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. 2026 Jun 1;37:104062. doi: 10.1016/j.fochx.2026.104062

Dynamic changes of physicochemical, microbial, and flavor characteristics in Xinjiang rawish cereal vinegar fermentation

Huizhen Wang a, Xinwei Wang a, Xin Zhou a, Shiran Sun a, Zaizhu Yuan a, Yuanguo Xi d, Chenqiang Wang e, Juan Du f, Bin Wang a,b,c,⁎, Xuewei Shi a,b,c,⁎
PMCID: PMC13265697  PMID: 42306503

Abstract

Rawish cereal vinegar is a traditional acidic condiment in Xinjiang, China. This study employed high-performance liquid chromatography (HPLC), gas chromatography–mass spectrometry (GC–MS), and high-throughput sequencing (HTS) to systematically analyze the dynamic changes in physicochemical properties, volatile compounds, and microbial communities. The analysis identified 7 organic acids, 7 phenolic compounds, and 74 volatile compounds, with 25 of the latter exhibiting odor activity values (OAV) greater than 1. Microbial community analysis revealed that Pseudomonas, Lactobacillus, and Acetobacter were the dominant bacterial genera, whereas aspergillus and Pichia were the principal fungal genera. Furthermore, spearman's correlation analysis revealed a significant positive association between Pseudomonas, Komagataeibacter, Monascus, and Cutaneotrichosporon and the production of key volatile compounds, including undecanal, furfural, pentyl acetate, and ethyl valerate. These findings provide insights into the flavor characteristics and production quality of Xinjiang rawish cereal vinegar

Keywords: Rawish cereal vinegar, Physicochemical properties, Volatile compounds, Microbial dynamics, Co-occurrence network

Graphical abstract

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1. Introduction

Vinegar, a traditional liquid condiment consumed globally, is manufactured through fermentation (Zhang, Huang, et al., 2025). Based on the substrate utilized, vinegar is broadly classified into fruit, alcohol, and cereal varieties (Chen et al., 2016). The history of cereal vinegar production in China is extensive, spanning over 3000 years (Zhang, Li, et al., 2022). Traditionally, cereal vinegar is produced via solid-state fermentation (Zhang, Wang, et al., 2025). Depending on whether the raw materials have been cooked, solid-state fermentation can be divided into ripe and rawish material fermentation. In rawish material fermentation, starchy cereals (such as corn, sorghum, and rice) are ground directly without cooking, allowing saccharification and alcoholic fermentation to occur simultaneously (Che et al., 2020). The production of vinegar from rawish materials has attracted increasing attention due to its simplified process, low energy consumption, comparable yield, and consistent flavor.

Xinjiang traditional cereal vinegar has a relatively long brewing history and is a major acidic condiment in this region. Xinjiang cereal vinegar possesses unique local characteristics owing to its specific geographical environment and distinctive microbial communities in traditional fermentation pits. Currently, research on cereal vinegar has primarily focused on products made using the cooked material method, including ripe cereal vinegar from Xinjiang (Li, Fu, et al., 2023). Although interest in rawish material fermentation is growing, little research has been conducted on the succession of microbial communities and the formation mechanisms of flavor compounds in Xinjiang rawish cereal vinegar.

Flavor is a key indicator of vinegar quality (Zhang, Wang, et al., 2025). Vinegar acidity is derived from multiple organic acids. Acetic acid provides a characteristic pungent taste, whereas lactic acid contributes to a mellow mouthfeel (Nie et al., 2017; Zhang, Xu, et al., 2020). In addition to organic acids, volatile compounds such as esters, alcohols, aldehydes, and ketones interact to shape the distinctive flavor profile of cereal-based vinegar (Al-Dalali et al., 2020). These flavor compounds are primarily generated by microbial metabolism during the fermentation process (Wang et al., 2016). Flavor compounds are continuously transformed under the dynamic influence of factors such as raw material type, fermentation duration, temperature, and production processes (Li et al., 2024). Consequently, numerous studies have explored the relationship between microbial communities and flavor metabolites, identifying key functional microorganisms in the process. For instance, Acetobacter and Lactobacillus are the dominant bacterial genera in Shanxi aged vinegar and are closely associated with the production of various flavor compounds (Zhu et al., 2018). Similarly, during the Hongqu fermentation stage, Aspergillus, Candida, and Issatchenkia contribute significantly to the formation of flavor (Li et al., 2022). Therefore, clarifying the relationship between microbial communities and flavor compounds is essential for understanding the flavor development of cereal vinegar.

This study employed high-performance liquid chromatography (HPLC), headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME-GC–MS), and high-throughput sequencing (HTS) to investigate the dynamic changes in the physicochemical properties, volatile compounds, and microbial communities during rawish cereal vinegar fermentation. Spearman's correlation analysis was used to assess the relationships between the microbial communities and volatile compounds. These findings provide a reference for understanding the dynamic changes in key indicators during rawish cereal vinegar production.

2. Materials and methods

2.1. Sample and reagents

2.1.1. Sample collection

Samples of rawish cereal vinegar at different production stages were collected between April and June 2022 from the production workshop of Xinjiang Xiaochu Vinegar Industry Co., Ltd., a representative vinegar producer in Changji, China. The traditional fermentation process for rawish cereal vinegar in Xinjiang is shown in Fig. S1 and Table S1. Corn and rice were crushed, mixed without cooking, and combined with potable water to prepare the fermentation raw materials. The initial mixture was collected and designated as corn and rice mash (CRM). At the saccharification stage (SS, 2 days), the fermentation starter fuqu (FQ) was added, and SS samples collected on day 0 were designated SS1. At the alcoholic fermentation stage (AF, 7 days), the starter jiuqu was added, and AF mash samples were collected on days 0, 3, and 7 and labeled as AF1, AF2, and AF3, respectively. During the acetic acid fermentation stage (AAF, 23 days), the starter (vinegar seed, VS) was added to the wine mash, rice husks, and wheat bran. Samples were collected on days 0, 7, 14, and 23 and designated AAF1, AAF2, AAF3, and AAF4, respectively. At the aging stage (AS, 32 days), samples were collected on days 0 (the salt was added), 15, and 32, and marked as AS1, AS2, and AS3. The collected samples consisted of liquid wine mashes (CRM, SS1, AF1, AF2, AF3), solid vinegar pei (AAF1, AAF2, AAF3, AAF4, AS1, AS2, AS3), and starter cultures (FQ and VS). At each sampling timepoint, samples were collected from three different fermentation tanks at a depth of 25 cm below the surface. All samples were collected before agitation. Upon collection, the samples were transported to the laboratory and immediately stored at −80 °C for subsequent analysis.

2.1.2. Chemicals and reagents

Standards (malic acid, tartaric acid, lactic acid, oxalic acid, succinic acid, acetic acid, citric acid, kaempferol, epicatechin, vanillic acid, chlorogenic acid, ferulic acid, rutin, gallic acid, and 3-octanol) were purchased from Shanghai Yuanye Bio-Technology Co., Ltd. (Shanghai, China).

2.2. Physicochemical characterization

For sample pretreatment, 100 mL of the wine mash was centrifuged at 8000 rpm for 10 min to obtain the supernatant. A 10 g sample of vinegar pei was added to 90 mL of distilled water and shaken at 120 rpm at room temperature for 2 h. Both samples were filtered through a 0.22 μm filter membrane, and the resulting filtrates were stored at 4 °C for later use. Total acidity was quantified by titration with a standardized 0.1 M NaOH solution to a pH of 8.2 (Zhang et al., 2023). The concentration of reducing sugars was determined using a 3,5-dinitrosalicylic acid (DNS) colorimetric assay (Huang et al., 2022). The ethanol content was measured using an alcohol meter, following the GB 5009.225–2016 standard method. The fermentation temperature was monitored by inserting a standard thermometer vertically into the fermentation vessel 10 cm below the surface. Amino acid nitrogen content was determined via formol titration, as prescribed by the method GB 5009.235–2016. The moisture content was determined gravimetrically by drying the samples in an oven at 105 °C until a constant weight was achieved. The pH of the samples was measured using a pH meter.

2.3. Determination of organic acids

Following the pretreatment in Section 2.2, the wine mash was diluted 20-fold, and the vinegar pei (already 10-fold) was further diluted 2-fold, yielding a final 20-fold dilution for both. Seven standard organic acids, namely tartaric acid, malic acid, oxalic acid, lactic acid, acetic acid, citric acid, and succinic acid were used to generate a standard curve for the quantitative analysis of organic acids (Table S2). Analyses were conducted using an HPLC system (Waters 2695, Waters Corporation, Milford, MA, USA) equipped with a C18 column (250 mm × 4.6 mm, 5 μm, Diamonsil Technology, Beijing, China). The mobile phase consisted of 97% 0.1% H3PO4 and 3% methanol, delivered at a flow rate of 0.5 mL/min. The column temperature was maintained at 30 °C. The injection volume was 20 μL, and UV detection was performed at 210 nm wavelength. Organic acids were quantified using linear regression equations derived from standard curves of peak area versus concentration (Wang et al., 2024).

2.4. Determination of phenolic compounds

The phenolic compound content was quantified using an HPLC system (Waters 2695, Waters Corporation, Milford, MA, USA) fitted with a C18 column (250 mm × 4.6 mm, 5 μm, Diamonsil Technology, Beijing, China). Monomeric phenols in the samples were extracted using ethyl acetate. A 1% acetic acid-methanol solution was used as mobile phase A, and a 1% acetic acid solution was used as mobile phase B. The column temperature was maintained at 30 °C, the mobile phase flow rate was 0.8 mL/min, the injection volume was 10 μL, and UV detection was performed at 280 nm. The gradient elution was performed as follows: 0–35 min, 5–40% A; 35–55 min, 40–95% A; 55–60 min, return to 5% A (Liu et al., 2025). The samples were identified based on their retention times, and quantitative analysis was performed using an external standard method.

2.5. Determination of volatile compounds

Volatile compounds were analyzed using HS-SPME-GC–MS equipped with an HP-Innowax column (30.0 m × 0.25 mm × 0.25 μm, Agilent Technologies, Santa Clara, CA, USA). Wine mash (5 mL) or vinegar pei (1 g of vinegar pei was mixed with 6 mL of ultrapure water) was mixed with 1.5 g of NaCl and 20 μL of 3-octanol (internal standard, 0.0822 mg/mL) and equilibrated at 45 °C for 20 min (Li et al., 2023). A 50/30 μm DVB/CAR/PDMS SPME fiber (Supelco, Bellefonte, PA, USA) was conditioned at 230 °C for 20 min, exposed to the headspace at 45 °C for 40 min, and desorbed at 230 °C in splitless mode for 5 min. The oven temperature was set at 40 °C for 10 min, gradually increased to 120 °C at 5 °C/min (held for 2 min), and then ramped to 230 °C at 10 °C/min (maintained for 5 min). The mass spectrometer was operated by electron ionization (EI) at 70 eV, with a scanning range of m/z 35–350 (Wang et al., 2022, Zhang et al., 2019). Volatile compounds were identified by comparison with the NIST mass spectral libraries and retention indices (RI). Their concentrations were determined by the internal standard method using the formula (peak area / internal standard area) × internal standard concentration. The odor activity value (OAV) was calculated using the formula OAV = C/OT, where C is the concentration of the compound in the sample and OT is the odor threshold (Fan et al., 2020).

2.6. Microbial diversity analysis

After centrifugation of the wine mash samples at 4 °C and 8000 rpm for 10 min, the resulting pellets were harvested. Both the pellets and the vinegar pei samples were separately pulverized into fine powder using a mortar and liquid nitrogen. Total genomic DNA was extracted from the fermentation samples using the E.Z.N.A.® Soil DNA Kit (Omega Bio-tek, Norcross, GA, USA). The quality and concentration of the extracted DNA were assessed using 1.5% agarose gel electrophoresis and a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific). Following the method of Li et al. (2023), primer selection, amplification program parameters, and product purification steps for microbial amplification were performed. For bacterial community analysis, the V3–V4 region of the 16S rRNA gene was amplified using primers 338F and 806R, and for fungal community analysis, the ITS region was amplified using primers ITS5 and ITS2. The PCR products were purified and used for DNA library construction using the TruSeq Nano DNA LT Library Preparation Kit (Illumina, California, USA). Library quality was assessed using an Agilent 2100 Bioanalyzer (Thermo Fisher Scientific). Qualified libraries were sent to Shanghai Paisenno Biotechnology Co., Ltd. for paired-end sequencing (2 × 250 bp) on an Illumina MiSeq 2500 sequencing platform. The DADA2 method (Callahan et al., 2016) was employed for primer removal, quality filtering, denoising, read merging, and chimera removal, followed by clustering of amplicon sequence variants (ASVs) with 100% similarity (Zhu et al., 2021). The UNITE 8.0 database was used for taxonomic assignment of fungal ITS sequences, and the Silva 132 database for bacterial 16S rRNA genes. Alpha and beta diversities were calculated using QIIME2 based on the ASV abundance matrix.

2.7. Statistical analysis

All experiments were performed in triplicate as independent, biological replicates. Statistical analyses were performed using IBM SPSS Statistics 26 (IBM, New York, USA). Principal component analysis (PCA) with UV scaling and two-way orthogonal partial least squares (O2PLS) analysis were performed using SIMCA 14.1 software (Umetrics, Sweden). Multi-y-axis plots, stacked histograms, sunburst charts, and chord diagrams were generated using Origin 2022 (OriginLab Corporation, Northampton, MA, USA). Heatmaps were generated using an online platform (https://cloud.metware.cn/#/home). Network interaction diagrams based on Spearman's correlation coefficient (|r| > 0.6, p < 0.05) were constructed using Cytoscape software. All results are presented as mean ± standard deviation.

3. Results and discussion

3.1. Physicochemical characteristics during the fermentation process

The dynamic changes in pH, total acid, amino acid nitrogen, ethanol, reducing sugar, temperature, and moisture of rawish cereal vinegar were systematically measured throughout the fermentation process (Fig. 1 and Fig. S2). During the CRM and SS stages, the ethanol content gradually increased from 0 to 1.5% vol. During the SS stage, reducing sugar accumulated to 14.53 g/100 mL due to starch hydrolysis. Subsequently, during the AF stage, the ethanol content rose significantly to a peak of 8.67% vol, while the reducing sugar rapidly decreased from 15.81 g/100 mL to 6.9 g/100 mL (Fig. 1). This may be attributed to the conversion of sugars to ethanol during alcoholic fermentation (Yin et al., 2024). At the AAF stage, total acid increased from 1.38 g/100 g to 6.11 g/100 g, accompanied by a decrease in pH from 4.51 to 3.85 after the addition of bran, rice husks, and vinegar seeds. Simultaneously, the ethanol content decreased from 7.3 to 1.2% vol. This may be attributable to the activity of acetic acid bacteria, which oxidize ethanol to acetic acid (Zheng et al., 2022). During the AAF stage, the temperature rapidly rose to 41.6 °C, whereas during the AS stage, it gradually decreased to 27.7 °C. Meanwhile, the amino acid nitrogen content progressively increased from an initial 0.02 g/100 mL to 0.38 g/100 g by the AS3 stage (Fig. S2). This accumulation may be attributed to the enzymatic hydrolysis of raw materials and autolysis of yeast cells (Lei et al., 2013). The moisture content remained within the range of 58% to 70% throughout the process (Fig. S2).

Fig. 1.

Fig. 1

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Dynamic changes in physicochemical characteristics during fermentation of rawish cereal vinegar in Xinjiang. (CRM: raw materials, SS: starch saccharification, AF: alcohol fermentation, AAF: acetic acid fermentation, AS: aging stage). Reducing sugar (green), total acid (blue), ethanol (red), and temperature (purple). Different lowercase letters indicate significant differences between samples (p < 0.05). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.) Note: For liquid wine mash samples (CRM, SS, and AF), concentrations are expressed in g/100 mL; for solid vinegar pei samples (AAF and AS), the unit is given as g/100 g. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

3.2. Organic acids during the fermentation process

Organic acids are the main products generated by microbial metabolism during cereal fermentation and play a crucial role in the formation of the flavor profile of vinegar (Bordiga et al., 2023). This study employed HPLC to quantitatively analyze seven organic acids in samples of Xinjiang rawish cereal vinegar at different fermentation stages (Table S3 and Fig. 2). The concentrations of the seven organic acids varied with fermentation duration, showing a continuous increase in total organic acid content throughout the process, ultimately reaching 4272.82 mg/100 g. During the liquid-state SS and AF stages, the lactic acid content increased rapidly, peaking at 705.68 mg/100 mL, which may contribute to a softer flavor profile (Jiang et al., 2019). Throughout the solid-state AAF and AS stages, the acetic acid concentration surged dramatically from 113.72 mg/100 g to 2831.68 mg/100 g; concurrently, the lactic acid content gradually decreased to 475.29 mg/100 g and succinic acid content peaked at 815.96 mg/100 g during the AS2 stage, making them the predominant organic acids. Furthermore, although malic, tartaric, and citric acids were present at lower concentrations, their combined presence mitigated the sharpness of acetic acid, resulting in a more mellow acidity and a longer-lasting finish in the vinegar (Wang et al., 2017).

Fig. 2.

Fig. 2

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Content of organic acids in different fermentation stages of rawish cereal vinegar in Xinjiang. Different lowercase letters indicate significant differences between samples (p < 0.05).

Note: For liquid wine mash samples (CRM, SS, and AF), concentrations are expressed in mg/100 mL; for solid vinegar pei samples (AAF and AS), the unit is given as mg/100 g.

3.3. Phenolic compounds during the fermentation process

Phenolic compounds are integral components of cereal vinegar and function as antioxidants by eliminating free radicals (Özen et al., 2020). During the SS and AF stages, gallic acid exhibited the highest concentration among the phenolic compounds, and its content increased significantly as fermentation progressed (Fig. 3). During the AAF and AS stages, the concentrations of various phenolic compounds increased to varying degrees, reaching a total content of 8.76 mg/100 g by the end of fermentation. Gallic acid exhibited the most pronounced increase, rising from 0.68 mg/100 g to 2.65 mg/100 g, and became the most abundant phenolic compound. Ferulic acid was the second most abundant, with a concentration of 1.28 mg/100 g, whereas vanillic acid and kaempferol had concentrations of 1.14 mg/100 g and 1.07 mg/100 g, respectively. In contrast, epicatechin showed minimal change, increasing from 0.44 mg/100 g to 0.59 mg/100 g (Fig. 3). Previous studies have identified microbial genera such as Aspergillus and Bacillus as key contributors to phenolic acid biosynthesis, including the production of gallic and chlorogenic acids (Zárate et al., 2015). Moreover, raw materials such as bran contain abundant phenolic compounds, which are released through complex reactions between microorganisms and raw materials (Zhang, Yang, et al., 2019). The phenolic profiles of vinegars vary with the raw materials and processes, as illustrated by Shanxi aged vinegar, which is rich in gallic acid and catechins (Xia et al., 2017). These phenolic substances in vinegar have positive effects on human health (Kandylis et al., 2021).

Fig. 3.

Fig. 3

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Content of phenolic compounds in different fermentation stages of rawish cereal vinegar in Xinjiang. Different lowercase letters indicate significant differences between samples (p < 0.05).

Note: For liquid wine mash samples (CRM, SS, and AF), concentrations are expressed in mg/100 mL; for solid vinegar pei samples (AAF and AS), the unit is given as mg/100 g.

3.4. Volatile compounds during the fermentation process

Volatile compounds are critical indicators of vinegar quality and fermentation status. In this study, 74 volatile compounds were detected and classified, comprising 31 esters, 10 alcohols, 10 aldehydes, 9 acids, 7 ketones, and 7 other flavor compounds (Table S4). The dynamic evolution of volatile compounds was characterized by the accumulation of esters, acids, and ketones (Fig. 4A). The complexity and concentration of these compounds were lowest at the SS stage and showed a consistent increase as the production process advanced (Fig. 4B). Furthermore, vinegar pei samples exhibited greater diversity of volatile compounds than the wine mash samples (Fig. S3).

Fig. 4.

Fig. 4

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Changes in volatile compounds during different fermentation stages of rawish cereal vinegar in Xinjiang. (A) Content of volatile compounds in different fermentation stages; (B) Cluster heatmap of volatile compounds. Principal component analysis (PCA): (C) Score plot and (D) loading plot of volatile compounds. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Esters, formed through the esterification of acids and alcohols, are the most abundant volatile compounds in cereal vinegar. The total concentration increased sharply from the initial stage to a peak of 3053.60 μg/100 g at AS1, followed by a significant decrease to 2426.19 μg/100 g. A total of 31 esters were identified, of which 18 were ethyl esters and 9 were acetate esters. Ethyl and acetate esters are the main components that confer floral and fruity aromas to vinegar (Dumitriu et al., 2017). Ethyl butyrate, ethyl phenylacetate, ethyl caprylate, ethyl heptanoate, ethyl caproate, and 4-undecanolide were detected during the fermentation process. These compounds possess fruity and creamy aroma characteristics and may contribute to the overall flavor profile of the product (Guerrero et al., 2021).

Higher alcohols are primarily derived from the reductive deamination of amino acids and yeast-mediated metabolism of sugars containing aldehyde and ketone groups (Yin et al., 2024). These alcohols not only function as essential metabolic substrates during the AAF stage but also contribute directly to the characteristic aroma of vinegar. The concentrations of alcohols, such as 2,3-butanediol, ethanol, 2-heptanol, oct-1-en-3-ol, and phenylethyl alcohol, increased during the AF stage. This trend is consistent with that reported for Zhenjiang balsamic vinegar (Zhou et al., 2020). Notably, phenylethyl alcohol was among the predominant alcohols in the AAF stage and has long been a marker of vinegar aroma, as observed in Beijing rice vinegar (Zhang, Yang, et al., 2019). This compound is primarily synthesized via yeast-mediated amino acid metabolism (Etschmann et al., 2022). The progressive accumulation and subsequent conversion of ethanol during fermentation enhanced the overall flavor complexity of the cereal vinegar.

Acids constitute a major group of volatile compounds that are essential for the flavor of cereal vinegar. During the AAF stage, acetic acid was produced in large quantities (3101.93 μg/100 g), representing the main contributor to sourness and serving as a key indicator of the completion of fermentation (Özen et al., 2020). Acetic acid is a precursor for ester formation. As the rate of acid production exceeds that of esterification, acids tend to accumulate in large quantities (Al-Dalali et al., 2022). Other organic acids, such as 2-ethylhexanoic and octanoic acids, can mitigate the pungency of acetic acid and enhance the overall sensory quality. Several carboxylic acids, including acetic, butyric, hexanoic, and octanoic acids, gradually accumulate over time and serve as direct precursors of methyl ketones, alcohols, lactones, and esters, which collectively shape the characteristic flavor of cereal vinegar (Hao et al., 2025).

Carbonyl compounds, primarily aldehydes and ketones (Chinnici et al., 2009), typically impart nutty and fruity flavors and are derived from amino acid degradation, unsaturated fatty acid oxidation, and Maillard reactions (Zhao et al., 2020). Furfural and benzaldehyde were the predominant aldehydes. Furfural imparts characteristic almond and caramel aromas, and its concentration is essential for developing a pleasant flavor profile (Zhou et al., 2017; Zhu et al., 2020). Acetoin emerged as the principal aroma compound during the AS stage, accumulating to 633.56 μg/100 g and contributing to a characteristic nutty and roasted flavor. This compound, produced via the oxidation of 2,3-butanediol (Xiao et al., 2014; Xu et al., 2018), is a distinctive aroma biomarker for monitoring the aging of cereal vinegars (Durán-Guerrero et al., 2021). The presence of these substances significantly enriches the flavor of cereal vinegars.

Similar to other traditional vinegars, this cereal vinegar contains volatile phenols and nitrogen-containing heterocyclic compounds. Notably, 2-ethylphenol was identified exclusively during the AS stage and was specifically linked to the microbial metabolic activity (Chinnici et al., 2009). Tetramethylpyrazine was identified as a prominent nitrogen-containing heterocyclic compound, consistent with findings widely reported for other cereal vinegars, including Shanxi aged vinegar, Beijing rice vinegar, and Zhejiang vinegar (Li et al., 2024). In addition, trace amounts of trimethylpyrazine were detected, and 2,4-dimethyl-3-ethyl-1H-pyrrole was consistently present throughout the fermentation process. These nitrogen-containing heterocycles significantly contribute to the overall aroma of cereal vinegars.

To visualize and analyze the volatile compounds in different samples during fermentation, principal component analysis (PCA) was performed on 74 volatile compounds. The cumulative variance explained by PC1 and PC2 was 59.9% (PC1 = 46.7%, PC2 = 16.1%) (Fig. 4C). The PCA score plot revealed a clear separation among all sample groups, indicating significant differences in the volatile composition across the fermentation stages. The loading plot (Fig. 4D) showed that certain compounds, including hexyl acetate, 4-undecanolide, and 2-amylfuran, exhibited strong correlations during fermentation, suggesting their potential relevance as characteristic compounds in the fermentation.

3.5. Odor activity value during the fermentation process

To elucidate the specific contributions of individual volatile compounds to the overall aroma, their odor activity values (OAVs) were calculated. The odor threshold represents the minimum concentration of a substance that can be perceived by the human olfactory system, and an OAV greater than 1 indicates that a compound makes a significant contribution to the aroma profile. A total of 25 volatile compounds with OAV > 1 were identified at various stages of cereal vinegar fermentation. As detailed in Table S5, ethyl heptanoate (OAV = 62.84–6.14), ethyl hexanoate (OAV = 2.16–44.12), ethyl caprate (OAV = 9.96–274.52), ethyl caprylate (OAV = 5.00–36.76), 4-undecanolide (OAV = 11.34–50.13), nonanal (OAV = 5.20–227.3), and 2,3-butanediol (OAV = 2.05–4.02) exhibited the most substantial flavor contributions, having been detected with high OAVs throughout the entire fermentation process. The OAVs of these compounds underwent dynamic changes as fermentation progressed. For instance, the OAV of phenethyl acetate increased progressively during the AAF and AS stages, imparting a characteristic intense sweet aroma to the cereal vinegar. Furthermore, ethyl caprate, γ-dodecalactone, 2-octenal, and nonanal gradually became dominant aromas during the AS stage. Among fruity aromas, isopentyl acetate is considered a potentially significant contributor to the aged vinegar flavor (Zhang et al., 2023).

The subjective perception categories (inner circle) and related odor descriptions (outer circle) of rawish cereal vinegar are shown in Fig. S4. The key aroma-active compounds were analyzed and classified into four main types: “fatty aroma,” “flowery aroma,” “fruity aroma,” and “other aroma.” Esters are predominantly responsible for the fruity characteristics of cereal vinegar. The presence of ethyl phenylacetate, dodecanal, nonanal, and phenethyl acetate was associated with flowery aromas, whereas undecanal, 2-octenal, and butanal were identified as the compounds responsible for the fatty aroma of vinegar.

3.6. Microbial community during the fermentation process

3.6.1. Microbial diversity

In this study, HTS was performed on traditional cereal vinegars to investigate their microbial community structures. Sequencing quality control statistics for each sample are summarized in Table S6 and S7, confirming sufficient sequencing depth for downstream analysis. To characterize the microbial community, alpha diversity was evaluated using the Chao1 and Shannon indices, which measure species richness and diversity, respectively (Schloss et al., 2009). Within the fungal community (Fig. S5A), species richness, as determined by the Chao1 index, peaked at the AAF1 stage following the introduction of raw materials such as bran and vinegar pei. However, this richness subsequently declined as fermentation progressed. A congruent trend was observed for the Shannon index. In bacterial communities (Fig. S5B), the Chao1 index showed a gradual decline from its peak at the SS1 stage to the AS stage, whereas the Shannon index reached its zenith at the AF2 stage. Throughout the process, bacterial abundance and diversity were consistently and significantly higher than fungal abundance and diversity. The beta diversity of the microbial communities across different fermentation stages was analyzed using PCA, as illustrated in Fig. S6A and S6B. For fungi, the score plot revealed distinct clustering of samples from each fermentation stage. The first two principal components explained 74.1% of the total variance (PC1 = 41.5%, PC2 = 32.6%). For bacteria, samples from different stages were also clearly separated in the score plot, indicating significant shifts in the bacterial community composition throughout the fermentation process. The first two principal components accounted for 42.4% and 32.0% of the variance, respectively.

3.6.2. The taxonomic composition

Analysis of the shared ASVs revealed a stark disparity between the microbial kingdoms; only two fungal ASVs were shared across stages, compared to six shared bacterial ASVs (Fig. S7A and S7B). This finding underscores the marked contrast in community structure throughout the fermentation stages. A proliferation of bacterial and fungal communities characterized the initial fermentation phase, followed by a decline in their numbers. Collectively, these data indicate that the bacterial community harbored a considerably higher number of ASVs than the fungal community, reflecting its significantly greater diversity during the fermentation process.

Taxonomic analysis identified 5 fungal and 16 bacterial phyla, and tracking these dominant groups revealed dynamic successional changes in both communities. The fungal community was primarily composed of Ascomycota and Basidiomycota (Fig. 5A). This pattern of dominant fungal phyla is consistent with the findings of studies on Xinjiang ripe cereal vinegar (Li, Wang, et al., 2023). While Basidiomycota was the predominant phylum across most stages, Ascomycota was dominant during the AS2 stage. The major fungal genera were Aspergillus, Pichia, and Monascus (Fig. 5B). The average relative abundance of Aspergillus was markedly higher than that of other fungal genera, fluctuating from a minimum of 3.25% at the AAF1 stage to a maximum of 99.85% at the AS3 stage. Aspergillus is known for its role in saccharification, where it converts starch into sugar, and is widely used in the production of white wine (Wang, Wang, et al., 2022), soy sauce (Tan et al., 2022), and vinegar (Zhang, Zhang, et al., 2022). The second most abundant fungus, Pichia, reached its maximum relative abundance (33.44%) at the AAF3 stage. Monascus, a characteristic microbe in various vinegars, such as traditional “Fujian Red Vinegar” (Li et al., 2022), contributes significantly to the distinctive flavor profile of these foods by producing pigments and enzymes (Sirphochanart et al., 2022). Despite its low relative abundance, Candida was present throughout the brewing process and had a substantial impact on microbial diversity.

Fig. 5.

Fig. 5

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Dynamic changes in fungal (A) and bacterial (C) communities of different samples at the phylum level. Relative abundance of the top 15 fungi (B) and bacteria (D) during vinegar brewing at the genus level.

Proteobacteria, Firmicutes, and Cyanobacteria dominated the bacterial community, collectively comprising 99.26% of the total abundance (Fig. 5C). The abundance of Firmicutes increased significantly during the CRM and AF stages, reaching 93.71% in AF3. In contrast, Proteobacteria increased during the AAF and AS stages, peaking at 99.3% before declining. At the genus level, the succession of the microbial community was analyzed by focusing on the top 15 most abundant bacterial genera (Fig. 5D). Pseudomonas, Weissella, Acetobacter, and Lactobacillus were the predominant bacterial genera. Although Chloroplast, Leuconostoc, and Lactococcus were dominant in the CRM stage, their abundance decreased progressively as fermentation progressed. The relative abundance of Weissella at the SS1 and AF1 stages ranged from 43.52% to 52.37%. The abundance of Lactobacillus increased during the AF and AAF stages, reaching a maximum of 74.59% before declining, a phenomenon that may be ascribed to the inhibitory effect of elevated temperatures on its proliferation (Ge et al., 2019; Zhang, Xu, et al., 2020). The relative abundance of Acetobacter peaked (67.28%) during the AAF stage, where it played a crucial role in bacterial cellulose and organic acid production (Kashima et al., 2000). The relative abundance of Pseudomonas increased throughout the process, reaching a sharp peak of 97.8% during the AS stage, probably because of the bacteriostatic effect of salt and environmental shifts (Lee et al., 2021; Paul et al., 2006). A similar trend was observed in Xinjiang ripe cereal vinegar (Li, Wang, et al., 2023). The metabolic capabilities and environmental adaptability of Acetobacter, Lactobacillus, and Pseudomonas significantly enhance the quality and flavor of fermented products (Tang et al., 2017).

3.7. Associations between the communities during the production process

Microbial interactions are pivotal in governing growth patterns, adaptability, and metabolite production (Ivey et al., 2013). A correlation analysis of the bacterial community revealed predominantly positive correlations among its members, suggesting symbiotic relationships (Fig. 6A). However, Pseudomonas and Acetobacter showed a negative correlation with most other bacterial genera, while exhibiting a positive correlation with each other. Within the fungal community, highly significant positive correlations were observed among the different species (Fig. 6B). Specifically, Pichia displayed a strong positive correlation with several other fungal groups. Aspergillus showed a significant positive correlation with Kazachstania and Trichosporon but a negative correlation with most other fungi. Monascus was positively correlated with Cutaneotrichosporon and Cystofilobasidium, whereas the latter two were negatively correlated with Kazachstania. The associations between fungi and bacteria further elucidated the inter-kingdom dynamics of the fermentation process (Fig. 6C). For example, Aspergillus exhibited a significant negative correlation with Lactobacillus while maintaining a positive correlation with Pseudomonas and Weissella. Lactobacillus plays a central role in cereal vinegar maturation by synthesizing diverse volatile compounds (Zhu et al., 2018). Monascus showed a positive correlation with Pseudomonas and Acetobacter but a strong negative correlation with most other bacterial genera. Candida, Sarocladium, and Fusarium showed a significant positive correlation with most bacteria but a negative correlation with Pseudomonas and Acetobacter. In contrast, Aspergillus showed a predominantly negative correlation with bacterial communities. Acetobacter exhibits highly competitive abilities and becomes predominant throughout the fermentation process owing to its efficient catabolism of fermentation products and tolerance to acidity (Guo et al., 2020). In summary, these findings illuminate the complex network of potential interactions among microorganisms during the fermentation process. The observed positive and negative correlations likely influence the microbial community balance and overall ecological function.

Fig. 6.

Fig. 6

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Correlation analysis of microbial communities during fermentation. (A) Correlation between bacteria and bacteria; (B) Correlation between fungi and fungi; (C) Correlation between bacteria and fungi. The stronger the correlation, the larger the circle. The color bar indicates the nature of the correlation, with a positive correlation represented by pink and a negative correlation represented by blue. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

3.8. Associations between core microorganisms and volatile compounds during the fermentation process

Microbial metabolism is pivotal in the formation of volatile flavor compounds during cereal vinegar fermentation (Fang et al., 2021). The crucial microorganisms and flavor compounds were identified using a two-way orthogonal partial least squares (O2PLS) model. A variable importance in projection (VIP) threshold greater than 1.0 was used to confirm the variables with substantial contributions. To identify the core microorganisms, O2PLS analysis was performed with the top 15 fungal and 15 bacterial genera ranked by average relative abundance as X variables and 74 flavor compounds as Y variables. The model yielded R2X = 0.925, R2Y = 0.954, and Q2 = 0.739 (Fig. S8A), indicating that it adequately explained the differences in the microbial composition among the samples. Furthermore, permutation tests showed that the Q2 regression line intersected the vertical axis below zero (Fig. S8B), confirming the robustness of the model. Based on a VIP value >1.0, a core functional microbiota consisting of 8 fungi and 10 bacteria, along with 42 key flavor compounds, was identified (Fig. S8C and Fig. S9). The potential correlations between these dominant microorganisms and crucial compounds were further investigated using Spearman's correlation analysis, with significance defined as |r| > 0.6 and p < 0.05. Ultimately, the core microorganisms comprised 6 fungi and 8 bacteria, and the core volatile compounds included 3 alcohols, 4 aldehydes, 4 acids, 18 esters, 3 ketones, and 3 other compounds (Fig. 7).

Fig. 7.

Fig. 7

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Correlation networks between microorganisms and volatile compounds during fermentation. Correlation networks according to Spearman's correlation coefficients (|r| > 0.60, p < 0.05). The pink and green lines indicate positive and negative correlations, respectively. A thicker line indicates a stronger correlation. The size of the circle indicates the number of edges linked to it; the larger the circle, the more edges there are. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

The transformation of flavor compounds during fermentation is intricately linked to the ecological drivers of microbial community succession (Li et al., 2015). These fungal and bacterial genera were strongly correlated with fragrance substances. In this study, Fusarium exhibited negative correlations with 16 volatile compounds, most of which were esters, including isoamyl acetate, phenethyl acetate, and γ-dodecalactone. Although Fusarium showed a negative correlation with most esters, it has been reported to participate in the biosynthesis of esters, alcohols, and terpenes (Pessôa et al., 2017), which may contribute to the formation of vinegar flavor. Kazachstania exhibited a negative correlation with 7 volatile compounds, including ethyl acetate. It has been reported to be closely associated with the production of floral and fruity esters (Lin et al., 2022). Cutaneotrichosporon species are important producers of fatty alcohols and triacylglycerol (Koivuranta et al., 2018). Cutaneotrichosporon exhibited a significant positive correlation with 13 key volatile compounds, including 3 acids, 3 aldehydes, 4 esters, 1 ketone, and 2 other compounds. Pichia species can degrade polysaccharides, and this non-Saccharomyces genus is known to produce substantial quantities of alcohol, organic acids, and esters during various baijiu fermentation processes (Jiang, Liu, et al., 2019). A significant positive correlation was observed between Pichia and the levels of ethyl hexanoate, ethyl phenylacetate, and acetic acid. Monascus, a filamentous fungus known to produce pigments and functional secondary metabolites (Huang et al., 2019), was also positively correlated with 19 volatile compounds, including pentyl acetate, hexyl acetate, and phenethyl acetate. Lactobacillus generates pyruvate through sugar metabolism, which can be further oxidized to acetic acid (Gänzle, 2015) and can convert leucine, isoleucine, and valine into alcohols (Tian et al., 2023). In this study, Lactobacillus exhibited a strong negative correlation with 10 volatile compounds, including aldehydes, acids, and esters, which may be associated with the complexity of the vinegary flavor. Acetobacter is widely used in the industrial production of vinegar and can generate acetic acid, ketones, and acetoin (Chai et al., 2020). Acetobacter was positively correlated with 10 volatile compounds, including pentyl acetate, hexyl acetate, hexyl crotonate, and 4-undecanolide, and negatively correlated with oct-1-en-3-ol. Acetobacter, Lactobacillus, and Aspergillus are the dominant microorganisms in Zhenjiang vinegar (Fang et al., 2021). Pseudomonas is a bacterial genus commonly found in various fermented foods, such as Zha-Chili (Cai et al., 2021), fermented soybeans (Chen et al., 2019), and Zhejiang rosy vinegar (Fang et al., 2021). Pseudomonas showed a strong positive correlation with 30 volatile compounds, suggesting a potential association with vinegar flavor. The high relative abundances of Acetobacter, Lactobacillus, and Pseudomonas consume many nutrients, which may help inhibit the growth of spoilage microorganisms and contribute to stable food quality (Fang et al., 2021). Komagataeibacter showed highly significant positive correlations with 29 volatile compounds, including 4 acids and 16 esters. This is attributed to its ability to produce acetic and gluconic acids, which serve as key substrates for both enzymatic and non-enzymatic esterification reactions, thereby driving flavor formation (Liao et al., 2025). Furthermore, Enterobacter can synthesize biogenic amines along with lipases, which may influence the flavor profile of fermented products (Yan et al., 2024). Although some low-abundance genera (such as Cutaneotrichosporon, Komagataeibacter, and Enterobacter) have low relative abundances, they exhibit strong correlations with a wide range of volatile compounds. Therefore, a comprehensive understanding of dynamic microbial succession and the corresponding changes in volatile compounds is crucial for enhancing cereal vinegar quality.

It should be noted that, for commercial confidentiality reasons, the exact raw material ratios are not provided, which may limit absolute quantitative replication but does not affect the qualitative conclusions and mechanistic insights of this study.

4. Conclusions

This study employed HPLC, HS-SPME-GC–MS, and HTS technologies to systematically investigate the dynamic changes in the physicochemical properties, volatile compounds, and microbial communities throughout the fermentation of Xinjiang rawish cereal vinegar. The study revealed a complex microbial consortium integral to the fermentation process, identifying 5 fungal and 16 bacterial phyla. The dominant bacterial genera were Pseudomonas, Lactobacillus, and Acetobacter, whereas Aspergillus and Pichia were the predominant fungal genera. These microorganisms play a pivotal role in developing the characteristic flavor profile of vinegars. The relationship between microbial communities and volatile compounds was examined using Spearman's correlation analysis. A core functional group was identified, comprising 8 bacterial genera, 6 fungal genera, and 35 volatile compounds. This analysis demonstrated that Komagataeibacter, Pseudomonas, Monascus, Cutaneotrichosporon, and Acetobacter were significantly and positively correlated with the formation of key volatile compounds. These findings provide a scientific basis for optimizing the production of traditional rawish cereal vinegar, with direct implications for improving its flavor and quality, and offer a valuable reference for related fermentation industries.

CRediT authorship contribution statement

Huizhen Wang: Writing – original draft, Data curation, Conceptualization. Xinwei Wang: Formal analysis, Data curation. Xin Zhou: Investigation. Shiran Sun: Data curation. Zaizhu Yuan: Methodology. Yuanguo Xi: Resources. Chenqiang Wang: Validation. Juan Du: Validation. Bin Wang: Writing – review & editing, Funding acquisition. Xuewei Shi: Project administration, Funding acquisition.

Funding

This work was supported by the Unveiling the List and Taking Command Project of Seventh Division (QS2023009), Science and Technology Research Project of the Seventh Division (2024B09), National Natural Science Foundation of China (32260569), Autonomous Region Key Research and Development Program Projects (2022B02058), and Bingtuan Science and Technology Program (2024AB008, 2022 DB006).

Declaration of competing interest

The authors declare that they have no competing financial interests or personal relationships that could have influenced the work reported in this study.

Footnotes

Appendix A

Supplementary data to this article can be found online at https://doi.org/10.1016/j.fochx.2026.104062.

Contributor Information

Bin Wang, Email: binwang0228@shzu.edu.cn.

Xuewei Shi, Email: shixuewei@shzu.edu.cn.

Appendix A. Supplementary data

Supplementary material 1

mmc1.docx (1.9MB, docx)

Supplementary material 2

mmc2.zip (16.1KB, zip)

Data availability

Data will be made available on request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary material 1

mmc1.docx (1.9MB, docx)

Supplementary material 2

mmc2.zip (16.1KB, zip)

Data Availability Statement

Data will be made available on request.

Articles from Food Chemistry: X are provided here courtesy of Elsevier

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