Yong Hu

Bio: Yong Hu is an academic researcher from Hubei University of Technology. The author has contributed to research in topics: Fermentation & Aspergillus oryzae. The author has an hindex of 7, co-authored 10 publications receiving 103 citations.

Effect of a halophilic aromatic yeast together with Aspergillus oryzae in koji making on the volatile compounds and quality of soy sauce moromi

Abstract: Summary Koji making is an essential step in the production of high-quality soy sauce. In this study, we inoculated koji with a halophilic aromatic yeast (Zygosaccharomyces rouxii) and Aspergillus oryzae and investigated the effects on the volatile compounds and quality of soy sauce moromi. Our results suggest that the optimal yeast inoculation was approximately 1.5 × 106 yeast per gram of koji, and excessive yeast greatly decreased A. oryzae enzyme activity. In comparison with the control group, there were no significant changes in the concentrations of amino nitrogen, total titratable acids, total soluble nitrogen and reducing sugar by extending the fermentation time during the first fermentation month, whereas the concentration of glutamate in the yeast-inoculated sample increased by 46.16% and the arginine concentration decreased by 61.07%. After the second fermentation month, 17, 38 and 38 volatile components were identified by GC–MS in C1, C2 and C5, respectively. Moreover, a large number of volatile components, such as 2-Methoxy-4-vinylphenol, ethyl acetate and 1-Octen-3-ol were found in C2 and C5. And the total contents of volatile compounds in C2 were obviously higher than C5. This work furthers our understanding of the traditional multistrain koji making and provides a new method for enhancing the quality and flavour of soy sauce.

Screening and characterization of ethanol-tolerant and thermotolerant acetic acid bacteria from Chinese vinegar Pei

Abstract: 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.

Autolysis of Aspergillus oryzae Mycelium and Effect on Volatile Flavor Compounds of Soy Sauce.

Abstract: The autolyzed mycelia of Aspergillus oryzae are rich in proteins, nucleic acids, sugar, and other biomacromolecules, and are one of the main contributors to the flavor profile of commercially important fermented goods, including soy sauce and miso. We induced autolysis of the mycelia of A. oryzae over 1 to 10 d, and found that the maximum dissolved amounts of total protein and nucleic acid ratio accounted for 28.63% and 88.93%, respectively. The organic acid content, such as citric acid, tartaric acid, succinic acid, lactic acid, and acetic acid, initially increased and then decreased as autolysis progressed, corresponding to changes in pH levels. The main characteristic flavor compounds in soy sauce, namely, ethanol, 2-phenylethanol, and 2-methoxy-4-vinylphenol, were all detected in the autolysate. Subsequently, we tested the effect of adding mycelia of A. oryzae during the fermentation process of soy sauce for 60 d, and found that addition of 1.2‰ A. oryzae mycelia provided the richest flavor. Overall, our findings suggest that compounds found in the autolysate of A. oryzae may promote the flavor compounds of soy sauce, such as alcohols, aldehydes, phenols, and esters.

Soy sauce classification by geographic region and fermentation based on artificial neural network and genetic algorithm.

Abstract: 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.

Comparative analysis of protective effects of curcumin, curcumin-β-cyclodextrin nanoparticle and nanoliposomal curcumin on unsymmetrical dimethyl hydrazine poisoning in mice.

Abstract: The aim of this study was to compare the protective effects of curcumin, curcumin-β-cyclodextrin nanoparticle curcumin (BCD-CUR) and nanoliposomal curcumin (NLC) on unsymmetrical dimethylhydrazine ...

Acetic Acid Bacteria in the Food Industry: Systematics, Characteristics and Applications.

Abstract: The group of Gram-negative bacteria capable of oxidising ethanol to acetic acid is called acetic acid bacteria (AAB). They are widespread in nature and play an important role in the production of food and beverages, such as vinegar and kombucha. The ability to oxidise ethanol to acetic acid also allows the unwanted growth of AAB in other fermented beverages, such as wine, cider, beer and functional and soft beverages, causing an undesirable sour taste. These bacteria are also used in the production of other metabolic products, for example, gluconic acid, l-sorbose and bacterial cellulose, with potential applications in the food and biomedical industries. The classification of AAB into distinct genera has undergone several modifications over the last years, based on morphological, physiological and genetic characteristics. Therefore, this review focuses on the history of taxonomy, biochemical aspects and methods of isolation, identification and quantification of AAB, mainly related to those with important biotechnological applications.

Design of experiments and regression modelling in food flavour and sensory analysis: A review

Abstract: Background Food sensory science and flavour analysis are key processes in new product development, and is essential in understanding consumers by bridging the gap between product characteristics and consumer perception and acceptance. Scope and approach This article provides a critical review of computer-based approaches to flavour and sensory analysis, including optimal design approaches to sensory experimental designs, and incorporation of nonlinear modelling methods such as artificial neural network into the analysis of results. The advantages and disadvantages of these methods, as well as their statistical background will be discussed. The incorporation of these statistical and mathematical methods into existing analytical processes is briefly covered, along with an overview of available computer software packages. Key findings and conclusions Food flavour and sensory analysis is an information gathering process, and can be divided into two main stages: (1) the design of the experiment; (2) analyses and interpretation of results. The choice of an analytical procedure in sensory and flavour science is crucial in obtaining information correlating food products and consumers. Traditionally, sensory analysis is based on classical experimental designs and linear multivariate analysis techniques. Computer algorithm-based methods such as optimal designs in the design of experiments, and artificial neural network as a non-linear regression method may be used in conjunction with current methods, or adopted to overcome potential shortfalls of existing methods.