By now, it’s clear that the future of agriculture is digital, interconnected and technologically advanced. Ag equipment manufacturers are making great strides every year to produce new products that don’t just help farmers work the land, but also provide them with critical business insights.

But these new technologies are also being driven by cross-industry partnerships with advanced learning laboratories worldwide, where engineers and researchers pilot new methods of collecting and analyzing farm data.

One of these institutions is the Purdue University College of Agriculture, where Dr. Dennis Buckmaster is the Dean’s Fellow for Digital Agriculture. During AEM’s recent Thinking Forward event at Purdue, Dr. Buckmaster sat down for a podcast interview about some of the cutting edge research that’s going on, what needs to happen next in the evolution of digital agriculture, and how the ag brain drain is being reversed.

AEM: There are a wide variety of sciences under the umbrella of “digital agriculture.” How is this changing the nature of ag science, and the programs offered at Purdue University?

Buckmaster: We still have almost every traditional discipline—agronomy, agricultural engineering, ag economics and animal science. But we’re now currently working on, as part of this initiative, either a certificate or a minor, perhaps both, that are specific to analytics and digital agriculture.

So that would include the data flow from the device that makes a measurement to the app that helps (a grower) make a better decision. That whole data flow process would be a part of that educational thrust.

AEM: And you’re not just teaching about these subjects, you’re out in the field, experimenting and pioneering new technologies. What are some of the big breakthroughs you’re working on right now?

Buckmaster: It is very much a three-pronged effort. It’s education, it’s extension and outreach, and it’s research and development.

One specific project that was recently launched, in which Purdue is a major player, is called the Wabash Heartland Innovation Network (WHIN). And in that project, we will have very active test beds of Internet of Things for agriculture, both at the farm level and beyond the farm gate.

That’s research and development into the sensors themselves—the communications systems that allow the data to flow— and the analytics that make sense of the data that should be flowing. It’s all that together, and trying to make those things interoperable and valuable.

AEM: Are you putting IoT sensors in the fields themselves, is it in the equipment, or is it somewhere else?

Buckmaster: Yes and yes and yes. Some of the sensors are going to be in the soil or in the crop canopy. Some of the sensors are in the grain bin. Some of the sensors are in the airspace around the field to measure the flux of gasses coming off the land. Some of the sensors are in the water streams—whether it’s a creek, a stream or a tile, we’re going to instrument those sorts of things.

And, my roots are as an agricultural engineer, so of course we will also take advantage of the data that the machinery in the field is already generating. Because they’re instrumented to the hilt already, so they can do their work in the best way. We will try to capture that data as well.

AEM: With all this data pouring in, what’s the most complex challenge you face?

Buckmaster: Making these data streams interoperable, so you can actually mine it and learn something, is a key part of it.

There is a term that’s new to many of us, “metadata,” which is really data about the data. It’s really the backstory or the context.

So to many in agriculture, yield data is the data we want. But in order for that to really be valuable, you need to not only know the population of the planting, but the variation in the population. You need to know the topography of the land. You need to know, not just total rainfall over the season, but exactly when did it happen.

Those become the metadata elements. And to truly optimize these systems, we need to have better metadata than our systems currently enable. So some of this research and development, teaching and outreach, is targeted toward better context information so you can use the data in a better way.

AEM: Our recent “Future of Agriculture” report outlines trends that manufacturers must be ready for. And one of these is the expectation that whole farm digital solutions will provide farmers with real-time, big picture analyses to help them make decisions. What progress is being made toward that goal?

Buckmaster: That’s a very good question. We use the term “interoperability” and that captures part of this problem… though maybe we should look at it as an opportunity that we’re facing at the moment.

But farmers don’t have a corn planter problem or opportunity. They don’t have a soil fertility problem or opportunity. They really just want to optimize the production of whatever crop they’re growing.

So that involves soil, machinery, nutrients, weather. And because there isn’t any single company that encompasses all of that, we need systems that work across those lines of business. We need to be able to integrate the data so that we can make better sense of it.

AEM: What is it going to take to establish interoperability standards that are up to the challenge?

Buckmaster: There are standards efforts underway, in organizations like AEM, ISO, AgGateway, the Open Ag Data Alliance. But we do need to move these efforts faster than they’ve ever moved before, because the problems are outpacing our ability to solve them.

AEM: What role do you get to play at Purdue in facilitating that cooperation?

Buckmaster: One role we’re trying to play here at Purdue is to bring “open source” to agriculture, through the Open Ag Technology and Systems Center that was just established.

Of course, there will be proprietary solutions also. But when we need to make data, sensor systems and analytics work across companies, that really requires some collaboration that allows that company to consume the data that my equipment might be generating, as an example.

And so just as the internet was built on open source technologies that allowed things to be compatible without too much effort, that’s what we need to do in agriculture. Instead of proprietary silos, we need to at least release APIs so we can have data exchanged—so that I’m not manually handling, in my email and on flash drives, countless files. Most of us didn’t get involved in agriculture and farming because we like handling data files on the computer. No, we just want that to be seamless.

AEM: You mentioned earlier how important aerial surveillance data is. What role are unmanned aerial vehicles, AKA drones, playing in this process?

Buckmaster: Simply using an unmanned vehicle to pre-scout a field can save you time. From a remote point of view, you can see what parts of the field are similar and what spots are anomalies, so instead of randomly sampling a field, you can sample those spaces more proportionally to what’s happening in the field.

Of course as we start to use hyperspectral imaging indices of many different types, we can start to uncover exactly what the issues are in the ground so we can address diseases, fertility issues and that sort of thing.

AEM: Agriculture is one of the oldest professions in the world, but it’s recently suffered from kind of a generational brain drain, where young people might not be interested in the field. Are these new technologies starting to change that?

Buckmaster: It’s changing, and it’s not only the young people who see it as a fun and exciting way to do innovative things.

It’s an energizing space. I teach a senior seminar course, and I have all the students explain on the first day of class what they did over the summer. And those who are most excited are the ones who flew drones, did scouting and those sorts of things in their summer job.

AEM: You go hands-on with the future of agriculture every day. What’s your outlook on that future?

Buckmaster: We talk about increasing efficiency and autonomy a lot. Maybe I won’t just sit inside and watch my farm completely operate itself. But increasingly, I’ll have to do less of what was thought of as the farming operation, and do more of the decision making about what that operation should be, and then send a machine, a bot, or a UAV to do some of those things.

Technology really doesn’t save us time, it allows us to do different things with our time.

AEM members learned about this and other topics at a Thinking Forward event at Purdue University on October 16.

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