Identification of Armeniacae Semen Amarum and Persicae Semen from different origins based on near infrared hyperspectral imaging technology.
10.19540/j.cnki.cjcmm.20201015.202
- Author:
Jie ZHENG
1
;
Chen-Lei RU
2
;
Lu ZHANG
1
;
Wen-Jun YIN
1
;
Hui ZHANG
1
;
Ji-Zhong YAN
1
Author Information
1. Traditional Chinese Medicine Research Institute, College of Pharmaceutical Sciences, Zhejiang University of Technology Hangzhou 310014, China.
2. State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University Hangzhou 310027, China.
- Publication Type:Journal Article
- Keywords:
Armeniacae Semen Amarum;
Persicae Semen;
authentication;
near-infrared hyperspectral technology;
origin classification
- MeSH:
Drugs, Chinese Herbal;
Hyperspectral Imaging;
Least-Squares Analysis;
Semen;
Support Vector Machine;
Technology
- From:
China Journal of Chinese Materia Medica
2021;46(10):2571-2577
- CountryChina
- Language:Chinese
-
Abstract:
In order to establish a rapid and non-destructive evaluation method for the identification of Armeniacae Semen Amarum and Persicae Semen from different origins, the spectral information of Armeniacae Semen Amarum and Persicae Semen in the range of 898-1 751 nm was collected based on hyperspectral imaging technology. Armeniacae Semen Amarum and Persicae Semen from different origins were collected as research objects, and a total of 720 Armeniacae Semen Amarum samples and 600 Persicae Semen samples were used for authenticity discrimination. The region of interest(ROI) and the average reflection spectrum in the ROI were obtained, followed by comparing five pre-processing methods. Then, partial least squares discriminant analysis(PLS-DA), support vector machine(SVM), and random forest(RF) method were established for classification models, which were evaluated by the confusion matrix of prediction results and receiver operating characteristic curve(ROC). The results showed that in the three sample sets, the se-cond derivative pre-processing method and PLS-DA were the best model combinations. The classification accuracy of the test set under the 5-fold cross-va-lidation was 93.27%, 96.19%, and 100.0%, respectively. It was consistent with the confusion matrix of the predicted results. The area under the ROC curve obtained the highest values of 0.992 3, 0.999 6, and 1.000, respectively. The study revealed that the near-infrared hyperspectral imaging technology could accurately identify the medicinal materials of Armeniacae Semen Amarum and Persicae Semen from different origins and distinguish the authentication of these two varieties.
