A new report details how researchers have developed an “e-nose” that can distinguish different types of whisky.
The e-nose project was led by Associate Professor Steven Su with PhD students Wentian Zhang and Taoping Liu, from the University of Technology in Sydney, Australia, in collaboration with chemists Prof. Shari Forbes and Dr. Maiken Ueland.
They set out with the notion of Scotch or Irish, single malt or blended, how a whisky enthusiast might be able to distinguish the good stuff from run-of-the-mill by smell alone. A counterpoint to the fact that many drinkers tend to rely on the label.
Whisky has become one of the most popular alcoholic beverages across the globe, with some high-end brands fetching five or six figures. This also makes it a favorite target for fraud.
In order to combat this, these researchers have developed an electronic nose (e-nose) that can distinguish between different brands, origins, and styles by “sniffing” the liquor.
“Up until now, detecting the differences between whiskies has required either a trained whisky connoisseur, who might still get it wrong, or complex and time-consuming chemical analysis by scientists in a lab,” said Associate Professor Su in a prepared statement. “So to have a rapid, easy to use, real-time assessment of whisky to identify the quality, and uncover any adulteration or fraud, could be very beneficial for both high-end wholesalers and purchasers.”
The team used their new e-nose prototype (called NOS.E), developed at the university, to identify the differences between six whiskies by their brand names, regions, and styles in less than four minutes.
The experiment used samples of three blended malts and three single malt whiskeys, including Johnnie Walker red and black label whiskey, Ardberg, Chivas Regal and a Macallan’s 12-year-old whisky.
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The study, recently published in the journal IEEE Sensors, showed the e-nose reached 100% accuracy for detecting the region, 96.15% accuracy for brand name and 92.31% accuracy for style.
NOS.E is designed to mimic the human olfactory system, using eight gas sensors to detect odors in a vial of whisky. The sensor array generates the unique signal matrix according to the different odor molecules it comes into contact with.
It then sends the data to a computer for analysis, with a machine learning algorithm trained to recognise whisky characteristics. The researchers confirmed the NOS.E findings using state-of-the-art lab tests on the whisky samples.
The research team explained that this technology has applications not only in the alcohol industry, with beverages such as wine and cognac as well as whisky, but also for other products that are subject to counterfeiting such as high-end perfume.
The e-nose technology has also been used to detect illegal animal parts sold on the black market, such as black rhino horns, and has potential for health applications and disease detection.
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