High-Performance Thin-Layer Chromatography hyphenated with image processing and chemometrics as a tool for forensic discrimination of Cannabis sativa L. chemotypes

IF 2.6 3区医学 Q2 CHEMISTRY, ANALYTICAL

Forensic Chemistry Pub Date : 2023-09-07 DOI:10.1016/j.forc.2023.100528

Nataša Radosavljević-Stevanović , Aleksandra Kovačević , Dragan Manojlović , Petar Ristivojević

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Abstract

Cannabis sativa L. is the most widely cultivated, trafficked, and abused illicit drug. The reliable distinction between drug type and fiber type C. sativa remains a topic of interest for forensic chemists. For the first time, we applied a combination of simple, cost-effective, and reliable High-Performance Thin-Layer Chromatography (HPTLC) with image analysis as well as sophisticated multivariate tools for differentiating C. sativa drug, fiber and intermediate chemotypes. After extraction, major cannabinoids from 43 seized C. sativa were separated using the HPTLC method. Peak areas of Δ⁹-THC, CBN, and CBD were calculated by simple image processing, and Xfactor = [THC + CBN]/CBD was determined as criteria used to discriminate three C. sativa chemotypes. The obtained results were compared with Gas Chromatography with Flame Ionization Detection (GC-FID) as the reference method for the determination of Xfactor.

Principal Component Analysis and Hierarchic Cluster Analysis were applied to classify three C. sativa chemotypes according to their chemical pattern. The proposed approach clearly distinguishes 26 drugs, 13 fiber, and 4 intermediate chemotypes in seized C. sativa, aligning with GC-FID analysis. The results showed that the HPTLC technique in combination with multivariate methods is an accurate and reliable tool for high-throughput and forensic screening of three C. sativa chemotypes. Compounds such as Δ⁹-THC and CBD were marked as the most important cannabinoids responsible for the classification of the seized C. sativa chemotypes.

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结合图像处理和化学计量学的高效薄层色谱法在大麻化学型鉴定中的应用

大麻是最广泛种植、贩运和滥用的非法药物。药物类型和纤维类型之间的可靠区分仍然是法医化学家感兴趣的话题。我们首次将简单、经济、可靠的高效薄层色谱(HPTLC)与图像分析相结合，以及复杂的多变量工具用于鉴别大麻药物、纤维和中间化学型。提取后，采用高效液相色谱法对43株大麻中主要大麻素进行分离。通过简单的图像处理计算Δ9-THC、CBN和CBD的峰面积，确定Xfactor = [THC + CBN]/CBD作为判别三种红花化学型的标准。并将所得结果与气相色谱-火焰电离检测法(GC-FID)作为测定x因子的参考方法进行了比较。利用主成分分析和层次聚类分析对三种苜蓿的化学型进行了分类。该方法与GC-FID分析结果一致，明确了检获的芥花中26种药物、13种纤维和4种中间化学型。结果表明，HPTLC技术与多变量方法相结合，是一种准确可靠的高通量和法医鉴定三种苜蓿化学型的工具。Δ9-THC和CBD等化合物被标记为最重要的大麻素，负责对检获的大麻化学型进行分类。

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来源期刊

Forensic Chemistry CHEMISTRY, ANALYTICAL-

CiteScore

5.70

自引率

14.80%

发文量

审稿时长

46 days

期刊介绍： Forensic Chemistry publishes high quality manuscripts focusing on the theory, research and application of any chemical science to forensic analysis. The scope of the journal includes fundamental advancements that result in a better understanding of the evidentiary significance derived from the physical and chemical analysis of materials. The scope of Forensic Chemistry will also include the application and or development of any molecular and atomic spectrochemical technique, electrochemical techniques, sensors, surface characterization techniques, mass spectrometry, nuclear magnetic resonance, chemometrics and statistics, and separation sciences (e.g. chromatography) that provide insight into the forensic analysis of materials. Evidential topics of interest to the journal include, but are not limited to, fingerprint analysis, drug analysis, ignitable liquid residue analysis, explosives detection and analysis, the characterization and comparison of trace evidence (glass, fibers, paints and polymers, tapes, soils and other materials), ink and paper analysis, gunshot residue analysis, synthetic pathways for drugs, toxicology and the analysis and chemistry associated with the components of fingermarks. The journal is particularly interested in receiving manuscripts that report advances in the forensic interpretation of chemical evidence. Technology Readiness Level: When submitting an article to Forensic Chemistry, all authors will be asked to self-assign a Technology Readiness Level (TRL) to their article. The purpose of the TRL system is to help readers understand the level of maturity of an idea or method, to help track the evolution of readiness of a given technique or method, and to help filter published articles by the expected ease of implementation in an operation setting within a crime lab.