中国食品添加剂2026，Vol.37Issue(1)：23-32,10.DOI:10.19804/j.issn1006-2513.2026.1.004
效应面法结合BP神经网络模型优化五冬果茶提取工艺
Optimization of Wudong fruit tea extraction process using RSM and BP neural network model approach
摘要
Abstract
To optimize the extraction process of Wudong fruit tea,based on preliminary screening,the water-to-material ration and extraction time were selected as key independent variables,with dry extract yield,psoralen content,and sensory evaluation serving as dependent evaluation indices.A comparative analysis was conducted on the applicability of three weighting method(AHP,CRITIC,and AHP-CRITIC hybrid),the AHP-CRITIC hybrid weighting method was ultimately selected to determine the index weights.A star-point design combined with response surface methodology(RSM)was employed for optimization of the extraction process,followed by a backpropagation(BP)neural network model to predict and validate the optimal conditions.The optimal extraction parameters were determined as follows:the prescribed medicinal materials was extracted with boiled water at 13-fold amount twice,and 60 minutes of extraction time(per cycle,for two cycles),followed by filtration.The integration of the star-point design-RSM and BP neural network demonstrated robust stability and reproducibility in optimizing the extraction of Wudong fruit tea,providing a scientific foundation for the optimized method in future research.关键词
五冬果茶/提取工艺优化/星点设计-效应面法/AHP-CRITIC混合加权法/BP神经网络Key words
Wudong fruit tea/extraction process optimization/star-point design-response surface methodology/AHP-CRITIC hybrid weighting method/BP neural network分类
轻工纺织引用本文复制引用
曾大洋,罗渝欢,李业航,覃柳娇,王一垚,范丽丽,黄俊善,陈卫卫..效应面法结合BP神经网络模型优化五冬果茶提取工艺[J].中国食品添加剂,2026,37(1):23-32,10.基金项目
广西研究生教育创新计划项目 （）
2023年广西学位与研究生教育改革课题(编号JGY2023179) （编号JGY2023179）
