Science has already determined that the very smell of coffee can make people smarter. Now, research from China is taking the knowledge of the nose even further, applying an e-nose to determine the origins of roasted coffees.
The e-nose is one of three advanced techniques the research team used to confirm what is essentially a fingerprint of volatile aroma compounds that were associated with coffees from eight specific countries.
According to the study authors, the goal was to build a methodology to better understand how origin shapes flavor, which might have practical implications as market actors seek to add value to coffee by enhancing or maximizing aroma.
Yet another goal was to explore faster, more reliable ways to trace the source of a coffee. Although not explored in detail in the study, the latter goal may be most applicable to counterfeiting.
“As research on food flavor deepens, the integration of multiple analytical techniques, rather than relying on a single method, offers a more comprehensive characterization of flavor profiles,” the study states. “This approach provides reliable information from multiple perspectives, enhancing the accuracy and depth of flavor analysis in experimental subjects.”
Arriving in the July 30 edition of the journal Food Chemistry, the study employed these three analysis techniques on roasted coffees:
- Gas chromatography time-of-flight mass spectrometry (GC-TOFMS), which identified 168 volatile organic compounds (VOCs), 34 of which were key contributors to coffee aroma;
- Gas chromatography ion mobility spectrometry (GC-IMS), which detected 105 VOCs and successfully distinguished coffees from different countries;
- and Gas chromatography electronic nose (GC-E-Nose), which mimics human smell and was able to rapidly distinguish beans from different origins based on their volatile profiles.
The coffee samples were all roasted arabica beans from China, Papua New Guinea, Indonesia, Ethiopia, Brazil, Kenya, Colombia, and one unidentified eighth country.
By identifying the specific aroma-related compounds — such as certain furans, ketones and pyrazines — based on region, the researchers said they were able to build predictive models to classify origin with a high degree of accuracy. The GC-E-Nose was then presented as a tool to quickly identify these markers.
“The findings provide a foundation for the rapid identification of the origin of roasted coffee beans,” the authors wrote.
The study was financially supported by the National Natural Science Foundation of China and two other Chinese state-funded scientific initiatives.
It follows a related study from researchers in Taiwan last year in which an AI-assisted e-nose identified specific coffees with up to 98% accuracy.
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