A Robot Nose Can Identify Whisky With 95% Accuracy
The NOS.E machine may help the whisky industry fight counterfeiters and improve quality
An electronic nose just got very, very close to 100% accuracy in a test run of identifying different whisky samples.
As published this year in the IEEE Sensors Journal, an olfactory device called NOS.E was able to identify a brand of whiskey with more than 95 percent accuracy after just one e-whiff.
While just published, the research actually dates back a few years. As the authors note, “The proposed e-nose solution was verified by a field testing displayed at the CEBIT Australia 2019 trade show, by reaching an accuracy of 96.15%, 100%, and 92.31% in brand name, region, and style classification, respectively.” The whiskies tested included blended and single malt Scotches, from Johnnie Walker Red and Black label brands to The Macallan’s 12-year-old single malt.
All well and good, but why an e-nose? As the scientists suggest, the device could be used for both quality assessment and fraudulent detection. “This lucrative industry has the potential to be a target of fraudulent activities such as mislabeling and adulteration,” says researcher Steven Su, an associate professor at the Faculty of Engineering and IT, University of Technology Sydney. “Trained experts and experienced aficionados can easily tell the difference between whiskies from their scents. But it is quite difficult for most consumers, especially amateurs.”
Per The Drinks Business, NOS.E is a machine designed to mimic the human olfactory system, using eight gas sensors to detect odors and, coupled with a machine-learning algorithm, trained to recognize particular whisky characteristics.
It’s not the only machine designed to identify whisk(e)y: Last year Eluceda launched a new rapid authenticity “taste” test for whisky in the form of a handheld machine, called the E-Sens, that used customized electrodes with specific catalysts, which react with the “unique groups of molecules” in whisky to produce a digital fingerprint in minutes.
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