基于傅里叶变换红外光谱及化学计量学方法的不同产地锁阳药材分类鉴别

目的:基于傅里叶变换红外光谱(FTIR)及化学计量学方法实现不同产地锁阳药材的分类鉴别。方法:采集5个省(区) 12个市(区/州/旗)的106批锁阳药材,以透射方式采集样品的FTIR光谱数据并进行光谱预处理,建立锁阳FTIR指纹图谱并进行光谱解析,以相关系数法计算不同产地锁阳的FTIR相似度,求取不同产地锁阳FTIR平均光谱的一阶导数(1D)光谱,以预处理后的1D光谱数据建立基于主成分分析(PCA)的软独立建模分类(SIMCA)鉴别模型,以前6个主成分建立正交偏最小二乘法(OPLS)鉴别模型。结果:不同产地锁阳FTIR指纹图谱的走势及主要吸收峰位基本一致,共指认出了16个共有特征吸收峰;不同产地锁阳FTIR指纹图谱的相似度及1D光谱均有显著、唯一的特征;所建SIMCA模型可实现不同省级产区锁阳的分类鉴别,所建OPLS模型可实现不同市级产区锁阳的精确分类鉴别,12个产地锁阳的分类鉴别体现了明显的地域聚集性特点。结论:基于FTIR及化学计量学方法能够实现不同产地锁阳药材的分类鉴别。

Classification and Identification of Cynomorii Herba from Different Producing Areas Based on Fourier Rransform Infrared Spectroscopy and Chemometrics

Objective: To realize the classification and identification of Cynomorii Herba from different producing areas based on fourier transform infrared spectroscopy (FTIR) and chemometrics. Method: FTIR spectrum data of 106 batches of Cynomorii Herba from 12 cities in 5 provinces were collected by transmission method and preprocessed. The FTIR fingerprints of Cynomorii Herba were established, and spectrum analysis was performed. The FTIR similarities of Cynomorii Herba from different producing areas were calculated by correlation coefficient method. The first derivative (1D) spectrum of average FTIR of Cynomorii Herba from different producing areas were obtained. The soft independent modeling of class analog (SIMCA) model based on principal component analysis (PCA) was established by the preprocessed 1D spectrum data. The orthogonal partial least squares (OPLS) model was established by top 6 principal components. Result: The FTIR fingerprint trend and main absorption peaks of Cynomorii Herba from different producing areas were basically the same,and 16 common characteristic absorption peaks were recognized. Similarity and 1D spectrum of FTIR fingerprint of Cynomorii Herba from different producing areas showed significant and unique characteristics. The established SIMCA model can realize the classification and identification of Cynomorii Herba from different provinces,while OPLS model can realize accurate classification and identification of Cynomorii Herba in different cities. The classification and identification of Cynomorii Herba from 12 city producing areas showed obvious geographical clustering characteristics. Conclusion: The established method based on FTIR and chemometrics can realize the classification and identification of Cynomorii Herba from 12 cities.