Researchers in Italy and the United States have proposed a new analytical workflow for identifying a roasted coffee’s geographic origin through lab analysis of volatile compounds.
The approach combines comprehensive two-dimensional gas chromatography (GC×GC) with computer vision-based pattern recognition, turning complex aroma data into image-like chemical fingerprints that can be compared across origins.
The study, by researchers affiliated with the University of Turin, the University of Nebraska-Lincoln and Italian coffee company Illycaffè, was published in May in the Journal of Chromatography A.
Practical Implications
The authors said the proposed GC×GC-CV workflow offers a “reliable strategy for origin identification and quality assessment,” although the paper does not present it as a market-ready plug-and-play tool for routine industry use.
This line of research often relates to coffee quality control and origin verification claims, both of which can carry meaningful premiums in the green coffee market. Origin claims have also been associated with green coffee fraud, underscoring the need for lab-based analysis.
GC×GC and Computer Vision
Standard gas chromatography separates hundreds of aroma compounds, but GC×GC essentially does the sorting twice, in two different “directions,” creating a two-dimensional map rather than a single line of peaks.
The result is greater separation power and a more structured pattern that can help analysts distinguish chemical families in very complex foods, such as coffee.
Computer vision is best known for tasks like recognizing objects in photos, but here it’s used to treat a GC×GC chromatogram like an image, then compare patterns across samples. The software does a first-pass comparison across the full pattern, then flags the regions that differ most by origin, according to the research team.
“Overall, the proposed GC×GC–CV workflow provided a clear, reproducible, data-driven representation of the coffee volatile fraction, allowing an integrated view of its chemical diversity and offering a reliable strategy for origin identification and quality assessment,” the authors wrote.
One of the study’s authors is an employee of Italy’s Illycaffè, and two others reported a financial interest in the company that provided the GC×GC software, although none said the work was influenced by those ties. The work received funding from the European Union’s Horizon Europe program.
Comments? Questions? News to share? Contact DCN’s editors here. For all the latest coffee industry news, subscribe to the DCN newsletter.
Source link