16 February / March 2016 Figure 4: A comparison of standard DHS and FET DHS
spectrometric detector (MSD), but also accurate mass information that can be used for full structural elucidation. An example is a recent investigation into a ‘pencil’ odour in water, where it was concluded that using an MSD with NIST search could lead to the misidentifi cation of the compound responsible. The use of accurate mass was able to confi rm the identity where the unit mass spectra were almost indistinguishable (Figure 6). When combined with the corresponding odour descriptors, the system becomes a powerful tool for investigative analysis of aromas.
Real-time Aroma Analysis Figure 5: A comparison of a single DHS extraction and the multi-volatile method (MVM)
A growing area of research in aroma analysis is the study of fl avour or fragrance release over time. Traditionally this would have been performed by collecting and analysing a number of samples over a given time period. However, for shorter time or real- time analysis, there are now a few alternative instrumental options. One example is selected ion fl ow tube mass spectrometry (SIFT-MS), which is based on chemical ionisation using selected reagent ions (H3
(O-, O2
O+, NO+ and O2 -, OH-, NO2
+ (positive ions) and - NO3 - (negative ions). As Figure 6: An example of structural elucidation using accurate mass for aroma compounds
One of the challenges with developing a DHS method, is knowing the temperature and volumes to use, as requirements will be matrix and analyte dependant. The Multi volatile method, (MVM) published by Gerstel originally for coffee [4], but more recently extended for green tea [5] aims to increase the range of compounds that can be trapped. This fully automated method extracts the same sample using a series of traps/methods and then employs a multi- desorption technique in order to obtain a single chromatogram. The benefi ts over a single DHS extraction are illustrated in Figure 5 for analysis of fragrance in a solid matrix.
GC-O the Ultimate Detector
For aroma analysis it is always worth linking analytical data with sensory. One direct
way to do this is to use an olfactory port (GC-O), such as the Gerstel Olfactory Detection Port (ODP), to directly assess the odour of components as they elute from the analytical column. This can be used for characterisation studies or to help identify compounds relating to a specifi c odour. Due to the low thresholds for some compounds, it is possible that an odour will be perceived, but no peak is observed using a traditional detector. In this instance it may be necessary to collect the peak of interest over several injections and re-analyse once enriched. This can be done with some systems by connecting an adsorbent tube in place of the ODP sniffer port. The choice of detector can also aid identifi cation of aroma active compounds. For example, using an ODP alongside a GC-QTOF detector provides not only an increase in sensitivity compared to a single quadrupole mass
these result in soft ionisation, simple spectra are obtained, enabling rapid monitoring of specifi c ions. The system set up results in quantitative results over a large dynamic range without the need to run standards for many analytes. Volatiles can be introduced to the system in a number of ways: directly (air or breath sampling), from headspace vials or tedlar bags using the Gerstel MPS, from thermal desorption of swabs, or even from ‘nose space’ during consumption of a foodstuff. Figure 7 shows an example of the measurement of release of fragrance from a detergent in real time at different temperatures [6].
Conclusions
There are many available options for sample preparation, the majority of which can now be successfully automated. There is not one sample preparation technique that is suitable for every analyte and matrix combination and the choice must always be dictated by the requirements of the analytical method. The analytical strategy will depend on the reasons for the sample preparation, whether to improve selectivity by removal of matrix interferences, or increase sensitivity by enrichment or derivatisation. The choice should also be
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