Making sense of data
With new crop technology helping farmers glean more and more data from their fields, the number of ways to put that data to use is growing rapidly.
Here are five key points farmers should keep in mind for gathering yield data and putting it to use, according to John Grandin, a certified crop adviser and seed agronomist with Growmark, Inc., in Oneida, Illinois.
- Yield monitor calibration
Lay solid groundwork before building your data portfolio. This starts with ensuring that your precision tools are sharpened before entering the field. Before making any decisions based on your yield monitor, you've got to make sure it's calibrated accurately.
"Compare the whole field yield monitor-determined yields with scale-determined yields for the whole field," Grandin says. "You can have greater confidence that your yield monitor data is sufficient for analyzing yield differences when this difference is smaller."
- Inaccurate data
Yield data isn't always right. It depends on accurate calibration, which can sometimes be a challenge when it comes to fields that are irregularly shaped or have trouble spots or row gaps. Including these areas can skew yield data, Grandin says. Make sure you factor in such areas in collecting yield data.
"Start- and end-of-pass delay settings will influence how yield data is interpreted in these areas," he says. "Areas with less than the set swath width being harvested will be displayed as lower yielding. Wide variations in crop moisture across a field may create yield variability.
"This is especially noticeable when a field is harvested during a several-day period." says Grandin.
- The highs and lows
No field is perfect -- each has its sweet spots and dark corners. Looking into the cause for each is key to obtaining accurate yield data for future crop-management decision making. According to Grandin, it's important to find out why the best- and worst-yielding parts of the field are skewing so far from the average. A thorough investigation may be necessary.
"Are there any differences in field conditions or production management between the highest- and lowest-yielding areas of a field? Can you correlate the yield differences to these other conditions?" he asks. "Don't jump to conclusions without thoroughly investigating your theory."
- Yield map interpretation
There's little room for fuzzy boundaries in yield maps. Crop-management practices, according to Grandin, create straight-line patterns with identifiable borders on yield maps just as they do in the field.
But, other factors can often lead to gray areas in conditions. "Naturally occurring variables often result in irregular patterns with borders that may or may not be well defined," Grandin says.
Be sure to take note of these types of conditions and factor them into yield maps to obtain accurate data, he adds.
- The obvious
When working with reams of yield data, it may seem like there are more factors and variables present than what you can realistically factor into crop-management decisions. But, be careful not to overlook a simple, obvious answer amidst all of the data.