Optimization of Ultrasonic-Assisted Extraction Conditions for Bioactive Components and Antioxidant Activity of <i>Poria cocos</i> (Schw.) Wolf by an RSM-ANN-GA Hybrid Approach
Shiqi Chen,
Huixia Zhang,
Liu Yang,
Shuai Zhang,
Haiyang Jiang
Affiliations
Shiqi Chen
Department of Veterinary Pharmacology and Toxicology, College of Veterinary Medicine, China Agricultural University, Beijing Key Laboratory of Detection Technology for Animal−Derived Food Safety, Beijing Laboratory for Food Quality and Safety, Beijing 100193, China
Huixia Zhang
Department of Veterinary Pharmacology and Toxicology, College of Veterinary Medicine, China Agricultural University, Beijing Key Laboratory of Detection Technology for Animal−Derived Food Safety, Beijing Laboratory for Food Quality and Safety, Beijing 100193, China
Liu Yang
Department of Veterinary Pharmacology and Toxicology, College of Veterinary Medicine, China Agricultural University, Beijing Key Laboratory of Detection Technology for Animal−Derived Food Safety, Beijing Laboratory for Food Quality and Safety, Beijing 100193, China
Shuai Zhang
Department of Veterinary Pharmacology and Toxicology, College of Veterinary Medicine, China Agricultural University, Beijing Key Laboratory of Detection Technology for Animal−Derived Food Safety, Beijing Laboratory for Food Quality and Safety, Beijing 100193, China
Haiyang Jiang
Department of Veterinary Pharmacology and Toxicology, College of Veterinary Medicine, China Agricultural University, Beijing Key Laboratory of Detection Technology for Animal−Derived Food Safety, Beijing Laboratory for Food Quality and Safety, Beijing 100193, China
In this study, a response surface methodology and an artificial neural network coupled with a genetic algorithm (RSM-ANN-GA) was used to predict and estimate the optimized ultrasonic-assisted extraction conditions of Poria cocos. The ingredient yield and antioxidant potential were determined with different independent variables of ethanol concentration (X1; 25–75%), extraction time (X2; 30–50 min), and extraction solution volume (mL) (X3; 20–60 mL). The optimal conditions were predicted by the RSM-ANN-GA model to be 55.53% ethanol concentration for 48.64 min in 60.00 mL solvent for four triterpenoid acids, and 40.49% ethanol concentration for 30.25 min in 20.00 mL solvent for antioxidant activity and total polysaccharide and phenolic contents. The evaluation of the two modeling strategies showed that RSM-ANN-GA provided better predictability and greater accuracy than the response surface methodology for ultrasonic-assisted extraction of P. cocos. These findings provided guidance on efficient extraction of P. cocos and a feasible analysis/modeling optimization process for the extraction of natural products.
