Optimization of ultrasonic-assisted extraction of total flavonoids from by a hybrid response surface methodology-artificial neural network-genetic algorithm (RSM-ANN-GA) approach, coupled with an assessment of antioxidant activities.

The objective of this research endeavor is to refine the ultrasonic-assisted extraction technique for total flavonoids from (TFO), utilizing a synergistic approach combining response surface methodology (RSM) and artificial neural network integrated with genetic algorithm (RSM-ANN-GA). The optimized extraction parameters determined through RSM yielded a TFO concentration of 13.538 mg g under the following conditions: an ethanol concentration of 61.95%, a liquid-solid ratio of 41.06 mL g, an ultrasonic power setting of 351.57 W, and an ultrasonic exposure duration of 58.95 minutes. Conversely, the RSM-ANN-GA approach identified an even more refined set of conditions, achieving a TFO concentration of 13.7844 mg g, with an ethanol concentration of 58.93%, a liquid-solid ratio of 41.16 mL g, an ultrasonic power of 350.22 W, and an ultrasonic exposure time of 58.18 minutes. These findings underscore the superior predictive accuracy and enhanced extraction efficiency offered by the RSM-ANN-GA model over the conventional RSM method. Furthermore, the study demonstrated that TFO possesses a potent antioxidant effect, as evidenced by its ability to scavenge DPPH, hydroxyl, and superoxide anion free radicals , highlighting its potential as a valuable source of natural antioxidants.