The increasing awareness toward the topic of functional diet posed the need for the detailed characterization of foods.

The aim of the present contribution is to show the potential of ambient mass spectrometry (AMS) for the characterization of complex foods, in their native form, avoiding complex sample preparation strategies.

Extra virgin olive oils (EVOOs) and aromatic plants were analyzed by two AMS techniques: 1) Rapid Evaporative Ionization MS (REIMS) coupled with a quadrupole-time of flight MS detector and an electroknife as sampling device (iknife); 2) Direct Analysis in Real Time (DART) connected to a single quadrupole by using quickstrip cards and solid phase microextraction (SPME) fibers as sampling devices. Spectra were collected through a chemometric software and used for the development of classification and predictive models based on Principal Component Analysis and Linear Discriminant Analysis.

y analyzed through DART, while frozen cubes were made as ready to cut materials for the iknife technology. Whereas, herbs were mixed with distilled water to create a conductive paste for the iknife, while they were dissolved in few mL of solvents prior to be spotted on quickstrip cards. The iknife spectra of EVOOs highlighted the presence of major constituents, triacylglycerols, while DART also enabled the detection of minor compounds, such as sterols, which are responsible for sample discrimination. Moreover, if SPME is used, phenols can be selectively detected resulting in more effective statistical models.

DART spectra of herbs were dependent on the solvent employed for dissolution, while the iknife allowed to achieve a holistic profile including both volatiles and non-volatiles. As a result, the iknife model was more accurate compared to DART.

AMS techniques provided a full metabolomic profile of foods in a very short time. The statistical models can be used against fraudulent activities.