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Building on decades of work done at Michigan State University, a company has sprung up to develop what they are calling a “land intelligence platform” which launched in early April.

The company, called CIBO Technologies, developed the platform so farmers and others interested in the value of land could have objective, science-driven intelligence about hundreds of millions of acres of farmland. Dan Ryan, CEO of CIBO, tells Wisconsin State Farmer that the new platform includes proprietary insights for each parcel, while also providing coordinated publicly available data that many farmers, investors, lenders, and other stakeholders in agriculture and the rural economy will find helpful.

Ryan said that as the company was developing the technology, they gathered together a group of farmers who offered their own fields for the data-driven platform and helped the company tweak the technology, helping make the parcel reports pop with the most relevant information.

“In these uncertain times we think this platform offers farmers the best information on land they may want to buy, own, lease, rent or operate,” he said.

While there are several other companies offering something like this, Ryan said there’s nothing out there that breaks down the information in so many ways. The company he leads was formed in 2015 to commercialize the work done at Michigan State University by Dr. Bruno Basso, a co-founder of the new company.

Their exclusively licensed technology simulates the way plants grow on a daily basis in varied environments. In the statement announcing the launch of the platform, Basso said he shared the company’s vision to bring the “highly proven ecosystem simulation technology from Michigan State as the starting point,” adding that “CIBO has invested heavily in scaling this technology and making deep science consumable by all users.”

In a telephone interview, Ryan said that Professor Basso’s decades-long work provided a great starting point to then create a platform that was commercially “scalable.”

“It handles huge, huge amounts of data – something like the equivalent of 500 billion pages of data and does it at scale. It performs at a very high level,” Ryan said.

CIBO’s proprietary insights include land and lease valuation, productivity, stability along with environmental impacts for each parcel. Additionally, past and in-season management practices and yields are provided, as well as the impact of various management practices and weather on the future productivity and value of a parcel. Valuation, predicted yield, crops planted, and environmental impact can also be aggregated at a portfolio, county, state, or national level.

They are aiming this technology toward a sustainability angle too. Based on Basso’s ecosystem work, the platform provides insights into the environmental effects of farming — calculating impacts like greenhouse gas emissions, nitrate leaching, and carbon accumulation in the soil over time. The platform creates a fact-based sustainability footprint for each parcel, giving farmers information they can use to choose regenerative agricultural practices and see the economic benefit. 

Ryan said that this objective information is available for land in all 48 contiguous U.S. states although the data is much richer in areas that have been farmed for decades like the Midwest and the Corn Belt.

“Cropping models have provided a rich source of information,” he said.

What some have called the “Zillow for farmland” includes public data like the owner’s name, township, county, tax information, satellite images, weather, soil maps and what crops have been planted and then adds proprietary insights. (Zillow is a real estate application providing information on residential properties.)

“Something like this hasn’t existed for agriculture,” Ryan said.  “The nature of farming is very opaque. How do you assess land that you might want to lease or buy? We are trying to provide a platform that will make that kind of information easily accessible to users and will modernize the way farmland is evaluated.”

Though not a farmer himself, Ryan fondly remembers as a kid going to a dairy farm owned by family in Renville County, Minnesota with his other cousins. He has enjoyed working with the farmers and ag lenders they brought into their advisory network and appreciates their practical views.

“When I talked to members of our farmers’ advisory network and they told me they were calling from their cab, I had to remind myself it wasn’t from a taxi – it was the cab of their tractor,” he said with a laugh. “They have been extraordinarily helpful.”

The value of his company’s new platform is that farmers can evaluate land they don’t know anything about in order to make plans, including yield predictions that can help guide decision-making. Ryan said this could also be very helpful to seed salesmen in terms of imported weather data and maturity dates and can be used to play out certain “what-if” scenarios.

One of the unique things about this new platform is that CIBO delivers its parcel-level information without requiring farmer data or user input. CIBO amasses vast amounts of public and private data, and processes it using its proprietary ecosystem simulation and data science, along with artificial intelligence and machine learning technologies. User access to the platform is from a web browser or mobile app, and can search parcels locally or nationally against over 20 criteria, including all the proprietary and public metrics.

Ryan explained that the platform is available at three levels: anonymously and free at the first level, which allows users a more limited amount of data; at a second level where users provide an email address; and third level where users pay a $9.99 per month subscription to use the platform.

Kyle Mehmen is a fifth-generation farmer in Northeast Iowa who serves on CIBO’s farmers’ advisory group. After college and a career with a crop science company, in 2005 he and his wife came back to the family’s farm at Plainfield, 40 miles north of Waterloo and now have two youngsters of their own. With his parents they grow corn and soybeans in seven counties in Iowa and five counties in Minnesota.

Wisconsin State Farmer reached him by telephone when he was in his sprayer last week. Mehmen said he’s been working with CIBO since its inception and had worked with Bruno Basso even earlier after meeting him at a John Deere meeting in Iowa.

“I’m excited to see where CIBO goes with this technology. There have been a couple of other platforms I’m familiar with that have tried to do appraisals from afar but to have a tool that relates one parcel of land to another is really helpful," he said. “It has a uniqueness built on Bruno’s yield predictability model and you can start to see the relative yield quantifier.”

He has made some suggestions on improvements to the platform as it was developed.

For a farmer like Mehmen who farms in different counties and even different states, it’s a valuable tool to harmonize things like the corn suitability rating or CSR, which is only used in Iowa, with the index values used in Minnesota or Illinois.

“None of them are the same,” he said. Using the platform, he can look at a field and know about how much corn he can expect to grow on it.

He feels that CIBO has made a good start on the tool, noting there is still some work to do.

“It’s not the end, it’s the beginning,” he adds. The company has a challenge in that others are “doing a good job” on some parts of this modeling but this one is put in a “format that’s believable.”

In residential and commercial real estate markets, similar tools have proven to be “valuable disruptors,” Ryan said, but that has not occurred in farmland markets, as objective information has not been readily available and usable. With its capabilities, he believes CIBO is “breaking the code” and will bring with it similar solutions in the agriculture and land markets.

Ryan explained that CIBO was founded with investment from Flagship Pioneering, a firm with a bigger vision for a “land intelligence platform” based on the use of science and data to generate objective information about land, at scale.

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