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.
Optimization and antioxidant evaluation of clean and efficient recovery of polyphenols from Phellodendron amurense waste leaves via ultrasound-assisted extraction.
通过超声辅助提取法优化黄柏废弃叶片中多酚的清洁高效回收及其抗氧化性能评价
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作者:Huo Huimin, Bao Haiying, Li Jingnan, Li Hongwei
| 期刊: | Ultrasonics Sonochemistry | 影响因子: | 9.700 |
| 时间: | 2025 | 起止号: | 2025 Sep;120:107512 |
| doi: | 10.1016/j.ultsonch.2025.107512 | 研究方向: | 其它 |
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