Xia Zhu

Bio: Xia Zhu is an academic researcher. The author has contributed to research in topics: Lees. The author has an hindex of 1, co-authored 3 publications receiving 4 citations.

Modeling of Furfural and 5-Hydroxymethylfurfural Content of Fermented Lotus Root: Artificial Neural Networks and a Genetic Algorithm Approach

Abstract: Abstract The aim of this study was to investigate the effect of different pretreatment and reducing sugar content on furfural (F) and 5-hydroxymethylfurfural (HMF) contents of fermented lotus root by vinegar. The lotus root samples were fermented using vinegar for 15 days, at different solution concentrations and temperatures. The processing conditions were considered as inputs of neural network to predict the F and HMF contents of lotus root. Genetic algorithm was applied to optimize the structure and learning parameters of ANN. The developed genetic algorithm-artificial neural network (GA-ANN) which included 23 and 17 neurons in the first and second hidden layers, respectively, gives the lowest mean squared error (MSE). The correlation coefficient of ANN was compared with multiple linear regression-based models. The GA-ANN model was found to be a more accurate prediction method for the F and HMF contents of fermented lotus root than linear regression-based models. In addition, sensitivity analysis and Pearson’s correlation coefficient were also analyzed to find out the relation between input and output variables.

Formation of 5-hydroxymethyl-2-furfural (HMF) and 5-hydroxymethyl-2-furoic acid during roasting of coffee

Abstract: The formation of 5-hydroxymethyl-2-furfural (HMF) and 5-hydroxymethyl-2-furoic acid (HMFA) during roasting of coffee was studied. At 240°C the maximum concentration of HMF occurs after 3 min with a quick degradation up to 10 min when most of the HMF has disappeared again. Similar to 5-hydroxymethyl-furfural, HMFA is formed in coffee but not in a model system consisting of sucrose, alanine with or without chlorogenic acid. It was shown that HMFA is produced from different precursors than HMF namely glyceraldehyde and pyruvate. The comparison of the laboratory scale roasting with industrial roasting showed that 5-hydroxymethyl-furfural decreases with a higher degree of roasting whereas HMFA did not change. In the laboratory scale experiments, the highest concentration of 5-hydroxymethyl-furfural in coffee (909 μg/g) was obtained after 3 min and the maximum concentration of HMFA after 4 min (150 μg/g). Industrially roasted coffee contained up to 350 μg/g 5-hydroxymethyl-furfural and 140 μg/g HMFA.

Analysis of the Hydrolytic Capacities of Aspergillus oryzae Proteases on Soybean Protein Using Artificial Neural Networks

Abstract: 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.

Relationship of Starch Synthesis with It’s Related Enzymes’Activities During Rhizome Development of Lotus(Nelumbo nucifera Gaertn)

Abstract: 【Objective】The objective of this paper is to study the relationship of starch contents with its related key synthease’s activities in lotus rhizome.【 Method 】 Using four lotus cultivars,the activity changes of adenosine diphosphoglucose pyrophosphorylase(ADPGPase),starch synthase(SSase) and starch branching enzyme(Q-enzyme) in rhizome during the development and their relationships with starch synthesis were studied.【Result】The peaks of fructose,glucose and total soluble sugar,sucrose content reached at early,middle,end stage of rhizome development,respectively.Total starch,amylose and amylopectin content in rhizome increased quickly after middle stage,total starch content reached 11.1% to 12.7% in fresh rhizome at end stage,and 70% of total starch was amylopectin.ADPGPase and SSase activities at the same development stage in different cultivar’s rhizome were obviously different,but Q-enzyme activity had little difference.During rhizome development SSase activity peak appeared earlier than ADPGPase and Q-enzyme at early stage,while ADPGPase and Q-enzyme activity peaks appeared at middle stage.ADPGPase activity at middle stage and SSase activity at early stage were very significantly and significantly correlated with total starch content at end stage in rhizome,co-efficients were 0.9830(P 0.01;n=12) and 0.8458(P0.05;n=12),respectively.Q-enzyme activity at middle stage was significantly correlated with amylopectin content at end stage,with co-efficient 0.7690(P 0.05;n=12).【Conclusion】Total starch content in matured lotus rhizome was determined by ADPGPase and SSase activities at middle and early stage;amylopectin content was determined by Q-enzyme activity at middle stage during lotus rhizome development.

Property Assessment of Sponge Cake Added with Egg Replacer

Abstract: Chicken egg which is always used in sponge cake production is likely to deteriorate during storage or transportation. This weakness prevents the wide use of chicken egg in sponge cake making. In order to solve this problem, egg replacer has been developed. In this study, effect of egg replacer on the property of sponge cake was analyzed. The result indicated egg replacer could improve the yield rate and specific volume of sponge cake. However, high content of egg replacer would negatively impact the internal structure and sensory property of sponge cake. Based on the result of this research, optimum content of egg replacer in sponge cake is 3.6 g. In the industrial production of sponge cake, different types of wheat flour and additives would be used. The optimum content of egg replacer may be different from the result of this research. Therefore, in the industrial production, the optimum content of egg replacer should be determined based on experiment.