Black glutinous rice wine (BGRW) is a traditional Chinese rice wine that is brewed using multiple strains. However, the roles of these microorganisms, particularly their contributions to aroma formation, are poorly understood. Accordingly, the main goal of this study was to determine the microbial communities and major metabolites of different traditional fermentation starters. Anshun (AS) starter and Xingyi (XY) starter were used for BGRW to provide insight into their potential contributions to the variation in flavor and aroma. High-throughput sequencing of the microbial community using the Illumina MiSeq platform revealed significant differences during fermentation between the two starter groups. Pediococcus, Leuconostoc, and Bacillus were the dominant bacterial genera in the AS group, whereas Leuconostoc, Pediococcus, and Gluconobacter were the dominant genera in the XY group. In addition, Rhizopus, Saccharomyces, and Saccharomycopsis were the predominant fungal genera detected in both samples. The major metabolites in the two groups were identified by high-performance liquid chromatography and headspace-solid-phase microextraction gas chromatography–mass spectrometry. A total of seven organic acids along with 47 (AS) and 43 (XY) volatile metabolites were detected, among which lactic acid was the primary organic acid, and esters were the largest group in both types of wine. Principal components analysis further revealed significant differences in the dynamic succession of metabolites between the two samples. Correlation analysis showed that 22 and 17 microorganisms were strongly correlated with the production of major metabolites in AS and XY, respectively. Among them, Pediococcus, Leuconostoc, Lactobacillus, Lactococcus, and Streptococcus were shown to play crucial roles in metabolite synthesis. Overall, this study can provide a valuable resource for the further development and utilization of starters to improve the aromatic quality of BGRW.

Panxian ham, a traditional Chinese dry-cured ham, is protected by national geographical indication. Similar to other fermented foods, the microbial population of dry-cured ham is pivotal to taste and flavor formation. This study aimed to establish the relationship between microorganisms and metabolites during the spontaneous fermentation of Panxian ham. Multivariate analysis based on metabolomics data revealed that continuous metabolic changes occurred during the entire fermentation process, with the most significant changes occurring in the initial stage of ripening. Thirty-one significantly different metabolites (SDMs) were identified as discriminant factor, and pathway analysis suggested that these metabolites were involved in 30 pathways, including alanine, aspartate, and glutamate metabolism; glycine, serine, and threonine metabolism; and arginine and proline metabolism. Microbial community analysis using the Illumina MiSeq platform indicated that the bacterial community was more complex than the fungal community, and their succession regulation differed during processing. At the genus level, 11 bacteria and five fungi were identified as core microbes, of which Staphylococcus was the dominant bacteria and Debaryomyces and Aspergillus were the dominant fungi. Further, statistical redundancy analysis (RDA) indicated that Staphylococcus, Debaryomyces, and Chromohalobacter promoted the production of amino and fatty acids; Cobetia and Aspergillus were associated with sugar metabolism, and Kushneria, Penicillium, and Yamadazyma were closely related with organic acids. These findings provide fundamental knowledge regarding the metabolically active microorganisms in Panxian ham, helping industrial processors to develop effective strategies for standardizing quality parameters.

Black waxy rice wine fermentation metabolites are closely related to the product's final quality. However, little is known about dynamic metabolite changes during fermentation. Here, we used gas chromatography time‐of‐flight mass spectrometry (GC‐TOF‐MS) metabolomics and multivariate statistical analysis to explore the relationship between metabolites and fermentation time. A total of 159 metabolites were identified during the entire fermentation process. The PCA analysis revealed a clear separation between the samples after 4 days and 2 days, and the samples after 4–24 days clustered together. This indicated that BGRW fermentation progresses rapidly in the first 48 hr of fermentation. A total of 40 metabolites were identified as differential during fermentation (VIP > 1 and p < .05), including 12 organic acids, four amino acids, one fatty acid, 17 sugars and sugar alcohols, one alcohol, and five other metabolites. Pathway analysis showed that the differential metabolites were involved in 28 metabolic pathways, and the most commonly influenced pathways (impact value > 0.1 and p < .05) were galactose metabolism, pyruvate metabolism; starch and sucrose metabolism; alanine, aspartic acid, and glutamate metabolism; the tricarboxylic acid cycle, glyoxylic acid, and dicarboxylic acid metabolism; and amino sugar and nucleotide sugar metabolism. Moreover, the integrated metabolic pathway was generated to understand the transformation and accumulation of differential metabolites. Overall, these results provide a comprehensive overview of metabolite changes during black waxy rice wine fermentation.

Pre-fermentation is crucial for black glutinous rice wine production. However, the dynamic changes occurring in metabolites during pre-fermentation remain unclear. Hence, multivariate analysis to investigate the relationship between metabolites and fermentation time was performed. Both PCA and OPLS-DA score plots showed a typical drift of metabolite profiles during fermentation for 0–60 h, whereas a reverse change occurred after 60 h. Of the 28 significantly different metabolites (SDMs) (VIP > 1 and p < .05) identified during pre-fermentation, 50% were enriched at 60 h including sugar, phenolic acid, and organic acid. This resulted in the highest levels of total phenolic and total acid. Pathway analysis based on SDMs indicated that the starch and sucrose metabolism, alanine, aspartate, and glutamate metabolism, and pentose phosphate pathway were most relevant to pre-fermentation (Pathway impact value > 0.1 and p < .05). The integrated metabolic pathway was generated to understand the transformation and accumulation of SDMs. Metabolite profiles at 0, 60, and 72 h were compared using S-plot. More sugar types were observed at 60 h than at 72 h. Moreover, succinic acid and 4-hydroxyphenylethanol, as metabolites of yeast, were significantly upregulated between 60 and 72 h. Therefore, 60 h is potentially optimal for pre-fermentation of black glutinous rice wine. This study rationalizes the pre-fermentation steps vital for black glutinous rice wine production.