SPME-GC–MS and chemometrics for coffee characterization, classification and authentication

In recent decades, the complexity of the food chain has contributed to a surge of food adulteration issues, resulting in numerous instances of food fraud. For this reason, ensuring the authenticity of food is crucial for society as a whole. In this context, beverages are particularly vulnerable to adulteration by adding flavors and aromas or incorporating unspecified substances to enhance volume, among other deceptive practices. This work focuses on the detection of fraud in coffee, one of the world's most popular beverages, which is a product easily prone to manipulation. Fingerprinting studies of volatile compounds in 185 samples were performed by gas chromatography (with polar and non-polar columns) coupled to mass spectrometry (GC–MS) and in combination with chemometrics for data analysis. In this group of samples, 42 were chicory, 96 were coffee of different species and geographical production regions, and 47 were soluble coffees. Headspace-solid phase microextraction (HS-SPME) was employed to obtain the volatile compounds in the samples directly from the solid coffee. The GC–MS fingerprints served as reliablechemical descriptors for the classification of coffee samples using chemometrics. Moreover, some compounds found in samples were tentatively identified using NIST Research Libraries. Furthermore, two adulteration coffee studies were performed using partial least squares (PLS) regression, which demonstrated the feasibility of the proposed methodology for the quantification of adulterant levels up to 15%, with calibration and prediction errors below 2.9% and 7.4%, respectively.