ABSTRACT
Baijiu production has relied on natural inoculated Qu as a starter culture, causing the unstable microbiota of fermentation grains, which resulted in inconsistent product quality across batches. Therefore, revealing the core microbes and constructing a synthetic microbiota during the fermentation process was extremely important for stabilizing product quality. In this study, the succession of the microbial community was analyzed by high-throughput sequencing technology, and ten core microbes of Xiaoqu light-aroma Baijiu were obtained by mathematical statistics, including Acetobacter, Bacillus, Lactobacillus, Weissella, Pichia,Rhizopus, Wickerhamomyces, Issatchenkia, Saccharomyces, and Kazachstania. Model verification showed that the core microbiota significantly affected the composition of non-core microbiota (P < 0.01) and key flavor-producing enzymes (R > 0.8, P < 0.01), thus significantly affecting the flavor of base Baijiu. Simulated fermentation validated that the core microbiota can reproduce the fermentation process and quality of Xiaoqu light-aroma Baijiu. The succession of bacteria was mainly regulated by acidity and ethanol, while the fungi, especially non-Saccharomyces cerevisiae, were mainly regulated by the initial dominant bacteria (Acetobacter, Bacillus, and Weissella). This study will play an important role in the transformation of Xiaoqu light-aroma Baijiu fermentation from natural fermentation to controlled fermentation and the identification of core microbes in other fermented foods.
Subject(s)
Bacteria , Fermentation , Food Microbiology , Microbiota , Bacteria/classification , Bacteria/metabolism , Bacteria/genetics , Bacteria/isolation & purification , Fungi/genetics , Fungi/classification , Fungi/metabolism , Fungi/isolation & purification , Alcoholic Beverages/microbiology , High-Throughput Nucleotide Sequencing , Taste , Flavoring Agents/metabolismABSTRACT
Solid-state distillation is a distinctive process for extracting the baijiu aroma compounds that determine the flavor character of baijiu. In this study, the changes in various chemical properties of the aroma compounds in three classical Jiangxiangxing baijiu fermented grain distillation processes were analyzed. The changes in the aroma compounds in the instantaneous distillates were quantified and correlation analyzes were conducted. The results showed that the effect of the aroma compounds was greater than the differences between the fermented grains. Eleven representative aroma compounds were selected to develop the kinetic models describing two opposing changes. For the regulation of the Jiangxiangxing baijiu aroma compounds, their recovery rates were calculated using a kinetic model. A comprehensive comparison of the recovery rates of the characteristic aroma and other aroma compounds at different cut-off values revealed that the optimum recovery rate of the characteristic aroma of Jiangxiangxing baijiu 2,3,5,6-tetramethylpyrazine was 14.53% at cut-off values of 3.9 and 19.8 min. In this study, representative changes in the aroma compounds and the selection of cut-off values to regulate the baijiu distillation aroma were proposed.
ABSTRACT
Moisture is essential in microbiota succession and flavor formation during baijiu fermentation. However, it remains unknown how moisture content affects microbiota, metabolism, and their relationship. Here, we compared the difference in volatiles, microbiota characteristics, and potential functions with different initial moisture contents (50 %, 55 %, 60 %, 65 %, 70 %). Results showed that the ratio of ethyl acetate to ethyl lactate and total volatile compounds content increased as the moisture content was elevated from 50 % to 70 %. As increasing moisture content, fermentation system microbiota dominated by Lactobacillus was formed more rapidly. Lactobacillus, Dekkera, and Pediococcus were positively correlated with moisture, promoting the production of propanol, acetic acid, butyric acid, and 2-butanol. The complexity and stability of ecological networks enhanced as moisture content increased (R2 = 0.94, P = 0.004). Our study revealed that moisture-drive microbiota was a critical contributor to flavor formation, providing the theoretical basis for moisture control to regulate flavor compounds.