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The growing production of strawberry-based foods generates large quantities of pomace, a phenolic-rich by-product with high valorization potential. This study aimed to optimize ultrasound-assisted extraction (UAE) of strawberry pomace and to evaluate the bioactivity of the resulting extracts. The greenness assessment using the AGREEprep metric yielded a score of 0.68/1, confirming the environmental friendliness of the process. Under the optimized UAE conditions (20 min, 50 °C, solid-to-liquid ratio 1:20 g/mL), the extract exhibited the highest total phenolic (16.49 mg GAE/g) and flavonoid contents (2.10 mg RE/g). The optimized extract showed strong antioxidant activity, with DPPH, ABTS, CUPRAC, and FRAP values of 32.70, 46.76, 57.29, and 38.90 mg TE/g, respectively. Enzyme inhibition was particularly pronounced against tyrosinase (55.45 mg KAE/g), while moderate inhibition of acetylcholinesterase and butyrylcholinesterase was also observed. Artificial neural network (ANN) modeling demonstrated excellent predictive performance (R2 > 0.99) and enabled effective optimization of extraction parameters. These findings confirm UAE as an efficient and sustainable approach for strawberry pomace valorization and highlight ANN-based optimization as a robust tool for developing multifunctional bioactive extracts for food, nutraceutical, and pharmaceutical applications.
Terzić et al. (Tue,) studied this question.