Syngenta Dives Deep into Digital Agriculture
For decades ag technology was all about the traditional and biological products companies brought to market. These days, that word applies to computers in the field and the office as much as any pesticide.
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BY DAN JACOBS
SENIOR EDITOR
As one of the largest providers of crop inputs, Syngenta is known for introducing new and innovative products. The company’s research and development (R&D) division continues to offer a regular stream of new solutions, but that’s only part of the company’s technological advances.
We sat down with Ron Cowman, Syngenta’s Head, Digital Agriculture Solutions, to talk about ag tech.
ABG: How does Syngenta define ag technology?
RC: You will get multiple answers to this question, but through the lens that we view, our work is subject to (either) precision agriculture technology or decision agricultural technology.
We focus the majority of our efforts on the decision side of technology. What that means is our technology platform, and the tools built upon that, really focus in on farm management, record keeping systems, so that we have a foundational base of what’s going on in the field, how those management practices are being applied, application inputs, marketing decisions, and return on investment.
It’s what we term agronomics to economics. Once you have that base established, then we start to think about other decision insight tools that might be useful. This is where you start getting into products, like Cropwise Protector (one part of a suite of a dozen digital farming offerings Syngenta developed that are designed bring solutions together for growers to connect their agronomic data and help them make well-informed, end-to-end decisions), which is a scouting technology at its core. But what it allows for is real time views of what’s going on in the field.
Those views are then connected to predictive algorithms that take into account environmental conditions and the pests that are being identified in the field. It brings forward what we call a histogram. It shows the pest presence against the disease thresholds so that a customer can determine (whether) it is in his or her best interest to make an application to mitigate the injury that the pest may cause.
We refer to that as a decision insight. It’s both taking the factors in the field, providing or serving up, if you will, a data insight that the customer can then apply his or her own management practices and knowledge to determine what best decision is right for them. Most of our tools, if not all, are certainly founded in that decision insight technology.
ABG: How would you say the view of technology in agriculture has changed?
| RC: When I began working in the technology sector, it was really focused more on what lagging indicators were there. So, it was about creating a digital file cabinet to capture everything that was being done on the farm, and where we see that evolving. In addition to decision (making) and insights, what type of risk mitigation tools can be put into play or what types of predictive modeling can be put into place so that a customer, a grower, isn’t always working off what had happened, but they are working off the current environmental conditions and what could happen. That’s probably the biggest change. Now, I would also tell you there is a bit more uptake in technology adoption as the farm succession plans convert over to the next generation. A lot of times that next generation is more comfortable with technology. They may or may not have the generational experience that was handed down to them. They’re looking for that additional data set to help them make decisions. |
ABG: The stereotype is the older you are, the harder it is to adapt to new technologies. Do you see that?
| RC: I think that’s very true. I think there is some truth in, “the older generation may not be as comfortable,” but that is not the norm. In today’s world, technology is very intuitive, and it needs to be built as such. Thus, when you adopt, you understand the value proposition there.
It’s got to be intuitive and that’s why we spend so much time relying on our grower-customers to provide us guidance as to: How should the tool be built? What should it do? How should it be delivered? We have them interact with them so they can help find value from it. As you continue to see new technology arise, it will be more intuitive and more customized. A lot of the technology that we’re bringing forward, you have a standard core functionality, but it allows for the local methodologies or local customizations to be applied for that particular user, whether that’s the user interface, dashboards, or reporting function. It’s making that customizable so the user can pick and choose what’s more apt or more applicable to them. |
ABG: You talked about the change in technology from reactive to more predictive. Ten years from now, where do you think these tools will be? What will be available? What do you hope will be available?
| RC: Well, your guess is as good as mine on this. The area of computational agronomy is likely the next area. And what I mean by that is where you’re really in depth at, and how the plants grow and interact with all the environments around them. The more we know about the plant interaction within that specific environment, the more detailed and prescriptive your data insight will be.
Things like phenology will be really, really important as we start to think about predictive algorithms, because predicted algorithms are dependent upon historical basis and what that historical base is attached to. The more detailed analysis we have of the growing environment, the soil, the plant itself and the interactions between all those environmental conditions will be a key piece into that agronomy insight or that predictability model. That’s where the future is headed from that perspective. And then, of course, the area of automation from the equipment perspective — driverless tractors and that I think that will all have a play down the road. I think there’s got to be some efficiency gained there, but there’s certainly commitment on companies to make that happen. And then, areas of precision application technology are going to be on the horizon, whether that’s a See & Spray technology or multiple AIs within a single application unit, those precision types of technologies are going to come to bear as well. |
ABG: How do you make sure that everything that’s in the pipeline, which starts 15 years ago before it comes out, meshes with the tools that get handed to the farmers or the retailers?
| RC: Well, there is a lot of collaboration and planning that our digital team does with our R&D team and with our marketing teams. As these AIs come into the staging environments. I would go back to our three-step process, first identifying the customer problem, then identifying the solution to that problem, and then thirdly, taking a digital tool and enabling that.
That holds true for an agronomic problem as well, which is the basis for how our AIs are developed. If you think about an AI that comes into a staging environment, let’s just say for insects, we know that as part of that enablement you’re going to need to better understand the environment by which those insects come to bear and the impact that they have on a specific crop in a specific area. We can begin to make some assumptions as to what digital enablement is needed. Once our products get into a pre-commercial R&D plot environment, we are also testing our digital tools alongside that AI and that product in that same environment. So, the last three to four years of that product’s lifecycle before it becomes commercial, we have done so in parallel along with our digital tools to better understand what capabilities and enablement the digital tool can bring to the to the AI or the commercial product that’s coming. |
ABG: How do you differentiate Syngenta’s digital offerings? And how has it been received by the ag community?
| RC: You have to take a step back. The challenge any company has with a digital tool is bringing something meaningful to the market the customer has a need for, and it is intuitive enough that it can be adopted, and the value realized. Regardless of what digital tool it is, just bringing a tool to market is only one small step.
From there, the real success that you see is when you can have a service model connected to that digital tool so that the tool and the customer and the value come along together. Just as with any technology tool, we must be comfortable that if we have a challenge or a question that we can speak to someone knowledgeable about how to help us walk through that. This is no different than in agriculture, where we bring a digital tool.
You may have a learning, a value you see one year, and the following year it’s a completely different learning and value because the pain point or the need changed either from a different crop, or different environmental condition. That’s important as we think about adoption — the tool itself is just that — it’s a tool. The service model, and the subject matter expertise that supports that tool are what’s critical to its long-term success. |
ABG: Ensuring ROI is critical for the success of any offering. Can you put actual numbers on the solutions Syngenta offers?
| RC: It’s difficult to answer that because each grower’s return on investment will be different. That’s the core foundational value to any digital tool. The digital tool must allow that grower customer to track, measure, and monitor his own value based upon how he or she farms in their environment.
It’s one of the reasons we do not establish a per-acre value or a license fee on our tools, because we don’t believe that we’re in a position to truly understand what the value is. We may overvalue it, we may undervalue it, but we create a system that allows customization and return on investment to be measured by the user at the local level. From there, we take those success stories and those can be shared by the user if he or she wishes or by us if we have permission. But it is very ambiguous — just as the industry itself — about what the returns are each year. Our systems allow you to track that, whatever that may be. |
ABG: You mentioned 12 elements to the Cropwise digital offering, but you only discussed six. Are these tools something a smallholder farmer can use or is it only useful for a certain size to take advantage of all these products?
| RC: Great question. And the answer is no. These tools are not limited or developed for specific size of growers there. And I’ll share with you the developmental cycle. We look at a grower’s decision-making process in a market and buy a multitude of crops and geographies.
Our objective as we think about the growers’ decision cycle is what digitally enabled tools help him through that. It’s not about the size, it’s about: Do I have a procurement decision? Do I have a planning decision? Do I have a planting decision? Do I have a seeding decision? Do I have a crop protection decision? Do I have an in-season pesticide decision? Do I have a marketing decision? Do I have a risk management decision? We think about all these and then we try to build out specific tools that will assist that. The reason we have the six that I shared in North America is those are applicable today that we’re ready to deliver. There are others that are different variations of what we have. If you think about a smallholder farm in India, Cropwise Imagery has a play there. But the play it has a of a smaller basis, a different filter. How is it delivered? Is it delivered via mobile? Is it delivered via report? Those are the differences that we see around the world. Thinking about our digital enablement in Europe, there is a lot of monitoring and MRL tracking and stewardship management that a digital tool enables. Here we have that embedded into our FMS where in Europe there is a very specific tool for that. You should expect some of the other tools that are currently being used in regions. Do they have applicability here? Yes. It’s a matter of interdependencies and when we bring them to market, as we think about getting our core products adopted today. |
ABG: What else do we need to know?
| RC: I think I would leave here saying that as we look at the future of digital agriculture, it is always going to be ever changing. And you might say, ‘well, sure, that’s true for all technology.’ But as we look at other industries around the world, agriculture lags in the technology uptake.
But what you’re seeing in the startup community and ag business tech, and as you start to see greater volatility in our industry, digital enablement tools will be more readily adopted because it’s another dataset that a producer can use to help inform his or her decision making. There’s always going to be a need for that. And as that evolves, I think the need for additional customization and the need for predictability models will certainly come into play as well. So, I would expect that this conversation will be different next year than what it is now and after that. But I fully expect technology in agriculture to be pretty robust over the next 10 to 20 years. • |
From Top to Bottom: Smart Future-Stock.Adobe.com; photo of Ron Cowman courtesy of Dan Jacobs.
