Honey has been reported as one of the most common food ingredient that is affected by food fraud worldwide. Many honey fraud cases were identified as mislabeling of botanical origin as the botanical origin can impact the market price of honey. Currently available methods for the identification of botanical origin of honey either are time-consuming (e.g. pollen analysis) or only target a few “known” types of markers (e.g. phenolic compounds). A quick and effective method is therefore needed for the identification of honey origin. Non-targeted analysis, using high-resolution mass spectrometry (HRMS) and advanced data processing tools, is able to investigate a broad range of fingerprints in honey, and the unique features can be served as chemical markers for the identification of botanical origin. In this study, a non-targeted method based on liquid chromatography (LC) coupled to HRMS was applied to explore the non-saccharide fingerprints of honeys of different floral origins (incl. buckwheat, blueberry and clover) collected from markets in Canada. Honey samples were analyzed using a “dilute and injection” method followed by a LC-quadrupole time-of-flight (QTOF)-MS analysis. Fold change and ANOVA analysis was conducted, and several features were identified as botanical markers. For example, a feature <i>m/z</i> 121.0300 [M-H]<sup>-</sup> was identified as a botanical marker for buckwheat honeys, and its structure was later confirmed by MS/MS and chemical standard as 4-hydroxybenzaldehyde. The present results demonstrate that LC-HRMS-based non-targeted workflow can be used to identify novel molecular markers for honey botanical classification. This workflow relies on a rapid (&lt;20 min per sample incl. sample preparation) and simple (no extraction step) analytical method, which can be easily translated to study the authenticity of other liquid/semi-liquid food (e.g. alcoholic beverages or maple syrup).

Non-targeted identification of botanical origin markers for honeys

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