Laboratory of Growth Regulators, Institute of Experimental Botany ASCR & Palacký University, Olomouc, Czech Republic.
Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, China.
Phytochem Anal. 2020 Mar;31(2):135-146. doi: 10.1002/pca.2886. Epub 2019 Aug 30.
Cannabinoids are organic compounds, natural or synthetic, that bind to the cannabinoid receptors and have similar pharmacological properties as produced by the cannabis plant, Cannabis sativa. Gas chromatography (GC), e.g. gas chromatography mass spectrometry (GC-MS), is a popular analytical tool that has been used extensively to analyse cannabinoids in various matrices.
To review published literature on the use of various GC-based analytical methods for the analysis of naturally occurring cannabinoids published during the past decade.
A comprehensive literature search was performed utilising several databases, like Web of Knowledge, PubMed and Google Scholar, and other relevant published materials including published books. The keywords used, in various combinations, with cannabinoids being present in all combinations, in the search were cannabinoids, Cannabis sativa, marijuana, analysis, GC, quantitative, qualitative and quality control.
During the past decade, several GC-based methods for the analysis of cannabinoids have been reported. While simple one-dimensional (1D) GC-MS and GC-FID (flame ionisation detector) methods were found to be quite common in cannabinoids analysis, two-dimensional (2D) GC-MS as well as GC-MS/MS also were popular because of their ability to provide more useful data for identification and quantification of cannabinoids in various matrices. Some degree of automation in sample preparation, and applications of mathematical and computational models for optimisation of different protocols were observed, and pre-analyses included various derivatisation techniques, and environmentally friendly extraction protocols.
GC-based analysis of naturally occurring cannabinoids, especially using GC-MS, has dominated the cannabinoids analysis in the last decade; new derivatisation methods, new ionisation methods, and mathematical models for method optimisation have been introduced.
大麻素是有机化合物，天然或合成，与大麻素受体结合，具有与大麻植物大麻（Cannabis sativa）产生的相似的药理学特性。气相色谱（GC），例如气相色谱-质谱联用（GC-MS），是一种广泛使用的分析工具，已被广泛用于分析各种基质中的大麻素。
综述过去十年中发表的关于使用各种基于 GC 的分析方法分析天然大麻素的文献。
利用多个数据库（如 Web of Knowledge、PubMed 和 Google Scholar）以及其他相关已发表材料（包括已发表的书籍）进行全面文献检索。使用的关键词在各种组合中都有出现，大麻素在所有组合中都有出现，搜索的关键词包括大麻素、大麻、大麻、分析、GC、定量、定性和质量控制。
在过去的十年中，已经报道了几种基于 GC 的大麻素分析方法。虽然一维（1D）GC-MS 和 GC-FID（火焰离子化检测器）方法在大麻素分析中相当常见，但二维（2D）GC-MS 以及 GC-MS/MS 也因其能够为各种基质中的大麻素提供更有用的数据用于鉴定和定量而受到欢迎。在样品制备方面实现了一定程度的自动化，并且应用了数学和计算模型来优化不同的方案，预处理包括各种衍生化技术和环保的提取方案。
基于 GC 的天然大麻素分析，特别是使用 GC-MS，在过去十年中主导了大麻素分析；已经引入了新的衍生化方法、新的离子化方法和用于方法优化的数学模型。
