Optimization of gas sensors measurements by dynamic headspace analysis supported by simultaneous direct injection mass spectrometry

Abstract Dynamic headspace extraction is frequently used in gas sensors measurements. The procedure may introduce artefacts but its influence in sensor signals interpretation is rarely considered. In this paper, taking advantage of the on-line combination of a quartz microbalance gas sensor array with a proton transfer reaction mass spectrometer, we have been able to track the evolution of the concentration of volatile compounds along 75 s of extraction of the headspace of differently treated tomato pastes. Proton transfer reaction mass spectrometer signals show that VOCs are characterized by a large diversity of the evolution of the concentration. VOCs kinetics has been described by an electric equivalent circuit model. On the other hand, sensor signals continuously grow approaching a steady value. The contrasting behaviour between sensors signals and the concentration of most of VOCs is explained considering that water is the dominant component in the tomato paste sample and that water is one of those compounds whose concentration in the sensor cell steadily grows. Analysis of variance show that sensors signals achieve the largest separation between classes when the concentration of VOCs in the sensor cell reached its peak. Thus, although the sensor signals continue to rise their information content decays. This finding suggests that measurement protocols need to be adjusted according to the properties of the sample and that the actual measurement times could be much shorter than those predicted from the behaviour of sensor signal.