In this study we investigated whether untargeted metabolomics, using UPLC with High Definition Mass Spectrometry (HDMS) and multivariate statistics, could differentiate honeys of different botanical origin.
UPLC provides high efficiency separations and comprehensive, unbiased HDMSE acquisition provides information-rich data including accurate mass and isotope distribution for precursor and fragment ions. The addition of ion mobility offers increased peak capacity, separation of isomers and spectral cleanup. The Progenesis QI workflow provides an easy-to-use, scalable system for analysis of food metabolomic data including accurate peak alignment and peak picking, classification of samples using multivariate statistical analysis, quantification of relative abundance of markers for each class and identification of markers from database searches supported by structural elucidation tools. This metabolomics workflow is emerging as a powerful approach for the discovery of biomarkers to tackle food fraud.
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