Research on Origin Traceability of Rhizoma Dioscoreae Based on LIBS
CAI Yu1, 2, ZHAO Zhi-fang3, GUO Lian-bo4, CHEN Yun-zhong1, 2*, JIANG Qiong4, LIU Si-min1, 2, ZHANG Cong-zi4, KOU Wei-ping5, HU Xiu-juan5, DENG Fan6, HUANG Wei-hua7
1. College of Pharmacy, Hubei University of Chinese Medicine, Wuhan 430065, China
2. Institute of Engineering Technology of Chinese Traditional Medicine and Health Food of Hubei Province, Wuhan 430065, China
3. School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
4. Department of Pharmacy, the First Affiliated Hospital of Hubei University of Science and Technology, Xianning Central Hosptial, Xianning 437100，China
5. Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
6. School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074，China
7. FiberHome Technologies Group, Wuhan 430074，China
Abstract：Rhizoma Dioscoreae contains polysaccharides, polyphenols, saponins, mucins and vitamin C, which have anti-tumor, anti-oxidant, anti-inflammatory, hypoglycemic, and hypolipidemic effects. Due to the differences in growth conditions of Rhizoma Dioscoreae from different origins, resulting in significantly different contents of medicinal ingredients, combined with unique processing technology, which in turn lead to large differences in market prices, it is crucial to identify the origin of Rhizoma Dioscoreae Tablets. In order to trace the origin of Rhizoma Dioscoreae Tablets, this paper proposed a Multiplicative signal correction-improved genetic algorithm-support vector machine (MSC-IGA-SVM) model based on Laser-induced breakdown spectroscopy (LIBS) technique for accurate identification of Rhizoma Dioscoreae origin. In the paper, LIBS experiments were conducted using eight Rhizoma Dioscoreae Tablets of different origins. The Rhizoma Dioscoreae Tablets of eight origins were ground and sieved to make powder pressed tablets. The recognition results of the spectra were compared by collecting LIBS spectra of Rhizoma Dioscoreae Tablets using a single classifier and a model using spectral preprocessing, feature extraction and pattern recognition algorithms, respectively. In the research, the spectral signals were divided into training and test sets in the ratio of 2∶1, and the test set accuracy of the K-Nearest Neighbor (KNN) model using five cross-validations was used as an evaluation index for the optimization of preprocessing parameters. The overall trend of the average spectra of all herbs was consistent. The contained spectral peaks were the same, but the peak intensities varied due to different origins, and the enrichment ability of some metal elements (K, Na, Ca, Mg, Al) was greater for Rhizoma Dioscoreae growed in the Dao-di Areas than for those not growed in the Dao-di Areas, among which, the peak of the characteristic spectral line of element K (769.90 nm) was the highest, i. e., the Rhizoma Dioscoreae Tablets contained the most element K. Related studies showed that the root of Rhizoma Dioscoreae has the strongest enrichment capacity for element K. Thirty-five key spectral lines were selected for analysis. Improved Genetic Algorithm (IGA) could discriminate the nonlinear relationships in the spectra more clearly than Principal Component Analysis (PCA) in the case of many identification species and difficult identification while being less affected by noise. The MSC-IGA-SVM model had the best origin traceability. The accuracy of the MSC-IGA-SVM model was 96.9% for the cross-validation set, and the accuracy of the test set was 97.32%, which was 0.87% higher than the best model Support Vector Machine (SVM) built directly using the original signal (96.43%) for the test set. Meanwhile, the MSC-IGA-SVM model reduced the dimensionality of the input variables by 99.93%. The results showed that the origin of Rhizoma Dioscoreae Tablets could be traced by the LIBS technique combined with the MSC-IGA-SVM model quickly and accurately.
蔡 羽，赵志方，郭连波，陈运中，姜 琼，刘思敏，张聪子，寇卫萍，胡秀娟，邓 凡，黄伟华. 基于LIBS的山药饮片产地溯源研究[J]. 光谱学与光谱分析, 2023, 43(01): 138-144.
CAI Yu, ZHAO Zhi-fang, GUO Lian-bo, CHEN Yun-zhong, JIANG Qiong, LIU Si-min, ZHANG Cong-zi, KOU Wei-ping, HU Xiu-juan, DENG Fan, HUANG Wei-hua. Research on Origin Traceability of Rhizoma Dioscoreae Based on LIBS. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(01): 138-144.
