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牛膝药材的红外指纹图谱建立及多元统计分析
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| 篇名： | 牛膝药材的红外指纹图谱建立及多元统计分析 |
| TITLE： | Establishment of infrared fingerprints and multivariate statistical analysis of Achyranthes bidentata |
| 摘要： | 目的 建立不同产地牛膝药材的红外指纹图谱，并进行多元统计分析。方法采用SpectrumforWindow3.02和OMNIC9.2软件建立61批牛膝药材样品的红外指纹图谱；以红外指纹图谱共有峰的相对峰高为变量，采用Excel2016软件进行正态分布分析，采用SPSS22.0软件进行聚类分析和主成分分析并计算综合得分，采用SIMCA14.1软件进行正交偏最小二乘法-判别分析，以变量重要性投影（VIP）＞1为标准，筛选影响牛膝药材成分质量的标志性波数。结果61批牛膝药材样品红外光谱图的相关系数为0.9672～0.9977；共有13个共有峰。正态分布分析结果显示，河南产与河北产牛膝药材共有峰相对峰高的正态分布曲线未有交叉，河南产与内蒙古产牛膝药材的正态分布曲线存在交叉。聚类分析结果显示，当组间距离为15时，61批牛膝药材样品可聚为3类，其中N1～N12聚为一类，N13～N45聚为一类，N46～N61聚为一类。主成分分析结果显示，前3个主成分的累计方差贡献率为91.121％；河南省焦作市驾步村产牛膝药材（编号N40）的综合评分最高（2.39），河北省安国市新安村产牛膝（编号N4）的综合评分最低（－2.89）。正交偏最小二乘法-判别分析结果显示，61批牛膝药材样品可分为3类，其中N1～N12为一类，N13～N28为一类，N29～N61为一类；共筛选出7个影响药材样品质量的标志性波数，其VIP值从大到小对应的波数依次为1059、927、2933、813、1732、1128、3367cm－1，其中1732cm－1处为皂苷类成分的特征吸收峰，1059、1128、927cm－1处为糖苷类成分的特征吸收峰。结论红外指纹图谱结合正态分布分析、聚类分析、主成分分析和正交偏最小二乘法-判别分析可用于鉴别不同产地牛膝药材。 |
| ABSTRACT： | OBJECTIVE To establish the infrared fingerprints of Achyranthes bidentata from different producing areas ，and to conduct multivariate statistical analysis. METHODS The infrared fingerprints of 61 batches of A. bidentata samples were established by Spectrum for Window 3.02 and OMNIC 9.2 software. Taking the relative peak height of common peaks of infrared fingerprint as the variable ，the normal distribution analysis was carried out by Excel 2016 software；SPSS 22.0 software was used for cluster analysis and principal component analysis ，and the comprehensive score was calculated ；the orthogonal partial least squares-discriminant analysis was carried out by SIMCA 14.1 software，and the marker wave numbers affecting the quality of A. bidentata were screened by taking the variable importance in projection （VIP）＞1 as the standard. RESULTS The correlation coefficients of infrared spectra of 61 batches of A. bidentata samples were 0.967 2-0.997 7；there were 13 common peaks. The results of normal distribution analysis showed that the normal distribution curve of relative peak height of common peaks for A. bidentata from Henan and Hebei did not cross ，and the normal distribution curve of A. bidentata from Henan and Inner Mongolia crossed. The results of cluster analysis showed that when the distance between groups was 15，61 batches of A. bidentata samples could be clustered into 3 categories，including N 1-N12 were clustered into one category ，N13-N45 were clustered into one category，and N 46-N61 were clustered into one category. The results of principal component analysis showed that the cumulative variance contribution rate of the first three principal components was 91.121％；comprehensive score of qq.com A. bidentata （number N 40） in Jiabu village ，Jiaozuo City ， Henan Province was the highest （2.39）， and that of A.bidentata（number N 4）in Xin ’an village ，Anguo City ，Hebei Province was the lowest （－2.89）. The results of orthogonal 163.com partial least squares-discriminant analysis showed that 61 batches of A. bidentata samples were divided into three categories ，including N 1-N12 were clustered into one category ，N13-N28 were clustered into one category and N 29-N61 were clustered into one category. Seven marker wave numbers affecting the quality were selected. The corresponding wave numbers of VIP from large to small were 1 059，927，2 933，813，1 732，1 128 and 3 367 cm－1，1 732 cm－1 was the characteristic obsorption peak of saponins ，1 059，1 128，927 cm－1 were the characteristic obsorption peaks of glycosides. CONCLUSIONS Infrared fingerprint combined with normal distribution analysis ，cluster analysis ，principal component analysis and orthogonal partial least squares-discriminant analysis can be used to identify A. bidentata from different producing areas. |
| 期刊： | 2022年第33卷第02期 |
| 作者： | 贾豪，雷益铭，张维方，雷敬卫，杨春静，李莹莹，谢彩侠 |
| AUTHORS： | JIA Hao，LEI Yiming ，ZHANG Weifang ，LEI Jingwei ，YANG Chunjing ，LI Yingying ，XIE Caixia |
| 关键字： | 牛膝；红外指纹图谱；正态分布分析；聚类分析；主成分分析；正交偏最小二乘法-判别分析；产地 |
| KEYWORDS： | Achyranthes bidentata ；infrared fingerprint ；normal distribution analysis ；cluster analysis ；principal component |
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