天然产物研究与开发 ›› 2023, Vol. 35 ›› Issue (4): 630-639.doi: 10.16333/j.1001-6880.2023.4.010

• 开发研究 • 上一篇    下一篇

基于大数据与模式识别技术对中药材品质的快速评价研究

张立军1,张新玥2,马冬妮3,张转平1*,谭艳萍1,钟海婷1,熊贤锋1,刘   丽1   

  1. 1陕西省安康市食品药品检验检测中心,安康 725000;2北京中医药大学中药学院,北京 100029;3甘肃省敦煌市医院,敦煌 736200
  • 出版日期:2023-04-24 发布日期:2023-04-24
  • 基金资助:
    陕西省社会发展科技攻关项目(2015SF286);安康市社会发展科技攻关项目(AK2021-SF-01)

Study on rapid evaluation of Chinese herbal medicine quality based on big data and pattern recognition technology

ZHANG Li-jun1,ZHANG Xin-yue2,MA Dong-ni3,ZHANG Zhuan-ping1*,TAN Yan-ping1,ZHONG Hai-ting1,XIONG Xian-feng1,LIU Li1
  

  1. 1Ankang Inspection and Detection Center of Food and Drug Control,Ankang 725000,China;2Beijing University of Chinese Medicine,Beijing 100029,China;3Dunhuang Hospital of Gansu Province,Dunhuang 736200,China
  • Online:2023-04-24 Published:2023-04-24

摘要: 基于大数据背景下,通过多项指标的快速检测与整合分析,建立北柴胡药材品质综合评价模型与等级划分的评价方法。收集本中心2015年~2020年抽检样品中采用《中华人民共和国药典》(以下简称《中国药典》)2015年版检测的130批北柴胡药材各项检测数据;通过近红外光谱(NIRS)技术采集各批药材对应的光谱图,采用模式识别技术建立北柴胡快速溯源分析模型,同时构建各检测指标与光谱之间的拟合模型,开展多批次北柴胡药材的系统检测;采用数学建模方法构建北柴胡药材品质综合评价指数(Fq)计算方法,建立其品质综合评价与等级划分数据库。建立了北柴胡药材溯源分析快速定性鉴别模型;建立了北柴胡药材水分、灰分、酸不溶性灰分、浸出物、柴胡皂苷a和d总量及茎秆(地上部分)占比6项指标的近红外预测模型,应用模型完成了对20批次北柴胡药材的快速检测;建立了北柴胡品质快速评价与等级划分数据库。该方法基于大数据背景下利用现行《中国药典》监管体系产生的原始数据实现了对北柴胡药材品质的快速综合评价和等级划分,为中药材科学监管研究提供了新的解决方法。

关键词: 大数据, 品质综合评价指数, 北柴胡, 近红外光谱技术, 系统建模, 等级划分

Abstract:

Based on the background of big data,through the integration analysis of several testing indexes,an integrated evaluation method of quality evaluation and a grade identification system of the roots of Bupleurum chinense DC.(BCD) were developed.Collected the test data of 130 batches of the roots of BCD detected by the 2015 edition of "Chinese Pharmacopoeia" in the random inspection samples of our center from 2015 to 2020.The near-infrared spectroscopy (NIRS) technology were collected the spectra corresponding to each batch of samples.The pattern recognition technology was used to establish a fast traceability analysis model of samples,and developed to establish fitting model between the NIRS and the content with detection index of samples respectively.Carry out the system detection of multiple batches of the roots of BCD samples.The mathematical modeling method was used to construct the calculation method of the quality comprehensive evaluation index factor (Fq), and established the comprehensive evaluation and grade division database of medicinal materials.The novel rapid qualitative analysis the roots of BCD identification model were established.The NIRS model of 6 indexes including water,total ash,acid-insoluble ash,extract,the total amount of saikosaponins a and d,and the proportion of stem of BCD were established,and then applied to detect of 20 of batches of the roots of BCD samples.Established a database for rapid quality evaluation and grade division of the roots of BCD samples.This method is based on the background of big data and uses the original data generated by the current "Chinese Pharmacopoeia" supervision system to realize the rapid comprehensive evaluation and grading of the quality of the roots of BCD samples,and provides a new solution for the scientific supervision and research of Chinese herbal medicine.

Key words: big data, quality comprehensive evaluation index factor, Bupleurum chinense DC., NIRS, system modeling, grade division

中图分类号:  R286