## 2 Results and Discussion
### An Overall View of the Volatiles Associated with Baking in Broas  
Sensory analysis in a previous study [77] revealed that the _broa_ prepared from the available commercial maize hybrid variety (B12) showed the lowest scores for'smell and odor' and 'taste and aroma'. In contrast, the traditional _broas_ (obtained from the traditional open-pollinated varieties) were poorly discriminated among them [77]. A subsequent study revealed that these differences could at least be partially explained by their volatile composition [27]. Thus, a PCA (principal component analysis) was performed to explore further these differences for an easy, rapid and global assessment of the main differences in the volatile composition among the studied _broas_. Figure 5 shows the projection of samples and variables in the space defined by the two principal components, corresponding to 59.2% of the total variance. A hierarchical cluster analysis combined with a heatmap representation was also constructed and shown in Figure S4. Figure 5: Projection of _bros_ (coloured dots) and variables (grey) (Table 1) in the plane defined by PC1 and PC2, corresponding to 59.2% of the total variance. The volatiles that strongly (PC \(>\) 0.85) contributed to differentiating the samples along the two PCs are represented in black. Since all _proas_ were prepared following the same procedure and submitted to the same temperature of kneading and baking, it can be stated that the differences observed among the different _proas_ were caused by differences in the corresponding maize flours, which affect the Maillard reaction. A matrix correlation analysis was conducted and represented by a heatmap to shed some light on the volatile compounds which might have been formed from the same precursors (Figure 6 and Tables S4 and S5). The volatiles that strongly contributed to differentiating the samples along PC2 (Figure 5) are represented in group A of the correlation matrix (Figure 6) and highlighted in Tables S4 and S5. This group is characterized by a simple pattern of strong and positive correlations amongst several furans and furanones. In low-moisture starch foods, such  
Figure 6: Correlation heatmap of the 128 volatile compounds in _proas_. The correlation coefficients of volatiles are represented through a chromatic scale from deep blue (\(-1\)), corresponding to negative correlations, to red (\(1\)), corresponding to positive correlations. The letters correspond to volatiles that (**A**) strongly contributed to differentiating the samples along PC2; (**B**) strongly contributed to differentiating the samples along PC1 and (**C**) negatively contributed to PC1 and PC2. as _proas_, the Maillard reaction seems to be the main route of their formation [78; 79]. Thus, higher amounts of the Maillard reaction precursors, such as amino acids and sugars, may have generated _proas_ with higher amounts in fururans. Alternatively, the presence of interferents, for instance, phenolic compounds [27], may explain these correlations since they may promote [27; 80] or inhibit [74; 80] the reaction. In particular, very strong correlations (R \(>\) 0.85, _p_\(<\) 0.05) were observed among 2-methylfuran (F2), 5-methyl-2-furanmethanol (F19) and 2-acetyl-5-methylfuran (F25), which are usually produced by caramelization reactions and by the breakdown of the Amadori or Heyns intermediates in the early stages of the Maillard reaction (Figure 1) [14; 19; 20]. Strong and positive (R \(>\) 0.7, _p_\(<\) 0.05) correlations were also found between dihydro-2-methyl-3-(2\(H\))-furanone (Fo2) and sulfur-containing heterocycles. Higher amounts in dihydro-2-methyl-3-(2\(H\))-furanone, which reacts with ammonia and hydrogen sulfide (produced from cysteine by hydrolysis or by Strecker degradation) [19; 20; 24; 81], may directly cause higher amounts of thiazoles and thiophenes.