## 3 Results and Discussion
### The Impact of Roasting on Primary Metabolites Patterns  
Roasting, conducted in a lab-scale ventilated oven under previously optimized time/temperature conditions [55] (180 \({}^{\circ}\)C--0 min), enabled the development of an optimal flavor, color, and crunchy texture. Under these conditions, key-odorants showed strong negative correlations (Pearson correlation) with precursors distribution [37]. The Strecker aldehyde 3-methylbutanal was linearly correlated to Ile (\(R^{2}\) 0.9284); 2,3-butananedione/2,3-pentanedione with fructose/glucose derivatives (\(R^{2}\) 0.8543 and 0.8860); 2,5-dimethylpyrazine with Ala (\(R^{2}\) 0.8822); and 1H-pyrrole, 3-methyl-1H-pyrrole, and 1H-pyrrole-2-carboxaldehyde with Orn and Ala derivatives (\(R^{2}\) 0.8604). In the current study, the focus was on the total detectable metabolome and not only on aroma precursors and/or on nutrients; therefore, to add a further tracking point on the roasting profile, the process was extended to reach a higher roasting temperature (200 \({}^{\circ}\)C--10 min), which is still acceptable for industrial applications. This \"over-roasted\" stage was similar to that applied in industrial transformation for \"granella\" (hazelnut grains) used in confectionery toppings. The results are visualized in Figure 3A by principal component analysis (PCA) scores  
Figure 2: Univariate box-plots illustrate the % response for some primary metabolites and aroma precursors (Pro and Ala) in the analyzed hazelnut samples. For Pro and Ala, a further description of their distribution according to the geographical origin is shown (T—GE and T—IT). plot based on % responses from all 430 UT peak features. The explained variance of the first two principal components (F1 and F2) was 25% of the total variance. However, samples appear clearly clustered according to the extent of thermal treatment. The impact of roasting tracks along F1 (Figure 3A) and, from right to left, metabolites signatures of raw hazelnuts, green indicators, evolve to the over-roasted stage (blue indicators) with a concurrent slight decrease of the group's internal variability as shown by confidence ellipses (95% confidence level). By tracking known metabolites along the roasting profile, those with meaningful variations across the three steps (raw, roasted, over-roasted) were reactive amino acids: Ala, Pro, Leu and Val, Asp, and pyroglutamic acid (a derivatization product of glutamic acid (Glu)). All amino acids followed a decreasing trend along roasting time with variations on % response ranging from \(-83\%\) for Leu and Val to \(-96\%\) for Glu. Sugars such as saccharose and galactose showed less marked decreases with \(-56\%\) and \(-46\%\), respectively. Histograms in Figure 4 illustrate the % response variation for a selection of targeted analytes, with error bars corresponding to \(\pm\) SD for the class. Results are consistent with those of [PERSON] et al. [9], who reported a generalized decrease in absolute concentrations of all amino acids. Since our roasting protocol was by higher temperatures (i.e., 180-200 \({}^{\circ}\)C vs. 104-126 \({}^{\circ}\)C) the decrease of most reactive species was more marked. When the roasting impact is examined in light of aroma precursors distribution (Table 2), the clustering of samples by PCA is even clearer. Figure 3B shows the PCA scores-plot based on % responses from 15 precursors. The intra-class variability for the roasted samples is lower (as shown by confidence ellipses) while the total explained variance is 68%. Aroma precursors (fructose, glucose, maltose, saccharose, Ala, Pro, Ile, Leu, Orn, 5-oxoproline above all) are all reactive species within the Maillard reaction and sugar degradation pathways and, during roasting, form potent odorants. In particular, carbohydrates dehydration and isomerization cause the formation of \(\alpha\)-dicarbonyls (2,3-butanedione and 2,3-pentanedione) and furanones (5-hydroxymethylfurral and 4-hydroxy-2,5-dimethyl-3(2H)-furanone).