The Saskatoon company’s camera-based system mounts on a sprayer boom and captures field conditions as farmers make passes across the field. Using machine learning, it analyzes thousands of images to generate crop and weed maps, along with plant stand counts.

The system was first introduced in a limited rollout in 2022 and went through on-farm testing before expanding more broadly. Early versions were installed on a small number of farms to gather data and refine the technology.

“We spend a couple of years using the product in the field before it’s commercialized,” CEO Cory Willness said.

“By the time something gets commercialized, it has already been used internally and has been through pretty rigorous testing.”

Adding in-season data to zone maps

SWAT Cam is designed to complement the company’s core SWAT Maps platform, which divides fields into management zones based on soil, water and topography. While those maps are relatively static, SWAT Cam adds a layer of in-season observation.

As the sprayer moves through the field, cameras mounted on the boom capture images every 50 to 60 feet. Those images are processed to measure plant populations and identify weed pressure and are then overlaid onto existing zone maps.

“It’s really a tool that uses the SWAT Map as the base underneath to define what’s happening in different areas of the field,” he said.

The system is not designed to make real-time decisions. Instead, it provides information that farmers and agronomists can use to evaluate performance and adjust management in future seasons.

For example, growers can use the data to compare expected and actual plant stands or identify patterns in crop performance across different parts of a field. In some cases, that can lead to changes in seeding rates or other input decisions.

“It’s information that helps them make better decisions in the future,” he said.

“It’s like a quick check-up tool.”

Adoption to date has been concentrated in Western Canada, where the company operates both directly with farmers and through a partner network.

The technology can be used on crops such as canola, wheat and soybeans, although its effectiveness depends on crop stage and canopy conditions.

The milestone offers a snapshot of how Croptimistic’s platform is expanding beyond its original focus on soil-based mapping.

In recent months, the company has introduced a series of new initiatives aimed at building out that platform, including SWAT Labs, an in-house soil testing facility, and a white paper outlining its approach to regenerative agriculture.

Together, those efforts point to two sides of the company’s development — expanding its core services while building new tools and frameworks around them.

“We have what I call an innovation engine and a business engine,” Willness said.

SWAT Labs is an example of the “business engine,” reflecting an effort to bring more of the soil data pipeline under one roof, from sampling through analysis.

The white paper, meanwhile, falls under “innovation,” and signals a push to shape how that data is interpreted and used in agronomic decision-making.

“These initiatives are building toward bigger things,” he said.

CLARIFICATION, April 7, 2026: Cory Willness’ name was accidentally left out of the print version of this article in the April 9 issue. We regret the error.

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As participation in on-farm research grows across the Prairies, researchers are working to strengthen how strip-trial results are analyzed so farmers can make more confident decisions.

A recent panel at Ag Days in Brandon offered a snapshot of where on-farm research stands today.

Farmers involved in Manitoba Pulse and Soybean Growers’ On-Farm Network shared their experiences and why they continue to participate.

WHY IT MATTERS: Improving how those trials are designed and analyzed can make the results more reliable and help growers make better management decisions.

Simon Hodson, who runs Rosebank Farms in Lenore, Man., said the value isn’t necessarily a breakthrough yield response — it’s confidence.

“It’s not an emotional choice, it’s a data-backed decision,” he said.

A null result can still be useful

Andrew Doerksen of Beaver Creek Farms at McGregor, Man., and Jayden Buchanan, who farms near Crystal City, Man., echoed that sentiment.

Several panelists pointed to “no statistical difference” results as some of the most useful outcomes. While that finding can feel anticlimactic, it often confirms that an added input or higher rate isn’t delivering enough return to justify the cost.

Soybean planting rates were one example.

Trials showed similar final plant stands across a range of starting populations, giving growers confidence to reduce seeding rates and save on seed costs.

Inoculant trials also showed little consistent yield benefit in many cases. With tight margins and rising input prices, those null results translated directly into savings.

READ MORE: On-farm research translates crop breakthroughs into ‘farmer speak’

Chris Forsythe, on-farm network agronomist with Manitoba Pulse and Soybean Growers, said most trials do not produce dramatic yield differences.

“Maybe 10 to 20 per cent of the time there is a difference, but 80 per cent of the time there isn’t,” he noted. Used carefully, that information helps growers avoid unnecessary inputs, extra passes or equipment purchases.

In one Manitoba Pulse and Soybean Growers trial on Doerksen’s farm, residual nitrogen spikes proved less consequential than expected, suggesting soybeans may tolerate more fluctuation than previously assumed.

Other trials have revealed subtler insights. In a wheat PGR trial on Hodson’s farm, yield did not change, but plant height did.

“If we weren’t working with the agronomists, we wouldn’t have been able to gain that information, and we might not have realized the value in that product,” said Hodson.

Strengthening trial design

Across the panel, the common thread was not chasing yield gains but narrowing uncertainty. Replication across multiple farms and public reporting strengthened certainty that findings were not local anomalies.

However, realism comes with a tradeoff.

WATCH: AgGronomyTV: Evaluating on-farm research

Field-scale trials capture the variability farmers live with, yet that same variability can make results harder to interpret. Long strip trials, differences in soil zones and yield monitor lag — the delay between crop entering the header and yield being recorded — can all mask real treatment responses.

A project funded by the Western Grains Research Foundation, SaskOilseeds, Saskatchewan Pulse Growers and SaskWheat and led by University of Saskatchewan professor Steve Shirtliffe, is focused on improving how on-farm trials are designed and analyzed.

Research officer Racquelle Peters, who manages the project, said on-farm research fills a gap that small-plot trials cannot. While small-plot research provides generalized recommendations under controlled conditions, field-scale strip trials reflect commercial realities.

“It feels more real to them, and there’s a good reason for that,” said Peters.

READ MORE: A whole new approach to on-farm research

“When you have that small plot research, which is also very valuable, they’re able to provide generalized recommendations, whereas, with the on-farm trials, you get specific recommendations, and that is very meaningful to farmers.”

Most on-farm trials follow a structured strip-trial layout designed to compare treatments fairly across a field. Improving how that framework performs under real field conditions is a central goal of Shirtliffe’s research team.

“What we’re doing is that we’re looking at ways to optimize that, using data that already exists,” said Peters.

Part of that effort involves re-evaluating older trial data with updated analytical tools, testing whether different approaches can strengthen the conclusions drawn from farmer-run trials.

Working at field scale means working with the variability farmers manage every season. That realism can make subtle treatment effects harder to detect.

The project is exploring approaches intended to improve sensitivity without sacrificing the practical advantages of on-farm trials.

Improving field-scale sensitivity

One method, the modulated on-farm response surface experiment, replaces single-rate strips with smooth ramps of application rates within a single pass. That allows researchers to analyze responses as a curve rather than a simple comparison of averages, improving sensitivity when identifying optimal input rates.

“I think of like turning one strip into a dozen mini-plots without any borders,” said Peters.

For fixed-rate decisions, such as fungicide application, the project is also testing precision strip trials that alternate treated and untreated segments within a single pass.

READ MORE: Sask. producer learns from his own on-farm trials

Varying the length of those segments helps account for yield monitor lag and allows spatial analysis to separate real treatment effects from background noise.

“It’s kind of like an on-off treatment system,” Peters said.

Keeping trials farmer-friendly

Peters said improving trial design isn’t about making on-farm research more complicated for growers. Most modern equipment already supports variable-rate prescriptions and precision application, so many of the improvements focus on making better use of the data already being collected.

That matters because on-farm research only works if it fits into normal operations. At the Ag Days panel, growers repeatedly stressed that trials must be practical and easy to integrate into busy seasons.

“The goal is to get precise, trustworthy recommendations that reflect their local conditions,” said Peters.

The post Prairie on-farm research programs refine strip-trial methods for clearer results appeared first on Grainews.

Launched in 2019, the program pairs Deere with hand-selected startups for year-long, project-based collaborations designed to test how emerging technologies perform in agricultural and construction use cases. It is not primarily an acquisition or investment vehicle.

“We’ve intentionally designed it that way,” said Colton Salyards, who manages the program within Deere’s corporate development and strategy group.

“The program was never designed to be an investment or an acquisition vehicle.”

WHY IT MATTERS: Emerging sensing and AI technologies could eventually improve soil analysis, equipment uptime and precision decision-making on farms.

Instead, Deere and each startup define a joint project, outlining objectives on both sides and evaluating how a given technology might perform in agricultural or construction use cases.

With the addition of this year’s five companies, Deere will have worked with 42 startups through the program.

Each year, Salyards said, public announcements of the cohort generate significant inbound interest from startups hoping to participate. The response can be “overwhelming,” but the companies selected stand out.

“There’s a key reason why we’ve selected them,” he said.

“There are use cases across agriculture that we believe could be of tremendous customer value.”

Sensor sensibility

Among the 2026 cohort is Australian firm resonAg, which is adapting miniaturized MRI-based sensing technology — technology originally developed for medical imaging, and later adapted for industries such as mining and oil and gas — for use in advanced soil sensing.

Deere is exploring how that sensing capability could support precision agriculture applications.

“This is of huge importance for precision agriculture,” he said.

“Imagine a planting system that can sense and act in real time to conditions across the field.”

Another company, AIRS ML, is developing edge-AI systems that combine machine sensor data with on-device machine learning to predict equipment failures in real time. The goal is to improve uptime by identifying potential maintenance issues before they lead to breakdowns.

The remaining companies in the cohort include:

• IoTag, which focuses on telematics and mixed-fleet performance insights.
• TorqueAGI, which is developing AI foundation models for robotics.
• Aerobotics, which applies drone imagery and computer vision to specialty crop production.

While not designed as an acquisition vehicle, the program has, in two instances, led to investment or acquisition when the strategic fit aligned. Salyards emphasized that integration into Deere equipment is not the default outcome.

“This is one vehicle among many that we use to understand what innovative companies are out there,” he said.

“Ultimately, it helps us determine how well those technologies could fit for our ag and construction customers.”

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The finding addresses a question that has surfaced in U.S. research and among Prairie growers managing high-pH soils: does choosing a low IDC score come at the cost of yield where chlorosis is not present?

“We didn’t know the answer to this question until just now,” U of M researcher Kristen MacMillan said during a presentation at Ag Days in Brandon.

WHY IT MATTERS: Understanding how variety selection affects yield helps farmers make more confident decisions in challenging soil conditions.

“It’s a highly visual condition,” said MacMillan, who is also Manitoba Pulse and Soybean Growers’ agronomist in residence.

“We’re choosing varieties based on their visual response, but what is the actual yield correlation to that?”

IDC is a common issue in calcareous, high-pH soils, where iron becomes chemically unavailable to the plant.

The condition causes yellowing between the veins of young soybean leaves, typically appearing in patches and lasting from mid-June into July. While symptoms may only persist for a few weeks, early-season stress can reduce yield potential.

How much yield does IDC cost?

To understand how IDC severity translates into yield loss, MacMillan collaborated with Manitoba Agriculture to analyze six years of data from single-row plots rated annually for IDC response near Winnipeg. Those plots were taken through to harvest to compare visual scores with final yield.

The analysis confirmed that yield declines as IDC scores increase in affected areas.

MacMillan reported a yield loss of roughly 1.5 to 2.8 bushels per acre for every one-point increase in IDC score. In practical terms, a two-point difference between varieties could mean a three- to six-bushel swing in IDC-prone zones.

Is there a yield trade-off?

The more pressing question, however, was whether selecting for low IDC scores sacrifices yield elsewhere in the field.

Many growers report IDC often affects only portions of a field, yet variety decisions are made for the entire field. Research in North Dakota and South Dakota has identified yield trade-offs in some soybean populations, where selecting for IDC tolerance reduced yield under non-IDC conditions.

To test whether that trade-off exists under Manitoba conditions, MacMillan established paired trials in IDC and non-IDC areas of the same field using identical varieties. She also identified a common set of varieties grown over three years to ensure consistency in comparisons.

“What we’re finding is that yield is also negatively correlated with IDC score or not related at all. So this is good news,” she said.

In other words, varieties with strong IDC tolerance performed well in affected areas without yielding less in unaffected parts of the field.

MacMillan also examined whether precision-planting different cultivars in IDC and non-IDC zones would provide an advantage.

Because no yield penalty was detected, splitting varieties within a field offered little benefit in most scenarios. Only in fields almost entirely affected by IDC did a particularly strong cultivar show a measurable advantage.

“If IDC is a constraint in your fields, continue choosing varieties with low IDC score and high yield,” she said.

For growers managing high-carbonate Prairie soils, the data reinforce current practice: selecting IDC-tolerant varieties remains the most reliable defence without sacrificing yield potential where chlorosis never appears.

The post Selecting IDC-tolerant soybeans doesn’t reduce yield, Manitoba study confirms appeared first on Grainews.

Artificial intelligence, automation and data systems dominated nearly every session, from crop protection to robotics to biotech discovery.

However, beneath all that, one quieter theme kept surfacing.

A lot of the early, practical value of these systems is not in running machines. It is in interpreting data and turning it into recommendations.

WHY IT MATTERS: As AI tools take on more of the data work, farmers will still need trusted advice to turn those recommendations into decisions that work in their fields.

In fact, based on the discussions at the summit, that part of the conversation was in the rear view mirror. Much of the focus now is on what comes next — building systems that can act on those recommendations.

Soil tests, weather stations, satellite imagery, equipment data is familiar ground for agronomy. What is changing is how quickly and how consistently that information can be processed.

In one session about biotech discovery, speakers described AI systems that can design and refine experiments with minimal human input.

It is a long way from a Prairie field, but it is easy to imagine that same approach being used to improve plot trials or even guide on-farm decisions aimed at maximizing yield.

And it is already happening.

On the farm, that same capability is showing up in decision support — not perfect, not complete, but improving. These tools are getting better at taking large volumes of information and turning it into clear, actionable decisions.

From interpretation to action

And that raises a fair question. If more of that interpretation work can be done by a system, where does that leave farm agronomists?

The answer is not that they disappear. It is that the job shifts.

Research agronomists are not really in the crosshairs here. They are still building the knowledge base. The question is what happens to the people turning that knowledge into decisions on the farm.

That kind of agronomy has never just been about reading numbers off a report. It is about context: knowing the field, the farmer, the equipment and the risks they are willing to take.

A recommendation generated from data still has to be weighed against reality. Is the field fit? Does the timing work? What happens if the weather turns? Does it fit the rest of the rotation?

Those are not problems that go away with better models. In some ways, they become more important because more recommendations are coming, faster and with more confidence behind them.

What these systems may change is how agronomists spend their time. Less time pulling data together. Less time building base recommendations from scratch. More time stress-testing those recommendations, adapting them to local conditions and helping farmers decide what to act on and what to ignore.

There is also a practical layer to this that did not get as much attention on stage. These tools do not just appear on farms fully formed. They need to be set up, calibrated and understood. Someone has to translate them from a product into something that actually works in a field.

One discussion on soil health touched on a more basic issue: even something as fundamental as soil testing is not fully standardized. Results can vary depending on how samples are taken, handled and processed.

That is an opportunity.

It suggests there is still a role for the local private agronomist — someone who knows the region and their customers, understands local soil conditions, along with insect and disease pressure, and someone who farmers know personally and trust.

The role doesn’t disappear, it changes

It is easy to frame new technology as a threat to existing roles, but agriculture has22s a way of absorbing new tools and reshaping the jobs around them.

GPS did not eliminate the nesed for farm agronomists. Variable rate did not either. They changed the conversation.

This one feels different. These systems are starting to take on the interpretation work that has traditionally defined farm agronomy. However, the pattern is familiar.

The technology is moving quickly, that much is clear. However, it is still being tested against the same reality. Fields, weather and economics have a way of exposing weak ideas.

On-farm agronomy does not sit outside that process. It is part of it.

If anything, the need for people who can bridge the gap between what a system suggests and what actually works on the ground will only grow.

The post How AI is changing on-farm agronomy and decision-making appeared first on Grainews.

Manitoba corn growers have long relied on weed-management research from Ontario or the U.S. Midwest, even though growing conditions rarely match what farmers see in their own fields.

A new set of trials by U of M researcher Loveleen Kaur Dhillon is set to change that.

WHY IT MATTERS: With most corn-based weed guidance borrowed from other regions, Manitoba growers need local research to fine-tune their spray timing.

Dhillon is in her first year as the university’s agronomist-in-residence (special crops), a five-year applied research role funded through the Manitoba Crop Alliance (MCA).

The position covers three “special crops” as defined by the program — corn, sunflower and flax — which are considered special because of their relatively low acres in the province, despite their potential.

Coming into the role with agronomy and plant breeding training, Dhillon said that aside from corn, which she had worked with during her master’s research in India, everything else was a fresh start.

She admitted she was nervous early on but settled in quickly once fieldwork began and she could see how producer-driven the program would be, allowing her to focus on basic, but essential, agronomy questions.

“I get to work on all those fun projects,” she said.

That farmer-facing element is central to how she sees her role.

Dhillon said the MCA partnership gives her a clear sense of grower priorities and helps her shape the work around what producers want studied.

Among this year’s work were two corn studies conducted at three Manitoba sites: Carman, Melita and Arborg.

In the first study, Dhillon used three widely grown hybrids and planted them on different dates to see whether adjusting seeding windows might influence how corn fits into the province’s shorter warm period.

The second study focused on the critical weed-free period, which is the window before early-season competition starts to cut into yield. Dhillon wanted to see how U.S. and Ontario recommendations hold up under Manitoba conditions.

She divided the work into two complementary approaches: one that let weeds grow for set periods before removal, and one that held plots weed-free for set periods before allowing weeds back in.

She said the work is also meant to help growers spray only when it matters most, making weed control more efficient, cost-effective and sustainable over the long term.

A season of contrasts

The three sites offered three distinct pictures of the growing season.

Melita had favourable weather, giving clean comparisons across weed-removal timings.

Carman had heavy weed pressure, which made the contrasts more obvious, even visible from the field edge and in drone images.

Arborg, however, was dry for much of the season, and the crop there looked very different from the other sites. Weed density and species composition also shifted under drought, which changed how the competition played out.

Dhillon said that although the conditions were challenging, the variation itself added value. Each site contributed a different piece of the puzzle, helping her understand how Manitoba’s range of environments might influence weed timing.

She hasn’t analyzed the data yet and won’t make recommendations until she has accumulated more site-years. Even so, based on differences seen in the field, Manitoba conditions don’t appear to mirror the conditions on which U.S. and Ontario recommendations are based.

Farmers who have managed corn here for years already know some of those discrepancies from experience; Dhillon’s first-year observations simply reinforce that Manitoba’s conditions deserve Manitoba-made research.

With more data coming next year, and with all three special crops under her long-term mandate, Dhillon said she hopes to give growers clear, locally grounded guidance they can use in their day-to-day decisions.

For now, she has something just as important: proof of concept that the province’s unique conditions behave differently enough to justify a made-in-Manitoba approach — and the beginnings of a program built to deliver it.

“The differences are quite clear,” said Dhillon.

“The protocol and the design of the experiment really worked.”

The post Corn research looks for Manitoba-based weed control appeared first on Grainews.

That was one of the central messages from Michael Wunsch, a plant pathologist with North Dakota State University, speaking at CropConnect 2026 in Winnipeg in February.

Fungicides do not protect future growth. They only protect the canopy that exists at the time of application.

“When you spray, you’re protecting the canopy that’s there,” Wunsch said.

“All that new growth is unprotected.”

That biological reality has implications for fungicide timing, especially if more than one pass is planned.

Bloom stage isn’t the whole story

White mould develops when small, mushroom-like structures form beneath the canopy in moist soil. Wunsch said growers need five to seven days of sustained soil moisture in the top inch of soil as crops enter bloom to produce spores.

Infection occurs through senescing blossoms. Once a blossom dies and forms a small pin-shaped pod, the plant becomes susceptible.

“The per cent of plants with pin-shaped pods is the per cent of plants in a susceptible state,” he said.

Because of that, he uses the percentage of plants with initial pin pods as a guide for fungicide timing.

However, timing isn’t just about bloom stage. Growers also need to think through their season-long plan.

“When you spray should be determined by the number of applications you plan to make,” Wunsch said.

One pass: wait for more canopy

In black and pinto bean trials conducted under high disease pressure, Wunsch’s team tested different timings based on the percentage of plants with pin pods.

When only one fungicide application was made, early applications performed poorly. Spraying at first bloom or before significant pin pod development protected only a small portion of the canopy.

During early bloom, beans are growing rapidly. Within days of an application, plants can be significantly taller and wider. That new biomass is not protected.

If only one application is planned, Wunsch said growers should generally wait until a high percentage of plants have initial pin pods — often 60 to 100 per cent — before spraying, assuming conditions favour disease.

Applying too early sacrifices protection during the period of maximum susceptibility, when the canopy is full and moisture is trapped within it.

Two passes: move earlier

The logic shifts when a second application is planned.

With a two-pass program in dry beans, Wunsch found the first spray often performed best when applied at roughly 30 to 50 per cent pin pod and sometimes as low as 10 per cent under higher-risk situations.

The reason is that the second application protects the new growth that develops after the first spray.

“You don’t want to sacrifice those early infections,” he said.

In this case, the grower is no longer choosing between early and late protection. The second pass covers the expanding canopy.

However, there is still a penalty for going too late.

“Applications must be made prior to pathogen infection,” Wunsch said, adding that once the pathogen has invaded the plant, fungicides cannot eradicate it.

Three passes under high pressure

In high-pressure pinto and kidney bean environments, particularly under sustained cool and wet conditions, Wunsch’s trials showed that three applications — often seven to 10 days apart — provided the most consistent control. Under those conditions, the first application was made earlier, at first bloom, before significant pin pod development.

Subsequent applications protected new growth, and shorter intervals improved consistency under elevated disease pressure.

Even so, three passes did not eliminate the disease.

Soybeans follow the same rules

Although white mould in soybeans is more sporadic on the Prairies than in dry beans, Wunsch said the same principles apply. He recommended that a single application be made when 100 per cent of plants reach the R2 growth stage unless canopy closure occurs earlier. In that case, application should coincide with canopy closure.

As in dry beans, the decision depends on risk. If conditions do not favour white mould as the crop enters bloom, he advised waiting until they do.

Practical field scouting

Wunsch offered a simple method to assess pin pod development.

Walk into areas of the field where white mould risk is highest. Examine 10 consecutive plants in a row and count how many have pin pods. Repeat that in at least 10 locations across the field.

That percentage provides a practical indicator of crop susceptibility and can guide timing decisions.

He also urged growers to pay attention to droplet size when applying fungicides, saying it can “make a world of difference” in efficacy.

However, even with precise timing, optimized droplet size and multiple applications under high pressure, white mould was never entirely suppressed in his trials, indicating the resilience of the pathogen under current management practices.

“White mould control isn’t that good,” said Wunsch.

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The practice is commonly treated as a get-it-done-early job, with fields rolled soon after seeding to push down stones and smooth the surface.

Extension guidance for post-emergence rolling has typically urged caution, often pointing to the first trifoliate stage as a safer window while also emphasizing the role of soil and weather conditions.

WHY IT MATTERS: Risk of yield loss from bent and broken plants is one thing, but risk of damage from squashing your soil should also be considered.

However, an ongoing study from the University of Manitoba is taking a stage-by-stage look at how that risk develops. The work is helping define the post-emergence window more clearly, showing low risk early and rising damage if rolling is delayed.

A multi-year study led by U of M researcher Kristen MacMillan, with support from Manitoba Pulse and Soybean Growers, tested rolling soybeans across a wide range of crop stages, from post-seeding through flowering, to better understand where that flexibility ends.

The results show a clear window where post-emergence rolling causes little damage and no yield loss — and a sharp line where risk rises quickly.

Rolling is standard practice on many soybean farms, particularly on stony ground. The goal is to protect low-hanging soybean pods and reduce harvest losses by smoothing the seedbed.

However, MacMillan said rolling can also create unintended soil problems.

“We’re crushing those soil aggregates,” she said.

“We’re dispersing them into very fine particles.”

That can lead to surface sealing and poor infiltration during rainfall events, a problem in years when moisture is already limited. It can also increase the risk of wind erosion, especially on finely worked ground.

Those risks prompted the team to ask a simple question: if rolling has downsides, how long can growers safely delay it?

The study compared an unrolled check with rolling at multiple soybean stages: post-seeding, emergence, cotyledon, unifoliate, V1–V2, V3–V4 and flowering.

Rolling was also done under different conditions, including warm, sunny days and cooler, cloudy ones, when plants are more brittle. The roller used in the trial was slightly heavier than most commercial rollers, creating a conservative test.

At the cotyledon stage, damage was minimal.

“Only about one per cent of the plants in the plot were broken,” MacMillan said.

“This was really surprising.”

She noted that the seed furrow plays an important protective role early on. Plants emerging within the furrow were often shielded from the roller, while damage was more likely where the furrow was flattened by tractor tires.

At the unifoliate and early trifoliate stages, results were similar. Plant breakage remained low — generally less than three per cent early, and still less than 10 per cent through V2 — with no yield loss observed.

“Plants were bouncing back very nicely,” she said.

As soybeans advanced toward V3 and V4, damage increased sharply, with tire tracks playing a big role in plant breakage.

By the third to fourth trifoliate stage, about 17 per cent of plants were broken overall. Within tire tracks, damage climbed to 24 per cent, compared with about nine per cent in undriven rows.

“More than double most of the plant damage is happening from the tire tracks,” MacMillan said.

Yield losses followed the same pattern, increasing as rolling was pushed later into the season.

At flowering, results were unequivocal. Nearly half of all plants were broken when rolled at R1, with severe stem damage visible immediately after the pass.

“That was really late,” MacMillan said.

“Those plants did not look happy.”

Based on two years of data so far, the study points to a practical takeaway: growers have roughly a two- to three-week window after emergence where rolling can still be done safely.

Under Prairie conditions, that typically means the first three weeks of June, when soybeans range from unfolded cotyledons through V2.

Rolling beyond that point carries rising risk, especially once soybeans reach the third trifoliate stage and tractor tire damage becomes unavoidable.

MacMillan said the work is ongoing, with one more year of data still to come. However, the pattern has been consistent.

“There is a window,” she said.

“They can be rolled post-emergence, and that can help reduce those soil impacts.”

The post When post-emergence soybean rolling works, and when it doesn’t appeared first on Grainews.

That was the core message Brendan Metzger delivered at the Manitoba Agronomists Conference.

The chemistry itself, he said, has not suddenly changed. What has changed is the cropping context around it, particularly as glufosinate moves into systems that expose management mistakes more quickly and more consistently.

WHY IT MATTERS: With glufosinate use expanding on the Prairies, careful management will matter more in slowing resistance pressure.

Metzger, a senior herbicide biologist with BASF, said the risk facing Liberty is real and accelerating. Glufosinate resistance has already emerged in other regions, and Prairie farmers are now using the product in crops and rotations that strip away many of the safeguards that once kept resistance at bay.

Reports of glufosinate-resistant waterhemp in several U.S. Midwest states, and kochia escapes being reported in North Dakota, suggest resistance is now close at hand.

Liberty still works, he said, but the margin for error is narrowing.

Longevity so far

To understand why management now matters so much, Metzger first walked agronomists through why glufosinate avoided resistance for so long in Western Canada, especially when compared to glyphosate.

Glufosinate was introduced in the mid-1990s, at roughly the same time glyphosate-tolerant crops entered the market. Yet while glyphosate resistance emerged relatively quickly, Liberty avoided that outcome for nearly 30 years.

“It’s been largely a success story,” Metzger said.

“There’s been no documented cases of resistance to glufosinate in Western Canada.”

He said that longevity had little to do with glufosinate being inherently resistance-proof. Instead, it reflected how and where it was used.

For much of its commercial life, glufosinate lagged behind other herbicides in total acres treated. Lower overall use meant lower selection pressure on weed populations. Just as importantly, most glufosinate applications in Western Canada occurred in canola.

Canola’s competitiveness played a quiet but critical role.

Rapid early growth and quick canopy closure suppressed escapes and reduced the number of weeds exposed to sub-lethal doses. That cultural weed control helped mask small mistakes that might otherwise have contributed to resistance.

“So we have the cultural weed control aspect working in our favour as well,” Metzger said.

Rotation added another layer of protection. Even in relatively simple canola–wheat systems, glufosinate was rarely applied back-to-back on the same acres. Breaking up modes of action further reduced resistance risk.

Those factors combined to give Liberty a long runway, Metzger said, but that runway is now shortening.

Less competitive

Metzger warned that as soybean acres expand, so will selection pressure on glufosinate.

While Liberty-enabled canola already accounts for a large share of Prairie acres, Metzger said the more consequential shift is happening in soybeans as seed companies move aggressively toward glufosinate-tolerant platforms across North America.

Roughly a quarter of western Canadian soybean acres are expected to be Liberty-enabled in 2026. Metzger said that expansion is being driven largely by widespread glyphosate resistance, with glufosinate long viewed as a relatively underused alternative.

Unlike canola, soybeans are far less competitive.

Wider row spacing and slower canopy closure mean fewer escapes are hidden. Weeds that survive an application are more likely to remain visible, reproduce and contribute seed back to the soil.

Corn shares some of those same characteristics. In those systems, Metzger said, poor management is more likely to translate directly into resistance risk.

Another concern for Liberty is that its mode of action amplifies the consequences of poor application.

Glufosinate is a contact herbicide. It only affects weeds it lands on, and those weeds must receive a lethal dose to be killed. That makes the product especially vulnerable to sub-lethal exposure.

“A sub-lethal dose, whether that means not adding enough product to the sprayer or not getting it to the target at the proper dose, can select for resistant individuals over time,” said Metzger.

Risk management

Delta T, which relates spraying conditions to air temperature and humidity, is particularly important for water-based formulations such as Liberty, said Metzger.

Compared to oil-based products, glufosinate droplets take longer to cross the leaf cuticle, increasing the risk that moisture evaporates before the active ingredient can move into the plant.

Metzger said Liberty remains an effective tool, but he cautioned against assuming it will behave the same way it did when most acres were in canola.

As more soybean and corn acres shift toward glufosinate tolerance, resistance risk will be shaped less by the chemistry itself and more by how consistently it is managed.

Coverage, timing and weed size are no longer details to fine-tune, Metzger said. They are the difference between preserving the tool and quietly selecting for trouble.

Liberty still works, but on today’s Prairie farms, it no longer forgives mistakes.

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“Some positive news coming out of Beijing, which is great,” said Delaney Ross Burtnak, executive director of Manitoba Canola Growers Association. “This is a preliminary announcement at this point, so there’s still some work to do to understand what it means and what the final decision will be.”

The proposed agreement would ease tariffs on Canadian canola as part of a broader trade package between Canada and China, raising hopes for improved market access after months of disruption.

Ross Burtnak welcomed the significant reduction of canola seed tariffs and the expected elimination of the tariff on canola meal.

“That’s good news,” she said. “We’re not sure what’s happening with canola oil, so we need to understand that a little further.”

Ross Burtnak said tariffs have affected farmers most clearly through price and uncertainty. She noted there appeared to be an uptick in canola prices following news of the proposed tariff reductions, but said the bigger concern over the past 17 months has been whether farmers would be able to sell their canola at all.

“If the elevator or exporter doesn’t have a market to sell that canola into, they’re not going to be buying it from farmers,” she said. “This decision helps prevent that worst-case scenario.”

Ross Burtnak said the announcement offers some reassurance after a prolonged period of uncertainty for canola growers.

“There’s definitely some cautious optimism with this news this morning,” she said.

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