Outlook 2016: Banking On Big Data Progress

The expectation among many that 2015 would reveal the long-term winners and losers in regard to the glut of precision ag data management solutions in the market was unfortunately never realized. From a grower perspective, heading into the New Year the Big Data revolution in farming remains as unsettled as the Cleveland Browns muddy quarterback situation.

“Right now it looks to me like everybody is scrambling to get farmers enrolled into their programs, to supply data into their programs — it just looks like there’s a lot of players out there,” says John Reifsteck, owner, Reifsteck Farms. “If you went to InfoAg this year you just saw so many people that were in the data collection and analysis business.”

The main dilemma, according to Reifsteck, is that over-crowding on the data management bandwagon has many growers reaching for the pause button.

“So they’re all trying to sell me their product, and it starts getting confusing,” he explains. “There’s not room for all those people, you wonder who’s going to get bought by who, and it’s causing certainly some confusion and reluctance by farmers because you don’t want to jump into one of these things and then find out that it’s not going to be a long-term solution.

“For the average farmer you’re getting very close to the point at which they just freeze and say ‘I’m going to wait to see how this settles out and push it off for another year.’”

So this whole data thing that we’ve been championing all year through our PrecisionAg Innovation Series meetings and our Think Data First editorial series still needs some sorting out. Fair enough. But one data-based practice that Reifsteck says is catching on (based on his experience at InfoAg this summer) is variable rate nitrogen applications.

“Everybody’s looking at prescription nitrogen, and I think part of that is because it fits well within the farm economy now from the standpoint of maximizing yields and reducing the nitrogen cost when we’re under such economic and environmental pressures.
“If you look at it from the standpoint of I want to spend dollars on nitrogen for yield, how do I distribute that nitrogen in a way that maximizes yield,” he asks. “But we’re also uncertain of what the methodology is and to a certain degree I think we’re scared of it as well, because if you follow that through you know you’re going to be putting on more in some areas and less in others — and less tends to scare guys that have been doing flat rate for 20-plus years.”

Still, Reifsteck believes that variable-rate application will soon become as commonplace as flat rate applications have been.

“I’m thoroughly convinced — absolutely convinced — that at some point in time that’s the way that we will be putting on the nitrogen. I just don’t know if it’s a year from now or five or 10 years from now. It’s just a matter of when, not if.”

Plug & Play Agriculture

Application Program Interfaces (API) were a big step in the right direction for the equipment industry in 2015 as nearly everyone agrees the industry needs to move closer to true “plug and play” agriculture.

Everyone from Deere (DN2K API) to AGCO (AgCom­mand API) to Trimble (Ag Developer Network) to Raven (Slingshot API) and even aerial imagery provider GEOSYS (Bridge API) got into the API game in 2015, and as we anticipate even more APIs being released this coming year, true “plug and play” (i.e., the ability to pair nearly any equipment color with any controller/planter/monitor, etc. and collect data) agriculture moves closer to reality.

“Fundamentally, that is one of the things that farmers have been encumbered by — the compatibility issue and having different systems work together. From the farmer’s perspective they don’t really care whether I am using ‘Brand X’ versus ‘Brand Y’, they’re trying to make a decision,” says Charles Baron, cofounder and VP, Farmers Business Network. “Making data easily usable is what’s going to get growers to see the value in precision. If I can’t get the value of precision because of data problems, then why would a grower adopt and upgrade their equipment?”

For growers like Reifsteck, who began his path to precision ag adoption 12 years ago in Central Illinois, cross-brand compatibility remains a significant barrier to success.

“Farmers want to buy different pieces of equipment — maybe they want to pull a John Deere planter with an AGCO tractor,” Reifsteck says. “I had a situation a few years ago, I had one brand of tractor, a second brand of GPS controller and a third brand of planter, and getting all three to work together easily was a real challenge.”

Reifsteck has since remedied his connectivity issues, but the occurrence still sticks with him as an example of why agriculture needs to focus on compatibility going into 2016.

“So it got to the point where I had a technician from each one of those three companies standing there in my yard, trying to figure out what was the problem and whose fault it was,” he continues. “What that does is it allows people to not take responsibility, because if you’ve got everything in one brand, well then they can’t say that’s not our fault, because obviously it is. When you start adding two or three different brands they can point the finger at the other brand or point the finger at the fact that they’re not robust enough to work together.

“In an ideal world you’d be able to walk up to the back of your tractor and plug a blue planter into a red tractor and it would all work easily and you’d be able to get the data off of it and do the things that you want to do. It’s just not that way right now.”

Always the historian, Reifsteck compares the current issue with machine-to-machine connectivity to a well-known prior problem that was eventually solved by standardization.

“When I was a kid growing up on the farm we always talked about the problem with the hydraulic couplers,” he explains. “If you had a Deere piece of equipment, the hydraulic couplers — the little pieces at the ends of the hydraulic hoses that hook together — were proprietary, so they wouldn’t fit a red tractor. You’d have to switch the tips out or use an adapter. You’d always be messing with this big messy box of adapters.

“So years ago they standardized and now you’ve got one standardized hydraulic coupler across all brands of equipment, so now I can pull my tractor into any dealership in the country and I can hook up to any piece of equipment and the tips are going to work. That is true plug and play — albeit from a hydraulics standpoint — but we’re not quite there yet with the electronics.”

Prescriptive Analytics

It seems over the past few months I’ve heard a lot of chatter about advanced analytics platforms like Aglytix and, even more so, IBM’s long-awaited Watson platform.

However, according to an IBM-issued white paper “Analytics in agriculture: Driving efficiencies and insight to create ‘Smarter Agribusinesses’, the computing giant is already demonstrating the power Watson possesses to possibly reshape the future of agribusiness.

Using only a basic mobile phone, IBM recently created a system in India where nearly one million farmers were able to use automated voice and SMS text messaging, as well as a live call center staffed by top Indian agronomists, to get timely agronomic intelligence.

So that’s all well and good, but it’s the next paragraph where I could see U.S. ag retailers feeling a bit uneasy with what IBM is proposing.

Such applications have potential for expansion to provide “virtual agronomist” capabilities: Computing systems that can access vast amounts of structured and unstructured data, take verbal input in natural language and respond more accurately and rapidly than humans, based on data rather than intuition. This would be similar to the Watson technology showcased in the Jeopardy game show, providing a user-friendly interface for farmers.

Could IBM and other analytics outfits be angling to eventually replace the local retail field agronomist with automated talking robots? Probably. Local expertise from the trusted advisor, however, will always hold water at the farmgate.

“They’re (the local retailer) out there seeing what’s happening and if you think about it, they’re predictive,” says Reifsteck. “My data from what happened on my farm last year is in the past, what happened at Iowa State is kind of in the past, but the local guy is predictive. He’s looking and projecting the technologies into the future. So there’s still huge room and a necessity for those local advisors that understand you’re farming operation.”

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