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Layers of Data

December 7, 2013
By: Margy Eckelkamp, Director of Content Development, Machinery Pete
zone maps
What a difference a year makes. The map on the left was made using an uncalibrated yield monitor. The map on the right was captured the next year using the correct calibration, providing spatial variability correlating to soil types.   

Zone management decisions hinge on precise data

With every combine pass, you have the opportunity to harvest more than grain. Farmers know there is variability across their fields, but having a GPS-referenced yield map provides a solid foundation for future zone management decisions.

"We’ve found that the most important data are the yield maps," explains Neal Wolheter, who farms near South Milford, Ind. "We’ve used soil maps for 12 years for zone management and a yield monitor for the past five to help refine those zones."

The key step to gathering usable data with a yield monitor takes place before harvest even begins—with proper calibration.

"Many yield maps have not been usable in zone management decisions because the calibration process was not done properly," explains Farm Journal Associate Field Agronomist Missy Bauer. "You have to teach the monitor what’s considered low, medium and high yields for each grain type."

Bauer and her crew have worked with farmers across Michigan, Indiana and Ohio to develop management zones. When preparing for harvest every year, she says the most common mistake is the size of calibration loads.

new zone map

This NDVI aerial map indicates several areas that need to be ground-truthed.

"Incorrectly, farmers will often run a calibration load as a whole semi load," she says. "We do 4,000-lb. to 8,000-lb. loads at the different speeds to simulate bushels per acre. That cleans up the data, but those calibrations are only good for +/- five moisture points in corn. So we run a high-moisture corn type and a lower moisture corn type when we calibrate."

For Wolheter, his motivation to properly calibrate yield monitors comes from the value of the data.

"We’ve seen how good-quality yield maps translate into better zone management," he says.

Following the calibration instructions changes the yield monitor from measuring averages to precisely mapping variability.

 "If a grower calibrates by the semi load, his maps could be accurate to the average of the field, but you can’t pick out the variations in yield. Those maps don’t show any defined patterns in yield," Bauer says.

Identifying that variation in a field is the difference between measuring accuracy and preciseness. This is the definition of spatial variability.

"If your yield monitor is accurate but not spatially accurate, it’s only good for managing inventory," says Farm Journal Field Agronomist Ken Ferrie. "It won’t be a good tool for zone management because it’s all about precision. We really need an accurate and spatially variable map. However, I can work with a spatially variable yield monitor that is 10 bu. off from the elevator better than one that only displays accuracy."

Ferrie encourages farmers to think of the yield map as their report card.


"Of all the layers we are going to look at, the yield maps show the history of the field. From there, we can make predictions on how different things will affect yield—nitrogen management, population, drainage—but it all comes down to what actually happens in the yield map," Ferrie says.

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FEATURED IN: Farm Journal - December 2013

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