Practical answers on precision tech – Part 3

Precision agriculture technology does not come one-size-fits-all. Limitations, specific on-farm needs, and overall goals all dictate what makes good business sense. With this in mind, four North American farmers share how they make precision pay. In Part 3: Mark Brock from Ontario.

Refined data analysis is what Brock identifies as the best opportunity to improve efficiency, though it’s also one of the most significant challenges for his grain operation.

Variety of technologies

Brock makes use of a variety of technologies, including section control on all equipment, a UAV (drone) in combination with NDVI for diagnosing problems (e.g. whether a fungicide application is warranted), RTK guidance for additional precision, and a planter fully customised with aftermarket parts. This is combined with a variety of data tools, including Climate FieldView, Farmers’ Edge, Agrimatics, and several others.

I always joke our planter has more in it in terms of aftermarket planting parts than I paid for the whole planter. But it’s just a phenomenal tool

“There’s some really cool hardware and equipment technology on the precision ag side. We just incorporate it as much as we can whenever we can because we see value in it. I always joke our planter has more in it in terms of aftermarket planting parts than I paid for the whole planter. But it’s just a phenomenal tool,” he says.

In Part 1 of this series, Clinton Monchuk explains why precision tech for him is a cost-saver rather than money maker

Bettering profitability and mitigating risk is a constant challenge

The combination of variable rate and sectional control hardware, plus a wide range of software means Brock is able to have full confidence when entering and leaving the field – provided he is confident in their information analysis.

Brock uses many different analytical tools because he has yet to find one that does everything he wants it to do. But while they generate tons of data, bettering profitability and mitigating risk is a constant challenge.

We have data out the wazoo, but sometimes its not the data we’re looking for

“I think we get caught up somewhere in the hardware and the cool maps, but it really has to make money at then end of the day,” he says. “We have data out the wazoo, but sometimes its not the data we’re looking for.”

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Mark Brock says data tools and accompanying precision hardware can save money in some cases, make money in others, and save time. Achieving these things just requires analysis, and realistic expectations. – Photo: Mark Brock

Transfer or convert data between different platforms

Additional challenges to making data actionable include an inability to transfer or convert data between different platforms, and the absorption of agriculture-focused tech start-ups by large companies.

“You kind of have this relationship with a company that you feel you’ve helped them get going. When they move on to something bigger and better, you can worry you may not have that relationship any longer.”

Overall, though, Brock says data tools and accompanying precision hardware can save money in some cases, make money in others, and save time. Achieving these things just requires analysis, and realistic expectations.

In Part 2 of this series, Justin Hiebert talks about how he makes variable rate work