all?
Three examples of water test results conducted by labs in Canada
All three of these tests report a large number of properties and identify specific minerals and other solutes. Which ones are important in spraying? Here is the order in which I look at the numbers.
Conductivity: This property is usually expressed as micro Siemens per cm (µS/cm) and simply identifies how many ionic solutes are in a sample (watch for alternate units such as mS/cm and convert if necessary). It doesn’t differentiate between any minerals or other molecules, and therefore has limited information. But it does tell us if there is a large or small issue with water quality. If conductivity is below 500 µS/cm, the water is probably good for spraying. If the value is around 1000 to 2000, further investigation is necessary. Some water samples return conductivity of more than 10,000 µS/cm, and it’s important to identify which salts are causing that problem.
Note that Total Dissolved Solids (TDS) are often listed, and these are related to conductivity. A common way to get TDS is to multiply conductivity by 0.65. The conversion factor depends on which salts are dissolved but the bottom line is that TDS and conductivity are closely related.
Bicarbonate: Bicarbonates are HCO₃ and their concentration is measured in milligrams per Litre (mg/L), which is the same as parts per million (ppm). Bicarbonates can antagonize Group 1 modes of action and the common threshold is 500 ppm. Research at NDSU has shown that Urea -Ammonium-Nitrate (UAN or 28-0-0 liquid fertilizer) can reduce bicarbonate antagonism in some Group 1 herbicides.
Bicarbonates are negatively charged and are associated with a positive ion, often the hard water cations sodium (Na), calcium (Ca) or magnesium (Mg). As such, waters that are high in bicarbonates are often also hard.
Total Hardness (calculated): This is one of the important parameters. Hardness antagonizes most weak acid herbicides, most importantly glyphosate and g;ufosinate, and also ties up surfactants and emulsifiers which can result in problems with mixing and compatibility. Hardness is caused by metal cations, in order of strength these are iron (Fe⁺⁺), magnesium (Mg⁺⁺), calcium (Ca⁺⁺), sodium (Na⁺), and potassium (K⁺). Of these, Mg and Ca are typically most abundant, although some water is high in Na.
The Total Hardness (ppm) reported in water tests is done by taking the most common two cations, calcium and magnesium, and using this formula: 2.497*Ca + 4.118*Mg. Note that some tests report hardness in Grains per Gallon, in this case, multiply grains by 17.1 to get ppm.
While this calculation usually gives an accurate prediction of hardness, you may need to have a look at iron and sodium as well. Iron is less common, but some well waters are high in sodium or potassium. These minerals are not captured in the Total Hardness measurement. A water test low in Total Hardness may still be high in sodium, these are typically the samples with high conductivity.
The threshold for Total Hardness depends on the herbicide, its rate, and the water volume. The most common quoted values are 350 ppm for the lower rates of glyphosate (1/2 L/acre equivalent), and 700 ppm for the higher rates. Lower water volumes increase the concentration of herbicide, and reduce the impact of water hardness or bicabonates.
pH: This parameter is a bit over-rated because it is later affected by the herbicide and adjuvant dissolved in it. There is usually no concern with pH between 6 and 8, and water is rarely outside this range. It is best not to change the pH of water unless it is required on the label for mixing, because some products require low, and others require high pH for optimum solubility. Compatibility is an ever greater concern as our tank mix complexity increases.
Water Conditioners
The most common water conditioner is ammonium sulphate [AMS, (NH₄)₂ SO₄]. In its pure form (21-0-0-24), a concentration of 1% to 2% w/v (8 to 17 lbs AMS/100 US gallons of spray water) solves most hard water and bicarbonate issues. Be cautious of using too much AMS (>3%), when added at high concentrations to some herbicides it can burn crops.
Research has shown that AMS works in two ways: The sulphate ion binds with hard water cations, forming an insoluble precipitate that prevents the antagonistic cations from binding to, and inhibiting, the herbicide. The ammonium ion has been shown to improve cellular uptake by weak ion herbicides.
Some product labels call for UAN as an adjuvant. UAN contributes ammonium, but not sulphate ions. As a result, while it may improve herbicide performance, it does not remove antagonizing cations from the mixture.
Acids have been used to combat hard water. Most common herbicides are weak acids, and the acid constituent, usually a carboxilic acid, has a unique pKa. The pKa is the pH at which half the molecules are protonated (contain a hydrogen atom, resulting in an uncharged acid constituent) and the other half are not protonated (negatively charged). If the spray mixture has a pH below the pKa, the weak acid herbicides become protonated. This means the herbicide becomes less water-soluble, but also that it has less chance of interacting with a hard water cation. Acids that work in this way are less effective at ameliorating the effect of hard water than AMS.
A small group of acids that includes citric acid and sufphuric acid can sequester or bind with hard water cations. But they do not contribute the ammonium ion that assists in weak acid herbicide uptake.
If your water is questionable for spraying, there are four common choices:
- Select a different well or dugout
- If the problem is barbonates or hardness, treat water with a conditioner such as Ammonium Sulphate (AMS), available in pure form as 21-0-0-24. Some acids (citric, sulfuric) can form conjugate bases with hard water cations, removing them from solution. But the associated significant lowering of pH should be treated with an abundance of caution as it may affect solubility of some pesticides.
- Reduce water volumes or increase herbicide rates.
- Use a municipal treated water source or invest in a reverse-osmosis (RO) system. RO is neither cheap nor fast and requires additional investment in storage, and a way to deal with solute-enriched waste water. But it may be the best option for some.
An Ammonium Sulphate calculator, originally developed by Winfield United using data from NDSU, can be downloaded here:
AMS-Calculator-Sprayers101-1 Download
An excellent resource for adjuvant and water quality topics is this addendum in the North Dakota State University Guide to Weed Control.
Using good quality water lowers the likelihood of problems with mixing and overall performance and that pays significant dividends later.
April 1, 2026
Wanted: A New Technology for Assessing Spray Coverage – The Spray Doctor
“If you can’t measure it, you can’t improve it”. While the source is nebulous (Peter Drucker, Lord Kelvin, or Antoine-Augustin Cournot), the sentiment is clear.
The status quo
In the world of crop protection, considerable resources are expended to distribute a pesticide over a target. And yet, sprayer operational settings and spray coverage are rarely assessed. As a result, too much time elapses between the application and observing the biological results to evaluate and correct equipment performance. The damage (be it waste or an inconsistent and sub-lethal dose) is done. All sprayer operators know this to be true, so why do precious few perform these assessments?
Perhaps, dear reader, you have personal experience assessing coverage and already know the answer. Perhaps you’ve performed the iterative dance that is placing, spraying, retrieving, assessing and re-placing water sensitive paper (WSP). Perhaps you’ve sprayed fluorescent tracers and hunted for faint glows at twilight using UV lights. Perhaps you’ve looked for residue from diatomaceous earth or fungicides. Or, perhaps, you’ve trusted in the falsely-comforting “shoulder check” and assumed dripping must mean you’ve hit the target.
Existing methods are complicated, subjective, messy and time-consuming. We need an alternative.
The alternative
Consider a permanent, solar-powered sensor that supplies real-time spray coverage data to your smartphone via a cellular connection. The output could be visualised in a simple and intuitive way, and immediately available to both sprayer operators and farm managers. If the sensor was relatively inexpensive, sufficiently hardy, and easy to deploy, its utility would only be limited by your imagination:
- Stakeholders could confirm the correct functioning of their equipment before committing to the application. Decisions could be made to change operational settings, repair equipment, or delay until conditions improved.
- The sensors would provide coverage data specific to their location and orientation. Units could be installed in difficult-to-spray regions such as treetops, or canopy-centres, or fruiting zones. Sensors could be placed where pest/disease pressure has been historically high, or where wind is a known issue.
- Large operations could install them in a test-row, where sprayer operators would perform a gauntlet-style calibration run prior to a day of spraying.
- Spray records could inform compliance audits, supplement insurance or CanadaGAP traceability requirements, or be used in agronomic assessments.
In 2025 I was approached by an Australian developer who claimed he had a device that did all of this. And, if that weren’t enough, it could also monitor certain meteorological factors such as pre-spray moisture levels and temperature and report post-spray evaporation rates. I could barely contain my excitement. A prototype was in my hands a few weeks later.
Prototype, 8-sided sensor located in a blueberry bush.
Solar panel powering three, 8-sided prototype sensors spanning 10 meters of highbush blueberry.
Benchmarking the sensor
The Spray Doctor (working name for the prototype) started its life as a leaf wetness sensor, evolving into a spray coverage sensor piloted in 2023/24 in Australian and New Zealand grape production. The history of earlier iterations and company schisms is convoluted, and fortunately immaterial to our purposes. All I needed to know was that we weren’t starting from scratch. Several of the questions regarding how accurately the surface could detect spray deposition were already addressed by independent research.
The sensing surface is impregnated with an array of capacitive wetness sensors. The sensor responds to the surface area covered and not deposit density. Researchers reported a reliable response range between ~10% and 50% surface coverage. Given the arguable “ideal” coverage standard of 10-15% surface area, this includes the range of interest for most sprays.
Benchmarking against WSP was part of the foundational assessment. A droplet of water deposited on WSP produces a high angle of contact and very little spread, while the same droplet deposited on plant tissue tends to produce a lower angle of contact and more spread. This means the stain produced on WSP is smaller than would be produced on plant tissue, depending on how smooth, vertical or waxy the tissue surface was.
It was therefore surprising that WSP were found to report a higher degree of spray coverage during water-only sprays than the sensor. It seemed droplets more easily coalesced and ran off the sensor surface. This was ultimately interpreted as an advantage, because the sensor would better emulate how a leaf surface would respond to the influence of surfactants and spray quality.
Adding a surfactant to a spray solution improves droplet adherence, and/or reduces surface tension, improving the degree of contact on plant surfaces. Likewise, it was found that surfactants increased the degree of coverage reported by the sensor, and when actual chemistry was sprayed (e.g. sulphur powder or copper sulfate) there was an effect on the degree of coverage reported. This is unlike WSP, where adjuvants and chemistry do little to increase the spread.
And so, like every method for assessing spray coverage, the sensor has limitations and caveats. If you have some doubt as to the sensor’s accuracy, do not get distracted by the fine detail. Remember, most operators currently have no feedback whatsoever; even a binary response (e.g. hit or miss) would be welcome. The sensor is sufficiently sensitive and consistent to resolve coverage in a range relevant to most sprays, and therefore worth field testing.
The experiment
My role in this story was to work with a grower to evaluate the sensor’s ability to report coverage information in a clear and actionable way. There were three questions:
- Does data from the sensor influence a sprayer operator’s behaviour?
- Does that change in behaviour lead to improved spray coverage (implying more efficient and effective crop protection).
- Could we “dial in” the hardware and the interface based on the grower’s feedback?
In part two, we share our experience installing and using the Spray Doctor, as well as supply answers to these questions. Stay tuned.
Thanks to Brandon Falcon (Falcon Blueberries) for volunteering his time and farm for this evaluation, and the developer for the in kind donation of the prototype Spray Doctor.
January 23, 2026
Evaluating the return on investment of optical sprayers for horticulture
Investing in an optical sprayer for horticulture is not a straightforward financial decision. Compared with a conventional boom sprayer, the upfront capital cost is substantially higher, often by an order of magnitude, and most commercial systems require an annual software or service subscription to operate. Despite these barriers, adoption is accelerating, and many growers who have made the investment report very positive outcomes.
To help clarify when and where this technology makes financial sense, I developed a calculator to estimate the return on investment (ROI) of optical sprayers under a range of production scenarios. The goal of this tool is not to promote the technology, but to provide growers and advisors with a structured way to evaluate whether it fits their specific operation.
Note: This calculator was designed for onion and carrot production in Ontario, Canada. Model parameters can easily be adjusted reflect other production systems. However, if you need assistance making these changes you can contact me by email.
New versions may be uploaded as the calculator evolves through experience and based on user feedback, so check back. You can download Version 1.1 (April, 2026), HERE.
How to use the calculator
At first glance, the calculator may appear overwhelming because it requires a fair amount of information to be entered. This is the minimum data required to reflect real-world conditions while avoiding an oversimplification that could lead to misleading conclusions. Cells shaded in yellow are meant for user input. All other values are calculated automatically based on those inputs.
For convenience, the calculator is pre-filled with generic values derived from grower discussions and informal benchmarks. These default numbers are meant only as placeholders and to provide general reference. They are not sufficiently accurate on their own to support financial decisions.
Users should replace all default values with operation-specific data whenever possible. As with any economic model, the quality of the output depends entirely on the quality of the inputs.
The calculator is organized into three spreadsheets (see tabs at bottom).
1. Introduction
This tab provides general instructions and contact information. No data entry is required.
2. Sections Explained
This is a reference tab that explains each section of the calculator in detail. It is intended to help users understand how different inputs affect the results and the intention of each section (small table) withing the sheet. No values should be entered here.
3. Calculation Sheet
This is the main working tab. All data entry occurs here. To prevent accidental changes that could break formulas, the sheet is protected. For most input fields, a brief explanation is provided immediately to the right of the cell. In the results section, short interpretations are often included, such as: “Decrease of 36% ($101,250/year) in hand-weeding cost with optical sprayer.” Within this tab, scenario tables are also provided. These tables are designed to illustrate how different acreages of the two crops analyzed affect each of the calculated financial indicators.
Insights from scenario testing
Even using rough approximations, several consistent patterns emerge from adjusting the calculator inputs:
Herbicide savings alone rarely justify the investment
In high-value horticultural crops, herbicide costs are often a relatively small portion of total production costs compared with labor, equipment, and the overall value of the crop. In many cases, any reduction in herbicide expenditure is largely offset by increased tractor hours resulting from slower operating speeds and narrower effective spray widths typical of optical sprayers.
Labor savings can be decisive
When the technology results in meaningful reductions in hand-weeding, the financial impact can be substantial. This is especially true in crops such as onions, where hand-weeding is both costly and difficult to source reliably. In these situations, labour savings alone can drive a favorable ROI.
Yield protection may outweigh cost savings
Several growers report stand losses and weakening associated with herbicide phytotoxicity as a major production risk. By limiting spray exposure to crop plants, optical sprayers can significantly reduce or even eliminate this issue. In high-value systems, relatively small yield gains resulting from improved crop safety can translate into revenue increases large enough to justify the technology, even if other savings are modest.
Scale matters
When evaluating advanced sprayer technologies, scale becomes a decisive factor. The high capital investment and ongoing service fees may be difficult to justify for small, and in some cases, even medium-sized operations.
What about herbicide resistance?
The long-term implications of optical sprayers for herbicide resistance management are still uncertain. Recent research from the University of Arkansas has raised concerns in field crop systems, suggesting that poorly optimized optical spraying can result in short term gains, but these can be outweighed over time by higher weed escape rates compared with broadcast applications. If these escapes are allowed to grow and set seed, rapid seedbank replenishment and accelerated resistance development may occur.
This highlights an important limitation of short-term ROI calculations. A single-year economic benefit may look attractive, but if the system allows even a small number of weeds to consistently escape and reproduce, the long-term consequences can be severe.
On the other hand, optical sprayers may eventually enable new resistance-management strategies. It is possible that new active ingredients, higher labelled rates, or novel use patterns could be registered specifically for targeted spraying in horticultural crops that would not be feasible with broadcast applications. Such developments could significantly improve resistance management tools. As always, it is essential to remember that the label is the law: only registered products and rates may be used, regardless of perceived crop safety.
ROI implications beyond herbicide spraying
Optical sprayers can deliver value beyond herbicide applications, even though weed control is their primary use. These additional uses may improve overall ROI. However, because their economic impact is still difficult to quantify, they have not been included in the calculator.
Depending on the model, additional value-generating capabilities can include:
- Creation of weed maps: Some systems can generate weed maps automatically while spraying, at no additional operational cost. These maps can support future management decisions.
- Application of fertilizers and other pesticides: Although optimized for herbicides, optical sprayers may also be used to apply other inputs, such as fertilizers or non-herbicide pesticides.
- Crop thinning: Certain manufacturers have developed algorithms for automated crop thinning, particularly in crops like lettuce.
Conclusion
Even using approximate inputs, it is clear why optical sprayer adoption is expanding rapidly in Canada.
- For medium to large-scale operations, the ROI can be highly attractive, and the range of potential benefits continues to grow.
- As the technology matures, more equipment options are emerging to serve a wider diversity of crops and farm sizes.
- Manufacturers are introducing wider and more flexible platforms, and Ontario-based companies are actively developing alternative machines and service-based business models that may better suit smaller operations.
It is difficult to argue that optical spraying is a passing trend. While it’s not a universal solution and must be implemented carefully, the technology is clearly here to stay. It will reshape weed management and production economics over the long term.
January 16, 2026
Crop-Adapted Spraying in Highbush Blueberry: Nine years of pesticide savings
This case study is taking place on a 15 acre highbush blueberry operation in southern Ontario. In 2016, considerable pressure from spotted-wing drosophila (SWD) prompted the growers to make changes to their crop management practices and their spray program. They employed a three-pronged approach to improving crop protection:
1. Significant changes to canopy management and picking / culling practices
2. Investing in a new sprayer
3. Adopting the Crop-Adapted Spraying (CAS) method of dose expression
We have been tracking pesticide use, water use and yield compared to historic values. We also monitored spotted-wing drosophila catches both in crop and in wild hosts along the border of the operation for three years.
Canopy Management
In 2016 the operation made the following changes to their canopy management practices:
- They performed their first-ever heavy pruning and planned to to maintain an ideal crop density by removing ~30% plant material annually. This more-or-less took place.
- They regularly collected and buried culled and dropped berries.
- They picked cleanly and more frequently.
Heavy pruning in 2016.
Most years, bushes were pruned ~30% to maintain an ideal size and shape.
Pickers were educated in how to pick cleanly and dropped / culled fruit was collected and buried.
There were initial concerns that such dramatic pruning would reduce production per acre and require trellising to prevent berries weighing down the smaller bushes. However, in 2017 (and thereafter) they found that the quality of the berries was greatly improved and noted fewer hours spent culling berries during packing. Financially, the growers felt they came out ahead.
Application Technology
In 2018 they replaced their old, inefficient KWH sprayer with a low profile axial with conventional hydraulic nozzles to permit greater control of the spray. The KWH design was intended for standard fruit trees. It produced >100 mph air and an Extremely Fine spray quality and was therefore a bad fit with the planting architecture and canopy morphology of highbush blueberry.

They considered a cannon-style sprayer hoping to spray multiple rows in a single pass but given the desire for improved coverage and reduced waste, they elected to drive every row using a low-profile axial.
Fore: An old KWH air shear sprayer. Rear: Low profile axial sprayer with conventional hydraulic nozzles.
The new sprayer was more reliable, quieter, and more fuel efficient. Further, the old sprayer leaked and the air-shear nozzles did not respond when shut down at the end of rows. Eliminating these sources of waste represented a savings of ~20% of the spray volume traditionally used per acre.
Crop-Adapted Spraying
The redundancy inherent to product label rates for three-dimensional perennial crops has long been recognized. In response, rate adjustment (or dose expression) methods have been developed to improve the fit between rate and canopy coverage (e.g. Tree-Row Volume, PACE+, DOSAVIÑA). Each has value, but their adoption has been slow because they are region- or crop-specific and they can sometimes be quite complicated.
CAS lends structure and repeatably to the informal rate adjustment methods already used to spray three-dimensional perennial crops (e.g. Making pro rata changes by engaging/disengaging nozzles in response to canopy height or altering travel speed in response to canopy density).
The CAS method relies on the use of water sensitive paper to confirm a minimal coverage threshold of 85 deposits per cm² as well as 10-15% area covered throughout a minimum of 80% of the canopy. Using this protocol, we calibrated air energy and direction, travel speed and liquid flow distribution. This process is covered in detail here and in the new edition of Airblast101. In that first year we reassessed coverage every few weeks between April and June using water-sensitive paper.
Spray volume / Pesticide
By matching the sprayer calibration to a well-managed canopy, the growers were able to go from ~1,000 L/ha to ~400 L/ha of spray mix. The ratio of formulated product-to-carrier remained the same, but less spray was warranted per acre. Stated differently, the grower mixed the spray tanks per usual, but drove further on a tank.
This also saved an estimated 15 hours of filling/spraying time per year, which translates to reduced operator fatigue and exposure as well as reduced manhours and equipment hours.
The decision of what and when to apply was at the growers’ discretion. Chemistry was rotated and applications were made according to IPM in early morning (if there were no active pollinators) to avoid potential drift due to thermal inversions. The following image shows what those papers looked like in June of the first year.
Example of water sensitive paper coverage on a windy day (worst case scenario) in June, 2018.
Note how little spray escapes the target rows in the following video. The wind was too high for spraying, but we were only using water and saw it as an opportunity to test a worst-case scenario. Air-induction hollow cones were used in the top nozzle position on each side so droplets were large enough to fall back to ground if they missed the top of the canopies.
SWD monitoring
SWD represents a serious economic threat to blueberry operations. Traps were placed in the operation (three in the crop and one in an unmanaged wild host along a treeline) and monitored weekly. Traps were also placed in surrounding horticultural operations which were employing standard pest control practices. This not only provided regional information about SWD activity but allowed us to compare the level of SWD control from the Crop-Adapted Spraying approach.
- In 2018 the comparison included up to 16 other sites that were berry and tender fruit.
- In 2019 the comparison included 10-12 sites (depending on the week) and they were berry and tender fruit sites.
- In 2020 the comparison included 4 other sites (blueberries, raspberries and cherries).
2020 & 2021 – Covid 19 and Heavy Rain
In agriculture, every year is an adventure, but 2020 and 2021 were exceptionally difficult and the circumstances should be considered when deciphering the results. Covid-19 has had a significant impact on global agriculture.
In 2020, fearing a reduction in the availability of seasonal labour, the operation pruned their bushes heavily. This was done to reduce the yield in order to make harvest manageable.
In 2021, labour was once again secure. Given the heavy pruning the year previously there was no need to prune again, so the crops densified. This coincided with abnormally high levels of precipitation to create significant anthracnose issues. Additional fungicide applications took place that raised costs, but the grower maintained CAS-optimized rates and sprayer settings.
Quantitative Results
Prior to replacing their sprayer, and adopting CAS, the operation sprayed about 78,260 L/yr. Their average savings in spray volume (water) has been 54,720 L/yr, or 70%.
In terms of pesticide savings, we compare each year to the 2017 baseline. In order to make for a fair comparison, we update pesticide prices each year using current costs. Therefore, the 2017 total has increased by about $2,600.00 (wow). Their average savings represents $5,575.00 CAD/yr or 62.5%.
Yield is more difficult to interpret due to mitigating circumstances in 2019 and 2020:
- In 2016, prior to any changes, they harvested 12,076 flats (about 9lb of fruit each).
- In 2017, following the canopy management changes, harvest increased to 18,335 flats (~50% increase).
- In 2018, using CAS, harvest was essentially unchanged compared to 2017, which was excellent.
- In 2019, harvest started a month late compared to previous years. Further, blueberry prices were low, and the operation elected to stop harvesting a month early. However, when those issues are factored in, the harvest was comparable.
- 2020 was particularly challenging for agriculture and with the possibility of reduced labour due to the pandemic, the operation elected to prune heavily and reduce their yield.
- 2021 saw unpruned bushes (following the heavy pruning in 2020) and abnormally high levels or precipitation which created anthracnose issues. As a result, more applications were made than any other year on record, but maintained the CAS-optimized rates and sprayer settings.
- 2022 was (thankfully) fairly typical. Low SWD, average anthracnose and no drama.
- 2023 was very much like 2022 with low SWD, average anthracnose and no drama.
- 2024 saw a LOT of rain. The season started and ended early, but yields were par. “Pivot” replaced “Tilt”.
- 2025 was pretty average all things considered. No drama whatsoever. “Inspire-Super” was added to product list.
Trap counts for SWD were only performed during three years of the CAS study, so we are only able to present 2018-2020 data. It should also be noted that while the presence of SWD in an operation represents an impact on yield, there is not necessarily a correlation between the number of SWD captured the amount of damage.
In 2018 and 2020, average counts were higher in the surrounding operations employing standard practices (STD) compared to the CAS trial. In 2019, average counts were higher in the CAS trial. When total average counts are compared, the difference is negligible. Berries were tested regularly by the growers and the damage due to SWD was within acceptable limits. It should also be noted growers monitored and reported satisfactory disease control throughout the study.
We have not applied any statistical rigor, but the trend suggests that the level of control provided by the CAS method was comparable to conventional methods. This conforms with our previous results in Ontario apple orchards and similar evaluations of optimized application methods world wide.
Qualitative results
Beyond the quantifiable results, the growers reported qualitative benefits:
- Customers of the U-pick portion of the operation regularly enquire about pesticides. The operation’s reduction in pesticide use became a positive speaking point and aligned with the grower’s philosophy about reduced environmental pesticide loads.
- While many blueberry growers experienced a market shortage of certain fungicides in 2018, this operation returned unused product to the distributor.
- Growers reported less early-season disease damage, which saved considerable time on the packing line because there was less fruit to cull. Disease levels rose to typical levels later in the season, but there was still a net savings in labour.
Conclusion
The success enjoyed in this berry operation was a result of several canopy management and crop protection changes. This is a situation where the whole equaled more than the sum of its parts – it could only be achieved by making holistic changes to the operation. At the end of three years the growers themselves stated:
“Based on my experience losing multiple crops to SWD, I can say with absolute certainty it works. <The results are> superior to what I expected. What we are doing is successful.”
Here’s a narrated PowerPoint presentation of this study (includes data up to 2020):
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The monitoring portion of this project was funded by Niagara Peninsula Fruit and Vegetable Growers Association, Ontario Grape and Wine Research and Ontario Tender Fruit Growers in collaboration with private consultants.
January 6, 2026