Foods · 2023 · 54 citations · 54 references
AgricultureFood ScienceMicrobiologyFermentation ScienceFood MicrobiologyMicrobial EcologyFermentation MicrobiologyFermented Foods MicrobiologyFood FermentationMetabolic Pathways In FermentationMicrobial AnalysisMicrobial Physiology In FermentationCarbohydrate Fermentation ProfilesFlavor Compound ProfilingFlavor Profile EvaluationMicrobial Ecology Of FermentationMicrobial Ecology Of Fermented FoodsNatural Flavor CompoundsPhysicochemical PropertiesSpontaneous Fermentation
Daqu is a traditional starter for Baijiu fermentation and is produced by spontaneous fermentation of ground and moistened barley or wheat. The quality of Daqu is traditionally evaluated based on physicochemical and subjective sensory parameters without microbiological analysis. Here, we compared the physicochemical characteristics of qualified (QD) and inferior (ID) Daqu, their microbial communities based on plate counting and PacBio SMRT sequencing of rRNA gene libraries, and their impacts on Baijiu fermentation. The results showed that the glucoamylase and α-amylase activities of QD were significantly higher than those of ID. The counts of yeasts and relative abundances of functional microbes, especially the amylolytic bacterium Bacillus licheniformis and fungi Saccharomycopsis fibuligera and Lichtheimia ramosa, were significantly higher in QD than in ID. The laboratory-scale Baijiu fermentation tests showed that the relative abundances of the amylolytic microbes were higher in the QD than the ID fermentation set, resulting in more efficient fermentation, as indicated by more weight loss and higher moisture content in the former. Consequently, more glycerol, acetic acid, ethanol, and other volatile compounds were produced in the QD than in the ID fermentation set. The results suggest that Daqu quality is determined by, and can be evaluated based on, its microbial community.
54
VSEARCH: a versatile open source tool for metagenomics
Torbjørn Rognes, Tomáš Flouri, Ben Nichols et al. · PeerJ · 2016 · 11K citations · Full text
The igraph software package for complex network research
Gábor Csárdi, Tamás Nepusz · Medical Entomology and Zoology · 2006 · 10.4K citations
Evaluation of 16S rRNA gene sequencing for species and strain-level microbiome analysis
Jethro S. Johnson, Daniel Spakowicz, Bo‐Young Hong et al. · Nature Communications · 2019 · 2.3K citations · Full text
Life Sciences, Biology, Microbiology +14