包装与食品机械2025，Vol.43Issue(3)：42-53,12.DOI:10.3969/j.issn.1005-1295.2025.03.005
基于GA-BP神经网络和响应面法优化山黄皮叶黄酮提取工艺及其抗氧化活性分析
Optimization of flavonoid extraction process from clausena anisum-olens leaves using GA-BP neural network and response face method with antioxidant activity analysis
摘要
Abstract
To optimize the ultrasound-assisted extraction process of flavonoids from clausena anisum-olens leaves,analyze flavonoid composition and in vitro antioxidant capacity,response surface methodology(RSM)and genetic algorithm-optimized backpropagation(GA-BP)neural network were employed for modeling and prediction.Flavonoid components were identified via liquid chromatography-mass spectrometry(LC-MS),and antioxidant activity was evaluated through in vitro assays.Results showed that the GA-BP-optimized extraction yield(5.59%)slightly exceeded RSM results under optimal conditions:ultrasonic duration 58 min,temperature 40℃,liquid-to-material ratio 31 mL/g,ethanol volume fraction 55%.Thirteen flavonoids were identified,including rutin,hyperoside,and quercetin.The half-maximal inhibitory concentration DPPH and ABTS+·radical scavenging were 0.64 mg/mL and 0.18 mg/mL,respectively.At 2.5 mg/mL flavonoid concentration,iron ion reduction ability reached 94.81 mmol/mL.This study provides technical support for utilizing clausena anisum-olens leaves.关键词
山黄皮叶/黄酮类化合物/响应面法/GA-BP神经网络/成分分析/体外抗氧化活性Key words
clausena anisum-olens leaves/flavonoids/response surface methodology/GA-BP neural network/composition analysis/in vitro antioxidant activity分类
轻工纺织引用本文复制引用
王润铃,郭德军,张涛,郑树芳..基于GA-BP神经网络和响应面法优化山黄皮叶黄酮提取工艺及其抗氧化活性分析[J].包装与食品机械,2025,43(3):42-53,12.基金项目
广西科技计划项目(桂科AB25069244) （桂科AB25069244）
广西农科院专项(桂农科2021YT159) （桂农科2021YT159）
