Search

The fungal community structure and flavor quality of white, yellow and black high-temperature Daqu from company A in Xiangyang, China were analyzed using MiSeq high-throughput sequencing and electronic nose technology. The sequencing results showed no significant differences in the α-diversity or β-diversity of fungal community among different colored Daqu (P > 0.05); the dominant fungal genera belonged to Ascomycota including Thermomyces (36.50%), Thermoascus (27.15%), Saccharomycopsis (9.23%) and Dipodascus (1.19%), and Mucoromycota including Aspergillus (9.36%), Rhizopus (1.44%) and Rhizomucor (1.03%). The electronic nose exhibited high sensor responses to volatile organic sulfides, terpenoids, hydroxides and ethanol and low sensor responses to aromatic substances in high-temperature Daqu; the Mann-Whitney test revealed significantly higher sensor responses to aromatic substances (P < 0.01) and lower sensor responses to the other aroma components (P < 0.05) in yellow than black Daqu. In addition, based on the fungal sequence data from the MG-RAST database for three different colored high-temperature Daqu produced by company B, comparative analysis of the fungal community structure of high-temperature Daqu produced by companies A and B was carried out. It was found that there were highly significant differences (P < 0.01) in the α-diversity and β-diversity of fungal community between Daqu produced by the two companies, and the results of cluster analysis showed that the Mahalanobis distance between the different colored high-temperature Daqu from the same company was closer. Finally, in this study, four strains of S. fibuligera were isolated from high-temperature Daqu produced by company A by traditional pure culture method. In conclusion, there was a significant difference between the fungal communities of high-temperature Daqu produced by companies A and B, which was greater than the difference between different colored high-temperature Daqu produced by the same company.

This study was undertaken to reveal the correlation between the taste quality and bacterial community of Dazhu rice wine. Taste attributes were measured using an electronic tongue, the types and contents of organic acids and amino acids were analyzed, and lactic acid bacteria were isolated and identified from the rice wine. Moreover, analysis and functional prediction of its bacterial community were carried out using MiSeq high-throughput sequencing technology. Finally, the correlation between various taste attributes and bacterial community was calculated. The results showed that Dazhu rice wine varied widely in terms of saltiness, sourness and bitterness. The rice wine contained seven organic acids and 15 amino acids, the predominant organic acids being lactic acid (8.82 mg/g) and acetic acid (6.27 mg/g), and the predominant amino acids being glutamic acid (8.06 mg/g), leucine (4.10 mg/g) and aspartic acid (3.94 mg/g). A total of 14 lactic acid bacteria were isolated by pure culture and identified as five species, namely Limosilactobacillus fermentum (four strains), Pediococcus pentosaceus (four strains), Lacticaseibacillus paracasei (two strains), Lactiplantibacillus plantarum (two strains) and Leuconostoc pseudomesenteroides (two strains). High-throughput sequencing results showed that the average relative contents of Firmicutes and Proteobacteria were greater than 1.0%, with a cumulative content of 96.93%; the relative contents of Lactobacillus, Pediococcus, Weissella, Lactococcus, Leuconostoc and Acinetobacter were greater than 1.0%, with a cumulative content of 89.43%. Correlation analysis showed a significant negative correlation (P < 0.05) between Weissella and taste indicators such as aftertaste A, astringency and bitterness. These findings showed that the major organic acids in Dazhu rice wine were lactic acid and acetic acid, that the major amino acids were glutamic acid, leucine and aspartic acid, and that bacterial community was dominated by lactic acid bacteria such as Lactobacillus, Pediococcus and Weissella. Weissella could have a positive significance on the formation of rice wine quality.

In this paper, the effects on drying time (Y1), the color difference (Y2), unit energy consumption (Y3), polysaccharide content (Y4), rehydration ratio (Y5), and allantoin content (Y6) of yam slices were investigated under different drying temperatures (50–70 °C), slice thicknesses (2–10 mm), and radiation distances (80–160 mm). The optimal drying conditions were determined by applying the BP neural network wolf algorithm (GWO) model based on response surface methodology (RMS). All the above indices were significantly affected by drying conditions (p < 0.05). The drying rate and effective water diffusion coefficient of yam slices accelerated with increasing temperature and decreasing slice thickness and radiation distance. The selection of lower temperature and slice thickness helped reduce the energy consumption and color difference. The polysaccharide content increased and then decreased with drying temperature, slice thickness, and radiation distance, and it was highest at 60 °C, 6 mm, and 120 mm. At 60 °C, lower slice thickness and radiation distance favored the retention of allantoin content. Under the given constraints (minimization of drying time, unit energy consumption, color difference, and maximization of rehydration ratio, polysaccharide content, and allantoin content), BP-GWO was found to have higher coefficients of determination (R2 = 0.9919 to 0.9983) and lower RMSEs (reduced by 61.34% to 80.03%) than RMS. Multi-objective optimization of BP-GWO was carried out to obtain the optimal drying conditions, as follows: temperature 63.57 °C, slice thickness 4.27 mm, radiation distance 91.39 mm, corresponding to the optimal indices, as follows: Y1 = 133.71 min, Y2 = 7.26, Y3 = 8.54 kJ·h·kg−1, Y4 = 20.73 mg/g, Y5 = 2.84 kg/kg, and Y6 = 3.69 μg/g. In the experimental verification of the prediction results, the relative error between the actual and predicted values was less than 5%, proving the model's reliability for other materials in the drying technology process research to provide a reference. [ABSTRACT FROM AUTHOR]

A drying temperature precision control system was studied to provide technical support for developing and further proving the superiority of the variable-temperature drying process. In this study, an improved neural network (INN) proportional–integral–derivative (PID) controller (INN-PID) was designed. The dynamic performance of the PID, neural network PID (NN-PID) and INN-PID controllers was simulated with unit step signals as an input in MATLAB software. A drying temperature precision control system was set up in an air impingement dryer, and the drying temperature control experiment was carried out to verify the performance of the three controllers. Linear variable-temperature (LVT) and constant-temperature drying experiments of cantaloupe slices were carried out based on the system. Moreover, the experimental results were evaluated comprehensively with the brightness (L value), colour difference (ΔE), vitamin C content, chewiness, drying time and energy consumption (EC) as evaluation indexes. The simulation results show that the INN-PID controller outperforms the other two controllers in terms of control accuracy and regulation time. In the drying temperature control experiment at 50 °C–55 °C, the peak time of the INN-PID controller is 237.37 s, the regulation time is 134.91 s and the maximum overshoot is 4.74%. The INN-PID controller can quickly and effectively regulate the temperature of the inner chamber of the air impingement dryer. Compared with constant-temperature drying, LVT is a more effective drying mode as it ensures the quality of the material and reduces the drying time and EC. The drying temperature precision control system based on the INN-PID controller meets the temperature control requirements of the variable-temperature drying process. This system provides practical and effective technical support for the variable-temperature drying process and lays the foundation for further research. The LVT drying experiments of cantaloupe slices also show that variable-temperature drying is a better process than constant-temperature drying and is worthy of further study to be applied in production. [ABSTRACT FROM AUTHOR]