Analytische Chemie
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- SPME-GC-MS (2) (entfernen)
An experimental investigation has been carried out to characterize and discriminate seven saffron samples and to verify their declared geographical origin using a voltammetric electronic tongue (VE-tongue). The ability of multivariable analysis methods such as Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) to classify the saffron samples according to their geographical origin have been investigated. A good discrimination has reached using PCA and HCA in the VE-tongue characterization case. Furthermore, cross validation and Partial Least Square (PLS) techniques were applied in order to build suitable management and prediction models for the determination of safranal concentration in saffron samples based on SPME-GC-MS and UV-Vis Spectrophotometry. The obtained results reveals that some relationships were established between the VE-tongue signal, SPMEGC-MS and UV-Vis spectrophotometry methods to predict safranal concentration levels in saffron samples by using the PLS model. In the light of these results, we can say that the proposed electronic system offer a fast, simple and efficient tool to recognize the declared geographical origin of the saffron samples.
The detection of the aroma and flavour volatile compounds of spices is key in product quality control. Accordingly, it is necessary to develop new electronic sensing systems for food adulteration control and authenticity assessment for protecting customer's health.
In this work, the capability of the E-nose and VE-tongue in combination with SPME-GC-MS to correctly discriminate between several cumin samples of different geographical origins and to detect their adulteration, by using unsupervised and supervised chemometric tools, was evaluated. Regarding the aroma profile, eleven volatile compounds were characterized by SPME-GC-MS; all of them were found in cumin powder while only eight are found in cumin seeds. The main volatile compounds detected were b-pinene, m-cymene, g-terpinene, cuminaldehyde and cuminic alcohol, in different proportions depending on the cumin sample form (seed or powder). In summary, the results obtained are sufficiently encouraging as a starting point for the development of new electronic sensing systems with more improvement in the reliability of the sensor's performance as well as chemometric tools in order to deal with a complex dataset.