Corn moisture answers in real-time. In the rows, on the cob, and on the go, SCiO is a new pocket-size, handheld device capable of providing corn moisture data within a few clicks. Scan five cobs, open a mobile app, and receive a near-instant moisture level reading on par with laboratory analysis, according to Consumer Physics, developer of SCiO.
The SCiO analyzer is a miniaturized near infra-red (NIR) spectrometer capable of hundreds of scans powered by a rechargeable battery. Scan data is sent to the cloud and returned seconds later with results, allowing farmers and agronomists to sample from large areas, project harvest and potentially save on drying costs.
The unit (weighing 35 grams) connects to any smart device (Apple or Android based platforms) via Bluetooth. “This is the first micro-based NIR on the market that comes to our users pre-calibrated and ready to use,” says Terry Allen, North America Head of Business Development for Consumer Physics.
Initially developed for seed corn breeders and seed corn companies, SCiO is capable of reading moisture levels from 8% to 80%. “Farmers can benefit from this technology because it is able to analyze moisture levels above 25% accurately and requires no shelling of the cob,” Allen explains.
“Instead of moving heavy equipment into fields such as a combine, and checking, farmers can take the SCiO, walk into a field, and determine the moisture levels in minutes. This can help in pre-harvest planning which fields to harvest first. It is also an excellent tool in helping to determine pre-harvest yields.”
“All sales in the U.S. are through our Distributor Shore Measuring Systems,” Allen continues. They have been working closely with farmers in providing moisture meters to farmers and producers since 1968 and understand their need for accurate testing.”
Once analysis is complete, a user can add notes, and email or text the results, according to Allen. Additionally, the SCiO app tracks the location of each analysis; contains a built-in heat map from every plotted analysis; and identifies dry-down trends.
For more information, see SCiO.