## 3 Results and Discussion
### NMR and NIR Analysis  
The same 15 samples analysed via GC-MS were analysed using NMR and NIR spectroscopy. The \({}^{1}\)H-NMR spectra of marc distillates are shown in Figure 3. Each spectrum could be split into three regions mostly containing signals of aromatic compounds (region 1), carbohydrates (region 2) and higher alcohols (region 3).  
The region where the main differences were expected, as a function of the different toasting temperatures and wood processing, was found in the aromatic-compounds section,  
Figure 3: \({}^{1}\)H-NMR stacked spectra of all samples. In box 1, signals related to aromatics; in box 2, signals related to carbohydrates; in box 3, signals related to higher alcohols. For the numbering of the spectra presented in the figure, refer to Table 1.  
between 12 ppm and 5.5 ppm. Given that in regions (2) and (3), the signals were partially modified via solvent suppression, the chemometric analysis of the spectra was performed on region 1 of the spectra.  
In Figure 3, the spirits refined with non-toasted wood and strongly toasted wood appeared to have similar aromatic NMR fingerprints. Moreover, distillates refined with lightly toasted wood seemed to have quite different aromatic NMR fingerprints from both the control sample and other samples. According to the quantile plot, the main differences among the different spectra were due to the signals at around 9.6 ppm, 7.5 ppm and 6.5 ppm. The assignment of these peaks to specific compounds was beyond the purpose of the study; however, the loading plots emphasized that in spirits refined with lightly toasted woods, aldehyde compounds were present that were not detected in the control samples and other samples refined with highly toasted woods. In the aromatic region, around 8 ppm to 5.5 ppm, the profiles of the samples showed different signals that were not present in the control sample.  
Figure 4 shows the results of PCA analysis. The first two principal components together explained 60.61% of the total variance. The score plot showed a good separation of the samples on PC1 based on the toasting temperature. Moreover, the control sample was well distinguished from the other groups. It is noteworthy that samples refined with strongly toasted woods were well separated from lightly toasted ones. With regards to the different wood formats, the PCA analysis highlighted an only partial separation among groups, in particular, between the majority of samples refined with peeled wood and those refined with sliced wood (samples 9, 10 and 11).  
NIR spectroscopy was also employed in this study to explore its potential to characterize the wood alternatives. Indeed, the promising performance of this technique has been recently verified for analysing both wines [10] and spirits [14] aged with oak alternatives. The results of the PCA based on the NIR spectra of 15 distillate samples showed that a certain variance was present (summarized by the two main components representing more than 50.60%) and confirmed the interest of previously selected spectral zones for application in aged spirits. Figure 5 highlights that some specific assortments of wood alternatives (e.g., wood tablets for shape) were also grouped using the NIR analysis. The method failed, however, in further characterizing the dataset, due to the low number of available samples, which was certainly sub-optimal for a chemometric approach such as NIR application. Therefore, further trials are needed to extend the potential of the technique in wider datasets, eventually taking advantage of the dedicated application of Functional Data Analysis, which has recently been shown to be useful in discriminating wine and spirit ageing technologies in wide datasets [13].  
Figure 4: PCA score plot for spirits aged with different alternative products. Results of NMR analyses. The graph highlights the effect of toasting on spirit composition. Yellow, NT, non-toasted wood; red, heavy toasting; orange, light toasting.