使用Py-GC/MS对含有THC的食用食品进行直接分析
Fatma Almadani1, Samar Gewily1, Adnan Lanjawi1
1Dubai Police, General Department of Forensic Science and Criminology, Forensic Chemistry Section, Dubai P.O. Box 1493, United Arab Emirates.
Science & justice : journal of the Forensic Science Society
|November 30, 2025
概括
热解气色谱-质谱 (Py-GC/MS) 提供了一种更快,更可靠的方法来分析四大麻素 (THC) 食用品. 这种技术简化了样品的准备,并减少了与传统方法相比的错误.
科学领域:
- 法医化学 法医化学
- 分析化学 分析化学
- 大麻素分析分析
背景情况:
- 可食用大麻素产品因其精神活性作用而受欢迎,需要强大的分析方法.
- 准确监测四大麻素 (THC) 食用食品对于法医和监管目的至关重要.
研究的目的:
- 评估热解气色谱-质谱 (Py-GC/MS) 作为分析食用大麻素的有效技术.
- 为了比较Py-GC/MS的灵敏度和效率与传统的气体染色体质谱法 (GC/MS).
主要方法:
- 2017-2022年期间收集的七种不同的可食用大麻素样本的定性分析.
- 使用Pyrolysis与GC/MS (Py-GC/MS) 结合用于大麻素分析.
- 结果与传统的GC/MS分析进行了比较.
主要成果:
- 对于食用大麻素的分析,Py-GC/MS显示出高可靠性,在度和丰度之间实现了线性回归 (R2 = 0.99).
- 与标准GC/MS分析相比,观察到显著减少的矩阵效应.
- Py-GC/MS分析需要更短的样品准备时间和更少的化学试剂,尽量减少成本和潜在的人为错误.
结论:
- Py-GC/MS被证实是用于分析大麻食用品的可靠,高效和具有成本效益的技术.
- 与传统的GC/MS相比,该方法在速度,简单性和减少错误方面具有优势.
- 这个创新的应用程序支持对食用大麻素产品进行增强的法医分析.
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