Analysis of the Forecasting Model and Optimization route to Extract Syringin From Branches of Syringa reticulata
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Abstract:
The ultrasonic process to extract syringin from the branches of Syringa reticulata was optimized using a central composite design and response surface methodology. With the ethanol volume fraction, ultrasonic extraction time, and solvent ratio as the independent variables and the extraction rate of syringin as the dependent variable, multiple linear regression analysis and binomial fitting were performed with the independent variables. Ridge analysis and response surface methodology were used to optimize the extraction process, and predictive analysis was performed. The analysis indicated that the optimum conditions to extract syringin were as follows: 17.03-fold amount of 54.64% ethanol, and ultrasonic extraction for three times. Each extraction was carried out for 85.23 min with an ultrasonic power of 80 W at 30 ℃. The deviation between the observed verification results obtained under optimal conditions and the values predicted by the model was 1.26%, and the correlation coefficient of the binomial fitting complex model was 0.9047. The results showed that the quadratic polynomial model could accurately describe the relationships between the extraction rate of syringin and the influencing factors and had a high reliability. Moreover, these findings demonstrated that the extraction process optimized by central composite design and response surface methodology was simple and stable for extracting syringin from the branches of S. reticulata, with high precision. Thus, this method can be used for actual production.
