The ACQUITY RDa for Routine Food Profiling – Detecting the Unexpected in Honey

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Gitte Barknowitz, Sara Stead
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Honey analysis is highly complex and requires the use of multiple analytical techniques as adulteration types can be numerous. The simultaneous detection of multiple components using spectroscopic and spectrometric techniques, coupled with multivariate analysis (MVA), is a promising approach to achieve botanical discrimination. LC-HRMS is one technique that has been used extensively for metabolic profiling in the food and beverage industry including for the analysis of honey. In this study we investigated whether untargeted metabolomics could differentiate honey samples from polyfloral and single botanical origin and detect illicit fortification of a honey supplement, using a novel high-performance bench-top orthogonal acceleration time-of-flight LC-MS system with simplified and optimized standard operation modes with intuitive software and automated workflow methods including multivariate statistics.

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