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Using proton-transfer-reaction time-of-flight mass-spectrometry (PTR-ToF-MS), we investigated the extraction dynamic of 95 ion traces in real time (time resolution: 1 second) during espresso coffee preparation. Fifty-two of these ions were tentatively identified. This was achieved by on-line sampling of the volatile organic compounds (VOCs) in close vicinity to the coffee flow, at the exit of the extraction hose of the espresso machine (single serve capsules). Ten replicates of six different single serve coffee types were extracted to a final volume of between 30 - 110 mL, according to the recommended cup size of the respective coffee capsule (Ristretto, Espresso and Lungo), and analyzed. The results revealed considerable differences in the extraction kinetics between compounds, which led to a fast evolution of the volatile profiles in the extract flow and consequently to an evolution of the final aroma balance in the cup. Besides exploring the time-resolved extraction dynamics of VOCs, the dynamic data also allowed the coffees types (capsules) to be distinguished from one another. Both Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA) showed full separation between the coffees types. The methodology developed provides a fast and simple means of studying the extraction dynamics of VOCs and differentiating between different coffee types.

A robust and reproducible model was developed to predict the sensory profile of espresso coffee from instrumental headspace data. The model is derived from 11 different espresso coffees and validated using 8 additional espressos. The input of the model consists of (i) sensory profiles from a trained panel and (ii) on-line proton-transfer reaction mass spectrometry (PTR-MS) data. The experimental PTR-MS conditions were designed to simulate those for the sensory evaluation. Sixteen characteristic ion traces in the headspace were quantified by PTR-MS, requiring only 2 min of headspace measurement per espresso. The correlation is based on a knowledge-based standardization and normalization of both datasets that selectively extracts differences in the quality of samples, while reducing the impact of variations on the overall intensity of coffees. This work represents a significant progress in terms of correlation of sensory with instrumental results exemplified on coffee.

Mass-spectral results on alkali clusters containing one host-atom with ns2 valence-shell configuration (Mg, Ca, Sr, Ba, Zn, Eu, and Yb) are presented. They allow uncoupling of the number of atoms in the cluster from the number of its valence electrons by probing with elements with more than one valence electron and different ionization potential and atomic radius. Prominent intensity maxima for specific cluster sizes are observed. Based on an electronic shell model, a systematic interpretation of the intensity maxima as a function of the incorporated heteroatom is presented. Although most of the gross features can be rationalized within a purely electronic model, a more refined analysis prompts one to geometric structure effects which have to be included to more fully describe the spectra.