This might sound dramatic, but it’s becoming a real possibility for Canadian farmers. As agriculture embraces automation, cloud platforms and remote monitoring, the risks of cyberattacks are growing — and most farms aren’t ready.

In fact, a recent study by MNP and RealAgristudies found that only seven per cent of farmers say they feel very knowledgeable about cybersecurity and nearly 80 per cent don’t have an incident response plan. And while tech adoption is accelerating, basic cyber hygiene often lags.

So, what should you do if your farm goes offline? And more importantly, how can you prevent it from happening in the first place?

The new front line: Cybersecurity in agriculture

Farms today are more connected than ever. Robotic milking systems, GPS-enabled ear tags, automated feeding and cleaning systems, and cloud-based management platforms are all part of the modern operation. These tools bring efficiency, but they also create new vulnerabilities.

Take automated milking systems, for example. Many people use proprietary communication protocols that aren’t encrypted. That means a hacker could intercept or alter commands, disrupting the milking process and potentially harming cow health.

Or consider the sensors monitoring barn temperature and humidity. If those devices still use default passwords (which many do), they’re easy targets. A cybercriminal could manipulate the data, leading to poor decisions or even equipment failure.

Even GPS tracking isn’t immune. Spoofing or jamming signals from cow ear tags can throw off herd management, delaying health interventions or causing animals to go missing.

And then there’s the cloud. Many farms rely on cloud-based platforms to manage everything from herd health to finances. But weak authentication or misconfigured access controls can leave critical data exposed or even enable attackers to shut down operations remotely.

Real risks, real consequences

The impact of a cyberattack on a farm isn’t just technical; for the modern farm, it’s deeply operational. If your feed system is compromised, cows might be underfed or overfed. If your cleaning schedule is disrupted, hygiene suffers. If your milk cooling system is tampered with, spoilage can occur before you even realize there’s a problem.

These aren’t hypothetical scenarios. They’re increasingly common in sectors such as dairy, where automation is widespread, but cybersecurity isn’t always top of mind.

And the consequences go beyond the farm gate. A breach in your supply chain tracking system could delay deliveries, tamper with safety data or damage your reputation with buyers and consumers.

Building a cyber-resilient farm

Now that we’ve got the bad news out of the way, the good news is that you don’t need to be a tech expert to protect your farm. Cyber hygiene starts with a few simple, practical steps:

• Change default passwords on all devices. It sounds basic, but it’s one of the most common entry points for attackers.

• Make sure your systems, especially those controlling feeding, cleaning and environmental conditions, are running the latest firmware. Updates often include security patches that close known vulnerabilities.

• Segment your network so that your IoT devices (such as sensors and trackers) aren’t on the same system as your business operations. That way, if one part is compromised, the rest remains protected.

• Don’t forget about data encryption. Whether it’s temperature readings or herd health records, secure transmission helps prevent tampering.

• It’s worth investing in monitoring tools that can flag unusual activity, such as a sudden spike in barn temperature or a feed schedule that doesn’t match your usual routine.

• Limit remote access. If vendors need to log in to your systems, make sure it’s done securely and that you know exactly who has access and when.

What happens if you’re hit?

Even with safeguards in place, no system is bulletproof. That’s why having an incident response plan is critical.

Know who to call, whether it’s your IT provider, your insurance broker or a cybersecurity expert. Have a checklist of systems to shut down, data to back up and steps to take to get back online.

In terms of insurance, make sure your policy covers cyber incidents. Many farms are underinsured in this area. Coverage should include data recovery, business interruption, legal costs and notification requirements. Increasingly, farmers are choosing specific cyber policies to protect their modern farm from modern risks. These policies typically also include coverage for payments that are made due to fraudulent payment requests.

The bottom line

Cybersecurity might not be the first thing you think about when you walk into the barn, but as technology becomes central to farm operations, it needs to be part of your daily management.

You don’t have to overhaul your entire system overnight. Start with the basics: strong passwords, regular updates and a plan for what to do if things go wrong.

Because when your farm goes offline, it’s not just about lost data. It’s also about lost time, lost product and, potentially, lost trust.

Meghan Mackenzie Bell is a seasoned farm insurance specialist with deep expertise in equine and agricultural coverage. As associate vice-president of sales for NFP’s equine and farm division, she leads strategic initiatives to enhance sales operations and streamline proposal creation, helping Canadian equine and farm clients protect what matters most. You can contact Meghan at meghan.mackenziebell@nfp.com

Is your farm hackable?

As newer digital technologies such as AI, robotics, drones, digital twinning and wearables are increasingly used in agriculture, cybersecurity is becoming a big issue for today’s farms and it’s one that isn’t being talked about nearly enough.

“I think farmers need to be aware that cybersecurity is an issue and it’s a growing issue,” says Dr. Emily Duncan of the department of sociology and social studies at the University of Regina, who recently published results of a survey of farmers and industry experts called I grow food, IT people do cybersecurity: Addressing cybersecurity risks in Canada’s agri-food sector.

“The basics of cyber hygiene — regularly updating passwords, using antivirus software, backing up files often — are things that more farmers need to be learning and implementing into their business practices,” she says.

Duncan has put together a checklist of some cyber hygiene best practices for farmers and retailers (see Cyber Hygiene Best Practices Checklist).

The agri-tech industry lags behind many sectors. Duncan says it needs to step up and make sure that when they are developing digital platforms for farmers that they have high cyber security standards in place, such as firewalls and multi-factor authentication.

“There is a lot of room to grow and when we are dealing with living systems, whether it’s animals or crops, they are fragile and in fragile environments,” she says.

“When we think about controlled environment agriculture, such as vertical farming or temperature-controlled barns with 40,000 chickens inside it, if someone hacks that, things can go wrong pretty quickly. Putting those protections in place is super important to protect farming businesses and food security.

— Angela Lovell, CG contributor

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According to the Canadian Agri-Food Policy Institute (CAPI), “Digital agricultural tools available to producers today have been proven to boost productivity and competitiveness and reduce environmental impacts with the potential to unlock a further $750 million to $1.5 billion in annual net revenue over the next decade.”

The rate of adoption can depend on any number of factors, for instance, the age of the farm owner, available labour, type of technology, type of operation and infrastructure. It could also depend on the cost to implement, potential return on investment, compatibility with existing technology on the farm and how available are the knowledge and skills needed to utilize the technology and the data it produces.

What’s driving digital technology adoption on farms?

Invariably, the reasons farmers adopt any technology is to improve productivity and efficiency, increase profits and help solve major pain points such as labour shortages. Staying competitive and reducing costs are major drivers.

“Farmers today are competing not just inside their province, or Canada, but internationally,” says Maryna Ivus, manager, economics research at the Information and Communications Technology Council (ICTC). “So, competitiveness is an important driver of technology adoption.”

Farmers across the board are struggling to find labour and existing technologies that have helped to address this issue for many producers. The digital era, with advancements in areas such as autonomous farming, remote sensing and sophisticated AI-driven systems to integrate and manage multiple functions and operations, could solve it once and for all.

“Whether it’s true automation technology or just more updated equipment that makes things run a little bit smoother, farmers are investing in what’s needed to allow the farm to operate,” says Phyllis MacCallum, senior program manager, research and knowledge mobilization, Canadian Agricultural Human Resource Council (CAHRC). “It can allow a production facility to continue on if they are short-staffed. And herd health is important whether you are in milk or beef production, so these technologies can allow farmers to monitor and ensure that the herd is staying healthy while they manage everything else.”

Setting the stage for autonomous agriculture

AI, machine learning and autonomous technology are at the forefront of technological trends in agriculture and many other industries. In agri-food, AI is being used for diverse applications from managing greenhouse operations to evaluating embryo viability in cattle.

“Automation and AI allow for 24/7 operations, which means constant quality control as well as safety control when it comes to worker performance, as well as reducing costs through things like precise use of fertilizers, water and other inputs,” says Ivus.

“AI-driven planning tools for co-ordinating field equipment are starting to gain traction, especially in Western Canada where large grain and oilseed farms rely on multiple machines working together,” says Godard, CEO and co-founder of Verge Ag, a company that creates AI-driven software designed to help farmers plan, simulate and streamline how their equipment operates in the field. The aim is to make existing equipment more efficient, ease the workload on operators by optimizing routes, and reduce costs by minimizing overlap and reducing fuel consumption.

“Since most farm equipment already comes equipped with GPS and autosteer, these optimized routes leverage existing capabilities, bringing us closer to a future of fully autonomous farming,” says Godard.

The tech can work for any type or size of farm, although larger farms tend to see the most immediate impact because even small efficiency improvements can lead to significant cost savings. However, benefits such as reduced overlap, lower fuel consumption and improved timing apply across the board.

Digital twin technology

Digital twin technology, while well established in the gaming industry, is a relatively new concept for agriculture. On its website, IBM describes a digital twin as “a virtual representation of a physical object or system that uses real-time data to accurately reflect its real-world counterpart’s behaviour, performance and conditions.”

“If you are looking to invest, to innovate and create better efficiencies on the farm, this technology has the ability to do that,” MacCallum says.

Whether you are bringing innovation in, or you are remodelling, you can use digital twinning technology to simulate what it would look like once everything is put in place, and assess whether that would create efficiencies and, overall, more profitability. It allows you to physically see how things will look in a 3D form before you execute.

Phyllis MacCallum
Canadian Agricultural Human Resource Council (CAHRC)

“For most of the people taking this program, digital twinning is a new technology, and they are learning about its capabilities. There is so much capability for the technology, no matter the farm or the application. There is always a way to incorporate this. The technology can be as simplistic or as complex as someone wants it to be.”

But digital twins are not just for planning; they also form the basis of a fully functional system connected to sensors, robots, cameras and other technology that can allow for continued remote monitoring and managing of operations. It could also be used to create virtual reality models for things such as health and safety training.

CAHRC is working with various partners and Palette Skills to offer a free 12-week training program called Seeding Digital Skills that introduces farmers and employees in agriculture and the food and beverage processing industries to digital twin technology. The program, valued at $12,000, is currently being funded by Upskills Canada.

“There is so much opportunity to co-ordinate with other applications like sensors, so it is monitoring the field and growth,” MacCallum says. “Or for sustainability questions in terms of crop production, to determine where the most efficient use of the land is, (for example) if you have marginal land, whether that needs to be left because it’s not returning an ROI or be put into a different level of production.”

Using AI to manage risk

A real-world example of digital twinning is offered by Agi3. The platform brings crop planning and risk management tools into one AI workflow. Farmers can create a field-level digital twin that connects with land, climate, management and market data to generate a risk profile and individualized insurance options.

“Farmers gain fair, individualized coverage and pricing that reflect their actual fields and practices, not provincial averages, so strong management is recognized rather than averaged away,” says David Hodge, chief strategy officer for Agi3 Group.

“With risk and coverage properly aligned, farms can invest in productivity-enhancing practices with greater confidence, instead of ‘farming to the average’ and leaving margin on the table.

“Claims are faster and more defensible because losses are verified with time-stamped, geo-referenced evidence, which improves program integrity and reduces friction. Agi3’s platform also provides a clean digital twin of the operation, simplifying planning and interactions with lenders, insurers and other partners. Overall, these elements deliver better protection, stronger economics and clearer, data-driven decisions for farmers.”

What is holding some farmers back from adopting digital technology?

CAPI’s report The Future is Digital: Digital Agriculture and Canadian Agriculture Policy, notes that adoption rates of digital technologies among Canadian farmers remain low due to factors such as poor rural connectivity, costs and uncertainty about the return on investment (ROI) and concerns over stewardship of the data that these technologies generate.

“If farmers are financing a technology, that is a risk, and that technology often requires additional finance for things like energy or additional infrastructure, for example broadband access. Securing an autonomous tractor doesn’t mean that you can utilize it tomorrow. There are additional expenses that sometimes are not clear. So, financial concerns are definitely number one for most farmers.”

Maryna Ivus
Information and Communications Technology Council (ICTC)

It’s often difficult to calculate the ROI of digital technology because it can take several years before benefits, such as productivity or profitability, start to show. Furthermore, some of the benefits can be intangible, such as improved safety.

“It has to be able to pencil out, whether that is over a number of years or over per head of cattle,” says MacCallum. “For producers who may only have a few more years in the industry, or those just entering the industry, they have to ensure that the investment that they’re making is worth the time and the commitment, and that in trying to find the efficiency, it doesn’t slow them down in profitability and production by investing too big or too fast. There is a lot to consider.”

Another big hurdle to adoption for many farm owners or managers is having the skills and knowledge to actually use these technologies and understand the data that they generate.

“It’s not about just acquiring the technology, it’s having someone who can use it and understand and analyze the data properly to make sure that it’s not underutilized,” says Ivus. “Someone who has the background in technology and agriculture is hard to find.”

Compatibility with other technologies already being used on the farm and ensuring that they can both connect and communicate with each other, can be another challenge. It may require some specialized skills to overcome but may also require farmers to think differently about how they approach getting the work done on their operations.

“The main hurdles are more about behaviour than technology,” says Godard. “Most farms already have the necessary hardware, for example, GPS, autosteer and precision guidance, but aren’t yet using planning software to co-ordinate machine operations across their fields. This requires a shift in how farmers approach their work, with more emphasis on planning digitally before heading into the field.”

There’s gold in the data

Digital technologies continuously create a monumental amount of data. Every operation in the field or cycle of production generates information that has tremendous value to help improve operations, offer solutions to create more efficiencies, identify and address problems, and create more profitability on the farm, but it’s not much use unless it has been properly analyzed and made useful. AI is going to play a big part in unlocking the ‘gold’ in that data.

“As producers innovate at a pace that’s comfortable for them, how do we ensure that they can harness the data that they are collecting?” MacCallum asks. “How do we ensure that data is available to them and that they can use it to better their production system? A producer who is busy running his operation doesn’t have time to sit down and look through thousands of data points, so how do we set up AI to analyze and generate reports or summaries that show the trends through this data collection so producers can better use that information?”

Who owns the data?

Farmers are understandably concerned about who actually owns the data that is being generated by all the technologies on their farms, where that data ends up and what is being done with it.

“It comes down to an issue of trust,” says Dr. Emily Duncan, department of sociology and social studies, University of Regina. She carried out a large-scale survey of 1,000 farmers across Canada around the adoption of digital technology, which was summarized in the report I grow food, IT people do cybersecurity: Addressing cybersecurity risks in Canada’s agri-food sector.

“Farmers had a lot of concerns around where the data goes once it leaves their farm, because end user license agreements, or the terms and conditions of using these platforms are not very clear about what that company can do with the data,” she says. “That does hold farmers back because the decisions that you make on your farm, how you get to that level of productivity, or what you use, is information that you might not want shared widely with third parties.”

Although farmers acknowledge that there is value to data sharing, Duncan learned that they are more comfortable sharing certain types of data than others.

“Farmers were more comfortable sharing environmental information like weather data that they might collect from an on-farm weather station, or soil data that they might collect from soil testing or soil mapping,” Duncan says. “When it came to data about decisions around use of inputs and productivity levels, these were types of data that farmers were much less comfortable sharing.”

It also matters to farmers how their data is shared. Farmers were most uncomfortable sharing raw data that comes off the sensors or implements on their farms. Once that data is uploaded to their service provider’s platform and is combined and averaged (called summarized data), they were a little more comfortable sharing it. The data they were most comfortable sharing was fully aggregated data that is pulled from many different farms in the region and remains anonymous.

Finally, Duncan asked who farmers are most comfortable sharing data with.

“Farmers were generally more comfortable sharing with industry groups, other farmers and researchers, and rated tech service providers as the actors they were least comfortable sharing data with,” Duncan says. “These are the people who have access to the data and are the people that farmers have little trust in.”

Dr. Emily Duncan
Department of sociology and social studies University of Regina

That could be because farmers are also skeptical about who is benefiting most from the data that they are subscribing to and paying for.

“Farmers aren’t really seeing any of the returns from the data that they are generating that these companies are making profits off,” Duncan says.

Despite all the misgivings that farmers may have about digital technologies, Duncan believes the industry is heading in the right direction.

“Farmers are interested in technology and are keen to improve their productivity and sustainability through new tools,” she says. “The challenge with new tools is sometimes they create a whole new set of problems, like issues around cybersecurity or trust and data sharing governance, but I think the industry is moving in the right direction in terms of trying to develop sector-specific solutions that empower farmers, and that is the most important thing.”

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But is AI everywhere except on your farm? Are you missing out on the new revolution?

Here’s the good news: You’re already using AI and other people are using it in ways that benefit your farm. So, taking the first step is not as scary as you might think.

But first, what exactly is AI?

Defining AI

There’s no single definition for artificial intelligence. AI is used in all kinds of ways to describe many different things. Generally, AI is a process where computers do something normally done by humans. This could be something complicated, like a computer model that forecasts climate change, or something simple like a heater that turns on when the temperature drops.

Some people default to thinking of “chatbots,” such as ChatGPT, when they think of AI. Chatbots are software programs that can answer questions based on information they’ve “read,” and sometimes generate new information.

There’s more to AI than chatbots, but chatbots are a key piece of the puzzle.

For this article, ChatGPT was asked to define AI for a farm audience, using an account personalized to use a “critical and sarcastic” tone. This is ChatGPT’s response:

Imagine a smart hired hand that never sleeps, doesn’t complain about the weather, and works from data instead of gut feeling. It can read soil maps, predict yields, plan spray timing, monitor livestock health, or even drive machinery — though it still can’t fix a seized bearing or find that one missing wrench in the shop. In short: AI uses information to make smarter, faster choices. The farmer’s brain is still the boss; AI just crunches the numbers faster than anyone with a coffee thermos ever could.

You’re already using AI

Dr. Felippe Karp, instructor and researcher at the Werklund School of Agriculture Technology at Olds College of Agriculture & Technology in Alberta, opens his presentations about AI by telling farmers that it’s not the future, “It’s the present.”

Do you use an app to check the weather? “Guess what?” Karp said. “There’s AI behind that.”

Machinery automation is also AI. “Auto-steering is one of the most adopted precision agriculture systems,” Karp said.

Auto-steer equipment is driven by an algorithm that uses data from satellites and field locations. The algorithm directs the machinery so it can steer without human intervention.

Automation in newer combines also uses AI. It’s changed combines to the point that, Karp said:

“Someone with no experience running the equipment can jump in there and run it.”

Given the shortage of ag employees Karp added, “This is quite amazing.”

Knowing we already use AI makes it easier to take the next step. “We need to demystify AI,” Karp said. “It runs in a hidden way where we don’t directly interact with it, but it makes our lives easier.”

Smartphone apps that identify weeds, insects and disease are also AI at work. “This can empower people that might not have the expertise to go in the field and do some scouting for you,” he said.

However, powerful AI doesn’t replace real farmers and experts. For example, Karp suggests, imagine your phone app misidentifies a bug. You still need a farmer or agronomist with field experience to detect errors.

“This critical thinking portion is key,” he said.

Karp and other instructors at Olds College are training students to think critically about results from AI and help students see where they can add value in a world of rapidly changing technology.

Researchers are using AI for you

Dr. Rozita Dara is the director of Artificial Intelligence for Food (AI4Food), a technology hub at the University of Guelph that promotes responsible development and use of AI in Canada’s ag and food sector. Dara agreed that Canadian farmers already use AI in many ways, most of which are rather simple to explain.

For example, many AI tools have been developed for greenhouses. “Because it’s a relatively controlled environment, it’s easier to develop AI solutions,” Dara said. AI-enabled equipment helps greenhouse managers decide when to spray and how much to irrigate.

In poultry barns, cameras connected to AI systems can monitor animals for stress. Human experts “teach” the systems what kinds of movements and behaviours to “watch” for before the system is operable.

“When we build AI solutions it’s always with humans in the loop,” Dara said.

More complicated cases

“Generative algorithms” don’t just analyze data; they also build on it to create new information. These algorithms are complicated, so the results can be less predictable than, say, a steering wheel that makes a turn if a rock knocks the tractor off its straight course.

Because they’re more complex, generative AI systems have been known to go off the rails and provide very incorrect results. This has been referred to as “AI hallucination.”

Because this can happen, we’ll always need people to verify complicated results. Dara encourages farmers to “trust the technology but also validate.”

Dara’s current project is an example of a complicated algorithm guided by humans. Dara and her team are combining several data sources to detect avian flu outbreaks in its early stages, with the goal of getting information to decision makers.

Their data includes everything from satellite images to social media posts. AI looks for patterns in reams of data, identifying correlations that humans might miss.

“Our goal is to extract risk factors from these data sets.”

Dr. Rozita Dara, director
Artificial Intelligence for Food (AI4Food)

Dara’s team can detect potential avian influenza outbreaks two or sometimes three weeks before it’s been officially confirmed. The extra time helps decision makers monitor and act before an outbreak becomes severe.

Meanwhile, scores of other ag researchers are using AI in their labs to analyze genetics for faster plant breeding, correlate satellite data with in-field information for optimal cropping information and speed up every area of ag research you can imagine.

It comes down to good data

Much of the work is less than glamorous.

“AI is 90 per cent data,” Dara said. “People don’t understand the effort we put into data cleaning. It’s 90 per cent of the work.”

Karp has also spent more than his share of time processing data for AI. “We have to guarantee that good data is coming in,” he said, referencing the “garbage in, garbage out” maxim of computer models.

For example, crop yield maps show variations throughout the field. “We know that this is based on sensors,” he said. “Sensors can get things wrong.” Yield maps are only useful after any sensor errors are found and corrected.

There is a lot of data to clean. But AI becomes more powerful when it has access to multiple data sets, what Karp calls “data fusion.”

For example, adding yield data to rainfall data, along with soil test and EC (electrical conductivity) data makes a database that would drown an Excel spreadsheet.

“Imagine how powerful this information could be if we were to build models based on this data.”

Dr. Felippe Karp
Werklund School of Agriculture Technology, Olds College of Agriculture & Technology

He believes data fusion will let AI empower ag decision makers at a new level, bringing on a “digital revolution in agriculture.”

It’s all coming together, but a lot of the work is still at the “data collection” point.

Eventually, data-empowered AI will identify patterns and forecast results, giving farmers better insights into questions such as: Do your strawberries need pest control? Is it a good time to price your feed barley?

“But who makes the final decision?” Karp said. “The farmers.”

Here’s how to start now

You can start your AI journey at home, right now, with Farm Credit Canada’s (FCC) chatbot designed just for Canadian farmers.

Nicole Hayes, director of FCC’s Innovation Hub, said FCC found “producers were feeling the gap in availability of advisory services across Canada.” A chatbot that could answer agronomy and farm management questions could fill that gap and also be a safe space for farmers to learn to integrate AI into their businesses. The first version of FCC’s chatbot called Root was released in July 2024.

“Root is a great starting point,” Hayes said.

“It’s free, it’s available to everybody. It’s a great tool for people to start becoming more comfortable asking questions and getting responses, engaging in that dialogue.”

Nicole Hayes, director
Farm Credit Canada Innovation Hub

Unlike other chatbots, with Root, Hayes said, “We can ensure that the dialogue that we’re engaging in is focused on agriculture.” FCC only allows Root to base its chats on reliable information. “We’ve done some of that fact checking and validation behind the scenes,” Hayes added.

Root can “chat” with farmers based on Agriculture and Agri-Food Canada information and databases, FCC information and other sources FCC deems trustworthy. “We’ve got quite a substantial database that exists underneath the surface,” she said.

For now, users might find Root’s answers to be a bit limited, but that will change. “We’re at the early stages of development. It’s something we’re continuing to build and expand on. We are continuing to expand the knowledge sources that we’re using and who we’re partnering with in the industry.”

Even more options

In October 2025, Wharton Business School listed the top chatbots used by business leaders to analyze data, summarize reports, make presentations and generate ideas. ChatGPT and Microsoft Copilot were the most common off-the-shelf chatbots. Some businesses build their own custom AI models, with access to confidential internal data.

Create your own free account at ChatGPT.com and ask it about your farm (or anything, really). It finds information faster than a Google Search, does math quicker than your calculator, and writes business letters more formally than your seventh-grade English teacher.

When asked “What’s the best fertilizer rate for canola?” ChatGPT led with: “There’s no magic number that fits every field — if there were, agronomists would be out of work and the rest of us could just read the bag.”

It also provided some general NPKS guidelines and a recommendation of 80 to 150 pounds of nitrogen per acre.

A free account on Microsoft’s Copilot (which comes bundled with most Microsoft Office software) said the best rate “depends on your yield goals, soil nutrient levels and environmental conditions.” Copilot suggested 125 to 150 pounds of N per acre and also listed reference links, with one to the Canola Council of Canada.

Root wouldn’t go out on a limb with a suggested rate, which was sensible given that it didn’t know how much N is already in the soil. However, Root listed factors to consider, mentioned 4R fertilizer practices and referenced an Agriculture and Agri-Food Canada article titled “Managing nitrogen use efficiently.”

Using Root feels a bit like asking your sensible uncle. You’re not likely to get the wrong answer, and you might need to use its suggestions (links) to find the answer on your own. Other chatbots respond more like your wild cousin.

Did ChatGPT or Copilot give better responses? That depends on your field and your own expertise.

Ask harder questions

Don’t be afraid to ask more difficult questions. Chatbots are great at brainstorming and they may come up with answers you weren’t expecting, but do take a critical look at the answers.

When asked for suggestions for new crops in southeast Saskatchewan, Root provided great links and resources. When pushed, it suggested quinoa.

ChatGPT suggested a long list of crops that included soybeans and sunflowers but not quinoa. When asked, “What about quinoa?” ChatGPT “answered”:

“Ah, quinoa — the hipster of grains. Everybody loved it until they realized it was actually hard to grow here. Then they went back to complaining about canola.”

ChatGPT was willing to forecast revenues and expenses for a new crop — making the kind of assumptions Root would never make. It wasn’t always 100 per cent correct, but it wasn’t ludicrously wrong. Responses like this are either extremely helpful, or very dangerous. As Dr. Dara would say, “verify.”

You know more about your farm than a chatbot, but interaction can still help you come up with new ideas.

What’s next?

“In the coming months or years,” Dara said, “there will be many more AI assistant tools that are more reliable. They will definitely become much smarter.”

Whether or not you use it, Dara said “this technology is here. It’s not going to go away.” AI will be embedded in many of the tools we use, on or off the farm.

“Just as we can’t say ‘no’ to mathematics, we can’t say ‘no’ to AI,” Dara said.

“Eventually AI will be everywhere, and agriculture and food cannot fall behind.”

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But just because the latest whiz-bang creation can, for the sake of argument, combine, check the markets, and cook an egg, all while holding a conversation, doesn’t necessarily mean it meets your vision for your farm.

Considerations

Fortunately, producers aren’t so tempted by the latest shiny thing that they’ll bring home without running the decision to buy it or not to buy through numerous considerations that are part of their vision for their farm and its future growth.

Darren Bond, a farm management specialist with Manitoba Agriculture, says farmers should ask some questions: “Does this save them time in completing jobs on the farm? Does this allow them to do tasks more efficiently to save money? Will this purchase allow them to produce more or produce a higher quality product and increase profitability on the farm?”

Producers will also consider whether a potential buy can reduce risk on their farm.

“Generally speaking, if the new purchase doesn’t accomplish one of these goals, the purchase does not go ahead,” says Bond.

How farmers weigh these variables will vary from operation to operation.

“Depending on the farmer’s vision and risk appetite for their farm, they will usually weigh these goals differently and prioritize investments in equipment and technology differently than other farms,” says Bond.

Importance of a business vision

Bond finds most family farms have a common vision for their farm.

“While some family farms and farmers change over time, grow apart and split their operations to become independent of each other, the vast majority of family farms stick together and evolve together,” says Bond.

Equipment and technology purchasing decisions are just one part of the overall vision for success for the farm, he says.

“Considering how costly farming has become and the amount of risk involved, it’s going to become even more important that family members on a family farm have a unified vision and are on the same page from a strategic planning perspective,” says Bond.

Budget tightening in 2025

Farm Credit Canada (FCC) senior economist Justin Shepherd advises farmers to match their technology or equipment purchases to their farm’s vision where it makes sense for their budget.

“The key for farmers is to know their financial numbers and make sure that the operation can afford it today, even if the tech enhancements may support a longer-term vision,” explains Shepherd. “Producers need to always ask themselves: Do the tech improvements, whether its enhancing yield, product quality, or a reduction in labour hours, balance my return on investment?”

Bond says that with the sector heading for tighter margins in 2025, many farmers are likely to be even more careful when considering any new equipment or technology purchases.

“New purchases will have to have a positive cost-benefit outcome with respect to increased productivity or reducing overall costs for the purchase to be made,” says Bond. “Having a clear vision on needs versus wants is incredibly important for success in managing in a tight margin environment.”

FCC’s Leigh Anderson adds that with falling commodity prices, high operating costs and lower profits, farmers are placing a greater emphasis on their price per acre equipment costs. The senior economist says that farmers are seeking cost saving measures, which include delaying purchases and planning to further reduce equipment costs.

The overall effect will be weaker demand for large farm equipment, which will in turn pressure sales and prices in 2025, FCC predicted in November 2024.

But Anderson adds that as demand slows and prices adjust, there could be buying opportunities for farmers who are considering investing in new equipment.

“Lower interest rates, combined with strong revenues in select sectors, could make it a great time to invest in new equipment as it’s more affordable per acre,” she says, but cautions that a lower Canadian dollar versus the U.S. greenback could see higher imported equipment prices. 

Industry adjustments

Likely in the face of these anticipated changes, equipment makers are making adjustments,

Scott Garvey, a senior editor for machinery and equipment at Glacier FarmMedia, points out that John Deere and AGCO are starting to focus on the retrofit market, offering technology upgrades for existing machines, and thereby allowing farmers to get higher levels of digital capability and efficiency without needing to buy an entirely new machine.

Also, buyers can now get brands to unlock some high-tech features built into their equipment for a limited time, based on acreage or hours used, he says.

“That allows even smaller-scale growers to be able to afford more advanced features, such as spot spraying. We will see more of this in the future,” says Garvey.

The post The pros and cons of new technologies appeared first on Country Guide.

On Jan. 14, guests gathered in the high tower of the Sheraton Cavalier in Saskatoon for the premiere of License to Drive. It showcases equipment close-ups, in-the-cab footage and equipment exhibitors.

This is the second of three episodes in the documentary series, which is a behind-the-scenes look at what happens during Ag in Motion, the annual outdoor farm show that happens every July near Langham, Sask.

With the equipment focus in mind, GFM’s machinery editor, Scott Garvey, is featured sharing his knowledge. Many will know Garvey from his videos and articles on all different types of farm machinery.

In the film, Garvey shared tidbits such as how and why farm machines adopted tracks instead of tires and what being at the show is like, likening it to DisneyWorld for farmers.

This episode’s focus is on the big equipment, while the first episode features cattle and livestock handling equipment. Episode one launched in November during Canadian Western Agribition. The third and final episode will launch in February.

Melonee Ochitwa, GFM’s Saskatchewan sales and sponsorship co-ordinator, has had a hand in the organization of Ag in Motion for the last three years and has also appeared in the documentary.

She shared her excitement about the series and at seeing the second episode come to life, after having a sneak peak at some of the clips before hand.

“It’s amazing when it all comes together, and it’s always so exciting. And it always amazes me how they can kind of take all these little pieces and put it together and make it a show.”

Ochitwa has a background in agricultural manufacturing, and comes from a farm family, so she’s familiar with what’s important to farmers when looking at equipment. Ag in Motion is a great spot to do it, too, she added, with the ability to do more than just look.

“It really gives them those touch points of being able to see … but when they can actually experience it, feel it, see it run, it just makes all the difference.”

The show features equipment demonstrations and the ability to test drive the machinery. Garvey gets the chance to do just that in the documentary, even having a little competition with Western Producer editor Robin Booker.

This casualness adds to the community feel of the show, which Garvey and Ochitwa say is a key piece of it.

“It doesn’t matter whether you’re a competitor, you know, side by side,” Ochitwa said.

“When you’re at Ag in Motion, everybody is friends, you’re all friends in the business trying to provide the best solution for our farmers.”

Episode two, License to Drive, is available on YouTube. Episode one, Working Cattle, and other ag videos, such as Garvey’s equipment features, are also available on the Western Producer‘s YouTube channel.

The post Crop Production Show 2025: Episode two of Western Producer documentary launches appeared first on Country Guide.

Ross Breckels, a senior scientific evaluator with Health Canada’s Pest Management Regulatory Agency (PMRA), said the process of getting common pesticides “on-label” for use by drone is coming along faster than he expected a year ago.

Four requirements must be satisfied before the agency makes an on-label decision for a pesticide and, in this case, its method of application. Those include drift risk, efficacy, maximum residue limits and impacts of operator and bystander exposure. It’s up to chemical companies to submit pesticides for on-label drone use and make a case for their safety, Canadian authorities have said.

Some — including Breckels — previously suggested there hasn’t been a lot of activity in that domain.

He’s more optimistic today, thanks to research being conducted around the world.

Perhaps the biggest example of that work is the Unmanned Aerial Pesticide Application System Task Force. That’s a group of eight agricultural chemical companies generating drone-spraying data on off-site movement, operator/handler exposure and human dietary exposure for regulatory authorities around the world. The task force has an annual multimillion-dollar budget.

Breckels takes the number of zeros in that figure as a sign that major chemical companies are taking the file seriously.

“It’s not an insignificant amount of money that they’re putting into this. So, obviously there is a lot of interest from chemical registrants,” he said.

Companies involved in that initiative include BASF, Bayer CropScience, Corteva Agriscience, FMC, Gowan, NuFarm, Syngenta and Valent.

Results coming out of the task force might mean good news for farmers hoping to use drones for pesticide application, said Breckels.

“They have been conducting worldwide drift trials in 2023 and some are still ongoing in 2024. They are going to submit their data to the PMRA sometime this fall as well.”

Breckels also pointed to a presentation at the American Chemical Society conference in August, which hinted at “encouraging” preliminary results from residue trials.

“They’re hopefully going to provide the PMRA with the data from those results in the coming months.”

To date, only four chemical products have received PMRA approval for drone application — none directly related to agriculture. Garlon XRT herbicide was approved for industrial use this summer, while the others are larvicides for mosquito control.

This effectively makes the spraying of any ag pesticide by drone illegal, with fines up to $10,000.

Drones have their share of advocates and skeptics. In an interview earlier this year, spray expert Tom Wolf cautioned that their smaller tanks and lower water volumes translate to very fine spray droplets, which have more risk of going off-target.

Markus Weber — a central Alberta drone salesperson and instructor — does not agree with that assessment. He cited leading spray drone manufacturers such as DJI, XAG and Hylio that are already manufacturing drones capable of adjusting droplet size.

“A drone operator is able to change droplet size from as low as 50 or 100 microns — extremely drift-prone droplets but in some cases necessary, say, for an orchard where you’re trying to penetrate a canopy for insect control. In those cases, some really fine droplets are called for.

“And then, in situations where you have higher winds and you need to control drift in more of a typical Western Canada field scenario, then the larger droplet size makes sense, and that one tool lets you do all of that.”

Weber says the first ag products approved for drones will likely be fungicides and chemicals for various niche uses.

“That’s been proven true with Garlon XRT,” he said.

How popular spray drones will be once common ag pesticides are registered is another matter, said Breckels, adding they won’t likely replace ground sprayers or manned aircraft as application methods.

“They’ll work in conjunction with them, so the pesticide companies would still get their revenue from field sprayers and air applicators.”

– This article was originally published at the Western Producer.

The post Legal drone spraying takes step closer to reality appeared first on Country Guide.

At issue is on-farm use of drones for the application of pesticides. Drones with the capability to apply pesticides are now being actively marketed to farmers. Innovative producers are excited. They believe drone application is a great new technology that could add value to their businesses. However, they are frustrated that regulations have not kept up to the technology and that pesticide manufacturers are hesitant to endorse the use of their products via drones. These farmers also worry about resistance from environmentalists and the public.

This issue became clear to me this past fall at the Agri-Trade show in Red Deer, Alberta. I spoke with three of the at least four exhibitors there marketing drones capable of applying pesticides. All made compelling cases why farmers should consider using a drone instead of their current options, i.e. a ground sprayer or hiring a licensed aerial applicator.

Each also told me they knew of farmers already using drones to apply fungicides and herbicides to cropland and pastures. But what the three vendors did not mention, until I questioned them, was the regulatory restrictions on using their drones for pesticide applications. This is when the conversations really became interesting.

But before I expand on that, this trade show was not the only place where farmer interest in drones is being expressed. Social media has reports of Canadian farmers already using drones. For example, a retailer of agricultural drones recently posted the following on Facebook: “… We also recognize that these won’t replace ground rigs completely yet. However, many of our customers are using these (drones) a couple of ways: smaller fields for fungicide application, ditch lines, headlands on calm days while the high clearance chews up the big acres.”

Then the post went on to add, “That said, we do have customers that opt for these overused pull types for their main sprayer. We have guys that have done 4,500+ acres in the past year with just one. With the bonus being they don’t leave tracks. But most importantly, they’re around $40,000, compared to $1,000,000 for a new high-clearance sprayer.”

On X (formally Twitter) there have also been posts by farmers about using drones for pesticide application. One poster recently wrote: “How far away until we start seeing high-clearance sprayers switched out for drones on farms in Western Canada,” to which one farmer replied: “I think it’s viable now. Just waiting for the rules to catch up,” and another: “We are being held back by gov’t regs more than tech… I expect to see them flying in my area in the next two to five years.”

Which brings me back to the real issue. Drones for use in the application of pesticides are being actively marketed to farmers eager to purchase and adopt this technology despite the fact there are only three pesticides currently registered for application by drones. All three are biological insecticides for mosquito control and are likely not the products being used by farmers who are already using drones.

Many farmers I spoke with thought that any pesticides labelled for aerial application can be used in a drone. Unfortunately, this is false but there is little incentive for salespeople to correct this misconception. In my experience, instead, it’s like there’s a buyer beware, “don’t tell if they don’t ask” sales tactic in use by drone vendors.

Worse yet, every player in this confusing situation seems to be pointing the finger at someone else for the label delays. It is a real catch-22.

So, who actually is responsible for reviewing, updating, harmonizing, and/or making regulatory changes that will enable farmers to operate drones? Here is what some invested parties have to say:

Farmers

First and foremost, a growing number of farmers are interested in using drones for pesticide application. Some already own drones and use them for field mapping, field scouting and personal fun. It’s natural to seek other applications for this technology on the farm.

Other farmers are intrigued by lower application costs. When a new drone equipped for pesticide application is four per cent of the price of a new high-clearance sprayer, farmers get interested fast.

For smaller-acreage farmers who cannot see ever being able to justify the cost of a high-clearance sprayer, a single drone might fulfill their needs.

Other attractions include eliminating wheel tracks and compaction and being able to navigate in the corners and small areas a lot more easily.

And then there’s maintenance. There’s a whole lot more that can go wrong on a million-dollar sprayer than on a drone. And, likely, the farmer can repair or replace faulty parts on a drone while the ground rig sits idle with a large tank full of product while the farmer waits for an expensive service call.

Some farmers aren’t prepared to wait for those changes and are using drones already.

Drone vendors

Drone vendors blame both government and industry for holding up official approvals for drone spraying and they seem to have no qualms about promoting the spray capability of their drones in order to build up farm pressure.

Even getting a fraction of farmers to buy spray-equipped drones would mean big new sales.

Drone suppliers focus on the much lower capital cost and the ability of a single drone to spray 25 to 40 acres an hour but there are other advantages as well. Less water is needed, the turnaround time for filling is quick, and there’s a safety benefit in having a maximum of 30 or 40 litres of product on board compared to a high clearance load of 800 to 1,600 gallons.

Besides, by changing the tank a drone can go from applying liquid pesticides to dry fertility products in minutes.

PMRA

Getting government regulatory approval for drone pesticide application is complex. All levels of government and a number of regulatory agencies evaluate, license, monitor, and ultimately enforce the Pest Control Act and its regulations.

Before any pesticide can be applied in Canada it must be approved by the Pest Management Regulatory Agency (PMRA), a division of Health Canada. According to a PMRA spokesperson “Health Canada’s primary objective in regulating pesticides is to help protect the health of Canadians and the environment. All pesticides must undergo a rigorous science-based review before being approved for sale in Canada. Depending on the type of active ingredient and the data on file, pesticides may require drone-specific data; there are several value, health (both occupational and dietary exposure), and environmental data requirements that need to be met before drones can be added to the respective product labels.”

“Pesticide application by drone is only permitted if stated on the registered pest control product label. The registered product will state ‘Remotely Piloted Aircraft Systems‘ and/or ‘RPAS’ on its label if permitted.”

At this time there are only three pesticides in Canada that are labeled as such and can be legally applied by a drone. They are the mosquito larvicide products mentioned above, which received federal approval for drone application in 2022 but are still held back by provincial restrictions.

These are all restricted class microbial products for use in mosquito control, not the pesticides farmers are likely to be applying.

The biggest roadblock is not the technology, but the lack of pesticides labeled for RPAS application. And because of the testing protocol required for this label amendment, changes to labels will not happen overnight, or even in the next year for most pesticides.

Data needs to be generated, packaged and sent to PMRA, after which PMRA typically needs one to two years to review – and sometimes more.

And until then, there are penalties for spraying products by drone that aren’t labeled for that use.

When I asked PMRA, I was told it would be a violation of the Pest Control Products Act. “Depending on the specific non-compliance situation,” the spokesperson said, “Health Canada has at its disposal a suite of enforcement tools.” Those include product seizures, fines and more.

PMRA is aware of farmer interest in drones and is already working with a number of national and international organizations studying pesticide applications with drones including OECD Drone/UASS Subgroup, the North American Remotely Piloted Aerial Application Systems (RPAAS) Working Group, the Unmanned Aerial Pesticide Application Systems Task Force (UAPASTF) spray drift trials, and the Agriculture and AgriFood Canada (AAFC) crop residue trials working group.

PMRA also points out they have a program to issue research authorizations, which could include research with drones for specific pest control products.

PMRA stresses too that they are not involved in regulating the marketing or sales of drones and that it is up to pesticide manufacturers to initiate pesticide label amendments for drone application.

Pesticide manufacturers

CropLife Canada represents Canadian manufacturers, developers and distributors of pest control products. Its president and CEO Pierre Petelle says: “Our members are actively working with PMRA on the use of drones for applying pesticides. There is definitely a place for this technology.”

Petelle says CropLife is working with PMRA to determine what data is needed to be collected to evaluate drone application of pesticides, but until anyone knows how much drone testing (such as spray pattern, drift and droplet size) will be needed, it isn’t possible to even put an estimate on when the first pesticides may be labelled for drone application.

Nor could he provide a cost estimate, although he says a rough ballpark estimate would about $1 million to get a ground-sprayer product approved for aerial application, and it would require data from a couple of growing seasons.

Petelle adds though that the U.S. is also working toward utilizing drones for pesticide application and CropLife Canada is working with regulatory agencies there to try to share knowledge and harmonize regulations.

Petelle notes PMRA has a lot on its plate besides drones but feels it needs to prioritize drone evaluation since drones are already in commercial use applying agriculture pesticides in countries including China, Australia and Argentina. He reports watching a video of a swarm of drones, numbering 30 wide, spraying a commercial field crop.

Aerial applicators

Shara Tardif, executive director of the Canadian Association of Aerial Applicators, feels farm show sales promoting drones for pesticide application border on false advertising. Her organization has raised its concerns with companies marketing drones. She feels farmers need to be informed that there are no herbicides or fungicides currently labelled for drone application.

She feels farmers should also be warned if they do apply a pesticide off label, they can face fines of thousands of dollars.

That said, Tardif says: “drones are coming. They are already being used in the U.S. where regulations are different.”

Tardif added her organization is not opposed to farmers using drones provided the user has the relevant pesticide applicator licensing and proper Transport Canada licensing to fly the drone, and also providing they follow the label. In fact, she feels some licensed aerial applicators may even invest in drones to use for spot spraying or in areas where because of field size, powerlines or other obstacles, fixed wing aircraft are not suitable.

Transport Canada

Transport Canada is responsible for all types of aircraft, including drones with specific criteria that would have an impact on a farmer wanting to use a drone to apply pesticides. When asked about using drones for pesticide application, a Transport Canada spokesperson stated: “All drone pilots operating in Canada must follow the rules set out in Part IX of the Canadian Aviation Regulations and are strongly encouraged to consult Transport Canada’s drone safety resources to ensure their operations are safe and legal. Under Part IX, all drones weighing 250 g to 25 kg must be registered and pilots must obtain a certificate for basic or advanced operations.

Pilots who wish to fly their drone outside of the rules of Part IX for a specific purpose must apply for a Special Flight Operations Certificate (SFOC) with permission to operate a drone for specific purposes under special conditions.

A SFOC is also currently required for operating a drone out of the line of sight, for drones weighing over 25 kg, and for drones carrying dangerous or hazardous payloads, which pesticides are likely to be considered. It can take up to a month or more to submit and receive a SFOC, which could have a severe impact on pesticide spray timing.

Additionally, federal, provincial, or territorial rules may apply to the dispersal of pesticides from drones. More details are available by Googling “Information Note Regarding the Use of Drones when Applying Pesticides.”

Fines for breaking Transport Canada RPAS regulations range up to $25,000.

Equipment manufacturers

The companies that manufacture ground and high-clearance sprayers also have an interest in the viability of drones. Adoption of this technology by farmers could have an impact on their business. However, when questioned as to what they feel the impact might be if drones are approved for pesticide application, all the major equipment companies declined to comment for this article.

The public

The greatest unknown in the issue of pesticide application by drones may be how receptive the public will be to drones applying pesticides.

The bottom line

If you are a farmer considering the purchase of a drone for applying pesticides on your fields… Buyer Beware! Even though you can legally purchase a drone capable of applying pesticide, there are no labelled agriculture pesticides a drone can legally apply in Canada, even on your own property.

This is unlikely to change soon. Off-label drone application by farmers will not speed up the licensing process and it may lead to the seizure of the drone and hefty fines. Worse yet, an accident with an illegal, pesticide-carrying drone could set back the approval process.

On the other hand, farmers should be lobbying government and especially the manufacturers of pesticides, in an effort to make the necessary research, testing and evaluation a priority so agricultural pesticide labels can be amended for drone application. Farmers interested in drone pesticide application need to express that interest to government and industry.

– This article was originally published in the January 2024 issue of Country Guide.

The post Summer Series: Drone spraying appeared first on Country Guide.

FARMER: “Farmbot, please make me a prescription map.” 
BOT REPLIES TO FARMER VIA TEXT: Would you like to do variable rate seeding on field 10?
FARMER: Seed costs are higher, so yes.
BOT: Would you like me to produce a rate map for you?
FARMER: Yes.
The Bot provides the map in seconds. Farmer looks at the map and sees a low topography area where the bot anticipates low yield.
FARMER: Why do you expect lower yield in the top right section of the field? 
BOT: The soil EC measurements you took last fall showed signs of salinity in that part of the field. I have ensured that all areas in the field with high salinity are receiving lower seed rate. 
FARMER: Okay.
BOT: Should I send this map to the seeding tool? 
FARMER: Yes, send it to the airseeder monitor in tractor S. 
BOT: Done.

This is the future. The farm’s central computer has all the farm data. It also scans seed performance comparisons, product labels and scientific papers in milliseconds. Artificial intelligence (AI), using powerful algorithms, synthesizes the data and makes recommendations on inputs to apply, including when, where and at what rates. Through regular communication, the computer learns the farmer’s preferences. Farmers make all final decisions.

“The bottleneck right now is that farmers have data but don’t necessarily know what it means. They often need a specialist to figure it out,” says Felippe Karp, a PhD candidate from McGill University doing fieldwork at Olds College of Agriculture & Technology.

Through a McGill, Telus and Olds College joint project, Karp is studying how to bring together multiple layers of farm data to support agricultural decision-making. “Having data from all commercially available sensors might not be practical for an individual farm,” Karp says. “One of the goals of this research is to identify which layers of data are most important to farm decision-making.”

Once researchers like Karp figure out what sensors and data are most useful, the AI platform would take over. Using farm data from these sensors as well as soil analysis, topography, combine yield maps, historical records on crop rotation, products applied, weather, and costs for labour and machinery operation, the AI platform will help farmers manage for higher profits per acre, lower emissions, less labour per bushel — whatever goals the farm may have.

This is easy to write about, but not so easy to do.

A dose of reality

“There is a lot of road kill in precision agriculture,” says Bruce J. Erickson, clinical professor of digital agriculture in the department of agronomy at Purdue University. “I’m almost 64 and I’ve seen all the crashes.”

Applications easy to adopt and with clear benefits tend to avoid the crash-and-burn. Guidance and on-off section control are good examples. Variable rate technology is one application mired somewhat in a data impasse. Interest in variable rate application of fertilizer, seed and pesticides has levelled off, according to the most recent Purdue and Croplife Precision Agriculture Dealership Survey. “Precision farming to manage zones turned out to be a lot more complicated than people realized,” says Erickson, who manages the survey.

Will AI remove the complication and attract more farmers to zone management of inputs?

Erickson is hopeful, but realistic. “AI has supposedly been around since the 1950s. Appearance of ChatGPT seemed to tip the public’s recognition of AI, and now it’s on every news show,” he says. “Is it a fad or trend?”

Trend is more likely, but a trend that takes time to become fully and permanently ingrained. Less disco. More mobile phone.

Raj Khosla, professor of precision agriculture and head of the agronomy department at Kansas State University, says the immense volume of data is only part of the challenge in mobilizing the AI trend.

Data quality is sometimes in question. Take combine yield monitors. Khosla wonders how many farmers find time to calibrate their monitors prior to harvesting. He also notes that yield monitors have a six- to 16-second entrance and exit lag between where the harvest happens to where the data is plotted. Without correction, it makes for nebulous yield zones.

Data is messy. “Data is not organized and not standardized. Currently, we have a limited repository of data in public domain. And that data is too fragmented,” Khosla says. It comes from various sources — many of them private companies. Companies and farmers hesitate to share.

“AI value depends on how well you train the machine, and issues with current data create a major conundrum for training the models,” Khosla says.

The training itself will be hard enough, even when all the data is sound and held in a common repository. “Farmers make decisions by interpreting all that they have known about farming. Likewise, we need to expose the machine to millions of iterations to integrate anomalies and translate that into information,” Khosla says. “Biology, chemistry, physics, economics, technology, social science and psychology all influence such problems and all at the same time.”

Khosla’s lab has been working on enhancing nitrogen use efficiency and water use efficiency through variable rate applications for 25 years. He is participating in a new study looking into AI for sustainability in agriculture. The $10 million project, with funding from the United States Department of Agriculture and the National Institute of Food and Agriculture, spans six states, collecting “as much data as possible” over five years. The goal is to identify what makes for consistent good performing areas. “If we don’t understand what the problem is, we can’t train the computer to identify anomalies,” he says.

Accurate and trustworthy AI guidance in farm decisions is still a ways off. “Sure a bot can write a prescription map today. And a four-year-old can draw lines inside a circle and call them management zones,” Khosla says. “I’m excited about the tool, but the notion that AI can solve this today is premature.”

Will we get there eventually? Both Erickson and Khosla say, “Absolutely.”

Closing the gap

Khosla spoke on AI in agriculture in his opening keynote at the 14th European Conference on Precision Agriculture this past summer in Italy. At the end of his presentation, Khosla shared hypothetical conservations between bot and farmer.

FARMER: I don’t think nitrogen side-dress is required.
BOT: Based on previous yield and current nitrogen state, it may reduce yield by 1.2 tonnes per hectare. Would you still not consider applying it?
FARMER: Okay! Then upload the prescription map along with irrigation chart.
BOT: It is now uploaded to precision system. You may actuate or set a reminder.
FARMER: Set a reminder.

Karp attended the conference, and his recollection of the presentation inspired the farmer-bot conversation at the top of this article.

“The likelihood of AI becoming able to estimate outcomes based on 20 years of data is high. But we don’t have that training data,” Khosla says. “We have so many gaps.”

To close the gaps, he says we need to overcome the challenge of “who owns the data.” And we need investment to tap into the wealth of knowledge from institutions.

The challenge has attracted research investment from legacy agribusinesses, startups and big computer companies. Microsoft FarmVibes, for example, is developing technologies for connectivity, data collection, data analysis using AI and data interface through a chatbot. The project goal, as described on the website, is to build affordable digital technologies that help farmers reduce emissions, predict weather variations and choose practices that improve soil health and profitability.

Moving AI from idea to on-farm implementation will depend on new explorers like Felippe Karp. Karp grew up in the Brazilian town of São João da Boa Vista, north of São Paulo. The farming region produces cattle, coffee, citrus, corn, soybeans and vegetables. While Karp has grandparents who farmed, his father managed the town’s Department of Environment, Agriculture and Supply. His uncle ran an electronics repair shop. Karp was fascinated by the circuit boards and technology. He studied agronomic engineering at the University of São Paulo’s Luiz de Queiroz College of Agriculture, and joined an extracurricular group that explored precision agriculture tools. “The group’s vision is that ‘precision agriculture’ would just become agriculture,” Karp says. “Data would be part of the job of farming.”

The goal is to help farmers reduce risk. Companies in other sectors already use data to manage inventory, run target marketing and design content specific to each user. But agriculture is different. “Plants are biological organisms,” says Bruce Erickson. “They don’t always do what we think they’re going to do.” Then you add in the weather.

“We can’t predict exactly what will happen, but we can use past data to guide decisions based on probabilities,” Karp says. “Will it be right all of the time? No. But if farmers had a choice between 60 per cent chance of being right and a 20 per cent chance, they will go with the 60 per cent chance.”

With AI to help farmers synthesize high quality data from the most appropriate sources, Karp says, “farmers won’t have to guess any more.”

FARMER: Thank you.
BOT: You’re welcome.

The post AI for data analysis appeared first on Country Guide.

Vajdik works with his brother-in-law Adam Gurr running Agritruth Research and the family farm at Rapid City, Manitoba. In addition to pre-seed burnoff, they are testing green-on-brown settings to apply fungicide where needed on flowering canola and pre-harvest desiccant where needed on edible beans. Their sprayer also has green-on-green settings to target green weeds in a green crop, but that is a work in progress. “We’re trying to find ways to use the optical system for the whole season,” Vajdik says.

Vajdik doesn’t have formal tech training but did some programming in high school and university, and enjoys exploring technology to make life easier. “I like pushing boundaries.”

In 2022, the farm had fields with drowned out and thin areas. Vajdik wondered how he might use the optical spraying system to target fungicide to only those areas that had enough crop to justify the cost.

With the optical spraying system, cameras mounted every 10 feet along the boom take pictures constantly, and feed them to the computer that divides images into a grid and analyzes each grid for green. Grids that meet the operator threshold for greenness get sprayed. For example, with pre-seed burnoff, a sensitivity of three per cent means that anything green that fills three per cent or more of a grid will get sprayed.

This process of photo, analysis and spray happens in fractions of a second while the sprayer travels 15 mph across the field.

Vajdik figured he could use this for fungicide by setting the sensitivity to 99 per cent. Any grid filled 99 per cent or more with green would be sprayed. Any grid with less than 99 per cent green — perhaps due to smaller, thinner plants or drowned-out areas — would not get sprayed. It was a quick way to isolate thicker areas of the field most likely to provide a return on investment for the fungicide.

They tried it on one canola field in 2022. The field included an Agritruth study on fertilizer rates. “We didn’t want bad disease to skew the data,” Vajdik says. He filled the sprayer for 120 acres and ended up spraying 150, stretching the fungicide across an extra 30 acres. Vajdik says an operator could use the manual touchscreen on-off in drowned out areas, but the automatic option is easier and reduces operator fatigue.

With no drown outs in 2023, he didn’t need that flexibility. On-off fungicide is not necessary when crop is uniformly good (it all gets sprayed) or uniformly bad (nothing gets sprayed.)

With pre-harvest spray of Reglone on edible beans, however, Vajdik again tried the green-on-brown setting. Plants still green got the high rate. Dry brown plants got the low.

The sprayer

Gurr and Vajdik run an Agrifac, made in the Netherlands, mounted with a Bilberry optical system, made in France. Why Agrifac? It had the features they wanted, including a recirculating boom, individually controlled nozzles and super-stable suspension. “You need a perfectly stable boom for the cameras to work. This sprayer was good for our undulating fields,” Vajdik says.

Nozzles are on 10-inch spacing and each has pulse width modulation with a solenoid to control the rate. This feature not only keeps the rate consistent on turns and with varying ground speed, it also provides the rate control needed for optical spraying.

With a recirculating boom, plumbing loops back through the system to maintain pressure along the full length. With individual nozzle shut-off, sprayers with recirculating booms can be primed without spraying. It also aids in complete cleanout. Agrifac introduced this feature to North America; various European and North American sprayer companies followed soon after.

Tom Wolf, sprayer expert and owner of Agrimetrix, is a fan of recirculating booms, individual nozzle control and optical spraying. Says Wolf: “Stephen Vajdik and Adam Gurr have the opportunity to broadcast and spot spray at the same time with this sprayer, applying a low dose across the whole field and a high dose where it sees larger weeds.”

This can also apply to fungicide and pre-harvest applications, as Vajdik has shown.

Green on green

The Bilberry optical spraying system also offers green-on-green and the ability to pick out green weeds in a green crop. Vajdik says it can target broadleaf weeds in cereal crops and grassy weeds in broadleaf crops. Corn is one exception where it can target both broadleaf and grassy weeds in the space between rows.

Vajdik tried green-on-green in one broadleaf field, applying a blanket low rate of herbicide and hitting wild oats with the high rate. But most crops have both broadleaf and grassy weeds, and Vajdik doesn’t see economic sense in going over fields a second time to use the optical system for a targeted spray. “I don’t see much use for green-on-green until we have induction or injection to add chem into the line,” he says. With that feature, the sprayer could target the broad spectrum of weeds with the main tank and use the optical system to give specific weeds a shot of something extra.

Carl deConinck Smith has a R4045 John Deere sprayer equipped with direct injection and optical spot spray. With direct injection, he has a separate tank for the spot spray product and the system injects that second product directly into the spray booms as needed and at variable rates. However, the farmer from Fiske, Sask., still doesn’t see value in green-on-green at this time. “Green-on-green has only 70 to 85 per cent accuracy in targeting weeds within crop,” he says. “Missing 15 per cent of weeds is not good enough.”

He adds that green-on-brown is also only 85 per cent accurate, but tiny weeds missed with a green-on-brown pre-seed can be controlled by the in-crop spray.

Tom Wolf, at his website sprayers101.com, wrote about a new Greeneye sprayer with an optical spraying system as well as a second tank and second boom. The Greeneye sprayer can broadcast a residual product while spot-spraying a post-emergent product in one pass. In the U.S., where farmers are dealing with major threats from glyphosate-resistant weeds, especially Palmer amaranth and waterhemp, the ability to target these weeds with residual products in corn and soybeans makes dual tank green-on-green systems more valuable, Wolf says. “This is the American reality for soybeans and corn,” he says. “There is a slightly less stringent need for that up here at this time.”

Sprayer technology is advancing quickly, and green-on-green algorithms will get better at spotting individual species, not just grassy or broadleaf weeds. One solution, Vajdik says, would be for algorithms to identify key crops and spray every plant that isn’t crop. That will save the program having to identify hundreds of different weed species. Optical spraying systems could also create maps of specific target weeds to target with spot sprays or other integrated actions later in the year, or subsequent years.

The way sprayer cameras see will also improve. Normalized difference vegetation index (NDVI), which senses the greenness of crops, would work really well to assess the fungicide need for individual plants, deConinck Smith says, adding, “That’s where the camera system will be in the future.”

In the meantime, deConinck Smith, like Vajdik, has found ways to expand the use of green-on-brown. For example, he can use it for spraying larger perennial or winter annual weeds in just-emerged canola. With the settings high enough to skip the tiny emerged canola crops, he can apply a high rate of glyphosate to the target weeds without spraying the canola. This is particularly useful if the farm missed a pre-seed burnoff and needs to spray these large weeds with a high rate and as soon as possible.

DeConinck Smith farms over 10,000 acres, and he figures an 8,000-acre farm could pay off the $200,000 to $300,000 cost for an optical spraying system and specialized boom within two years based on the chemical saved for pre-seed burnoff alone.

“If you’re buying a new sprayer, this add-on is a no brainer,” deConinck Smith says.

Wolf says optical spraying systems have matured beyond the original hype. “With these technologies, we overestimate their value in the short term and underestimate in the long term,” Wolf says. “These models are just going to get better and better at detecting weeds. And we will get more innovative. I see a bright future for the technology with people like Stephen and Carl innovating new ways to apply it.”

– Jay Whetter is an agriculture journalist and communications manager for the Canola Council of Canada.

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When Covid-19 shocked the global supply chain and choked off the supply of microchips, automotive production had to throttle back. Brands found themselves with acres of partially built cars and pickups waiting to make a second trip down the assembly line when their missing components would become available.

That slowdown in production limited the number of new vehicles available to dealers, and prices of both new and used vehicles surged thanks to the law of supply and demand kicking in.

To cope with the new manufacturing reality, automakers found themselves reducing or even stopping production of base-level vehicles. Instead they focused on high-end models chock full of options as they chased higher profit margins per vehicle. When combined with the boost in MSRPs, these profit margins more than made up for the lost revenue due to production shortfalls, leaving brands with those record profits.

Ag equipment manufacturers suffered the same supply chain disruptions. And, yes, just like the automakers, they, too, found themselves rolling in cash, partly for the same reason.

While overall tractor sales numbers were down in North America, the reduction occurred primarily in the low horsepower market (below 100). Those are tractors mainly bought by consumers rather than commercial agricultural operations. In fact, sales of tractors over 100-horsepower remained pretty strong. In the U.S., sales of rigid frame models in that group jumped by over 11 per cent. In Canada that segment remained nearly flat, but four-wheel-drive tractor sales rose 6.3 per cent. Sales of new combines saw double-digit increases in both countries.

That means the most expensive, highest profit margin machines saw strong sales, despite healthy price increases.

“We finished 2022 with solid results,” CNH Industrial CEO Scott Wine said during an investor conference call on the company’s end-of-year totals. “Fourth-quarter revenues were up over 27 per cent, driving full-year consolidated revenues up 21 per cent.”

That’s got to be the very definition of “buoyant.”

“Our strength was broad-based with double-digit year-over-year price realization coming from all regions,” Wine said. “We expanded profit margins in both agriculture and construction despite significant cost increases.”

AGCO’s year-end report reveals it too saw a jump in net profits in 2022, with a total of US$11.1 billion flowing into their pockets. And the percentage of that money it got to keep went up as well. Operating margin grew from 9.1 per cent in 2021 to 10.3 per cent.

Things were pretty rosy at John Deere too. Net income attributable to it in its 2022 fiscal year was $7.13 billion, compared with $5.96 billion in 2021.

Even though corporate shareholders were smiling about the size of their dividend cheques at a time of manufacturing disruptions, executives at all three ag equipment majors have been working to create a higher and even more stable income stream, one that will make them less vulnerable to market swings in the future.

One of their primary goals is to continue to increase overall profit margins. John Deere has targeted a lofty overall 20 per cent profit picture by 2030, up from the roughly 15 per cent it currently enjoys.

For all brands, those profit margin gains will come partly from cost-cutting efforts through a variety of new-parts sourcing strategies as global supply chain routes gradually realign, but part of it will also come from sustained higher retail prices, which Scott Wine sees as continuing. “… customers have responded with continued demand for our high-end product at prices offsetting increased production costs. With confidence in the stickiness of our price increases, we expect to build on our margin gains by taking more costs out of our system.”

What that means for producers is don’t expect any major price incentives to stimulate sales of new machinery in the foreseeable future — unless market conditions change pretty drastically.

There is also another strategy all the brands have been chasing to improve profitability. It’s a relatively new income model in the ag equipment sector, one where repeatable subscription fees account for an increasing share of overall brand revenue.

“Since inception, Deere has relied on a business model that monetized products at point of sale,” said Ryan Campbell, CFO at John Deere. “However, the nature of our solutions (read: products) are changing. They combine the equipment, which will largely remain on a point-of-sale model, with machine learning and an ever-increasing software component … (that) ties payment more closely to value creation (for farmers), ultimately moving us from a point-of-sale, to creating on-going value for customers.”

Translated into plain language, that means Deere wants to increase the number of features on its equipment that the company can sell on a subscription basis. Executives believe farmers will be willing to pay for them in that way if they add value.

“We expect about 10 per cent of our revenue to be recurring by 2030,” said Deere’s deputy financial officer Joshua Jepson. “This will increase the consistency of our through-cycle earnings.”

That steady stream of cash will help smooth out the boom-and-bust cycles that have dominated sales in the ag machinery sector since, well, forever.

AGCO, too, has announced similar goals for repeatable services. But looking long-term, targeting them as just 10 per cent of overall income at brands may be peanuts, according to Deere CEO John May. He told a group of investment analysts during an information session in Des Moines earlier this year that the potential value of such as yet untapped business services globally may be as large as US$150 billion.

“We see a future where nearly 40 per cent of our revenue is recurring or less cyclical,” added Jepson. “And the per cent of earning (profit margin) tied to these recurring revenues will be even higher.”

Much of those recurring revenue streams will come from precision ag products and handling data that gets collected from machines, transferred and stored in the cloud. Services like John Deere’s Operations Centre will be at the heart of that kind of revenue stream.

And in a new twist for the industry, activation of the high-end features built in to new machines will begin to use that model. The functions will be built into all machines leaving the factory, but getting those features, like Deere’s new See & Spray selective spray technology, to operate on new sprayers will require a subscription fee. Instead of paying a one-time retail price for it, producers can enable the feature when they need it, then use and pay for it on a per-acre basis.

“Many of these solutions will be software- or machine-learning enabled, lending themselves well to recurring or per-use monetization models,” said Deanna Kovar, VP production and precision ag at John Deere.

And as autonomy begins to become more common in ag equipment, Deere sees the pay-as-you-need-it approach as a way to not only create ongoing revenue from that technology as well, but also to speed up the adoption of it.

“In order to accelerate that adoption, we plan to include the required autonomous sensors to compute (autonomous operation) in the base configuration (of new machines) in the next few years,” said Igino Cafeiro, the founder of Bear Flag Robotics, a company Deere purchased sin 2022. “And what this is going to mean for a farmer is with the tap of the screen they can unlock the full potential of autonomy on that tractor that’s already sitting in their yard. Autonomy will be the Aspirin a farmer needs, right when they need it most.”

So eventually all of Deere’s large ag equipment will come autonomy-ready right from the factory. If you want the machine to run that way, pay the subscription fee to unlock that built-in capability.

“The goal finally being that all large tractors that ship come with this autonomy kit on board,” added Willy Pell, vice-president of autonomy and new ventures at Deere.

Of course, the more that sophisticated features can be subjected to a subscription model, the more opportunity for brands to build that ongoing income stream.

“We are, this year, also in advanced testing at customer sites with four additional products in the ‘sense and act’ (read: automation) family,” said Jorge Heraud, vice-president of automation and autonomy at John Deere. “Two of them are in harvesting. One is in planting. And one is in construction. And there is more coming on later. This technology, robotics and artificial intelligence are going to be propelling us to the next stage. John Deere is quickly becoming a world-leading robotics and artificial intelligence company.”

All of that means the way ag equipment brands do business and earn income will be substantially different in the coming decades than in the past.

Said May: “The result is two outcomes. First, a structurally more profitable company. Second, an organization that is now prepared to deliver on the next opportunities. Or as we call them: leaps ahead.”

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