Spatial location within the incubation room shapes the microbial succession and metabolic profiles of high-temperature Daqu

This study investigated the spatiotemporal variation of Daqu microbiota and physicochemical properties across spatial positions. Cluster analysis of temperature profiles from 78 monitoring points revealed six distinct patterns. Daqu in the central pile, with the longest ∼60 °C period, primarily formed black_Qu, while those at the top and edges, experiencing lower peak temperatures (∼50 °C), predominantly became white_Qu, with the transitional zones mainly forming yellow_Qu. Black_Qu exhibited the highest acidity, whereas white_Qu showed superior saccharification enzyme activity. Volatile profiling showed that white_Qu, yellow_Qu, and black_Qu were respectively enriched in nitrogenous compounds, alcohols and phenols, as well as acids, aldehydes, and ketones. Microbial community succession shifted from initial mesophilic ( Weissella , Lactobacillus , Leuconostoc , Wickerhamomyces , Candida ) to thermotolerant taxa. At the end of fermentation, black_Qu was dominated by Saccharopolyspora , Kroppenstedtia , and Thermoascus ; yellow_Qu by Kroppenstedtia , Oceanobacillus , and Thermoascus ; white_Qu by Oceanobacillus , Bacillus , and Saccharomycopsis . Mantel tests and linear mixed-effects models identified temperature, moisture, and total acidity as sequential and interactive drivers of microbial succession. Co-occurrence networks showed microbial communities dominated by positive correlations with modular structures, where bacterial networks were consistently more complex than fungal ones. These findings demonstrate that spatial environmental heterogeneity shapes distinct physicochemical and microbial profiles of different Daqu types. • Spatial location shapes thermal niches, driving formation of three Daqu types. • Microbial community succession shifted from mesophilic to thermotolerant taxa. • Temperature, acidity, and moisture sequentially and interactively drive microbial succession. • Microbial networks were cooperative and modular with greater bacterial complexity.