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用于检测大麻籽油中大麻素的“一键式”分析平台的开发。

Development of a "single-click" analytical platform for the detection of cannabinoids in hemp seed oil.

作者信息

Risoluti Roberta, Gullifa Giuseppina, Battistini Alfredo, Materazzi Stefano

机构信息

Department of Chemistry, Sapienza University of Rome p.le A. Moro 5 00185 Rome Italy

Consiglio per la ricerca in agricoltura e l'analisi dell'economia agraria, Centro di Politiche e Bioeconomia via Pò 14 00198 Italy.

出版信息

RSC Adv. 2020 Dec 9;10(71):43394-43399. doi: 10.1039/d0ra07142k. eCollection 2020 Nov 27.

Abstract

In this work, an innovative screening platform is developed and validated for the on site detection of cannabinoids in hemp seed oil, for food safety control of commercial products. The novelty of this completely automated tool consists of a miniaturized NIR spectrometer operating in a wireless mode that permits processing samples in a rapid and accurate way and to obtain in a single click the early detection of a residual amount of cannabinoids in oil, including cannabidiol (CBD), the psychoactive Δ9-tetrahydrocannabinol (THC) and the Δ9-tetrahydrocannabinolic acid (THCA). Simulated samples were realized to instruct the platform and prediction models were developed by chemometric analysis of the NIR spectra using partial least square regression algorithms. Once calibrated, the platform was used to predict samples acquired in the market and on websites. Validation of the system was achieved by comparing results with those obtained from GC-MS analyses and a good correlation was observed.

摘要

在这项工作中,开发并验证了一种创新的筛选平台,用于现场检测大麻籽油中的大麻素,以控制商业产品的食品安全。这个完全自动化工具的新颖之处在于它是一个以无线模式运行的小型近红外光谱仪,能够快速、准确地处理样品,并通过一键操作实现对油中残留大麻素的早期检测,包括大麻二酚(CBD)、具有精神活性的Δ9-四氢大麻酚(THC)和Δ9-四氢大麻酚酸(THCA)。制备了模拟样品用于指导该平台,并通过使用偏最小二乘回归算法对近红外光谱进行化学计量分析来开发预测模型。校准后,该平台用于预测在市场和网站上获取的样品。通过将结果与气相色谱-质谱联用(GC-MS)分析结果进行比较,实现了系统的验证,并且观察到了良好的相关性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed1b/9058129/23421396d633/d0ra07142k-f1.jpg

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