Olive Oil Authenticity Studies by Target and Non-target LC-QTOF-MS combined with Advanced Chemometric Techniques

ABSTRACT: Food analysis is continuously requesting the development of more robust, efficient and cost-effective food authentication analytical methodologies to guarantee the safety, quality and traceability of food commodities with respect to legislation and consumer demands. Hence, a novel RP-UHPLC-ESI-QTOF-MS/MS analytical method was developed employing target, suspect and non-target screening strategies coupled to advanced chemometric tools for the investigation of authenticity of extra virgin olive oil (EVOO). The proposed method was successfully applied in real olive oil samples for the identification of markers responsible for its sensory profile. The proposed target analytical method includes the determination of 14 phenolic compounds and demonstrated low limits of detection (LODs) over the range of 0.015 (apigenin) - 0.039 (vanillin) μg/ml and adequate recoveries (96-107%). A suspect list of 60 relevant compounds was compiled and suspect screening was then applied to all the samples. Semi-quantitation of the suspect compounds was performed using the calibration curves of the target compounds having similar structures. Then, a non-target screening workflow was applied with the aim to identify additional compounds, responsible to differentiate EVOOs from defective oils. Robust classification-based models were built using supervised discrimination techniques, PLS-DA and CP-ANNs, for the classification of olive oils into EVOOs or defectives. Variance in Projection (VIP) was calculated to select the most significant features that affect the discrimination. Overall, 51 compounds were identified and suggested as markers; 14, 26 and 11 compounds were identified using target, suspect and non-target screening, respectively. Retrospective analysis was also performed to identify 19 free fatty acids.

OTHER RELATED OMICS DATASETS IN: PXD018322 PXD006154

INSTRUMENT(S): maXis (Bruker)

SUBMITTER: Natasa Kalogiouri  Steffen Neumann 

PROVIDER: MTBLS433 | MetaboLights | 2017-05-04

REPOSITORIES: MetaboLights