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Ultrasound-assisted extraction and dispersive liquid–liquid microextraction coupled with gas chromatography-mass spectrometry for the sensitive determination of essential oil components in lavender

机译:超声辅助萃取-液-液分散微萃取-气相色谱-质谱联用灵敏测定薰衣草中的精油成分

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In this research, a novel method based on ultrasound-assisted extraction and dispersive liquid–liquid microextraction (UAE-DLLME) coupled with gas chromatography-mass spectrometry (GC-MS) has been successfully developed for the determination of essential oil constituents in lavender. The effective parameters of UAE-DLLME, including the type of extraction solvent, type and volume of preconcentration solvent, type and volume of disperser solvent, extraction temperature, and extraction time, were studied and optimized in detail. The optimal analytical conditions were as follows: 2 mL 50% ethanol as the extraction solvent, 150 μL methanol as the disperser solvent, 40 μL CCl4 as the preconcentration solvent, an extraction time of 20 min and an extraction temperature of 50 °C. Under the optimum conditions, a total of 13 samples of three varieties of lavender were analyzed and 64 compounds were identified. The precision of UAE-DLLME-GC-MS was evaluated and the relative standard deviation (RSD) was below 9% (n = 5). Good linearity with correlation coefficients of 0.9982 was obtained; limits of detection ranging from 1.75 to 7.50 ng indicated high sensitivity. Principal component analysis (PCA) was used to distinguish different varieties of lavender. This is the first application of UAE-DLLME for the analysis of essential oil constituents in lavender. The results showed that UAE-DLLME-GC-MS is a fast, sensitive, simple and small sample consumption method for the determination of essential oils in plant materials.
机译:在这项研究中,已经成功开发了一种基于超声辅助萃取和液-液微分散分散萃取(UAE-DLLME)结合气相色谱-质谱法(GC-MS)的新方法,用于测定薰衣草中的精油成分。研究和优化了UAE-DLLME的有效参数,包括萃取溶剂的类型,预浓缩溶剂的类型和体积,分散剂溶剂的类型和体积,萃取温度和萃取时间。最佳分析条件如下:2 mL 50%乙醇作为萃取溶剂,150μL甲醇作为分散溶剂,40μLCCl4作为预浓缩溶剂,萃取时间为20分钟,萃取温度为50°C。在最佳条件下,共分析了三种薰衣草品种的13个样品,并鉴定了64种化合物。评估了UAE-DLLME-GC-MS的精度,相对标准偏差(RSD)低于9%(n = 5)。获得了良好的线性,相关系数> 0.9982;检出限在1.75到7.50 ng之间,表明灵敏度高。主成分分析(PCA)用于区分薰衣草的不同品种。这是UAE-DLLME在分析薰衣草精油成分中的首次应用。结果表明,UAE-DLLME-GC-MS是一种用于测定植物材料中精油的快速,灵敏,简单和小样品消耗的方法。

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