García Seval, VictorSaurina, JavierSentellas, SoniaNúñez Burcio, Oscar2023-01-312023-01-3120221420-3049https://hdl.handle.net/2445/192813A non-targeted LC-HRMS fingerprinting methodology using an Orbitrap mass analyzer, and based on C18 reversed-phase mode under universal gradient elution, was developed to characterize and classify Spanish honey samples. A simple sample treatment consisting of honey dis-solution with water and a 1:1 dilution with methanol was proposed. 136 honey samples belonging to different blossom- and honeydew-honeys from different botanical varieties and produced in different Spanish geographical regions were analyzed. The obtained LC-HRMS fingerprints were employed as sample chemical descriptors for honey pattern recognition by principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). The results demonstrated a superior honey classification and discrimination capability with respect to previous non-targeted HPLC-UV fingerprinting approaches, being able to discriminate and authenticate the honey samples according to their botanical origins. Overall, noteworthy cross-validation multiclass predictions were accomplished, with sensitivity and specificity values higher than 96.2%, except for orange/lemon blossom (BL) and rosemary (RO) blossom-honeys. The proposed methodology was also able to classify and authenticate the climatic geographical production region of the analyzed honey samples, with cross-validation sensitivity and specificity values higher than 87.1%, and classification errors below 10.5%.application/pdfengcc-by (c) García Seval, Victor et al., 2022https://creativecommons.org/licenses/by/4.0/Mel d'abellesRessenya genèticaQuimiometriaHoneyDNA fingerprintingChemometricsinfo:eu-repo/semantics/article7271882023-01-31info:eu-repo/semantics/openAccess