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基于化学模式识别结合灰色关联度法的鲜地黄药材质量评价
引用本文:徐杰,姚晓璇,黄梦婷,黄瑶,潘玲,张正.基于化学模式识别结合灰色关联度法的鲜地黄药材质量评价[J].中国现代中药,2024,26(1):18-28.
作者姓名:徐杰  姚晓璇  黄梦婷  黄瑶  潘玲  张正
作者单位:1.广东一方制药有限公司,广东 佛山 528244;2.广东省中药配方颗粒企业重点实验室,广东 佛山 528244
基金项目:广东省省级科技计划项目(2018B030323004)
摘    要:目的:构建基于化学模式识别和灰色关联度法的鲜地黄药材多指标综合评价模型,为鲜地黄药材整体质量评价提供参考。方法:收集不同产地的32批鲜地黄药材样品,测定各批样品中总灰分,酸不溶性灰分,浸出物,梓醇、地黄苷D、铅、镉、砷、汞、铜含量与指纹图谱,采用聚类分析(HCA)、主成分分析(PCA)、正交偏最小二乘法-判别分析和灰色关联度法对各指标数据进行分析。结果:HCA和PCA均可将32批鲜地黄药材分为4类,但无明显产地聚集现象;指纹图谱中峰1~3、9、10的峰面积及总灰分、浸出物、梓醇含量是体现各产地鲜地黄药材质量差异的主要指标;32批鲜地黄药材灰色关联度为0.036~0.042,灰色关联度差异为0~13.89%,综合质量差异不大。结论:化学模式识别结合灰色关联度法构建的多指标综合评价模型分析结果客观、科学、准确,可用于鲜地黄药材质量的综合评价。

关 键 词:鲜地黄  化学模式识别  灰色关联度  质量评价
收稿时间:2023/3/7 0:00:00

Quality Evaluation of Fresh Rehmannia glutinosa Based on Chemical Pattern Recognition and Grey Correlation Method
XU Jie,YAO Xiao-xuan,HUANG Meng-ting,HUANG Yao,PAN Ling,ZHANG Zheng.Quality Evaluation of Fresh Rehmannia glutinosa Based on Chemical Pattern Recognition and Grey Correlation Method[J].Modern Chinese Medicine,2024,26(1):18-28.
Authors:XU Jie  YAO Xiao-xuan  HUANG Meng-ting  HUANG Yao  PAN Ling  ZHANG Zheng
Institution:1.Guangdong Yifang Pharmaceutical Co., Ltd., Foshan 528244, China;2.Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Formula Granule, Foshan 528244, China
Abstract:Objective The multi-index comprehensive evaluation model of fresh Rehmannia glutinosa was established based on chemical pattern recognition and grey correlation method, aiming to provide a reference for the overall quality evaluation of fresh R. glutinosa.Methods 32 batches of fresh R. glutinosa from different origins were collected. The total ash, acid insoluble ash content, extracts, catalpol, digoxigenin D, lead, cadmium, arsenic, mercury, copper content, and fingerprints of each batch were determined. The data of each index component were analyzed by cluster analysis (HCA), principal component analysis (PCA), orthogonal partial least squares discriminant analysis, and grey correlation method.Results Both HCA and PCA can roughly divide 32 batches of fresh R. glutinosa into four categories, but there is no obvious origin aggregation. The peak areas of peak 1, peak 2, peak 3, peak 9, and peak 10 in the fingerprints of fresh R. glutinosa, as well as catalpol, total ash, and extract content are the main factors affecting the quality of fresh R. glutinosa from different origins. The floating range of grey correlation of 32 batches of fresh R. glutinosa is 0.036-0.042, and the difference in grey correlation is 0-13.89%, indicating a small comprehensive quality difference.Conclusion The multi-index comprehensive evaluation model based on chemical pattern recognition combined with grey correlation analysis has objective, scientific, and accurate results, and it can be used for the comprehensive evaluation of the quality of fresh R. glutinosa.
Keywords:fresh Rehmannia glutinosa Libosch    chemical pattern recognition  grey correlation  quality evaluation
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