Ma Shiyuan, Li Yong, Dong Yi, Zhou Yiyang, Tu Feiyong, Zhang Liqiang, Wu Chongde
College of Biomass Science and Engineering, Sichuan University, Chengdu 610065, China.
National Engineering Research Center of Solid-State Brewing, Luzhou 646000, China.
Int J Food Microbiol. 2025 Feb 2;429:111017. doi: 10.1016/j.ijfoodmicro.2024.111017. Epub 2024 Dec 12.
Daqu is a wheat-based fermentation starter essential for Chinese Baijiu production. The storage of daqu critically influences its quality. However, the assembly mechanisms of microbial communities in daqu during the storage phase and their impact on volatile flavor compounds remain unclear. This study investigated the microbial community assembly process and volatile compound profiles of daqu from three major regions of strong-flavor Baijiu production, Luzhou (LZ), Chengdu (CD), and Deyang (DY), during the storage phase. Fifteen biomarkers were identified across the regions using the random forest algorithm. Co-occurrence network analysis indicated that the LZ network was the most stable, while the CD network had the lowest complexity and stability, revealing 14 keystone species. Additionally, 42 differential volatile flavor compounds were identified. The analysis of microbial assembly mechanisms revealed that both stochastic and deterministic processes influenced the assembly of microbial communities in daqu during storage, as indicated by the modified stochasticity ratio (MST) and the neutral community model. Stochastic processes predominantly shaped the community of samples DY, while deterministic processes were more influential in the communities of samples LZ and CD. Notably, the important taxa (dominant microorganisms, keystone species, and biomarkers) were mainly influenced by deterministic processes, including temperature, dewpoint temperature, and surface air pressure, showing significant correlations with volatile flavor compounds. In conclusion, these findings highlight the effects of regional differences and storage processes on microbial community assembly and volatile flavor compounds in daqu, offering insights to regulate the daqu storage process and thereby optimize production.
大曲是中国白酒生产中必不可少的以小麦为原料的发酵剂。大曲的储存对其质量有至关重要的影响。然而，大曲在储存阶段微生物群落的组装机制及其对挥发性风味化合物的影响仍不清楚。本研究调查了浓香型白酒生产三大主要产区泸州（LZ）、成都（CD）和德阳（DY）的大曲在储存阶段的微生物群落组装过程和挥发性化合物谱。使用随机森林算法在各产区鉴定出15种生物标志物。共现网络分析表明，LZ网络最稳定，而CD网络的复杂性和稳定性最低，鉴定出14个关键物种。此外，还鉴定出42种差异挥发性风味化合物。微生物组装机制分析表明，修正随机比率（MST）和中性群落模型表明，随机过程和确定性过程都影响了大曲在储存期间微生物群落的组装。随机过程主要塑造了DY样品的群落，而确定性过程对LZ和CD样品的群落影响更大。值得注意的是，重要分类群（优势微生物、关键物种和生物标志物）主要受确定性过程影响，包括温度、露点温度和地面气压，与挥发性风味化合物呈现显著相关性。总之，这些发现突出了区域差异和储存过程对大曲中微生物群落组装和挥发性风味化合物的影响，为调控大曲储存过程从而优化生产提供了见解。
