The digital farm

Inside the cab of Brian Marshall’s tractors is a glimpse into the future of farming. Through the windows, he sees his 4,000 acres of corn and soybean crops. He also sees a slew of computer monitors.

“We have so much information,” says Marshall, who runs a farm with his father in Maysville, Missouri. He can, for example, take an iPad from his tractor, which will tell him the exact point on the field where his planter missed a seed.

“The accuracy on the equipment that we run now is amazing,” he says.

One screen monitors the planting. Another shows highly accurate maps that allow for precise adjustments as the seeds go into the ground. Still another screen monitors autosteer.

Forget self-driving cars; tractors can already drive themselves across fields using GPS signals accurate to less than inch of error, Marshall says.

Technologies like these help farmers plant more accurately and successfully, but the real potential is what happens when the data from thousands of tractors on thousands of farms is collected, aggregated, and analyzed in real time.

“What if we took that level of data we have on individual farms and analyzed it across tens or thousands of farms? What macro-level trends would we see?” asks Shannon Ferrell, an associate professor of agriculture law at Oklahoma State University.

Established brands in agriculture such as John Deere, Monsanto, and DuPont are now as much data-technology companies as they are makers of equipment and seeds. Trimble, a company known for GPS and other positioning systems, is also a big player.

Agriculture has been slower and more cautious to adopt big data than other industries, but Silicon Valley is taking notice. Startups like Farmers Business Network, which counts Google Ventures as an investor, have made collecting, aggregating, and analyzing data from many farms their primary business.

This is some of what big-data analytics make possible on the modern farm: Sensors can tell how effective certain seed and types of fertilizer are in different sections of a farm. Software will instruct the farmer to plant one hybrid in one corner and a different seed in another for optimum yield. It can adjust nitrogen and potassium levels in the soil in different patches. And this information can be fed to companies like Monsanto to improve hybrids.

Monsanto says its sensors on harvesting equipment generate about seven gigabytes of data per acre. Multiply that by the roughly 93 million acres of corn in the US or 80 million acres of soybeans and you have a lot of data.


Precision down to the meter

“Today, with this technology, we have the ability to go into a field and break that field up into regions or zones and plant two different hybrids,” says Scott Shearer, a professor and chair of the Department of Food, Agricultural, and Biological Engineering at Ohio State University.

These services can generate a “prescription” for each individual farm’s fields, Shearer says. “The analytics are going to drive the development of those prescriptions.”

Big-data firms can test varieties of seeds across hundreds of fields, soils, and climates. And in the same way that Google can identify flu outbreaks based on where web searches are originating, analyzing crops across farms helps identify diseases that could ruin a harvest.

“What if we could have crops telling us what their symptoms were before a full spread epidemic popped out?” Ferrell says.

In the low-margin business of farming, this can have a big effect on profitability.


A wait-and-see approach

Nevertheless, many farmers are opting to keep their data on their farms, shunning cloud-based services.

“The acceptance of big data is across the gamut,” says Mary Kay Thatcher, a senior director of congressional relations at the American Farm Bureau Federation. “What you still find in big data is a lot of skepticism in the country.”

Some farmers are worried about security and how companies could use and profit off their farms’ data.

“A lot of the data we keep track of is sensitive to the farm, and I’m a little concerned if someone else got a hold of it,” Marshall says.

He opts to share his data with small, local groups only.

Part of the reason for slower adoption is contention over who owns and licenses farmers’ data. Savvy farmers know that information about their yields and performance is incredibly valuable.

“The first question everybody asks is who owns the data from my farm, and it’s really not a straightforward answer,” Ferrell says.

Monsanto has been pushing big-data analytics across all its business lines, from climate prediction to genetic engineering. It’s trying to persuade more farmers to adopt its cloud services. Monsanto says farmers benefit most when they allow the company to analyze their data — along with that of other farmers — to help them find the best solutions for each patch of land.

“We’re not building a business based on housing their data,” says Anthony Osborne, vice president of marketing at The Climate Corporation, a subsidiary of Monsanto.

He says that The Climate Corporation makes it clear that the farmers own their data, and it allows them to download or delete all the data that it collects.

“By providing their data, they get better models,” he says.

While contracts with big-data firms are generally a license agreement whereby the farmer retains ownership of the information, most also give the companies free rein to conduct studies and use the data to create highly profitable products.

As soon as a consultant or a company creates a data report, Ferrell says the person or company that created it probably owns it.

“Very quickly, the idea of ownership loses a lot of meaning,” says Ferrell, who says personal data is generally not included in the aggregated information.

But farmers see how much companies are investing in big-data. In 2013, Monsanto paid nearly $1 billion to acquire The Climate Corporation, and more industry consolidation is expected. Farmers want to make sure they reap the profits from big data, too.

That’s why farmers like Brian Marshall — no slouch when it comes to adopting technology — is cautious about letting companies like John Deere or Monsanto access his data. He wants to make sure he knows where the data is going and who will see it.

But, he says, that once those questions are resolved, and most believe they will be, “It’s exciting to think about what you could do with uploading the data on the cloud.”