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采用薄层色谱扫描法(HPTLC)测定苦橙皮中辛弗林和去甲肾上腺素。

Determination of synephrine and octopamine in bitter orange peel by HPTLC with densitometry.

作者信息

Shawky Eman

机构信息

Faculty of Pharmacy, Department of Pharmacognosy, Alexandria University, Alkhartoom Square, Alexandria 21521, Egypt

出版信息

J Chromatogr Sci. 2014 Sep;52(8):899-904. doi: 10.1093/chromsci/bmt113. Epub 2013 Aug 2.

Abstract

This paper presents the development and validation of an improved method for the simultaneous analysis of synephrine and octopamine using high-performance thin-layer chromatography with densitometric detection. Separation was performed on silica gel 60F254 plates. The mobile phase is comprised of methanol, ethylacetate, methylene chloride and concentrated ammonia (2:2:1:0.05, v:v:v:v). The Rf values were 0.292 ± 0.0083 and 0.413 ± 0.0089 for synephrine and octopamine, respectively (n = 9). Ultraviolet absorbance detection at 277 nm was used for the alkaloids detection. Specificity, accuracy (recovery rates were between 96 and 99%) and precision (in both cases intra-day precision and inter-day precision were ≤ 2.0%) of the method were determined. Their amounts were calculated using the regression equations of the calibration curves which were linear in the range 0.2-1.2 µg/spot. The amounts of alkaloids in basic methanolic extracts of bitter orange peel measured by the method were 0.253 and 0.142% for synephrine and octopamine, respectively. Most of the factors evaluated in the robustness test were found to have an insignificant effect on the selected responses at 95% confidence level. The method was validated giving rise to a dependable and high-throughput procedure well suited to routine application.

摘要

本文介绍了一种改进的同时分析辛弗林和去甲肾上腺素的方法的开发与验证,该方法采用高效薄层色谱-密度测定法。在硅胶60F254板上进行分离。流动相由甲醇、乙酸乙酯、二氯甲烷和浓氨水(2:2:1:0.05,v:v:v:v)组成。辛弗林和去甲肾上腺素的Rf值分别为0.292±0.0083和0.413±0.0089(n = 9)。在277nm处采用紫外吸光度检测法检测生物碱。测定了该方法的特异性、准确度(回收率在96%至99%之间)和精密度(日内精密度和日间精密度均≤2.0%)。使用校准曲线的回归方程计算其含量,校准曲线在0.2-1.2μg/斑点范围内呈线性。用该方法测定的苦橙皮碱性甲醇提取物中生物碱的含量,辛弗林和去甲肾上腺素分别为0.253%和0.142%。在稳健性测试中评估的大多数因素在95%置信水平下对选定的响应影响不显著。该方法经过验证,产生了一种可靠且高通量的程序,非常适合常规应用。

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