## 4 Discussion  
Beer is a complex mixture of ingredients, brewed from raw materials including water, malt, hops, and yeast, that contains a broad range of different components that react and interact at all stages of the brewing process [2]. Yeasts employed in industrial fermentation processes can convert relatively high concentrations of sugars into ethanol, carbon dioxide, and a wide range of secondary metabolites [31], which impact in several ways the aromatic profile of beer. While these compounds are only produced at low concentrations, they are responsible for the complex aromas of fermented beverages. Currently, alternative yeast strains are being considered to provide new and innovative beers [32]. Under this scenario, and considering the recent market trends, bioprospecting research on pioneering wild yeast strains with the capacity to produce new beers is becoming an attractive field in food research. In this way, the recent finding of _S. eubayanus_ in Patagonia is a crucial element for beer microbial innovation [6; 9; 17; 22]. In this study, we analyzed the fermentation capacity and VC production of a genetically diverse set of Patagonian _S. eubayanus_ strains from Chile, previously described by [PERSON] et al. [22]. To our knowledge, this represents the first study that explores the landscape of VCs produced during beer fermentation in _S. eubayanus_ using HS-SPME-GC-MS. The differences observed between these strains relate to those previously reported, where strains with higher stress tolerance developed a greater fermentative capacity than other strains [22; 33]. Accordingly, the worldwide increase in beer consumption and the continuous growth of microbrewers highlight the need for the characterization of the aromatic profile of novel beers, requiring tools to evaluate beer quality and authenticity. In this context, the HS-SPME-GC-MS method, used in this  
Figure 7: Preferred amino acid consumption in _S. eubayanus_ strains at 24 h. Gray: CL905.1; Orange: CL602.1. (*******) depict significant differences between amino acids with a \(p\)-value \(<\) 0.001, one-way ANOVA. analysis, has been reported as a fast and sensitive technique for the identification of VCs in both industrial and craft beers [10; 34]. This technique develops reproducible data, with the improvement that avoids the injection of the standards, favoring several advantages, such as the time and cost of the analysis [10]. In HS-SPME (headspace solid-phase microextraction), analytes are extracted into a thin fused-silica fiber coated with the extracting phase by immersing it in the headspace of solid or liquid samples. Then, by GC-MS, compound identification is based on mass spectra matching with the standard NIST 08 MS library and on the comparison of retention indices (RI) sourced from the NIST Standard Reference Database MS Spectral Library 2014. The identification of the VCs by comparing the experimental mass spectra based on spectral similarity with those stored in the NIST MS library database, without chemical reference standards, should be regarded as putative compounds identifications (Level 2). Moreover, the determination of Kovats retention indices (RI) and their match with those available in previous literature [10; 34] represents a useful tool for identification purposes, being independent of the operating conditions, except for the polarity of the used stationary phase. Furthermore, considering complex matrices as word fermentation, which can contain hundreds of VCs to be analyzed, this analytical approach described above has the advantage that avoids the injection of the pure standards, favoring the time and cost of the analysis and the limitation that several standards are not commercially available. In this study, we compared the VC production profile of two different yeast species, _S. pastorianus_ (_Sp._W34/70, commercial lager strain) and _S. eubayanus_ (wild isolates from Chilean Patagonia) using HS-SPME-GC-MS. The main differences between _S. eubayanus_ and _S.