Extraction of pectin from watermelon rinds using sequential ultrasound-microwave technique: Optimization using RSM and ANN modeling and characterization.

This study aimed to optimize pectin extraction from watermelon (Citrullus lanatus) rind using sequential ultrasound-microwave assisted extraction (UMAE) with artificial neural network (ANN) and response surface methodology (RSM). The effects of pH, sonication time, microwave power, and irradiation time on pectin yield were evaluated. The ANN model showed higher precision in predicting yield compared to the RSM model.