## 3 Results and Discussion
### Detection of Aroma Substances in Beer  
#### 3.4.1 The Electronic Nose  
Principal component analysis (PCA) and latent Dirichlet allocation (LDA) were chosen for the analysis of e-nose data, where beer has a wide variety of volatiles, and PCA was used to analyze different broad categories of flavor substances in lagers, while LDA was used to determine the variability of the broad categories of substances among beers.  
From the figure, it can be seen that the contribution rates of the first and second principal components were 73.51% and 20.49%, respectively, and the total contribution rate was 94%, which can represent the characteristic information of the broad categories of volatiles of the samples. The flavor differences between the laboratory lager and the commercially available lagers were evident in PC\({}_{2}\), while PC\({}_{1}\) was close to that of the commercially available lager. The difference between PC\({}_{1}\) and PC\({}_{2}\) of the sugarcane lager and those of the ordinary and commercially available lagers was significant. This proves that the aroma of sugarcane lager is different from that of commercially available lager.  
The aroma of sugarcane lager is different from that of commercially available lager and laboratory lager, which is mainly due to the different raw materials and fermentation processes, as represented in Figure 1. The direction chosen by PCA maintains maximum structure between data in lower dimensions, while the direction chosen by LDA achieves maximum separation between the given classes [30]. The LDA classification results are more representative of the variability than the PCA results. The data collection points of the same type of lager under the same conditions in the ellipse in Figure 1b represent the fingerprint profile of that product type, and the more dense data points represent the higher repetition rate of that sample. As can be seen from the figure, the contribution of LDA discriminant LD\({}_{1}\) and LD\({}_{2}\) for lager samples were 98.64% and 0.93%, respectively, and the total sum was 99.57%, which can represent all the characteristic information of the samples. The data collected from each type of lager samples were distributed in different areas without overlapping and far away from each other; this indicates that there were significant differences in odor. This indicates that there were differences in the flavor quality of lagers brewed from different raw materials.  
As can be seen from the Figure 2, all the lighter samples had the highest response values for the three sensor types WSS, W1S, W1W, and W2W. The high response value for ammonia-oxygen compounds is due to the high sensitivity of the detector itself. The substances corresponding to inorganic sulfides in lager are sulfides, such as SO\({}_{2}\), which is a metabolic product of yeast in the fermentation process. The amount of SO\({}_{2}\) produced  
Figure 1: Electronic nose fingerprints of laboratory lager and market lager. (**a**) Principal component analysis results; (**b**) LDA analysis results.  
is related to the yeast strain, wort concentration, and fermentation process [31]. The high response value of the corresponding methyl group sensor in the figure is mainly due to the high content of 2-methyl sulfide substances in lager. In nature, 2-methyl sulfide is often produced by the decomposition of proteins and has a \"green\" and \"fruity\" aroma, i.e., sugarcane syrup can provide lager a high \"green\" and \"fruity\" aroma, and \"fruity\" aroma.