## 2 Results
### Profile of Volatile Metabolites  
The profile of volatile metabolites in the headspace of the fermentation broths is of particular importance to the food industry, imparting much of the flavour perception to fermented beverages and foods. Many of these compounds are produced during the exponential microbial growth phase [26]. Therefore, we investigated whether the effects on yeast growth from applying audible sound would impact the profile of volatile compounds produced during fermentation. To test this, the volatile compounds produced under the two sound treatments were compared with the silence control. We putatively identified a total of 522 compounds in the headspace of the samples analysed using the NIST 2017 mass spectral library. Among the 522 volatile compounds, 346 were present at significantly different levels among the three different sound treatments (Table S1; \(p\)! 0.05).  
Analysing the fold change differences between treatments revealed that the exposure to sound appears to have significantly affected the development of aroma-related compounds during fermentation. A total of 24 of the significantly altered volatile metabolites were identified as common aroma compounds found in fermented beverages (Appendix A; [32]). Of these, the levels of citrus-related aromas, in particular, showed overall increases (Figure 2). For instance, limonene (the orange/citrus peel aroma) was detected at levels 7.8-fold  
Figure 1: Growth curves of _Saccharomyces cerevisiae_ exposed to different sound conditions. Two growth experiments under control silence conditions were averaged, shown in blue. Growth curves exposed to high-frequency sound of 10 kHz (red) and low-frequency sound of 100 Hz (green) are presented. Plotted values are means of biological replicates (n = 3) from each time point and error bars (\(\pm\)Standard Error).  
higher in the high-frequency sound treatment compared to the silence control. However, compounds associated with sweet fruits, such as apricot aroma (ethyl octanoate), were significantly reduced under both high- and low-frequency sound treatments compared to silence (Figure 2). While most of the significant differences occurred between the two sound treatments and silence, some differences were also observed between the high- and low-frequency sound treatments. For example, production of benzoin by _S. cerevisiae_ was significantly (\(p<0.001\)) elevated in fermentations exposed to high-frequency compared to low-frequency sound treatment (Figure 2).  
To see if we could distinguish samples from different sound treatments based on the profile of aroma-associated compounds, we projected the levels of these aroma compounds from the three treatments onto a lower-dimensional space using linear discriminant analysis (LDA; Figure 3). LDA revealed very clear separations between each sound treatment, with 100% accuracy based on leave-one-out cross-validation (Table 1). The most significant compounds driving this separation (R-squared \(\geq 0.9\)) were the aroma building block _cis_-2-nonene, and the aroma compounds 1-nonanol and \(p\)-cymene, associated with citronella and cumin/thyme, respectively (Appendix B).  
Figure 2: Fold changes of aroma-associated volatile metabolite levels produced when exposed to high-frequency (10 kHz) and low-frequency (Hz) sound when both are compared to silence. Data are displayed as a heat-map (right), with red-shade indicating increased abundance blue-shade indicating decreased abundance (compared to silence). The pairwise significance for each compound was assessed using a post-hoc Tukey ANOVA (\(p<0.05\)); A- high-frequency versus silence, B- low-frequency versus silence, C- high-frequency versus low-frequency. Methyl benzoate, grey, was outside the range of our scale, with significantly higher abundance for both high-frequency and low-frequency sound treatments (33- and 30-fold, respectively).