Abstract
The objective of this research was to investigate the efficacy of 10 NDES, including 3 NDES with new formula, to extract procyanidins and anthocyanins from cranberry pomace with the assistance of ultrasounds. The highest amount of procyanidins (32.5 mg/g) was extracted by a tailor designed NDES 2 consisting of choline chloride: betaine hydrochloride: levulinic acid (1:1:2) and 32 mL water/100 mL NDES. This yield was 3.26-fold of that by 75% ethanol. NDES 8 consisting of glucose: lactic acid (1:5) and 20 mL/100 mL water had the highest extraction yield of anthocyanins at 1.58 mg/g, which was 1.79-fold of the yield by 75% ethanol. The response surface methodology model for extraction of procyanidins by NDES 2 under different conditions had R-2 = 0.977, which was comparable to artificial neural networking (R-2 = 0.973). The ANN models for extraction of anthocyanins using NDES 8 under various conditions performed better than RSM model (R-2 = 0.95 for ANN versus 0.88 for RSM). Highest extraction yields predicted by ANN and RSM were close to the experimental yields, suggesting artificial neural networking was an alternative or better approach than RSM for predictive modeling.