Rapid Classification of Unroasted Green Coffee Beans and Spices Based on the Tentative Determination of Volatile Compounds by Solid-Phase Dynamic Extraction (SPDE) and Gas Chromatography–Mass Spectrometry (GC–MS) with Supervised Learning

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The present study comprises the second part of our previous work that dealt mainly with the phytochemical and physicochemical characterization of commercial unroasted green coffee beans, clove, cinnamon–clove and nutmeg ethanolic extracts of grape origin. In the present study, we focused on producing a discriminating model concerning commercial unroasted green coffee beans, clove, cinnamon, cinnamon and clove mixture (1:1, w/w), and nutmeg fine powders based on multivariate analysis of variance and supervised learning from tentative data of volatile compounds analysis, carried out with solid phase dynamic extraction in combination with gas chromatography–mass spectrometry. Results showed that 7 volatile compounds, i.e., ethylene, methanol, 3-methylpentane, ethyl acetate, 9-hexadecen-1-ol, toluene, and methyl acetate, could differentiate the investigated samples resulting in a 100% classification rate using the cross-validation method of linear discriminant analysis. Results were further confirmed using partial least squares regression analysis. The study contributes to the typification of commercial unroasted green coffee beans, cinnamon, clove, cinnamon and clove mixture, and nutmeg, based on selected volatile compounds. In addition, the study provides further support to the literature by means of a possible substitution of these products in rapid analysis tests, given the statistical models developed.