The Chinese Baijiu industry produces over one billion tons of distiller’s dried grains with solubles (DDGS) annually, posing a significant environmental challenge. Traditional methods of utilization are hindered by numerous limitations, including insufficient treatment, low-value processing, and high energy consumption. In this study, ammonium polyphosphate (APP), an inorganic adhesive, was employed to bond DDGS for its materialization. APP self-condensed to intensify its van der Waals force attraction to DDGS—eschewing any chemical reaction with DDGS, resulting in the formation of DB-APP4, which exhibits optimal mechanical properties unaffected by variations in DDGS reactivity. With a modulus of rupture of 12.48 MPa, a modulus of elasticity of 2221.65 MPa, an internal bond strength of 0.56 MPa, and a thickness swelling rate of 5.53 %, DB-APP4 satisfies the fundamental performance criteria for particleboard as outlined in ISO 16978:2003. Furthermore, owing to APP’s ability to catalyze the formation of a protective carbon layer on the material surface while preserving the high porosity characteristic of biomass, the flame retardancy of DB-APP4 has reached Class B1. This study not only addresses the challenge of effectively repurposing DDGS but also provides a pioneering and practical approach for the industrial application of DDGS-based particleboards.

To investigate the mapping relationship between key process parameters and Baijiu yield during the steaming and distillation process of Baijiu fermented material (SDP-BFM) and to optimize these parameters for enhanced production efficiency, a Random Vector Functional Link Networks (RVFLNs) ensemble modeling method integrating Principal Component Analysis (PCA) and Particle Swarm Optimization (PSO) is proposed for yield prediction of Nongxiang Baijiu. First, to improve computational efficiency and avoid multicollinearity, PCA is applied to reduce the dimensionality of the high-dimensional output matrix of RVFLNs, following data cleaning and feature selection. Second, a PSO algorithm is introduced to optimize both the number of hidden layer nodes in sub-learners and the weight combination strategy of the ensemble linear regression method, ultimately achieving Baijiu yield prediction modeling based on the PSO-P-ERVFLNs algorithm. Comparative experiments demonstrate that the optimization strategy introduced by PSO can enhance the prediction accuracy of the RVFLNs algorithm and alleviate overfitting. Moreover, the proposed algorithm exhibits better computational efficiency and higher estimation accuracy, enabling accurate prediction of Baijiu yield during the SDP-BFM.

Luzhou-flavor baijiu is a grain-fermented product whose distinctive qualities result from the micro-ecological environment of the mud cellar. Generally, the development of fundamental flavors during the Luzhou-flavor baijiu fermentation is primarily influenced by the synergistic actions of microbial communities within the mud cellar environment. A comprehensive understanding of the spatial structure of the mud cellar and the composition of pit mud microorganisms is essential for enhancing the quality of Luzhou-flavor baijiu. Current research on the microbial composition of pit mud has been extensively studied, and the key flavor compounds have been well-identified. This review summarizes the micro-ecological characteristics of the mud cellar in the brewing of Luzhou-flavor baijiu, focusing on the construction mechanism of mud cellars, the microbiome of the pit mud, the mechanisms of fermentation metabolism, key acid-producing microorganisms and their flavor contributions. Additionally, it addresses the current applications, existing challenges, and future development prospects of mud cellars. It aims to encourage innovation, design, and optimization of mud cellar systems while offering multidimensional perspectives on how to modernize traditional brewing techniques and study solid-state fermentation ecosystems.

The production environment serves as a critical microbial reservoir that shapes the quality and stability of spontaneously fermented foods, yet the ecological rules governing its resident communities remain unclear. Through two-year monitoring of four core workshop habitats (indoor air (IA), equipment surface (ES), ground, and wall) in a strong-flavor Baijiu distillery, this study elucidated the spatiotemporal assembly of environmental microbiota. We identified ten fermentative genera, including Bacillus and Aspergillus, as the dynamic and stable core taxa across all habitats. Community assembly was dominated by stochastic processes, with dispersal limitation accounting for 48.64%-87.17% of the ecological dynamics. Interaction networks exhibited habitat-specific architectures, IA network displayed the highest complexity and modularity. Source tracking revealed the fermentation system as the main source of environmental microbes. Notably, eight genera, including Kroppenstedtia and Thermoactinomyces, were specifically enriched in IA. Partial least-squares path model further demonstrated that fungal communities were markedly more sensitive than bacteria to environmental factors, particularly the workshop's years of use and habitat type. Collectively, this work redefined the production workshop as a dynamically assembled microbial ecosystem. By analyzing the assembly patterns of the environmental microbiota and the driving environmental factors that drive them, it identifies potential control points that could inform future efforts to modulate microbial communities and manage the "microbial terroir". These findings lay a theoretical foundation for stabilizing product quality and for advancing traditional fermentation toward a more scientific and controllable production.

Background Fermented food microorganisms form a diverse microscopic ecosystem with significant potential for applications in food production, flavor development and human health. However, their complexity, the limitations of traditional culture methods, and the difficulty in functional analysis pose significant challenges to research. Together, these challenges restrict our understanding of underlying mechanisms. Scope and approach This review systematically outlines the paradigm shift brought by artificial intelligence (AI) in overcoming these limitations. We synthesize current research to detail the application of AI, particularly machine learning and deep learning, in mining and interpreting complex microbial datasets. Furthermore, we highlight the transformative applications and potential challenges of these computational methods in the fermentation food industry. Key findings and conclusions AI enables high-resolution microbial annotation and the accurate prediction of gene functions and novel metabolic pathways. Moreover, it empowers researchers to model the complex microbial interactions that drive food fermentation processes. Although challenges in data standardization, model interpretability, and real-world integration remain, AI has undoubtedly emerged as a transformative tool for mining microbial resources in fermented foods. It will accelerate the discovery of next-generation starter cultures and optimize fermentation processes for greater efficiency and consistency. These advancements are poised to significantly enhance industrial fermentation practices, supporting more sustainable and standardized food production. Furthermore, it will facilitate the creation of functional foods targeted at improving human health.

Zaopocu is traditionally produced using Jiuyao as a solid-state starter. However, rapid fermentation processes adopted in recent years often result in reduced aroma intensity and flavor complexity. In this study, a reproducible Jiuyao–Zaopocu fermentation workflow was established to clarify how starter culture affects downstream flavor formation under accelerated conditions. A temperature-controlled strategy was applied during Jiuyao production, and key factors were optimized using Plackett–Burman screening and Box–Behnken response surface methodology. The optimized conditions were identified as a mixing water temperature of 48 °C, Muqu addition of 1.9

Ethanol fermentation has long faced challenges in achieving high fermentation quality. Targeted regulation of the fermentation quality using natural enzymes could effectively address this issue. However, natural enzymes are often highly costly and difficult to control for industrial applications. In this study, the carbon dot nanozyme (CD-NZ) was first developed as a promising alternative for regulating the production of ethanol during fermentation. CD-NZ exhibited catalase-like (CAT-like) and superoxide dismutase (SOD-like) activities, effectively lowering reactive oxygen species (ROS) in yeast under stress conditions. Moreover, CD-NZ demonstrated an ultrafast electron transfer rate of 1.234 ns, showcasing its potential for large-scale applications. At a concentration of 50 mu g/mL, CD-NZ significantly boosted ethanol production by 22.90% and total ester production by 32.01%. Metabolomic analysis revealed enhanced fruity and floral flavors, and metagenomic shifts indicated changes in microbial communities that promoted ester and alcohol production. Importantly, the cost-effectiveness of CD-NZ, combined with its efficiency in improving fermentation performance, makes it a potentially sustainable and economically viable approach for industrial ethanol production. This work highlights the potential of CD-NZ for optimizing ethanol fermentation processes and enhancing product quality.

Strong-flavor Baijiu (SFB) production has relied on pit mud (PM) as a starter culture. The maturation time of natural PM (NPM) is about 30 years, so artificial PM (APM) with a shorter maturation time has attracted widespread attention. This study reveals the microbial and functional dissimilarities of APM and NPM, and helps to elucidate the different metabolic roles of microbes during substrate degradation and flavor formation. Significant differences in the microbial community were observed between APM and NPM, manifesting as variations in the abundance of core microorganisms. Total of 187 high-quality metagenome-assembled genomes (MAGs) were obtained based on the metagenomic binning technology, mainly including Firmicutes (n = 106), Bacteroidota (n = 15) and Chloroflexota (n = 14). Furthermore, the relative concentration of flavor compounds in 4-year APM was similar to those in 30-year NPM, but different from those in 100-year NPMs. Methanosarcina, Methanobacterium, Methanoculleus, Anaerolineae bacterium and Aminobacterium were the key bacteria responsible for the flavor differences. From a functional perspective, amino acid and carbohydrate metabolism were key functions of PM microbial, and showed differences between APM and NPM. Finally, substrate degradation and flavor generation pathways were found to exist in multiple microorganisms. Combine the relative abundance of microorganisms with the absolute abundance of enzymes, Clostridium, Lactobacillus, Petrimonas, Methanoculleus, Prevotella, Methanobacterium, Methanosarcina, Methanothrix, Proteiniphilum, Bellilinea, Anaerolinea, Anaeromassilibacillus, Syntrophomonas and Brevefilum were identified as the key microorganisms in APM and NPM.

This research examined the influences of electric field strength and pulse frequency of pulsed electric field (PEF) treatment, along with the combined effects of dissolved oxygen and ferrous iron ions on the aroma and components of strong-flavor baijiu. PEF treatment improved fruity aromas and decreased the pit mud odor. Electric field strength promoted the production of short-chain fatty acid esters, while pulse frequency facilitated the formation of acetal oxidation products. The most notable changes were observed at an electric field strength of 25 kV, and a pulse frequency of 350 Hz. Increasing dissolved oxygen significantly improves fruity and mellow aromas and promotes the generation of 17 compounds including ethyl lactate, ethyl butyrate, hexan-1-ol, octanoic acid, and 3-methylbutanal, while Fe2⁺ treatment reduces the fruity aroma of baijiu and significantly suppresses the production of 15 esters including ethyl hexanoate, hexyl hexanoate, and ethyl lactate. Dissolved oxygen may contribute to the generation of hydroxyl radicals and regulated oxidation reactions partially in baijiu. And, Fe2+ may react with organic acids to promote the hydrolysis of ester compounds. This study aims to offer valuable insights into the practical application of PEF in the flavor regulation of baijiu.

Microbial community analysis is an important field to study the composition and function of microbial communities. Microbial species annotation is crucial to revealing microorganisms’ complex ecological functions in environmental, ecological and host interactions. Currently, widely used methods can suffer from issues such as inaccurate species-level annotations and time and memory constraints, and as sequencing technology advances and sequencing costs decline, microbial species annotation methods with higher quality classification effectiveness become critical. Therefore, we processed 16S rRNA gene sequences into k-mers sets and then used a trained DNABERT model to generate word vectors. We also design a parallel network structure consisting of deep and shallow modules to extract the semantic and detailed features of 16S rRNA gene sequences. Our method can accurately and rapidly classify bacterial sequences at the SILVA database’s genus and species level. The database is characterized by long sequence length (1500 base pairs), multiple sequences (428,748 reads) and high similarity. The results show that our method has better performance. The technique is nearly 20% more accurate at the species level than the currently popular naive Bayes-dominated QIIME 2 annotation method, and the top-5 results at the species level differ from BLAST methods by <2%. In summary, our approach combines a multi-module deep learning approach that overcomes the limitations of existing methods, providing an efficient and accurate solution for microbial species labeling and more reliable data support for microbiology research and application.

The quality and aroma of strong-flavor Baijiu are mainly dependent on Daqu,pit mud（PM）,and the interaction of both.However,little is known about how their combination patterns affect the microbiome and metabolome of Zaopei,especially the metabolic function of rare taxa.Here,an experiment on industrial size was designed to assess the effects of 6 combinations（3 kinds of Daqu × 2 kinds of PM） on the composition and assembly of different taxa,as well as the flavor profile.The results showed that Zaopei’s microbiota was composed of a few abundant taxa and enormous rare taxa,and rare bacterial and abundant fungal subcommunities were significantly affected by combination patterns.The assembly processes of abundant/rare taxa and bacterial/fungal communities were distinct,and environmental changes mediated the balance between stochastic and deterministic processes in rare bacteria assembly.Furthermore,specific combination patterns improved the flavor quality of Zaopei by enhancing the interspecies interaction,which was closely related to rare taxa,especially rare bacteria.These findings highlighted that rare bacteria might be the keystone in involving community interaction and maintaining metabolic function,which provided a scientific foundation for better understanding and regulating the brewing microbiota from the viewpoint of microbial ecology.

To determine the unique contribution of the bioturbation to the properties of the medium-temperature Daqu, we investigated the differences in microbiota and metabolic composition using the meta-omics approach. Bioturbation increased the amounts of microbial specie and influenced the contribution of the core microbiota to the metabolome. Specifically, inoculated synthetic microbiota (MQB) enhanced the abundance of Bacillus amyloliquefaciens, while Bacillus licheniformis (MQH) increased the abundance of the two Aspergillus species and four species level of lactic acid bacteria. These changes of the microbial profiles significantly increased the potentials of carbohydrate metabolism, amino acid metabolism, and biosynthesis of ester compounds. Consequently, both patterns significantly increased the content of volatile compounds and free amino acids, which were 27.61% and 21.57% (MQB), as well as 15.14% and 17.83% (MQH), respectively. In addition, the contents of lactic acid in MQB and MQH decreased by 65.42% and 42.99%, respectively, closely related to the up- or down-regulation of the expression of their corresponding functional enzyme genes. These results suggested that bioturbation drove the assembly of the core microbiota, rather than becoming critical functional species. Overall, our study provides new insights into the functional role of exogenous isolates in the Daqu microecosystem.

To investigate the distribution of flavor components in Luzhou-flavor base Baijiu from different aged cellars,the aroma components in 18 samples of Luzhou-flavor base Baijiu from three cellars of different ages were identified and quantified by direct injection(DI),liquid-liquid extraction(LLE)or vortex-assisted surfactant-enhanced emulsification liquid-liquid microextraction(VSLLME)combined with gas chromatography(GC)and gas chromatography-mass spectrometry(GC-MS).The differences in flavor among different base Baijiu samples was analyzed by chemometrics methods such as principal component analysis(PCA),partial least squares-discriminant analysis(PLS-DA),and Spearman's correlation coefficient.The results suggested that 151,154 and 159 volatile compounds were identified in base Baijiu from freshly prepared cellar and those aged over 30 and 100 years.In total,148 aroma compounds were common to the three base Baijiu,accounting for 93.1％of the total number of identified compounds.The quantitative analysis of 61 major aroma compounds showed that the concentrations of ethyl caproate,ethyl butyrate,hexanoic acid,butyric acid and acetic acid in base Baijiu from each cellar exceeded 100 mg/L.The concentration of ethyl caproate was the highest,ranging from 1 156.4 to 2 142.2 mg/L.Chemometric results indicated that the flavor similarity of base Baijiu between the new and over-30-year-old cellars was higher when compared with the cellar aged over 100 years.This findings further strengthen the Baijiu industry's conventional knowledge of the influence of cellar age on the flavor of Luzhou-flavor Baijiu.

Pit mud (PM) is fermenting agents in the strong-flavor baijiu (SFB) production. In this paper, the discrepancies in fermentation parameters, microbial community succession patterns and metabolic phenotypes were compared in multidimensional PMs. The results showed that pyruvic acid, succinic acid, S-Acetyldihydrolipoamide-E, glycerol and glyceric acid were the key metabolites responsible for the metabolic differences between the 2-, 30-,100- and 300-year multidimensional PMs, while the butanoic acid, heptyl, heptanoic acid, heptanoic acid ethyl ester, hexanoic acid and octanoic acid were the key differential flavor compounds in the 2-, 30-,100- and 300-year multidimensional PMs. Concurrently, the diversity and abundance of microbial community also exhibited significant differences between the new and old multidimensional PMs, the assembly pattern of bacterial communities changed from deterministic to stochasticity from lower (bottom of the pit and under the huangshui fluid) to upper PM (up the huangshui fluid and top of the pit). Key microorganisms related to the succession process of the lower PM were Clostridium, Methanobacterium, Petrimonas, Lactobacillus, Methanobrevibacter, Bellilinea, Longilinea, Bacillus. In contrast, the upper PM were Caproicibacter, Longilinea, Lactobacillus, Proteinphilum, Methanobrevibacter, Methanobacterium, Methanobacteriaceae, Petrimonas, Bellilinea and Atopobium. Redundancy analysis (RDA) indicated that the key environmental factors regulating the succession of microbial in upper PM were lactic acid, moisture, pH and available phosphorus. In contrast, the lower was lactic acid, acetic acid and ammonia N. Based on these results, heterogeneous mechanisms between new and old multidimensional PMs were explored, providing a theoretical support for improving the quality of new PM.

Saccharomyces cerevisiae can metabolize sugars to produce ethanol and secondary metabolites that contribute to the complex flavor profile of Baijiu, a traditional Chinese distilled beverage. The yeasts that contribute to Baijiu fermentation are mostly adventitious strains that show low ethanol production and stress resistance, which results in lower Baijiu yields and quality. Here, we screened S. cerevisiae strains for ethanol production and stress resistance. The best selected strain, SW4, produced a final ethanol titer of 148.1 g/L, which was 113.8% higher than the initial 69.6 g/L. Additionally, the solid-state fermentation of Baijiu with the addition of S. cerevisiae SW4 (QH) resulted in a significant increase in the relative abundance of Pediococcus and Saccharomyces at days 0-14 compared to the control (KB), which may be the main reason for the alteration of Baijiu flavor. Analysis of flavor compounds revealed that QH increased the concentration of alcohols by 44.82% relative to KB after 7 days of fermentation, as well as increasing the concentration of alcohols and esters by 13.06% and 7.11% after 28 days of fermentation. Measurement of 15 differential flavor compounds revealed that 8 were positively correlated with Saccharomyces (p <= 0.05), all of which are important flavor compounds contributing to the quality to Baijiu. The Baijiu yield of QH was 25.18%, which was 11.47% higher than that of KB. Overall, this study confirms the positive effects of exogenously added S. cerevisiae on the microbial community structure and flavor of Baijiu at different stages of solid-state fermentation, providing novel opportunities for improving the yield and quality of this important traditional beverage.

Extrusion has been proven to be a novel approach for modifying the physicochemical characteristic of Baijiu vinasses (BV) to extract polysaccharides, contributing to the sustainable development of brewing industry. However, the comparison of the bioactivity and bioavailability of extruded (EX) and unextruded (UE) BV polysaccharides was unclear, which impended the determination of the efficacy of extrusion in BV resourcing. In this study, in vitro digestion and fecal fermentation experiments were conducted to investigate the bioavailability, and the results showed that EX exhibited less variation in the monosaccharide composition and molecular weight, while exhibiting a stronger antioxidant capacity compared to UE. Moreover, during fermentation EX increased the abundance of Parasutterella and Lachnospiraceae, while UE promoted the proliferation of Bacteroides, Faecalibacterium, and Dialister, resulting in variation in short-chain fatty acids. These findings indicate that extrusion can enhance the capacity of antioxidants and bioavailability of BV polysaccharides.

Elevating the flavor profile of strong flavors Baijiu has always been a focal point in the industry, and pit mud (PM) serves as a crucial flavor contributor in the fermentation process of the fermented grains (FG). This study investigated the influence of wheat flour and bran (MC and FC) as PM culture enrichment media on the microbiota and metabolites of FG, aiming to inform strategies for improving strong-flavor Baijiu flavor. Results showed that adding PM cultures to FG significantly altered its properties: FC enhanced starch degradation to 51.46% and elevated reducing sugar content to 1.60%, while MC increased acidity to 2.11 mmol/10 g. PM cultures also elevated FG’s ester content, with increases of 0.36 times for MC-FG60d and 1.48 times for FC-FG60d compared to controls, and ethyl hexanoate rising by 0.91 times and 1.39 times, respectively. Microbial analysis revealed that Lactobacillus constituted over 95% of the Abundant bacteria community, with Kroppenstedtia or Bacillus being predominant among Rare bacteria. Abundant fungi included Rasamsonia, Pichia, and Thermomyces, while Rare fungi consisted of Rhizopus and Malassezia. Metagenomic analysis revealed bacterial dominance, primarily consisting of Lactobacillus and Acetilactobacillus (98.80–99.40%), with metabolic function predictions highlighting genes related to metabolism, especially in MC-FG60d. Predictions from PICRUSt2 suggested control over starch, cellulose degradation, and the TCA cycle by fungal subgroups, while Abundant fungi and bacteria regulated ethanol and lactic acid production. This study highlights the importance of PM cultures in the fermentation process of FG, which is significant for brewing high-quality, strong-flavor Baijiu.

Converting distillers’ grains (DGs) into biochar (BC) is sustainable option for waste-recycling, but how different aging times and application rates DG-derived BC (DG-BC) influenced lettuce growth and cadmium (Cd) uptake in soil was unclear. This study explored DG-BC rate- and aging time-dependent effect on lettuce growth and Cd uptake, and effect mechanisms from insights of soil nutrient and Cd bioavailability, lettuce metabolic activity and rhizospheric bacterial composition. Pot experiments involved three DG-BC rates (1

This study aimed to isolate and characterize Seselopsis Tianschanica Schischk Polysaccharide (STSP), a natural functional ingredient, and to develop a compound fermented beverage of nutritional and health combining STSP with highland barley. Firstly, the STSP was isolated and characterized with ultrasound-assisted enzymatic method and chromatography, and analyzed the structural features of polysaccharide STSP-1. Then, a compounded fermented beverage integrating Tibet STSP and highland barley was created, with technology and flavor substances studied. Five kinds of organic acids, 18 kinds of amino acids, and 57 kinds of volatile flavor compounds were determined by GC-MS and HPLC, and quantified significantly enhancing the overall flavor profile of the compound drink-fermented. Moreover, it exhibited higher hydroxyl radical scavenging capacity (IC50 value was 42.68 μL) compared to conventional highland barley drink. This research is expected to provide a theoretical foundation for the utilization of STSP in the functional food industry and other industries.