ESCET-Escuela Superior de Ciencias Experimentales y Tecnología, Departamento de Tecnología Química y Ambiental, Universidad Rey Juan Carlos, C/Tulipán s/n, 28933 Móstoles, Madrid, Spain.
CQM-Centro de Química da Madeira, Universidade da Madeira, Campus da Penteada, 9020-105 Funchal, Portugal.
Toxins (Basel). 2022 Sep 20;14(10):650. doi: 10.3390/toxins14100650.
This work presents an optimized methodology based on the miniaturization of the original QuEChERS (μ-QuEChERS) followed by liquid chromatography coupled to mass spectrometry (HPLC-MS/MS) for the determination of tropane alkaloids (TAs), atropine, and scopolamine in leafy vegetable samples. The analytical methodology was successfully validated, demonstrating quantitation limits (MQL) ≤ 2.3 ng/g, good accuracy, and precision, with recoveries between 90-100% and RSD ≤ 13% for both analytes. The method was applied to the analysis of TA-producing plants (, and ). High concentrations of scopolamine were found in flowers (1771 mg/kg) and leaves (297 mg/kg) of . The highest concentration of atropine was found in flowers of (10.4 mg/kg). Commercial mixed leafy vegetables contaminated with and were analysed to verify the efficacy of the method, showing recoveries between 82 and 110% for both analytes. Finally, the method was applied to the analysis of eighteen samples of leafy vegetables, finding atropine in three samples of mixed leafy vegetables, with concentrations of 2.7, 3.2, and 3.4 ng/g, and in nine samples with concentrations ≤MQL. In turn, scopolamine was only found in a sample of chopped Swiss chard with a concentration ≤MQL.
本工作提出了一种优化的方法，基于原始 QuEChERS（μ-QuEChERS）的微型化，随后进行液相色谱-串联质谱（HPLC-MS/MS）分析，用于测定叶菜类样品中的托烷生物碱（TAs）、阿托品和东莨菪碱。该分析方法得到了成功验证，显示出定量限（MQL）≤2.3ng/g，良好的准确度和精密度，回收率在 90-100%之间，两种分析物的相对标准偏差（RSD）≤13%。该方法应用于产 TA 植物（ 、 和 ）的分析。在 的花（1771mg/kg）和叶（297mg/kg）中发现了高浓度的东莨菪碱。在 的花中发现了最高浓度的阿托品（10.4mg/kg）。对受 和 污染的商业混合叶菜进行了分析，以验证该方法的有效性，两种分析物的回收率在 82-110%之间。最后，该方法应用于 18 个叶菜样品的分析，在三个混合叶菜样品中发现了阿托品，浓度分别为 2.7、3.2 和 3.4ng/g，在九个样品中浓度低于 MQL。另一方面，仅在一份切碎的瑞士菠菜样品中发现了东莨菪碱，浓度低于 MQL。
