Optimization of Ethanol Extraction Conditions From Sun-Dried Apricot and Prediction of Antioxidant, Phenolic, and Flavonoid Contents and Their Effects on HCT116 Cells Using Artificial Neural Networks.
Journal:
Food science & nutrition
Published Date:
Jul 17, 2025
Abstract
This study aimed to optimize the ethanol extraction conditions of sun-dried apricot ( L.) and evaluate the antioxidant capacity, phenolic, and flavonoid contents of the obtained extracts. Response surface methodology (RSM) was applied to determine the optimal extraction conditions, which were identified as 60°C temperature, 34% ultrasonic power, 46 min sonication time, and a 4 g/mL solid-liquid ratio. Under these conditions, the extract exhibited a total phenolic content (TPC) of 4.20 mg GAE/g, a total flavonoid content (TFC) of 7.09 mg QE/g, a DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging capacity of 1.37 mg TE/g, a ferric reducing antioxidant power (FRAP) value of 9.12 mg TE/g, and a thiobarbituric acid reactive substances (TBARS) level of 1.69 mg MDA/g. The artificial neural network (ANN) model provided highly accurate predictions for these parameters. Additionally, cell culture experiments demonstrated that the extract exerted a dose-dependent cytotoxic effect on HCT116 colon cancer cells, significantly reducing their viability. These findings highlight the potential of sun-dried apricot extracts as natural antioxidants with possible applications in the functional food and pharmaceutical industries.
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