Search

To investigate the correlation between the microbial community structure and composition and physicochemical indicators as well as the sources of microorganisms in fermented grains during the stacking and pit fermentation processes in the first round of jiang-flavor baijiu production, traditional culture methods and Illumina MiSeq sequencing were used to study the composition and succession of microbial communities in the fermented grains and the brewing environment, and their correlation with physicochemical factors was analyzed. Furthermore, the SourceTracker software was employed to determine the sources and proportions of dominant microorganisms in the fermented grains. The results showed that on the 6th day of stacking fermentation, both the total bacteria and yeast counts reached maximum values of (3.45 ± 0.15) × 106 CFU/g and (40.5 ± 2.50) × 104 CFU/g, respectively. Unclassified_Lactobacillaceae (91.23%–91.77%) and Pichia (32.84%–91.00%) were the absolute dominant bacterial and fungal genera. Unclassified_Lactobacillaceae showed a significant positive correlation with the moisture content and acidity of the fermented grains, and Pichia exhibited a significant positive correlation with the moisture content and reducing sugar content. The microbial source tracing analysis indicated that the dominant microorganisms on the 0th and 3rd day of stacking fermentation primarily originated from the ground (32.44%–57.37%) and production utensils (26.89%–50.74%). From the 6th day of stacking fermentation to 43rd day of pit fermentation, the dominant microorganisms mainly originated from surfaces such as window sills and walls (86.41%–87.31%). Specifically, unclassified_Lactobacillaceae mainly came from the ground (85.79%) across the stacking and pit fermentation processes and from windowsill and wall surfaces (91.96%–94.91%). There were more diverse sources of Pichia (1.32%–87.06%) in the brewing environment. Before the 6th day of stacking fermentation, its major sources were the air inside the workshop and the surface of production utensils, windowsills, and walls. During pit fermentation, its major sources were the inner wall of the pit, accounting for 18.21%–30.79%. This study provides a theoretical basis for elucidating the brewing mechanism of jiang-flavor baijiu.

A nano-immunosensor for the rapid determination of 3-amino-5-methylmorpholino-2-oxazolidinone (AMOZ) in aquatic products was prepared by immobilizing anti-AMOZ antibodies onto a glass carbon electrode modified with a hybrid nanocomposite (Fe3O4@AuNPs/MWCNTs-COOH) consisting of magnetic ferric oxide (Fe3O4), gold nanoparticles (AuNPs), and carboxylated multi-walled carbon nanotubes (MWCNTs-COOH). The microstructure of the prepared nanoparticles of Fe3O4 and Fe3O4@AuNPs was analyzed using ultraviolet-visible (UV-vis) spectroscopy and infrared (IR) spectroscopy, and their microscopic morphology was characterized using scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The electrochemical performance of the prepared immunosensor was studied by cyclic voltammetry, electrochemical impedance spectroscopy, and the experimental conditions were optimized by differential pulse voltammetry using [Fe(CN)6]3-/4- as the probe. The optimized conditions were as follows: V(Fe3O4@AuNPs) to V(MWCNTs-COOH) ratio 1:2, electrolyte solution pH 7.0, antibody concentration 80 μg/mL, incubation temperature 37 ℃, and incubation time 30 minutes. Under these conditions, the current response of the immunosensor showed a good linear relationship with lg C[AMOZ] in the range from 1.0 × 10-10 to 8.0 × 10-7 mol/L, with a detection limit of 2.4 × 10-11 mol/L. The recovery rates of spiked crucian carp samples were between 92.78% and 102.61%, which was basically consistent with the results of high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). Furthermore, the immunosensor method has the advantages of simple pre-treatment and fast detection speed, and can be used for the rapid detection of AMOZ in actual aquatic products.

A prediction model for soybean meal protein content was developed using low-field NMR and near-infrared spectral data fusion for rapid protein content detection during soybean meal production. Firstly, the low-field NMR and near-infrared spectral data were collected from test samples. Secondly, the two collected signals were preprocessed and the Successive Projections Algorithm (SPA) was used to extract the characteristic variables of the low-field NMR and near-infrared spectra. The partial least squares method, BP (Back Propagation) neural network and Sparrow Search Algorithm (SSA) were employed to optimize the BP neural network (SSA-BP). The selected characteristic variables were fused to establish a prediction model for soybean meal protein content. The SSA-BP model, constructed by fusing low-field NMR and near-infrared feature layer data, showed the best performance, with a calibration set determination coefficient of 0.983 0, RMSE of 0.127 3, validation set determination coefficient of 0.956 4, and RMSE of 0.203 9. In summary, this method enables achieve rapid, non-destructive and accurate quantitative detection of soybean meal protein content while verifying, feasibility and effectiveness of low-field NMR and near-infrared data fusion.

Nitrogen-doped carbon materials have been widely used for the constructions of single-atom catalysts, while the effect of different species of doped nitrogen on the catalytic activity of CO2 electroreduction has rarely been investigated. Here we found that pyrrolic-N coordinated Ni2+ catalysts display much higher electrocatalytic CO2-to-CO activity and selectivity than the corresponding pyridinic-N coordinated low valent Ni(0−+2) catalysts, and pyrrolic-N coordinated Ni2 dual-atoms catalyst of Ni2/N-CNTs exhibits the best electrocatalytic performance, with over 90% Faradaic efficiencies in a broad potentials from −0.6 to −1.2 V vs. reversible hydrogen electrode, as well as an outstanding CO specific current of 56.2 A/mgNi and high turnover frequency of 6.2 × 104 h−1, over 7-times higher than those of pyridinic-N coordinated Ni catalysts. Electrochemical results indicate the weak electron-donor nature of pyrrolic-N facilitates the generation of a reduced active site at low overpotential for boosting CO2 electroreduction. Density functional theory calculations reveal that the reaction free energy for the *COOH formation on pyrrolic-N coordinated Ni catalysts are lower than those on pyridinic-N coordinated Ni catalysts, and a H2O-adsorbed Ni2/N-CNTs displays the optimized reaction free energy for both *COOH formation and CO desorption, which derive the best catalytic performance. [ABSTRACT FROM AUTHOR]