FTIR结合多元统计分析的易混淆中药鉴别研究

楚雄师范学院学报 ›› 2025, Vol. 40 ›› Issue (3): 50-57.

FTIR结合多元统计分析的易混淆中药鉴别研究

张川云, 李德盛^#, 梁思玥, 李伦, 刘芮帆, 张德清

楚雄师范学院物理与电气能源工程学院,云南楚雄 675000

收稿日期:2025-01-13 出版日期:2025-05-20 发布日期:2025-07-01
作者简介:张川云（1990–）,女,讲师,研究方向为分子光谱。
^#共同第一作者：李德盛。
基金资助:
云南省科技厅科技计划项目（No. 202101BA070001-187,202301BA070001-058）; 云南省教育厅科学研究基金项目（No. 2023J1049）

Study on Identification of Confusable Chinese Herbs by FTIR Combined with Multivariate Statistical Analysis

ZHANG Chuanyun, LI Desheng^#, LIANG Siyue, LI Lun, LIU Ruifan, ZHANG Deqing

School of Physics, Electrical and Energy Engineering, Chuxiong Normal University, Chuxiong, Yunnan Province 675000

Received:2025-01-13 Online:2025-05-20 Published:2025-07-01

摘要/Abstract

摘要： 文章利用傅里叶变换红外光谱技术（FTIR）结合多元统计分析对两种易混淆中药凹叶景天与马齿苋进行了鉴别分析。红外光谱分析结果显示两种中药所含化学成分相似,都含有酯类、蛋白质、碱类、糖类及黄酮类化合物,但二者在1800~700 cm^-1波段内的红外光谱及红外光谱的二阶导数谱均存在明显差异。另外,对随机取样的32个凹叶景天和马齿苋样本在1800~700 cm^-1范围内的二阶导数谱进行聚类分析、主成分分析以及判别分析。聚类分析结果显示,在组间距离为6时,32个中药样本聚为了两大类。主成分分析结果显示,提取的前三个主成分的累计方差贡献率已超过了96%,在主成分三维分布图上,32个中药样本分别聚合在两个不同区域,同种中药样本有很好的聚合性,分类效果明显。再以前三个主成分作为原始变量进行判别分析,32个中药样本可以根据判别函数准确划分为凹叶景天和马齿苋两个区域,并且通过判别验证,实现了对2个新采集的未知样本的100%的正确判别。上述研究结果,可为发展易混淆中药光谱鉴别技术在中药材的快速检测分类领域的应用提供理论依据和技术参考。

关键词: 凹叶景天, 马齿苋, 红外光谱技术, 多元统计分析

Abstract: In this paper, Fourier transform infrared spectroscopy ( FTIR ) combined with multivariate statistical analysis was used to identify and analyze the two kinds of confusable Chinese herbs, Sedum emarginatum and Portulaca oleracea. The analysis results of infrared spectra showed that the chemical components in these two kinds of confusable Chinese herbs were similar, and both of them contained esters, proteins, alkalis, saccharide and flavonoids. However, there were obvious differences in their infrared spectra and second derivative infrared spectra in the 1800-700cm^-1 band. In addition, hierarchical cluster analysis (HCA), principal component analysis (PCA), and discriminant analysis (DA) were sequentially conducted with the second derivative infrared spectra of 32 random herbal samples selected from them in the 1800-700cm^-1 range. The HCA results indicated that when the inter-group distance was 6, samples of the 32 Chinese herbs were clustered into two categories. The PCA revealed that the cumulative variance contribution of the first three principal components had exceeded 96%, and on the 3D distribution figure of principal components, the 32 samples were aggregated in two different regions with a significant classification effect, and the samples of the same Chinese herbs had good aggregation. Then, the first three principal components were utilized as the variables for discriminant analysis. The 32 herbal samples were accurately classified into two distinct groups–Sedum emarginatum and Portulaca oleracea–based on the discriminant function. Furthermore, through discriminant verification, 100% correct discrimination of the two newly collected unknown samples was achieved. The above research results can provide theoretical basis and technical reference for the development of spectral identification technology of confusable Chinese herbs in the field of rapid detection and classification of Chinese herbs.

Key words: Sedum emarginatum, Portulaca oleracea, infrared spectroscopy, multivariate statistical analysis

中图分类号:

O657.3

张川云, 李德盛, 梁思玥, 李伦, 刘芮帆, 张德清. FTIR结合多元统计分析的易混淆中药鉴别研究[J]. 楚雄师范学院学报, 2025, 40(3): 50-57.

ZHANG Chuanyun, LI Desheng, LIANG Siyue, LI Lun, LIU Ruifan, ZHANG Deqing. Study on Identification of Confusable Chinese Herbs by FTIR Combined with Multivariate Statistical Analysis[J]. Journal of Chuxiong Normal University, 2025, 40(3): 50-57.

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