Resumo:
The volatile composition of coffee exerts a substantial influence on its quality, as it defines the characteristics of the beverage. However, these compounds are influenced by factors within the coffee production chain, such as botanical origin, geography, processing methods, and roasting. Consequently, the identification of such compounds becomes a vital tool for characterizing coffees to these factors. In this context, gas chromatography with headspace extraction is widely used for aroma analysis, providing a composition closer to consumer perception. Headspace extraction offers speed, simplicity, minimal sample preparation, and no need for solvents. In this study, static headspace extraction (SHS) coupled with gas chromatography-mass spectrometry (SHS-GC-MS) was employed to establish the chemical profile of volatile compounds in Coffea arabica and Coffea canephora var. conilon and determine discriminants between the species. A total of 97 compounds, belonging to 17 chemical classes, were identified. The chemometric analysis highlighted furans, phenols, and carboxylic acids as key differentiating classes. Notably, furfuryl alcohol, acetic acid, 4-vinylguaiacol, N-acetyl-4(H)-pyridine, and N-furfurylpyrrole emerged as crucial volatile compounds. The variable selection using Fisher weight applied directly in the chromatograms, produced models consistent with relative area data, with furfuryl alcohol and 4-vinylguaiacol regions being particularly influential in differentiation.
