Research on the Quality Variation Patterns During the Fermentation Process of Coffee-Grounds Craft Beer

Abstract

To investigate the metabolic differences and mechanisms during the fermentation process of coffee-grounds craft beer, HS-SPME-GC/MS untargeted metabolomics technology was used to study the metabolic differences during the fermentation process of coffee-grounds craft beer. Multivariate statistical analysis and pathway analysis were combined to screen for significantly different metabolites with variable weight values of VIP ≥ 1 and p < 0.05. The results indicate that at time points T7, T14, T21, and T28, a total of 183 differential metabolites were detected during the four fermentation days, with 86 metabolites showing significant differences. Its content composition is mainly composed of lipids and lipid-like molecules, organic oxygen compounds, and benzoids, accounting for 63.64% of the total differential metabolites. KEGG enrichment analysis of differentially expressed metabolites showed a total of 35 metabolic pathways. The top 20 metabolic pathways were screened based on the corrected p-value, and the significantly differentially expressed metabolites were mainly enriched in pathways such as protein digestion and absorption, glycosaminoglycan biosynthesis heparan sulfate/heparin, and benzoxazinoid biosynthesis. The different metabolic mechanisms during the fermentation process of coffee-grounds craft beer reveal the quality changes during the fermentation process, providing theoretical basis for improving the quality of coffee-grounds craft beer and having important theoretical and practical significance for improving the quality evaluation system of coffee-grounds craft beer.

Keywords: HS-SPME-GC/MS; coffee-grounds craft beer (CGB); flavor substance; physicochemical index; sensory analysis.

Figure 1

Craft beer brewing process using coffee grounds.

Figure 2

(A) Radar response map of electronic tongue sensor for coffee-grounds craft beer and (B) radar response map of electronic nose sensor for coffee-grounds craft beer.

Figure 3

(A) Changes in alcohol content, (B) Diacetyl content, (C) Original gravity, (D) Real degree of fermentation, (E) Total acid, (F) pH, (G) Chroma, (H) Bitterness units, (I) Chlorogenic acid, (J) protein, and (K) caffeine, during the fermentation process of coffee-grounds craft beer. The values of different superscripts were significantly different (p < 0.05), while the values of the same superscripts were not significantly different (p > 0.05). (L) Pearson correlation coefficient heatmap based on basic physicochemical indicators of coffee-grounds craft beer. Positive coefficients are represented by red circles, which indicate a direct relationship between variables in the matrix, and negative coefficients are shown as blue circles, which reflect an inverse relationship. *: p ≤ 0.05; ***: p ≤ 0.001.

Figure 4

PCA analysis chart (A) of samples with different fermentation days, PLA-DA analysis chart (B) of samples with different fermentation days, PLS-DA displacement test chart (C) of samples with different fermentation days, and correlation heatmap of samples with different fermentation days (D).

Figure 5

Volcanic map of significantly different metabolites in different comparison groups. (A) T7 vs. T14 Volcanic map; (B) T7 vs. T21 Volcanic map; (C) T7 vs. T28 Volcanic map; (D) T14 vs. T21 Volcanic map; (E) T14 vs. T28 Volcanic map; (F) T21 vs. T28 Volcanic map.

Figure 6

Classification of metabolites with different fermentation days: (A) HMDB Superclass, (B) HMDB Class, and (C) HMDB Subclass.

Figure 7

(A) Multi-group comparison of differential metabolite clustering heatmap. (B) Triangle bubble thermogram for metabolite correlation analysis. Colors denote correlation coefficients (positive/negative values indicate positive/negative correlations), while pie size reflects p-values. Absolute correlation coefficients approaching 1 signify stronger positive/negative correlations between metabolites.

Figure 8

KEGG enrichment analysis of metabolites with different fermentation days. The color gradient of the columns reflects the enrichment significance of KEGG terms, where darker coloration corresponds to greater statistical significance. Enrichment levels are annotated as: *** for p-value < 0.001 and * for p-value < 0.05.