Technologies For Lactosucrose Synthesized By β-fructofuranoside

Lactosucrose(O-β-D-galactopyranosyl-(1→2)-β-D-fructofuranoside) is a kind of functional oligosaccharide. It has a range of physiological functions, such as low-calorie, indigestible, promotion the proliferation of bifidobacteria and inhibition pathogenic bacterium, non-cariogenicity, regulation intestinal function, decreasing blood sugar, blood lipid and cholesterol, and activation the absorption of mineral. So, lactosucrose has a huge developing space and very bright developing prospects. The study on lactosucrose has just started internally and its industrialization has never been reported in China because of the problem of enzyme activity and purification. This paper mainly focuses on research of synthetic process of lactosucrose byβ-fructofuranoside, and decolorization of lactosucrose and its purification were also investigated. The main contents and conclusions of this paper are induced as follows:1. To obtain the optimum parameters of lactosucrose synthesized byβ-fructofuranoside. Method:Lactosucrose was prepared from lactose as an acceptor and sucrose as a fructosyl donor by a fructose-transferring enzyme.β-fructofuranoside derived from Arthrobacter sp.10138. The process was optimized by a Box-Behnken design and response surface methodology. Results:Optimum conditions for the lactosucrose production were reaction time 22.77h, pH 7.0, reaction temperature 35℃, substrate concentration 20%, the ratio of solution volume of substrate:β-fructofuranoside 1:1(v/v). Under these conditions, the real reaction yield was 22.70%. Conclusion:The work proved that Box-Behnken design and response surface methodology could find optimal parameters for lactosucrose synthesized byβ-fructofuranoside and the model was reliable.2. To obtain the optimum parameters of decoloration of lactosucrose solution by granular charcoal. Method:Artificial neural network (ANN) and genetic algorithm (GA) were used to optimize the decoloration and lactosucrose recovery in solution with granular charcoal. Experimental data of the uniform design (UD) was used to build artificial neural network model. Three input variables (dosage of charcoal, time, and temperature) were adopted in constructing the back propagation neural networks (BPNN) model. Output variables were decoloration rate and lactosucrose recovery rate. GA was used to optimize the input space of the ANN model to find the Pareto-optimal set. Results:The best parameters were the dosage of charcoal varied from 2.1894 to 2.1897%, time from 64.05 to 64.06 min, and temperature from 74.22 to 78.90℃. Confirmative studies results showed that decoloration rate was 94.85% and lactosucrose recovery rate was 97.23%, and the relative error of network predicted values and actual measured values were 1.51% and 0.12%. Conclusion:The work proved that artificial neural network (ANN) and genetic algorithm (GA) could find the Pareto-optimal set of decoloration of lactosucrose solution by granular charcoal and the model was reliable.3. The simple purification of lactosucrose solution. Method:The simple purification of lactosucrose solution using the crystallization of lactose and cation exchange chromatography. Results:The optimum condition of purification was shown as following:Lactosucrose solution was concentrated to 25%, and placed in a refrigerator at 4℃for 2 days after adding crystal seeds, then centrifuged 20min at 4500r/min; And then the supernatant was purified by cation exchange chromatography. The experiments date showed that, when 5mL lactosucrose was used, the optimal purification result could be achieved on the resin column 5m with eluting rate 2mL/min at room temperature. Conclusion:The content of lactosucrose would be increased from 18.26% to 41.62% after the simple purification.4. A method was established for the detection of lactosucrose in the process of industrialization production by TLC-henol sulfuric acid method. Method:The developing agent was the mixture of normal butanol, acetic acid, water (8:3:1). The chromogenic agent was made of aminobenzene-diphenylamine-phosphoric acid and the sample amount was 5ul. The content of lactosucrose was analyzed by phenol-sulfuric acid method after chromogenic reaction. Results:The different compositions of lactosucrose from monosaccharide to trisaccharide could be separated by thin layer chromatography, and separated fructose and glucose from lactosucrose for the first time. The content of lactosucrose could be analyzed by phenol-sulfuric acid method. The linear relationship was in the rang of 10.8-39.6mg/mL(R2=0.9939), RSD of precision 1.51%, the average recovery 97.28% and RSD 3.99%. Conclusion:The detection of raffinose in food or oligosaccharide could be performed by TLC and phenol-sulfuric acid method. Comparing with HPLC method, the relative error was 3.07%. And this method is suitable for detection of lactosucrose in the process of industrial production.