## 4 Discussion  
Optimizing the fermentation process of food products is challenging because of the complex composition and succession of the microbiota [1; 2; 21]. Unraveling the functionality of the microbiota is fundamental to manipulating the community so as to produce the desired outcome, and this is the theoretical basis of solid-state fermentation mechanisms [22; 40]. Our results contribute to an understanding of the microbial mechanisms during solid-substrate _Baijiu_ fermentation and offer potential guidance for improving _Baijiu_ quality via fermentation. Coupling metagenomics with plate-counting techniques provided a clear overview of the microbial population. Compared with fungi, the bacteria at the late stage of fermentation were dominant. Notably, metagenomic sequencing showed that bacteria represented over 90% of all the microorganisms at the end of fermentation. This was in line with the results of culture-dependent analyses (Figure 1b), which was also in agreement with the results of a previous study [41]. Microbial composition during _Baijiu_ fermentation has been investigated using multiple approaches, however, most previous studies produced taxonomic identification only at the genus level [6; 9; 42; 43]. Over the time of fermentation, the microbial diversity decreased rapidly due to environmental factors, including nutrient limitation, high ethanol concentrations, and low pH values [44], and only _Lactobacillus_ and several yeasts survived until the end of the process. Considering that microbiota drive the fermentation process, functional microorganisms--i.e., metabolically active microorganisms--and their dynamics appear to be more important than the microbial composition [21]. We combined two metabolomic approaches in order to detect metabolites to improve our understanding of the biochemical processes involved in fermentation [45]. The concentration of the majority of metabolites, such as alcohols, esters, acids, amino acids, and phenols, that accumulated in fermented grain increased during the first 15 days, and then remained stable or decreased. Moreover, based on the PCA analysis of metabolites, there was an obvious shift from day 1 to day 7. Subsequently, to reveal the metabolic functions of the microbiota at gene level, functional gene categories were identified and annotated using sequence data. Shotgun metagenomics can provide strong evidence for functional predictions [16; 40]. We found that the abundance of genes associated with metabolism generally increased during the first 15 days, as annotated using different databases. Considering microbial composition dynamics, the most critical changes in both microorganisms and metabolites may be speculated to occur during the first 15 th days. This finding suggests that fermentation time during the solid-state fermentation process of light-flavor _Baijiu_ may be reduced. Based on the observed relationships between microorganisms and metabolites as well as functional gene annotation associated with the metabolic potential of microbial species, it was found that lactic acid bacteria were the predominant bacteria in light-flavor _Baijiu_ fermentation, particularly _Lactobacillus_. Different _Lactobacillus_ species contributed to the fermentation process. _La. plantarum_ provided enzyme-encoding genes for starch degradation, and some _Lactobacillus_ species such as _La. buchneri_ and _La. collinoides_ contributed to the production of \(\beta\)-glucosidase (EC3.2.1.21), which is associated with cellulose degradation and completes hydrolysis by converting cellobiose to glucose [46]. In addition, \(\beta\)-glucosidase can improve the production of some terpen, which enhance floral aroma characteristics [47]. _La. plantarum_ was reported to produce high-yield extracellular \(\alpha\)-amylase for starch degradation, following isolation from Nigerian fermented products [48].