Hubei Tulaohan Flavouring and Food Co.

Yichang, China

Hubei Tulaohan Flavouring and Food Co.

Yichang, China

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Li S.,Hubei Engineering University | Hu Y.,Hubei Engineering University | Hong Y.,Hubei Engineering University | Xu L.,Hubei Engineering University | And 5 more authors.
Journal of Food Processing and Preservation | Year: 2016

An artificial neural network (ANN) model was established to predict the hydrolytic capacities of Aspergillus oryzae proteases on soybean protein. The available training data were split in two subsets: training and testing data, which comprised 25 and six groups of proteases, respectively. These data served as the inputs of ANN to predict small peptide content, degree of hydrolysis and free amino nitrogen content. This network included three neurons in the single hidden layer with a low mean squared error. The predicted results were similar to the actual values (R2 > 0.92) and were superior to those of multiple linear regression. Sensitivity analysis revealed that there is a correlation between protease and soy protein hydrolysates. It was also verified that protease and soy protein hydrolysates could serve as inputs and outputs in the ANN. Among the tested proteases, aminopeptidase showed the highest hydrolytic capacity for soybean protein with sensitivity analysis. Practical Applications: The artificial neural network model is a powerful technique to predict the hydrolytic capacities of Aspergillus oryzae proteases for soybean protein. The results of this study could be used to test the amount of yielded hydrolysates of soybean protein under one combination protease, and also explained the mechanism underlying the protease-catalyzed hydrolysis of soybean. © 2015 Wiley Periodicals, Inc.

Chen Y.,Hubei University of Education | Bai Y.,Hubei University of Education | Li D.,Hubei University of Education | Wang C.,Hubei University of Education | And 3 more authors.
World Journal of Microbiology and Biotechnology | Year: 2016

Acetic acid bacteria (AAB) are important microorganisms in the vinegar industry. However, AAB have to tolerate the presence of ethanol and high temperatures, especially in submerged fermentation (SF), which inhibits AAB growth and acid yield. In this study, seven AAB that are tolerant to temperatures above 40 °C and ethanol concentrations above 10 % (v/v) were isolated from Chinese vinegar Pei. All the isolated AAB belong to Acetobacter pasteurianus according to 16S rDNA analysis. Among all AAB, AAB4 produced the highest acid yield under high temperature and ethanol test conditions. At 4 % ethanol and 30–40 °C temperatures, AAB4 maintained an alcohol–acid transform ratio of more than 90.5 %. High alcohol–acid transform ratio was still maintained even at higher temperatures, namely, 87.2, 77.1, 14.5 and 2.9 % at 41, 42, 43 and 44 °C, respectively. At 30 °C and different initial ethanol concentrations (4–10 %), the acid yield by AAB4 increased gradually, although the alcohol–acid transform ratio decreased to some extent. However, 46.5, 8.7 and 0.9 % ratios were retained at ethanol concentrations of 11, 12 and 13 %, respectively. When compared with AS1.41 (an AAB widely used in China) using a 10 L fermentor, AAB4 produced 42.0 g/L acetic acid at 37 °C with 10 % ethanol, whereas AS1.41 almost stopped producing acetic acid. In conclusion, these traits suggest that AAB4 is a valuable strain for vinegar production in SF. © 2015, Springer Science+Business Media Dordrecht.

Xu L.,Hubei University of Education | Li Y.,Hubei University of Education | Xu N.,Hubei University of Education | Hu Y.,Hubei University of Education | And 5 more authors.
Journal of Agricultural and Food Chemistry | Year: 2014

This work demonstrated the possibility of using artificial neural networks to classify soy sauce from China. The aroma profiles of different soy sauce samples were differentiated using headspace solid-phase microextraction. The soy sauce samples were analyzed by gas chromatography-mass spectrometry, and 22 and 15 volatile aroma compounds were selected for sensitivity analysis to classify the samples by fermentation and geographic region, respectively. The 15 selected samples can be classified by fermentation and geographic region with a prediction success rate of 100%. Furans and phenols represented the variables with the greatest contribution in classifying soy sauce samples by fermentation and geographic region, respectively. © 2014 American Chemical Society.

Liu J.-J.,Hubei Engineering University | Hu Y.,Hubei Engineering University | Chen M.,Hubei Engineering University | Chen S.-G.,Hubei Tulaohan Flavouring and Food Co. | And 5 more authors.
Modern Food Science and Technology | Year: 2015

A halophilic aromatic yeast (Zygosaccharomyces rouxii) was added to Aspergillus oryzae and their synergistic effect on the preparation of koji was explored in terms of the metabolic regulation of yeast with enzymatic systems, physicochemical indices, and volatile compounds. Changes in the numbers of the yeast colonies and Aspergillus oryzae spores, the activity of the enzymatic systems, and physicochemical indicators during the preparation of koji were dynamically monitored, while the volatile components of the finished product were analyzed by gas chromatography-mass spectrometry (GC-MS). The results showed that when the amount of yeast added was approximately 1.5×106 yeast/g koji and the inoculum size of Aspergillus oryzae was 0.15% (m/m), the number of Aspergillus oryzae spores did not significantly change and the neutral protease activity was 3100 U/g at 36 h, which was comparable to the results obtained for the control group. However, α-amylase activity decreased by 22% and saccharifying enzyme activity increased by 7% in the yeast-inoculated group, while aminopeptidase and acidic carboxypeptidase activities did not exhibit significant difference compared to the results obtained in the control group. After the preparation of koji was complete, the concentrations of amino nitrogen and reducing sugar were almost the same for the yeast-inoculated and control groups, while the organic acid content of the yeast-inoculated sample was lower than that of control. There were 32 and 23 volatile components identified by GC-MS in the yeast-inoculated and control groups, respectively. Comprehensive analysis showed that inoculation of a halophilic aromatic yeast during the preparation of koji did not show a significant effect on the enzymatic system and growth of Aspergillus oryzae; however, it improved the flavor and quality of the finished koji. ©, 2015, South China University of Technology. All right reserved.

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