Establishment of the thin-layer chromatography-surface-enhanced Raman spectroscopy and chemometrics method for simultaneous identification of eleven illegal drugs in anti-rheumatic health food. (October 2022)

• Record Type: Journal Article
• Authors: Yang, Fangwei; Wang, Cheng; Yu, Hang; Guo, Yahui; Cheng, Yuliang; Yao, Weirong; Xie, Yunfei
• Is Part Of: Food bioscience. Volume 49(2022)
• Publication Date: 2022-10
• Subjects: TLC-SERS -- Health food -- Illegal drugs -- Chemometrics -- Simultaneous identification -- Rapid detection; Food -- Biotechnology -- Periodicals; Food -- Research -- Periodicals; Aliments -- Biotecnologia -- Revistes; Aliments -- Investigació -- Revistes; Food -- Biotechnology; Food -- Research; Revistes electròniques; Periodicals; 664.005
• DOI: 10.1016/j.fbio.2022.101842
• Languages: English
• ISSNs: 2212-4292

Abstract

Abstract: The risk of the illegal addition of anti-inflammatory and analgesic chemical drugs in anti-rheumatic health foods should not be ignored. Market supervision and rapid on-site detection technology need to be strengthened. Thin-layer chromatography-surface-enhanced Raman spectroscopy (TLC-SERS), which has the advantages of simple operation, fast separation, and qualitative and quantitative detection, was used in this study. And these eleven chemical drugs (acetaminophen, acetylsalicylic acid, aminophenazone, dexamethasone, diclofenac sodium, hydrocortisone, indometacin, naproxen, phenylbutazone, piroxicam, prednisone 21-acetate) that may be added to anti-rheumatic health foods have been simultaneously identified by TLC-SERS combined with chemometrics method. The characteristic signals of the separated drug spots were collected by SERS, which were optimized by the gold colloidal nanoparticles' volume and integration time. Then SERS was subjected to principal component analysis (PCA) to reduce dimensionality and combined with the pattern recognition methods in chemometrics, such as PCA-Linear Discriminant Analysis (LDA), PCA-K Nearest Neighbor and PCA-Support Vector Machine, and eleven drug components were judged and identified. Moreover, the predictive performances of different models were also analyzed and compared. The results showed that the TLC plate and four organic solvents of petroleum ether, chloroform, ethyl acetate and acetic acid were selected as the developing agent. The dropping amount of gold colloidal nanoparticles and the integration time were set and optimized. The limit of detection of the simultaneous detection method of SERS was 10–100 mg/L. Furthermore, SERS was preprocessed by Gap-Segment 2nd Derivative, and then the PCA-LDA model was established, and the model's prediction accuracy can reach 100%. The method is simple, rapid, sensitive and accurate, and has low experimental instruments and equipment requirements. It is suitable for the on-site simultaneous detection of various anti-inflammatory and analgesic chemical drugs in health foods. It can also provide guarantee and support for the establishment of appropriate rapid detection methods and the development of supervision technology. Graphical abstract: Image 1 Highlights: The eleven illegal drugs in health food were simultaneously detected by TLC-SERS. Raman peaks under theoretically calculated and experimentally measured were similar. The dropping amount of gold colloidal and the integration time of SERS were optimized. The LODs of the simultaneous detection method of TLC-SERS were 10–100 mg/L. PCA-LDA discriminant model based on GSD pretreatment had the best predictive ability.