## 2 Analytical Strategies for Authentication and Quality Control
### Chromatographic and Hyphenated Techniques
This study highlighted the intrinsic problem inherent in LDA models: the algorithm assigns a projected sample to one of the categories used to develop the model even if the unknown sample belongs to a category not represented in the model itself as, in fact, occurred in the case reported in that study. Other authors [41] evaluated the effectiveness of headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME/GC-MS) coupled with two different chemometric tools, PLS-DA and Soft Independent Modelling by Class Analogies (SIMCA), as an analytical approach to discriminate 60 Gr samples with GI from 22 fruit and cerealdistillates produced in the same geographical area. SPME was performed using a 50/30 \(\upmu\)m (divinylbenzene/car-boxen/polydimethylsiloxane) DVB/CAR/PDMS fiber. The PLS-DA model provided the best results with the correct classification of all but one test sample. To identify the chemical markers that gave the greatest contribution in discriminating Gr from other categories of spirit drinks, the Variable Importance in Projection (VIP) indices were calculated [42; 43]. Compounds with a VIP index > 1 are considered significant for discrimination. Several discriminating compounds were identified, including \(\alpha\)-terpinene, \(\alpha\)-terpineol, ethyl heptanoate, ethyl dodecanoate and furfural. Interestingly, the same discriminating compounds for Gr spirits were also identified by other authors [44]. These authors analyzed 34 samples of Gr and Gr liqueurs of different brands using an integrated approach based on SPME-GC-MS (to identify compounds of the volatile fraction) coupled with chemometrics, the matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF/MS) technique (to determine the fingerprint of the non-volatile fraction) and MALDI-TOF MS/MS (to identify the components of the non-volatile fraction). SPME was performed using a 50/30 \(\upmu\)m DVB/CAR/PDMS fiber, as in the previous study. PCA analysis of SPME-GC/MS data of volatile compounds highlighted that Gr samples were discriminated by brand and that the most important marker compounds were ethanol and, to a lesser extent, ethyl esters of decanoic and octanoic acids, ethyl acetate and 1-pentanol. The MALDI-TOF MS technique allowed the simultaneous determination of many compounds of the non-volatile fraction, showing the differences at a qualitative and semi-quantitative level between the analyzed samples. This method proved to be an effective approach for reliable discrimination between the analyzed Gr samples. A more in-depth structural analysis of molecules within spectra performed by MALDI-TOF MS/MS allowed the identification of 12 non-volatile organic molecules. Furthermore, MS/MS spectra of some samples showed the presence of 5-methylfuran resulting from the degradation of carbohydrates during the aging period inside the barrels. Another technique used in the analysis of Gr volatile compounds is comprehensive bidimensional gas-chromatography (GCxGC or 2D-GC). It can provide more sensitivity and selectivity if compared with the more conventional GC-MS. In a work [45], HS-SPME/GCxGC-ToF/MS and HS-SPME/GC-MS were used to study the changes in the composition of volatile substances of an unaged Gr during the storage period and the relationship of those compounds with sensory attributes. After HS-SPME (performed using a DVB/CAR/PDMS 50/30 \(\upmu\)m fiber), the separation of the volatile substances was carried out with a GC-MS and then with a 2D-GC system working with two columns with moderate difference in polarity. This study demonstrates how 2D-GC analysis could be effective in determining compounds with similar chromatographic features that would be unresolved in one-dimensional analysis, allowing a greater number of compounds to be determined and correlated to sensory analysis. Besides Gr from Italy, other popular grape marc distillates with GI are Orujo from Spain, Eau-de-Vie de Marc from France and Greek Tsipouro [46].