Alcoholic Beverages: Fermentation Technology, Flavor Properties, Analytical Approaches and Bioactive Value

A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Drinks and Liquid Nutrition".

Deadline for manuscript submissions: closed (30 April 2025) | Viewed by 4566

Special Issue Editors


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Guest Editor
School of Food and Health, Beijing Technology and Business University, Beijing 100048, China
Interests: baijiu; flavor; aroma active compound; bioactive compound; byproduct

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Guest Editor
School of Perfume and Aroma Technology, Shanghai Institute of Technology, Shanghai, China
Interests: aroma; flavor; synergistic effect; microcapsules

Special Issue Information

Dear Colleagues,

Alcoholic beverages have held a prominent place in our diet and culture throughout history. They are an integral part of social gatherings, celebrations, and traditional rituals in many parts of the world. From fine wines to craft beers, baijiu and distilled spirits, alcoholic beverages offer a diverse range of flavors, aromas, and experiences.

Not only are alcoholic beverages deeply ingrained in our cultural fabric, but they also serve as a fascinating subject for extensive scientific research. Scientists and researchers are constantly exploring the complex processes involved in the production, fermentation, and maturation of these beverages. Understanding the chemistry, biology, and technology behind alcoholic beverages can lead to improved production methods, enhanced quality control, and a deeper appreciation of their sensory characteristics.

The journal Foods is pleased to announce a Special Issue that is entirely dedicated to the multifaceted aspects of alcoholic beverages. This Special Issue aims to provide a platform for researchers from various disciplines to share their latest findings and insights on the subject. By compiling diverse perspectives and approaches to research, we hope to foster a deeper understanding of the complex world of alcoholic beverages and stimulate further research in this field.

Prof. Dr. Jinyuan Sun
Prof. Dr. Yunwei Niu
Guest Editors

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Keywords

  • the inheritance and innovation of traditional fermentation processes
  • the influence of microbial communities on fermentation
  • sustainable fermentation technology
  • the formation mechanism of regional characteristic flavor
  • flavor stability and storage conditions
  • consumer preference of flavor
  • characterization and understanding of the flavor profiles of various alcoholic drinks
  • advanced analytical methods for detecting and quantifying components in alcoholic beverages
  • the application of multi-omics analysis in alcoholic beverages research
  • the standardization and quality assurance of analytical methods
  • bioactive compounds in alcoholic beverages and their potential health benefits

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Published Papers (3 papers)

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Research

17 pages, 5119 KiB  
Article
Machine-Learning-Assisted Aroma Profile Prediction in Five Different Quality Grades of Nongxiangxing Baijiu Fermented During Summer Using Sensory Evaluation Combined with GC×GC–TOF-MS
by Dongliang Shao, Wei Cheng, Chao Jiang, Tianquan Pan, Na Li, Mengmeng Li, Ruilong Li, Wei Lan and Xianfeng Du
Foods 2025, 14(10), 1714; https://doi.org/10.3390/foods14101714 - 12 May 2025
Viewed by 844
Abstract
Flavor is one of the crucial factors that influences the quality and consumer acceptance of baijiu. In this study, we analyzed the volatile organic compound (VOC) profiles of five different quality grades of Nongxiangxing baijiu (NXB), fermented during the summer of 2024, using [...] Read more.
Flavor is one of the crucial factors that influences the quality and consumer acceptance of baijiu. In this study, we analyzed the volatile organic compound (VOC) profiles of five different quality grades of Nongxiangxing baijiu (NXB), fermented during the summer of 2024, using 2D gas chromatography time-of-flight mass spectrometry (GC×GC–TOF-MS). We employed machine-learning (ML)-based classification and prediction models to evaluate the flavor. For TW, the scores of the sensory evaluation for coordination and overall evaluation were the highest. TW contained the highest concentration of ethyl caproate; we detected 965 VOCs in total, including several pyrazine compounds with potential health benefits. Principal component analysis (PCA) combined with orthogonal partial least squares discriminant analysis (OPLS-DA) enabled us to distinguish different samples, with eight VOCs emerging as primary contributors to the aroma of the samples, possessing variable importance in projection (VIP) values > 1. Furthermore, we tested eight ML models; random forest (RF) demonstrated the best classification performance, effectively discriminating samples based on their VOC profiles. The key VOC contributors that showed quality-grade specificity included 1-butanol, 3-methyl-1-butanol, and ethyl 5-methylhexanoate. The results elucidate the flavor-based features of NXB and provide a valuable reference for discriminating and predicting baijiu flavors. Full article
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17 pages, 3360 KiB  
Article
Baijiu–Peanut Pairing In Vitro and In Vivo: The Decreased but Prolonged Aftertaste of Baijiu Under the Effect of Mouth Coating Formed by Peanut Lipid
by Lu Chen, Jinyuan Sun, Yanyan Zhang, Hehe Li, Dongrui Zhao, Bowen Wang, Xingqian Ye and Baoguo Sun
Foods 2025, 14(3), 423; https://doi.org/10.3390/foods14030423 - 28 Jan 2025
Viewed by 950
Abstract
Baijiu–peanut pairing is a popular food combination, wherein peanuts, particularly their lipid component, possess the potential to influence the flavor of baijiu and consequently modulate its aftertaste. To reveal the role of peanut lipid within this system, headspace experiments and equilibrium constant measurements [...] Read more.
Baijiu–peanut pairing is a popular food combination, wherein peanuts, particularly their lipid component, possess the potential to influence the flavor of baijiu and consequently modulate its aftertaste. To reveal the role of peanut lipid within this system, headspace experiments and equilibrium constant measurements were conducted. It was determined that peanut lipids are capable of inhibiting the release of flavor substances in baijiu, and this inhibitory effect is concentration-dependent. Molecular dynamics simulation results show a strong interaction between peanut lipids and ethanol (E binding = −2.181 kJ/mol), which weakens the binding energy between ethanol and compounds, resulting in 1 + 1 < 2 effect. The Intraoral SPME experiment revealed the retention effect lipid-coating on the aroma release of baijiu. The flavor substances retained in the oral coating can continuously contribute to the aftertaste perception of baijiu. Peanut lipids, leveraging the Marangoni effect of ethanol, play a role in prolonging the aftertaste of baijiu, either through direct or indirect ways. This study provides a scientific basis for understanding the complex flavor experience in the food pairing process. Full article
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19 pages, 21119 KiB  
Article
Machine Learning and Multi-Omics Integration to Reveal Biomarkers and Microbial Community Assembly Differences in Abnormal Stacking Fermentation of Sauce-Flavor Baijiu
by Shuai Li, Yueran Han, Ming Yan, Shuyi Qiu and Jun Lu
Foods 2025, 14(2), 245; https://doi.org/10.3390/foods14020245 - 14 Jan 2025
Cited by 7 | Viewed by 1955
Abstract
Stacking fermentation is critical in sauce-flavor Baijiu production, but winter production often sees abnormal fermentations, like Waistline and Sub-Temp fermentation, affecting yield and quality. This study used three machine learning models (Logistic Regression, KNN, and Random Forest) combined with multi-omics (metagenomics and flavoromics) [...] Read more.
Stacking fermentation is critical in sauce-flavor Baijiu production, but winter production often sees abnormal fermentations, like Waistline and Sub-Temp fermentation, affecting yield and quality. This study used three machine learning models (Logistic Regression, KNN, and Random Forest) combined with multi-omics (metagenomics and flavoromics) to develop a classification model for abnormal fermentation. SHAP analysis identified 13 Sub-Temp Fermentation and 9 Waistline microbial biomarkers, along with 9 Sub-Temp Fermentation and 12 Waistline flavor biomarkers. Komagataeibacter and Gluconacetobacter are key for normal fermentation, while Ligilactobacillus and Lactobacillus are critical in abnormal cases. Excessive acid and ester markers caused unbalanced aromas in abnormal fermentations. Additionally, ecological models reveal the bacterial community assembly in abnormal fermentations was influenced by stochastic factors, while the fungal community assembly was influenced by deterministic factors. RDA analysis shows that moisture significantly drove Sub-Temp fermentation. Differential gene analysis and KEGG pathway enrichment identify metabolic pathways for flavor markers. This study provides a theoretical basis for regulating stacking fermentation and ensuring Baijiu quality. Full article
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