High-temperature Daqu, also called Jiang-flavor Daqu, is the saccharifying and fermenting agent for brewing Jiang-flavor Baijiu. During the spontaneous solid-state fermentation of high-temperature Daqu, variations in temperature and moisture lead to microbial diversity and various metabolites, contributing to the different colors of high-temperature Daqu (customarily referred to as white Daqu, black Daqu, yellow Daqu, and red Daqu in production). We aimed to investigate the differences in microbial communities, physicochemical indices, and potential functions among different high-temperature Daqu with different colors (labeled as QW, QB, QY, and QR) by amplicon sequencing. We found that Kroppenstedtia, Bacillus, and Thermoascus were predominant in all samples; Saccharopolyspora and Thermomyces were predominant in QB and QR; and Unclassfied_O_Eurotiales were predominant in QY. The results on the physicochemical characteristics indicated that compared with other Daqu samples, QW exhibited higher protease activity and lower acidity, whereas QB showed the opposite results. QR had the highest esterification yield, and QY exhibited the highest saccharification but lowest esterification yield. Functional prediction demonstrated that the higher abundances of genes encoding bacterial enzymes of QW and QY were related to the considerably higher abundances of Kroppenstedtia in QW (59%) and QY (87%), respectively. The highest abundance of Thermomyces in QB (80%) contributed to the highest abundance of genes encoding fungal enzymes in QB. This study revealed the microbial and functional dissimilarities of color-based high-temperature starters and helped facilitate the liquor fermentation process.

Food is the foundation of human survival. With the development and progress of society, people increasingly focus on the problems of food quality and safety, which is closely related to human's health. Thus, the whole industrial chain from farmland to dining table need to be strictly controlled. Traditional detection methods are time‐consuming, laborious, and destructive. In recent years, hyperspectral technology has been more and more applied to food safety and quality detection, because the technology can achieve rapid and nondestructive detection of food, and the requirement to experimental condition is low; operability is strong. In this paper, hyperspectral imaging technology was briefly introduced, and its application in agricultural products and food detection in recent years was systematically summarized, and the key points in the research process were deeply discussed. This work lays a solid foundation for the peers to the following in‐depth research and application of this technology.

In this study, a label-free fluorescent probe based on L-cysteine modified copper nanoclusters (L-cys–Cu NCs) is applied to directly detect fluazinam via the inner filter effect. L-Cys–Cu NCs are synthesized through a simple method and show green fluorescence. The as-prepared L-cys–Cu NCs have an optimal emission wavelength of 497 nm under excitation of 365 nm. In the presence of fluazinam, the fluorescence of the Cu NCs is significantly quenched due to the abundant Cu NC affinitive sites recognizing fluazinam through molecular interactions. In addition, the absorption of fluazinam obviously overlaps with the excitation of the Cu NCs. Thus, an effective inner filter effect occurs. Under optimal conditions, the fluorescent probe shows a reliable linear relationship ranging from 0.05 to 25 μM with a correlation coefficient of 0.9953. And the detection limit of this probe is 1.4 nM (S/N = 3). The proposed fluorescent probe is applied to real samples with satisfactory results, indicating promising applications in environmental monitoring.

Lack of moisture can lead to the aging of pit mud, excessive moisture will make it difficult to maintain its shape or even collapse. Therefore, a rapid and nondestructive detection technology for moisture in pit mud using hyperspectral imaging was firstly investigated. Modeling efficiency of various processing was compared in visible (400–1,000 nm) and near‐infrared (900–1,700 nm) regions, and the optimal model was SNV‐SPA‐SVM in near‐infrared spectroscopy; the and RMSEP of model were .9953 and 0.0029, respectively. Furthermore, the distribution map showed that the moisture in the new cellar was generally lower than that of old, and the moisture distribution of the old pit mud was more even. Moreover, the moisture content of different layers in the same cellar increased from top to bottom. This work provides strong technical support for liquor brewing enterprises to effectively implement online monitoring of pit mud changes and open a new era for the application of hyperspectral imaging technology in the field of liquor solid‐state fermentation.