Classification and Identification of Cynomorii Herba from Different Producing Areas Based on Fourier Rransform Infrared Spectroscopy and Chemometrics
10.13422/j.cnki.syfjx.20191114
- VernacularTitle: 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
- Author:
Zhi-rong GU
1
;
Tian-xiang MA
2
;
Lan-ping SUN
2
;
Zhuan-xia MA
2
;
Ai-xia XU
1
;
Yu-jing SUN
3
;
Mei QI
1
;
Bin GE
1
Author Information
1. Gansu Provincial Hospital, Lanzhou 730000, China
2. College of Pharmacy, Gansu University of Chinese Medicine, Lanzhou 730000, China
3. Key Laboratory of Chinese Medicine Quality and Standard in Gansu Province, Lanzhou 730000, China
- Publication Type:Research Article
- Keywords:
Cynomorii Herba;
fourier transform infrared spectroscopy;
first derivative spectrum;
soft independent modeling of class analog;
orthogonal partial least squares;
origin identification
- From:
Chinese Journal of Experimental Traditional Medical Formulae
2019;25(22):159-165
- CountryChina
- Language:Chinese
-
Abstract:
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.
