CO2 Monitoring: a New Grain Management Tool
After 10 years of research conducted by K-State and Purdue University, the first commercially ready, stationary CO2 monitoring system is available to help elevator operators make better business decisions.
However, Tim O’Connor, co-general partner with BinTech, cautions that there are some drawbacks to using hand-held sensors.
“In order to get quality data out of a bin, you have to measure it at the same time each day because the actual temperature of the headspace in the bin will vary by tens of degrees throughout a 24-hour period,” O’Connor says. “Many years of data across a wide variety of bins have shown us that the temperature fluctuation influences the movement of air in the bin and CO2 in the air. The stationary sensor takes a reading every hour, knows the temperature pattern and accounts for it. If you’re taking periodic hand-held readings, you don’t know what the cyclical pattern in that bin is, which can lead to errors in interpreting the data and overlooking a potential problem. I’m confident that people will find value in the reliability and automated convenience of hourly CO2 readings.”
Continued research
The K-State/Purdue/BinTech research project recently received a grant from the Kansas Corn Growers Association and will continue to look for better ways to interpret CO2 data.
Fromme and O’Connor are also dedicated to helping fund future post-harvest issues research at K-State by donating a portion of the proceeds from every BinTechCO2 to the university.
“The end user, through purchase of this product, can help fund future research even into areas that don’t necessarily benefit BinTech,” says Fromme. “We’re doing this in response to an industrywide concern about how to fund future research.”
After a difficult harvest year like 2009, elevator managers could use all the help they can get. Whether using hand-held sensors on temporary grain piles or BinTech’s permanently mounted sensors on 10,000- to 500,000-bushel-bins, research has proven the practice can effectively detect grain quality issues early on and can help elevator managers make smart business decisions.
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