Catechol (CC), resorcinol (RC) and hydroquinone (HQ) are dihydroxybenzene isomers that usually coexist in different samples and can be determined using voltammetric techniques taking profit of their fast response, high sensitivity and selectivity, cheap instrumentation, simple and timesaving operation modes. However, a strong overlapping of CC and HQ signals is observed hindering their accurate analysis. In the present work, the combination of differential pulse voltammetry with graphene screen-printed electrodes (allowing detection limits of 2.7, 1.7 and 2.4µmolL(-1) for HQ, CC and RC respectively) and the data analysis by partial least squares calibration (giving root mean square errors of prediction, RMSEP values, of 2.6, 4.1 and 2.3 for HQ, CC and RC respectively) has been proposed as a powerful tool for the quantification of mixtures of these dihydroxybenzene isomers. The commercial availability of the screen-printed devices and the low cost and simplicity of the analysis suggest that the proposed method can be a valuable alternative to chromatographic and electrophoretic methods for the considered species. The method has been applied to the analysis of these isomers in spiked tap water.
Screen-printed electrodes based on graphite, carbon nanotubes, carbon nanofibers, and graphene were tested as amperometric detectors for the determination of phenolic compounds by high performance liquid chromatography (HPLC). The chromatographic performance as well as the obtained sensitivity, detection and quantification limits suggest that carbon nanofibers modified screen-printed electrode (SPCE-CNF) is the amperometric sensor that provides the best analytical performance. Upon this confirmation, chromatographic data obtained using SPCE-CNF were exploited by means of linear discriminant analysis (LDA) to successfully characterize and classify 96 Spanish paprika (Capsicum annuum L.) samples with different origin and type: from La Vera (including sweet, bittersweet and spicy types) and from Murcia (including sweet and spicy types).
The development of a simple HPLC-UV method towards the evaluation of Spanish paprika’s phenolic profile and their discrimination based on the former is reported herein. The approach is based on C18 reversed-phase chromatography to generate characteristic fingerprints, in combination with linear discriminant analysis (LDA) to achieve their classification. To this aim, chromatographic conditions were optimized so as to achieve the separation of major phenolic compounds already identified in paprika. Paprika samples were subjected to a sample extraction stage by sonication and centrifugation; extracting procedure and conditions were optimized to maximize the generation of enough discriminant fingerprints. Finally, chromatograms were baseline corrected, compressed employing fast Fourier transform (FFT), and then analyzed by means of principal component analysis (PCA) and LDA to carry out the classification of paprika samples. Under the developed procedure, a total of 96 paprika samples were analyzed, achieving a classification rate of 100% for the test subset (n = 25).
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