Optimization of extraction and bioactivity detection of celery leaf flavonoids using BP neural network combined with genetic algorithm and response.

ABSTRACT

In the present study, ultrasound-assisted extraction was employed to extract the general flavone from celery leaves using response surface methodology and BP neural network model with a genetic algorithm (GA). The effects of temperature, time, solid-liquid ratio, and ethanol concentration on the extraction results were assessed by Box-Behnken design. Further optimization of the process was performed by GA-BP. Our results showed that the optimal conditions were an ethanol concentration of 70.31%, a temperature of 67.2 °C and an extraction time of 26.6 min. In addition, significant antioxidant activity and in vitro bacteriostasis were observed. We found that the total flavonoids of the celery leaves exerted a strong inhibitory effect on Escherichia coli, Staphylococcus aureus, and Bacillus subtilis. Additionally, considerable DPPH· and ·OH scavenging effects were exerted by flavonoids. Therefore, flavonoids from celery leaves can be considered natural antioxidants and bacterial inhibitors.