When Nate Linder began shelling a trial last fall, he ran and weighed several passes at different driving speeds. Yes, it slowed down harvest. But his goal was accuracy, not speed.
It took Linder, manager at the Meigs Farm, Romney, Ind., part of the Purdue University farms system, five passes to feel comfortable that the combine’s yield monitor was calibrated correctly.
You’re probably thinking since you’re not worried about research, you don’t have to worry so much about calibration. Bob Nielsen, Purdue University Extension corn specialist, says that all depends upon what you intend to get from yield maps.
Pretty picture or data?
“There are two approaches,” Nielsen says. “If you’re satisfied with yield maps that give you a general picture, then having the monitor dialed in with as little error as possible may not be as important. Maybe you’re using maps to show your landowners which fields need tile. If you can show them wet spots yield less, you may be satisfied.”
Finding farmers who know their yield monitor is off 5% or more isn’t hard. They don’t invest time to calibrate precisely.
If using maps for short-term decisions is your goal, nothing is wrong with that approach, he says. But if you want accurate data, you need to spend time calibrating.
“What concerns me is that some people have 15 years or more of maps in drawers,” he says. “If the yield monitor wasn’t calibrated correctly, what they have are pretty maps and not 15 years of solid data.
“How to analyze and use years’ worth of data has been slow in coming, but there are now people doing it,” Nielsen says. “Expect more people using past data to make decisions in the future.
“If you have accurate data for each year, you have valuable information. If you just have maps, you can’t go back and capture more precise data.”
The most important thing you can do is read calibration instructions in the operator’s manual, Nielsen says. “Do it right now if you haven’t done it already. Don’t wait until you’re ready to run full out.”
Different manufacturers suggest different steps, but the principles are the same, he says. What the yield monitor sees where it computes numbers is a series of electrical impulses. Those impulses come from the sensor in the clean grain elevator.
There are two types of sensors. Most monitors use impact sensors. What’s measured and converted to electrical signals is the force of kernels hitting the monitor plate. Today some monitors use optical sensors. The result is the same: Monitors compute data based on electrical impulses.
So why did Linder run at varying speeds when he was calibrating the yield monitor? Each pass is often called a “load.”
“He was training the yield monitor how to interpret the series of electrical impulses,” Nielsen says. “The goal is to simulate different rates of flow that sensors will see while harvesting. In the field at operating speed, flow varies due to yield differences. Running at different speeds mimics different flow rates. You dial in the monitor according to the operator’s manual so that differing flow rates correspond with yield variation.”
You can also take passes at full header width, three-fourths width and so on to generate reduced flows. Nielsen suggests following the procedure in your manual.
Calibrating once per crop per season won’t cut it if you’re after accurate data, Nielsen says. Ideally, recalibrate if you change hybrids, particularly if there’s a big difference in ear type or grain moisture. Also check accuracy of calibration and recalibrate, if necessary, if moisture changes significantly from one field to another.
Pete Illingworth, combine operator at Meigs Farm, found hybrid variation makes a big difference while running field-scale plots. Once the monitor was calibrated on one hybrid, error vs. grain cart weight on each load was about 0.5%. But when he changed hybrids, yield error shot up, varying from 1% to 2.5%.
The first hybrid had more rows of smaller, shallower kernels. The second hybrid had fewer rows of larger, deeper kernels. The impact of kernels on the sensor varied enough to affect yield results.
Moisture calibration is important because the monitor used that information to calculate dry weight. Many times operators check it and adjust one time based on comparisons between the monitor and a stand-alone moisture tester.
“It becomes a problem if moisture varies widely,” Nielsen says. “If you harvest corn that is 3 points wetter or drier than when you calibrated, you should recalibrate the moisture sensor.”
Worry over 'calibration after the fact.'>>>
~~~PAGE_BREAK_HERE~~~Be wary of ‘calibration after the fact’
Some farmers tell Bob Nielsen that they run all season, and then compare weigh tickets to yield monitor totals. Some yield mapping software lets them correct yield monitor data based on scale weights. Yield maps adjust to the new weights.
“The fallacy is that such software I’ve used adjusts on a blanket basis,” he says. “If after the season you discover yields for the entire field were 5% too high on the monitor, postharvest calibration with the software simply adjusts all data to make yields 5% lower.
“The problem is that’s not how the real world works. Yield monitor estimates for 50% of the field may be 10% too high. On average, yields for the entire field would be 5% too high, but adjusting the entire field’s data down 5% with the software is simply not correct.”
Nielsen says that’s because the software would unfairly lower yields that were spot-on, while not changing the truly incorrect data enough.
“You’re not getting a fair representation of what really happened,” he concludes.
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