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Data-Driven Farming

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Farm drone

Credit: Mauricio Lima, flickr.com, CC BY 2.0

by Taylor Dobbs, Popular Science

Since Dorn Cox began automating his 250-acre New Hampshire farm four years ago, he has installed dozens of sensors. Some measure moisture in soil around his squash. Some track temperatures in the greenhouse air around his cucumbers. Others track wind speed and rainfall in segments of field roughly a quarter-acre in size. When something is amiss — temperatures are too high or the soil is too dry — he receives an alert on his smartphone. He also sends out drones to survey his field crops for dryness, soil erosion, and plant health.
“On a farm, there’s a lot going on,” Cox says. “Being able to keep track of it all without having to hire more people is important. It lets you do a better, more efficient job.”

For centuries, farming was an intuitive process. Today, it’s networked, analytical, and data-driven. Large farms (1,000 acres or more) started the trend, adopting the tools of precision agriculture — using GPS-guided tractors, drones, and computer modeling to customize how each inch of land is farmed. Farm managers can measure and map things like soil acidity and nitrogen levels, and then apply fertilizer to specific plants — not just spray and pray. As a result, they get the most out of every seed they plant. Such methods have reduced farm costs by an average of 15 percent and increased yields by 13 percent, according to a 2014 survey by the American Farm Bureau Federation.

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© 2016 Popular Science

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