Farmers are the ultimate multitaskers. Part agronomist, part mechanic; manager and marketer; as willing to get their hands dirty turning a wrench as to don a suit to support the industry.

Now they must add data scientist to the list of hats they must wear, in order to get as much out of their crop as efficiently and profitably as possible.

The same is true for the researchers at Bayer. Data significantly speeds the company's robust research and development product pipeline without compromising safety. Hybrids that once took season after growing season to develop now take a fraction of that time. Whether collected by a sensor underground, on a sprayer or on a satellite orbiting Earth, data provides the foundation and building blocks in the development of hybrids that can be tailored to individual farmer's needs.

Take corn, for example.

"A large majority of this year's corn deployments were accelerated by at least a year due to data science," says Trent Yantes, Head of Trait and Pipeline Delivery at Bayer, noting this includes products such as SmartStax® corn, VT Double Pro® corn, and DroughtGard® Hybrids with VT Triple PRO® RIB Complete® corn blend. "Our team of data scientists use these analytics to not only pick elite germplasm but to make sure we're putting them in trait combinations that provide the most value."

Collecting data when breeding plants for desired traits has been commonplace since Gregor Mendel did it when planting peas in the garden of an Austrian monastery in the mid-19th century. As recently as 15 years ago, plant breeders still collected and noted their observations much like Mendel: in person with pen, paper and simple tools, plant by plant by plant, season after season after season. Not only was the process tedious and time-consuming, but it also left the data vulnerable to human interpretation and potential error.

Weather data is just one piece of the puzzle in developing new products at Bayer, and a crucial one in helping growers get the best return.

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"Traditionally, data was always collected with a lot of people, and it might take a couple days to take a single observation in a field," says Tom Jury, Head of North America Field Testing at Bayer. "Today, you take an image and plot the whole field in minutes rather than days."

Automating as much of that data collection as possible is the job of the Seed Production Engineering Team at Bayer. Dave Baitinger, who leads the team, says automation increases both the quality and accuracy of the data, allowing more confidence in the performance of the hybrids. "We look at all sorts of different layers of imaging that we can use to help automate more data collection," he says.

Drones and satellite imagery accelerate speed and accuracy, advancing the age-old breeding process, and they've also increased the sheer volume of data now available to farmers, requiring new ways to handle and analyze it.

Photo: Huseyin Bostanci/iStock/Getty Images Plus via Getty Images

   

"We've developed artificial intelligence models to sort through all this data and have started deploying hybrids using it," Yantes says. "These analytic models can run the data in a matter of minutes, whereas it might take a human days or weeks."

Before data science was incorporated, selecting corn hybrids was somewhat like selecting football players in the NFL Draft. While college players might display all the attributes that could lead to success, sometimes they never achieve their potential, or they're not a good fit for the team that picks them. Corn hybrids could be the same way.

However, thanks to these enormous data sets, the Bayer team can now evaluate every aspect of a corn hybrid and predict its expected performance against hundreds - if not thousands - of variables. It's like an NFL scout knowing how many games players will win before they ever step on the field.

"When a grower comes to you, it's not about picking the top yield-performing hybrid on the list. It's about picking what's best for that specific field," Jury says. "Knowing the performance of our hybrids against the variables that exist in a grower's field gives them the best likelihood for success."

Every field has its own specific conditions, below ground and above. That data helps drive new products for Bayer and optimal ROI for the grower.

Photo: Photo Courtesy of Bayer

   

But none of this matters if the information can't be put into the hands of growers. That's where Climate Fieldview™ platform comes in. A division of Bayer, The Climate Corporation's digital ag platform, FieldView, allows growers to input and visualize all data associated with their crop, from planting, through the growing season and all the way to harvest. Essentially, FieldView turns an entire farm into a test plot where layers upon layers of data can be analyzed to maximize return on investment.

"We have nothing if we don't have high-quality data," Jury says, "so we spend a lot of time looking at new technologies while also working with existing systems. If we know a farmer's risk or exposure, we're able to make recommendations that enable them to have the most successful season."

   

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^{This material may contain "forward-looking statements" based on current assumptions and forecasts made by Bayer management. Various known and unknown risks, uncertainties and other factors could lead to material differences between the actual future results, financial situation, development or performance of the company and the estimates given here. These factors include those discussed in Bayer's public reports which are available on the Bayer website at http://www.bayer.com/. The company assumes no liability whatsoever to update these forward-looking statements or to conform them to future events or developments.}

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