| Summary: | The production of edible and medicinal plants results in significant biomass waste, which can be a rich source of bioactive compounds. This study optimized the extraction of polyphenols from Phellodendron amurense leaf waste using ultrasound-assisted extraction (UAE), with modeling via both response surface methodology (RSM) and artificial neural networks (ANN). ANN exhibited superior predictive accuracy. Under optimal UAE conditions (60 min ultrasonic time, 1:20 g/mL w/v solid-to-liquid ratio, 60 % v/v ethanol concentration, and 190 W ultrasonic power), the highest total polyphenol yield of 28.66 ± 0.07 mg GAE/g DW was achieved. The resulting extracts exhibited strong antioxidant activity in cellular assays. A total of 25 polyphenolic compounds, including luteolin, isorhamnetin, and kaempferol, were identified by liquid chromatography paired with mass spectrometry (LC-MS/MS), and molecular docking predicted their interaction with collagen I (COL I) as a potential antioxidant mechanism. These findings support the value-added utilization of P. amurense leaf waste and provide a foundation for its application in antioxidant nutraceuticals and plant-based pharmaceuticals.
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