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主成分因子加权结合Box-Behnken响应面法优化栀子微波预处理工艺研究

Optimization of Microwave Pretreatment Processing Technology for Gardenia Jasminoides by Principal Component Analysis and Box-Behnken Response Surface Methodology
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摘要 目的:优化栀子微波预处理工艺。方法:以微波功率、微波时间、药材处理量为影响因素,通过Box-Behnken响应面设计结合主成分因子法,将多酚氧化酶(PPO)活性、过氧化物酶(POD)活性以及褐变指数(BI)计算权重得到灭酶抑褐综合得分,结合栀子指标性成分栀子苷含量为双评价指标,优化栀子微波预处理工艺。结果:对响应面试验给出的两个方案的进行验证,得到的最佳工艺结果为微波功率700 W,微波时间114 s,药材处理量225 g,灭酶抑褐综合得分和成分含量的RSD为别1.166%和为1.035%。结论:优化后的栀子微波预处理工艺有较好的稳定性和重复性,最大程度保证有效成分的含量,为栀子的产地加工技术升级提供参考。 Objective:To optimize the microwave pretreatment of Gardenia jasminoides.Methods:The weights of polyphenol oxidase(PPO)activity,peroxidase(POD)activity and browning value(BI)were calculated by principal component analysis to obtain the score of enzyme inactivation and brown inhibition,the score and the content of geniposide were used as evaluation indexes in the Box-Behnken response surface design method,with the microwave power、microwave time and medicines mass as facters to optimize the process.Results:Through the verification of the two schemes obtained from the response surface,the optimum process results were as follows:microwave power of 700 W,microwave time of 114 s and medicines mass of 225 g.The RSD of EIBI and the content of gardenoside were 1.166%and 1.035%in parallel with five batches of samples.Conclusion:The optimum process is stability and repeatability,which can ensure the content of active ingredients to the greatest extent,and can provide reference for the selection of processing methods in the producing area.
作者 黄潇 刘婧 陈瑶 付小梅 阚瑞 钟瑞 毛喜凤 郑宇枫 HUANG Xiao;LIU Jing;CHEN Yao;FU Xiao-mei;KAN Rui;ZHONG Rui;MAO Xi-feng;ZHENG Yu-feng(Jiangxi University of Chinese Medicine,Nanchang 330004,China)
机构地区 江西中医药大学
出处 《江西中医药大学学报》 2022年第4期72-77,85,共7页 Journal of Jiangxi University of Chinese Medicine
基金 国家自然科学基金项目(82060710) 江西省自然科学基金项目(20202BABL206153) 全国中药特色技术传承人才项目(T20184828005) 江西省教育厅科学技术研究项目(GJJ201229,GJJ190678,GJJ180684) 江西省卫生健康委中医药科研项目(2018A316,2018B132)。
关键词 栀子 微波 主成分因子分析法 响应面 Gardenia Microwave Principal Component Analysis Response Surface
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