YANG Yang, NIU Mansi, DAI Qiulian, et al. A Comparative Study on Physicochemical Indices and Fungal Community Composition of Medium-temperature and High-temperature Daqus from the Same Region[J]. Science and Technology of Food Industry, 2023, 44(13): 150−159. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2022090313.
Citation: YANG Yang, NIU Mansi, DAI Qiulian, et al. A Comparative Study on Physicochemical Indices and Fungal Community Composition of Medium-temperature and High-temperature Daqus from the Same Region[J]. Science and Technology of Food Industry, 2023, 44(13): 150−159. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2022090313.

A Comparative Study on Physicochemical Indices and Fungal Community Composition of Medium-temperature and High-temperature Daqus from the Same Region

  • In order to reduce the interference of seasonal, geographical and other factors and explore the effect of different peak-temperature control strategies on the fungal community of Daqu, this study mainly applied the high-throughput sequencing technology to analyze and compare the fungal community in medium-temperature and high-temperature Daqus collected from the same core production region of high-quality Baijiu. The correlation between the fungal community in Daqu and the main physicochemical indices was also evaluated by combining redundancy analysis. The results showed that the overall population of fungi (characterized by the copy numbers of ITS1 region of rDNA) in high-temperature Daqu was smaller than that in medium-temperature Daqu, but the richness, diversity, and evenness of overall fungal community in the former were higher than that in the latter. Thermoascus, Pichia, Aspergillus and Rhizopus accounted for a higher proportion in medium-temperature Daqu, with Thermoascus aurantiacus as the absolute advantage. Thermomyces, Rasamsonia, Monascus, and Byssochlamys accounted for a higher proportion in high-temperature Daqu, with Thermomyces lanuginosus as the absolute advantage. Based on the random forest prediction model, the first ten key ASVs that could best explain the differences between the two Daqu communities belonged respectively to three major groups including Thermoascus crustaceus (for 5 ASVs), Thermomyces spp. (for 4 ASVs), and Thermoascus aurantiacus (for 1 ASV). The results of redundancy analysis showed that Aspergillus, Rasamsonia and Hyphopichia in two types of Daqu had a positive correlation with saccharifying power, Pichia had a strong positive correlation with acidity, and Thermoascus had a strong positive correlation with moisture. This study further clarified the diversity of fungal community and biomarkers in Daqus with different peak-temperatures, explored the correlation between the fungal community in Daqu and the main physicochemical indices, and provided a reference for the optimization of Daqu making process and the screening of functional strains.
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