Coffee authentication using GC-MS and chemometric methods. Application to the detection and quantitation of adulterated coffee samples

Abstract

Food adulteration has been increasing in recent decades as a result of the complexity of the food chain, leading to cases of food fraud. It is for this reason that the verification of the authenticity of food is very important in quality control

and food safety in addition to being an issue of great interest to consumers, the food industry, regulatory authorities and the scientific community in general. In this field, beverages are food products which are easily adulterated by such methods as supplementation with flavors and aromas or the addition of unspecified substances to increase their volume, among other practices. The study presented in this paper was based on the detection of frauds in one of the world’s most popular drinks, coffee, which is an easily manipulated product. Metabolomic studies of volatile compounds in coffee samples (normal and adulterated) of different species (Arabica, Robusta, Arabica-Robusta mixture) were performed using gas chromatography (with polar column) coupled to mass spectrometry (GC-MS) and in combination with the chemometric methods partial least squares-discriminant analysis (PLS-DA) and partial least squares (PLS) regression, for classification, characterization and authentication. The volatile compounds in the samples were obtained directly from the solid coffee using headspace-solid phase microextraction (HS-SPME). The fingerprints obtained were good chemical descriptors for the classification of different coffee samples

using the PLS-DA chemometric method. In addition, a study of adulterated coffee was performed using PLS, based on Arabica coffee adulterated with Robusta coffee, which demonstrated the good ability of the proposed methodology for the detection and quantification of adulterant levels up to 15%, with calibration and prediction errors under 1% and 6%, respectively.