The Top 10 People In Precision Agriculture

The Top 10 People In Precision Agriculture

Precision agriculture — with all its wacky technologies and advanced algorithms and such — remains a people business. So, without further adieu, on the pages ahead are the Top 10 people (in alphabetical order) we feel are driving precision agriculture adoption forward in 2016.

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Be sure to also check out these top 10 lists:

Top 10 Technologies In Precision Agriculture Right Now

10 Bold Predictions For Precision Agriculture

MORE BY MATTHEW J. GRASSI

1. Wade Barnes, Farmers Edge, CEO

Wade Barnes Farmers Edge using FarmCommand

Farmers Edge, led by CEO Wade Barnes, has nearly 300 employees who specialize in everything from data science to hardware engineering, to soil science and sustainability.

Fresh out of ag school and working as an agronomist at the local co-op, Farmers Edge (Winnipeg, MB) CEO Wade Barnes bore witness to the first wave of precision agriculture adoption in his native Canada basically fall flat on its face, and he says that experience still drives him as his VRT-focused outfit ascends to the top of the Canadian precision ag data management realm.

“I saw guys spending $50 an acre to get a $10 return; I saw precision at its earliest stages (in Canada) and I saw it essentially fail,” he recalls of his early days consulting on acres in Western Canada.

Barnes ended up moving on to an independent cooperative a little further south near the Manitoba/North Dakota border, where he worked on remote sensing applications in high nitrogen sugar beet fields.

“It made me rethink the whole strategy and see all the things that we had done wrong in the first wave,” he remembers. “I could see that grid-sampling didn’t really make a ton of sense.”

Today, Farmers Edge has nearly 300 employees who specialize in everything from data science to hardware engineering, to soil science and sustainability.

“Field-centric weather is by far the most important (form of weather data), because everybody right now is making promises around taking this data and moving more towards ‘decision ag’,” Barnes says. “The problem is, everybody is trying to tap into this public weather data set, because there’s an infrastructure there and it’s free.

“Well, this data is coming from 30 miles away — weather is so variable, you can’t use data from a weather station 30 miles away to create a predictive model on fungicide (application). It doesn’t work. If you’re off by five or six days, you could cost that farmer thousands”