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Rapid Qualitative Analysis of Methamphetamine, Ketamine, Heroin, and Cocaine by Fourier Transform Infrared Spectroscopy (FTIR) |
LIU Cui-mei1*, HAN Yu1, MIN Shun-geng2* |
1. National Narcotics Laboratory, Drug Intelligence and Forensic Center of the Ministry of Public Security, Beijing 100193, China
2. College of Science, China Agricultural University, Beijing 100193, China |
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Abstract For the first time, this study has established an attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) method for fast qualitative analysis of methamphetamine, ketamine, heroin, and cocaine. Characteristic peak method was chosen as the qualitative analysis criterion of this method. Due to the lack of proper qualitative identification criterion, FTIR method has long just been used for fast qualitative screening in drug analysis. In order to expand its application in forensic sciences, two qualitative identification criteria of characteristic peak method and soft independent modeling by class analogy (SIMCA) classification method were investigated and compared. A total of 516 calibration and 864 prediction samples were used for method development and validation. For characteristic peak method, five to eight peaks in the range of 2 500~650 cm-1 with relative high intensity and interference-free from common cutting agents were selected as the characteristic peaks. When characteristic peak method (all of the characteristic peaks should be detected) was used for the qualitative analysis of 646 validation samples, the positive detection rate was 98.1%. A SIMCA classification model was constructed based on 516 calibration samples, consisting of 7 PCA models for methamphetamine HCl, ketamine HCl, ketamine base, heroin HCl, heroin base, cocaine HCl, and cocaine base. The classification results of 646 validation samples showed a recognition rate of 95.4%, and a false rejection rate of 100%. Therefore, the results of both the characteristic peak method and the SIMCA method were reliable and accurate. It is easy for the characteristic peak method to be used by local police officers after simple training, thus suitable for popularizing. In comparison, as the building of SIMCA model needs the collection of large number of representative calibration samples and the use of professional mathematical software, the SIMCA method is not suitable for popularizing. Therefore, the characteristic peak method was chosen as the criterion method for fast qualitative identification analysis. The ATR-FTIR method that is based on characteristic peak method will greatly increase the efficiency and reduce the cost of drug qualitative identification analysis.
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Received: 2018-06-06
Accepted: 2018-10-29
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Corresponding Authors:
LIU Cui-mei, MIN Shun-geng
E-mail: minsg@cau.edu.cn
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[1] Office of China National Narcotics Control Commission (中国国家禁毒委员会). Annual Report on Drug Control in China 2017(中国禁毒报告2017). Beijing, 2017.
[2] United Nations Office on Drugs and Crime (UNODC). World Drug Report 2016. United Nations, New York, 2017.
[3] United Nations Office on Drugs and Crime (UNODC). Recommended Methods for the Identification and Analysis of Amphetamine, Methamphetamine and Their Ring-Substitutes Analogues in Seized Materials. United Nations, New York, 2006.
[4] United Nations Office on Drugs and Crime (UNODC). Recommended Methods for Testing Cocaine. United Nations, New York, 1986.
[5] United Nations Office on Drugs and Crime (UNODC). Recommended Methods for Testing Opium, Morphine and Heroin. United Nations, New York, 1998.
[6] Rodrigues N V S, Cardoso E M, Andrade M V O, et al. Journal of the Brazilian Chemical Society, 2013, 24(3): 507.
[7] Marcelo M C A, Mariotti K C, Ferrāo M F, et al. Forensic Science International, 2015, 246: 65.
[8] Neto J C. Forensic Science International, 2015, 252: 87.
[9] Goh C Y, Bronswijk W V, Priddis C. Applied Spectroscopy, 2008, 62(6): 640.
[10] Grobério T S, Zacca J J, Botelho É D, et al. Forensic Science International, 2015, 257: 297.
[11] National Standard of the People’s Republic of China(中华人民共和国国家标准). GB/T 7764—2001 Rubber Identification Infra-Red Spectrometric Method (橡胶鉴定红外光谱法).
[12] Textile Industry Standard of the People’s Republic of China(中华人民共和国纺织行业标准). FZ/T 01057.8—2012. Test Methods for Identification of Textile Fibers Parts 8: Infrared Absorption Spectrum(纺织纤维鉴别试验方法第8部分:红外光谱法).
[13] SUN Su-qin, ZHOU Qun, CHEN Jian-bo(孙素琴,周 群,陈建波). ATC009 Infrared Spectrum Analysis Technology (ATC009 红外光谱分析技术). Beijing: China Quality Inspection Press and Standards Press of China(北京:中国质检出版社和中国标准出版社), 2013.
[14] LIU Shu-shen, YI Zhong-sheng(刘树深,易忠胜). Basic Chemometrics(基础化学计量学). Beijing: Science Press(北京:科学出版社),1999. 145. |
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