Characterization and Classification of Spanish Honey by Non-targeted LC-HRMS (Orbitrap) Fingerprinting and Multivariate Chemometric Methods

Abstract

A 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%.