Anti-glycated activity of polysaccharides of longan (Dimocarpus longan Lour.) fruit pericarp treated by ultrasonic wave

Ultrasonic wave was used to extract the polysaccharides of longan fruit pericarp (PLFP) in this work. The anti-glycated activity of PLFP was evaluated. Through artificial neural network toolbox of MATLAB software, a mathematical model between ultrasonic conditions and anti-glycated activity was constructed. The R2 and MSE (mean square error) values of the model were calculated to be 0.98 and 0.13, respectively, which suggested a good fitness of the neural network. Response surface plots showed that ultrasonic power, time and temperature had complicated and significant effects on the anti-glycated activity of PLFP. The optimal ultrasonic conditions for obtaining the highest anti-glycated activity were predicted to be 276 W, 24 min and 69 °C. The predicted anti-glycated activity was 60.4%. The experimental determinations under these conditions were not significantly different (P > 0.05) to the predicted value. It indicated the good prediction and optimisation capability of the artificial neural network.