Optimization of extraction process of Astragali radix-Paeoniae radix alba by comparing BBD-RSM and SA-BPNN and antioxidant activity

Abstract

The Box-Behnken design-response surface methodology (BBD-RSM) and Back-propagation neural network prediction model optimized by Simulated annealing (SA-BPNN) were used to optimize the extraction process of Astragali radix-Paeoniae radix alba by the green natural deep eutectic solvent (NADES), and the antioxidant activity of them was discussed. The best NADES for extracting Astragali radix-Paeoniae radix alba need to be screened out. The comprehensive evaluation value of the extraction yield was used as the index. The BBD-RSM and SA-BPNN were established for prediction and optimization. The antioxidant activity of Astragali radix-Paeoniae radix alba in vitro and in vivo was studied by detecting 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging rate and ferric reducing antioxidant power (FRAP) and the expression levels of SOD, MDA and GSH-Px in rat plasma. The results showed that the best NADES formula screened was Betaine-Urea (Bet-Ur). Compared with the BBD-RSM, the SA-BPNN had a higher degree of fitting, the comprehensive evaluation value was higher, and the error between tested and predicted value was smaller, which was more suitable as a prediction model for the extraction yield of Astragali radix-Paeoniae radix alba. Through the determination of antioxidant kits and oxidative factors, the results showed that Astragali radix-Paeoniae radix alba had antioxidant activity in vitro and in vivo. The study on the extraction process optimization and antioxidant activity of Astragali radix-Paeoniae radix alba were expected to provide a theoretical basis for its effective utilization.