Authenticating teas using multielement signatures, strontium isotope ratios, and volatile compound profiling.

High value food products are subject to adulterations and frauds. This study aimed to combine, in our knowledge for the first time, inorganic chemical tracers (multi-elements and Sr isotopy) with volatile organic compound (VOCs) to discriminate the geographic origin, the varieties and transformation processes to authenticate 26 tea samples. By measuring Sr isotope ratio using the multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS), 6 out of 11 regions were successfully discriminated. The combination with the ICP-MS inorganic pattern allowed to discriminate 4 more regions with a significance level of 0.05. VOCs fingerprints, obtained with selected ion flow tube mass spectrometer (SIFT-MS), were not correlated with origin but with the cultivar and transformation processes. Green, oolong, and dark teas were clearly differentiated, with hexanal and hexanol contributing to the discrimination of oxidation levels. With this multi-instrumental approach, it is possible to certify the geographical origin and the tea conformity.

Study of the Chemical Ionization of Organophosphate Esters in Air Using Selected Ion Flow Tube-Mass Spectrometry for Direct Analysis.

Organophosphate esters are an emerging environmental concern since they spread persistently across all environmental compartments (air, soil, water, etc.). Measurements of semivolatile organic compounds are important but not without challenges due to their physicochemical properties. Selected ion flow tube-mass spectrometry (SIFT-MS) can be relevant for their analysis in air because it is a direct analytical method without separation that requires little preparation and no external calibration. SIFT-MS is based on the chemical reactivity of analytes with reactant ions. For volatile and semivolatile organic compound analysis in the gas phase, knowledge of ion-molecule reactions and kinetic parameters is essential for the utilization of this technology. In the present work, we focused on organophosphate esters, semivolatile compounds that are now ubiquitous in the environment. The ion-molecule reactions of eight precursor ions that are available in SIFT-MS (H3O+, NO+, O2•+, OH-, O•-, O2•-, NO2-, and NO3-) with six organophosphate esters were investigated. The modeling of ion-molecule reaction pathways by calculations supported and complemented the experimental work. Organophosphate esters reacted with six of the eight precursor ions with characteristic reaction mechanisms, such as protonation with hydronium precursor ions and association with NO+ ions, while nucleophilic substitution occurred with OH-, O•-, and O2•-. No reaction was observed with NO2- and NO3- ions. This work shows that the direct analysis of semivolatile organic compounds is feasible using SIFT-MS with both positive and negative ionization modes.

Volatile fingerprint of food products with untargeted SIFT-MS data coupled with mixOmics methods for profile discrimination: Application case on cheese.

Volatile organic compounds (VOCs) emitted by food products are decisive for the perception of aroma and taste. The analysis of gaseous matrices is traditionally done by detection and quantification of few dozens of characteristic markers. Emerging direct injection mass spectrometry technologies offer rapid analysis based on a soft ionisation of VOCs without previous separation. The recent increase of selectivity offered by the use of several precursor ions coupled with untargeted analysis increases the potential power of these instruments. However, the analysis of complex gaseous matrix results in a large number of ion conflicts, making the quantification of markers difficult, and in a large volume of data. In this work, we present the exploitation of untargeted SIFT-MS volatile fingerprints of ewe PDO cheeses in a real farm model, using mixOmics methods allowing us to illustrate the typicality, the manufacturing processes reproducibility and the impact of the animals' diet on the final product.