Development and Analytical Assessment of an Electronic Nose Method for the Chemometric Discrimination of Cistus spp. Extracts

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The characterization of plant-derived extracts is strongly influenced by the extraction procedure and solvent polarity, which determine the recovery of bioactive compounds and volatile constituents. In this study, an electronic nose (E-nose) based on a metal oxide semiconductor (MOS) sensor array was evaluated as a rapid analytical tool for the classification of Cistus extracts obtained using solvents of different polarity. Leaves of Cistus salviifolius, Cistus crispus, and Cistus ladanifer were sequentially extracted with hexane, diethyl ether, tetrahydrofuran (THF), chloroform, ethanol, and methanol. Extraction yield, total phenolic content, flavonoid content, and antioxidant activity were determined, and volatile fingerprints were acquired using the E-nose system. Chemometric analysis was performed using principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). Differences were observed among extraction solvents regarding extraction efficiency, phytochemical composition, and antioxidant activity. PCA successfully discriminated extracts according to solvent polarity, explaining between 70.96% and 90.22% of the total variance depending on the Cistus species analyzed. Furthermore, the PLS-DA model achieved a classification accuracy of 87.5%, with sensitivity and specificity values of 87.5% and 97.5%, respectively. These results demonstrate that the combination of E-nose technology and chemometric tools provides a rapid, non-destructive, and cost-effective approach for the classification and characterization of Cistus extracts according to extraction solvent, highlighting its potential application in quality control and process monitoring of plant-derived products.

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