## 3 Results and Discussion
### Geographical Variability of Tuber borchii and Tuber mesentericum  
Table 3 shows the confusion matrix obtained from the linear discriminant analysis conducted as a supervised data pattern recognition method on the data pattern constructed by comparing the different harvesting zones of _T. borchii_. The analysis assumes that within-class covariance matrices are equal and takes prior probabilities into account at a significance level of 5%. The confusion matrix shows that, within the same species, most of the samples collected in the same harvested area obtained a correct classification rate between or above 50%, up to 74% for the \"Caserta coast\" area, 68% for the \"Salerno coast\" area, and 67% for the \"Caserta hill\" area. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**From**\textbackslash{}**To** & **Caserta Hill** & **Salerno Hill** & **Caserta Coast** & **Salerno Coast** & **Total** & **\% Correct** & **\% Correct** (Coast vs. Hill) \\ \hline
**Caserta hill** & 4 & 0 & 2 & 0 & 6 & 67\% & 67\% \\
**Salerno hill** & 3 & 5 & 0 & 4 & 12 & 42\% & 67\% \\
**Caserta coast** & 0 & 2 & 17 & 4 & 23 & 74\% & 91\% \\
**Salerno coast** & 2 & 0 & 4 & 13 & 19 & 68\% & 89\% \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Confusion matrix obtained from the discriminant analysis performed on the data pattern constructed considering the different harvesting areas of _T. borchii_. Higher misclassifications occurred for _T. borchii_ collected in the \"Salerno hill\" area (Table 3). However, considering the collection altitude of _T. borchii_ (coastal area, at sea level, and hilly area, above 350 m above sea level; see Table 1 for further details), we observed an increase in the correct classification rate, in which the \"coast\" sites were correctly classified 38 times out of 42, while the \"hill\" sites were correctly classified 12 times out of 18. Among the host trees of the coastal areas, there were Aleppo and Stone pine, while the hilly areas were represented by Oak trees (Table 1). Recently, Niimi, Deveau, and Splivallo [15] showed variations in the quantity of 48% of the volatile compounds identified based on the sites of truffle harvesting within the same geographical area. These differences were mainly attributed, as demonstrated by microbiome analysis, to differences in bacterial communities between the various collection sites [15]. Therefore, it is plausible that the coastal and hilly collection sites, subjected to distinct climates, vegetation (e.g., host trees), and, consequently, soil microbiota, played a key role in the differences in odour patterns obtained from the E-nose analysis. SPME-GC/MS analysis confirmed these differences. In fact, the different levels of volatile compounds allowed the samples of _T. borchii_ from the two harvesting zones to be grouped into two distinct clusters (Figure 4). Figure 4: Heatmap of significantly different (\(p<0.05\)) volatile compounds of _T. borchii_ samples harvested in different areas of Caserta and Salerno provinces of Campania region. Volatile compounds were plotted on the Y axis, while the X axis had the samples. Results are displayed as negative (\(-1\)) to positive (\(+1\)) correlation of the volatile compounds in the permuted matrix for the respective samples. The two collection areas exhibited quantitative differences in terms of specific volatile compounds rather than chemical class. For instance, _T. borchti_ collected at altitudes >350 m above sea level had a higher amount of 1-octen-3-ol, which is one of the VOCs quantitatively more abundant in _T. borchti_ (Table 2). In contrast, \"coast\" samples had a higher abundance of aromatic compounds and aldehydes. In terms of sulphur compounds, \"Caserta hill\" and \"Salerno hill\" samples showed higher concentrations of dimethylsulphide, while \"Caserta coast\" and \"Salerno coast\" showed higher concentrations of dimethylsulphone and thiophene derivatives (Figure 4). [PERSON] et al.