Multivariate Optimization of Ultrasound-Assisted Extraction of Phenolic Compounds from Apples

Borkh.) are among the most widely consumed fruits worldwide and represent a significant dietary source of phenolic compounds. Efficient extraction is a critical step for the isolation, characterization, and quantification of phenolic compounds. The extraction yield and composition are strongly influenced by multiple parameters, including solvent type and concentration, temperature, extraction time, solid-to-liquid ratio, and the presence and concentration of acidifying agents. This study aimed to optimize an ultrasound-assisted extraction (UAE) procedure using response surface methodology (RSM) to evaluate the effects of extraction temperature, solvent-to-sample ratio (SSR) and citric acid concentration on total phenolic content (TPC) and total flavonoid content (TFC). Statistical analysis showed that SSR and temperature were the most influential factors affecting phenolic recovery, while citric acid concentration exerted a secondary, interaction-driven effect. Optimization using a desirability function identified the operating conditions that maximized phenolic and flavonoid recovery: 55 °C, 10 mL/g SSR and 0.2% citric acid concentration. Model predictions were validated experimentally, confirming the reliability of the approach for TPC and TFC. Chlorogenic acid and flavan-3-ols, including monomers, such as catechin and epicatechin, and polymers such as procyanidins, were identified. Overall, the proposed approach provides a statistically supported framework for phenolic compound analysis in apples.