Integrating metabolomic data from multiple analytical platforms for a comprehensive characterisation of lemon essential oils

Abstract

AbstractCitrus cold pressed oils are of great importance to the flavour and fragrance industry. Because of their high added value, careful attention must be paid to ensure the oils' genuineness and authenticity. Characterising their chemical complexity in a holistic perspective constitutes a potent way to relate specific compounds to the organoleptic properties of interest and to assess their quality. In this context, a complete characterisation using untargeted metabolomics represents an analytical challenge. The present study takes advantage of multiblock data modelling to integrate heterogeneous signals collected from GC‐FID, 1H‐NMR, UHPLC‐TOF/MS‐ (negative mode) and UHPLC‐TOF/MS+ (positive mode) platforms to obtain a complete characterisation of 64 samples of cold pressed lemon oil (CPLO). Two statistical approaches (MB‐PLS‐DA and Consensus OPLS‐DA) were used to classify the samples according to their extraction processes [i.e. Sfumatrice, Food Machinery Corporation Inline Extractor (FMC), Brown Oil Extractor (BOE), Pelatrice, or mixed FMC + Pelatrice]. Furthermore, the multiblock strategy allows links between variables from different analytical methods to be drawn easily and facilitates the identification of compounds. Because citrus oils extracted using the Sfumatrice process constitute the reference quality from an organoleptic point of view, these samples were characterised thoroughly and are reported to contain less fatty acids but more sesquiterpenes and furocoumarins compared with products obtained using other extraction processes. Copyright © 2014 John Wiley & Sons, Ltd.