Abstract

Recent increase in the adulteration of spices and aromatic herbs in food industry constitutes a problem that requires exhaustive quality control. As every spice has a different composition with characteristic biomarkers, chromatographic profiles are especially valuable to authenticate these products. Thus, in this work a new high performance liquid chromatography (HPLC) method with UV–vis detection was developed for the characterization, identification and authentication of cinnamon, oregano, thyme, sesame, bay leaf, clove, cumin, and vanilla. Chromatographic separation was optimized based on the separation of six characteristic biomarkers (sesamol, eugenol, thymol, carvacrol, salicylaldehyde and vainillin) and was performed using a C18 reversed-phase column under a 35 min gradient elution based on 0.1% (v/v) formic aqueous solution and methanol by means of UV–Vis detection at 280 nm. 87 samples, purchased in local supermarkets, were analyzed and the obtained profiles were processed by chemometric techniques. First, data treatment was evaluated by principal component analysis (PCA); next soft independent modelling by class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA) were carried out in order to verify if classification according to their biomarkers was possible. The study concluded that PLS-DA (0.14–0.75% global error) classifies better the types of spice or aromatic herb than SIMCA (0.82–3.67% global error).

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