SPME-GC-MS untargeted metabolomics approach to identify potential volatile compounds as markers for fraud detection in roasted and ground coffee.

Roasted ground coffee has been intentionally adulterated for economic revenue. This work aims to use an untargeted strategy to process SPME-GC-MS data coupled with chemometrics to identify volatile compounds (VOCs) as possible markers to discriminate Arabica coffee and its main adulterants (corn, barley, soybean, rice, coffee husks, and Robusta coffee). Principal Component Analysis (PCA) showed the difference between roasted ground coffee and adulterants, while the Hierarchical Clustering of Principal Components (HCPC) and heat map showed a trend of adulterants separation. The partial Least-Squares Discriminant Analysis (PLS-DA) approach confirmed the PCA results. Finally, 24 VOCs were putatively identified, and 11 VOCs are candidates for potential markers to detect coffee fraud, found exclusively in one type of adulterant: coffee husks, soybean, and rice. The results for possible markers may be suitable for evaluating the authenticity of ground-roasted coffee, thus acting as a coffee fraud control and prevention tool.