Introduction: Natural deep eutectic solvents (NaDESs) are green and effective solvents that are used to extract 3 flavonoids from Yangyin Yiqi Huoxue prescription, a traditional Chinese prescription.
Methods: A total of 6 types of NaDESs were systematically screened and evaluated for the total extraction yield of puerarin, calycosin, and formononetin by high-performance liquid chromatography. Then, a 4-factor-three-level experimental scheme designed by the Box-Benhnken Design was applied on the basis of a single experiment to determine the extraction yield and the antioxidant property. Finally, the extraction process was optimized through response surface methodology (RSM) and the genetic neural network (GNN), respectively.
Results: The use of betaine-lactic acid as an extractant displayed significant advantages in the screening process. The optimum extraction parameters provided by GNN were as follows: water content 25% (v/v), liquid to material ratio 190 mg/ml, extraction time 37 min, and extraction temperature 63 °C. Under this condition, the average experimental comprehensive evaluation values of the extraction yield and antioxidant properties were 3.12 mg/g and 86.27%, and the relative deviations to the predicted values were 0.30% and 1.44%, respectively. In addition, the experimental results of GNN were better than those of RSM (p < 0.01).
Conclusions: We found the application of GNN to be effective and credible for bi-objective optimization of extraction yields and antioxidant activity in this study. Moreover, our results provide a reference and a theoretical basis for experimental and future industrial extraction for multi-objective situations.
Keywords: Genetic neural network; Natural deep eutectic solvents; Response surface methodology; Yangyin Yiqi Huoxue prescription; bi-objective optimization.
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