College of Pharmacy, Chungnam National University, Daejeon, Korea.
Phytochem Anal. 2012 Jul-Aug;23(4):359-64. doi: 10.1002/pca.1365. Epub 2011 Oct 18.
Rhubarb is a traditional Chinese medicine derived from the rhizome of three species: Rheum tanguticum, Rheum palmatum and Rheum officinale. There are several species that are often misidentified as rhubarb. Taxonomical identification of these various species can be challenging. We have developed an HPLC-based species classification to identify rhubarb.
The objective of this study was to develop a simple HPLC method for the simultaneous determination of bioactive compounds and identification of medicinal rhubarb rhizome and non-medicinal species.
Quantitative analysis was performed on a C₁₈-column using 0.05 M aqueous phosphoric acid and acetonitrile as the mobile phase under gradient conditions with ultraviolet detection at 280 nm. The method was validated with respect to linearity, accuracy, precision, and recovery. Statistical analysis was used to classify different groups of species.
All calibration curves showed good linearity (r ≥ 0.9995). The method showed good repeatability with intra- and inter-day standard deviations of less than 1.13% and 1.32%, respectively. The accuracy and recovery of all marker compounds were in the ranges of 98.0 to 102.6% and 99.21 to 102.04%, respectively. Seventeen peaks were selected, and 39 known and 57 unknown samples were classified into five species based on linear discriminant analysis with an accuracy of 100%.
A chemical-based species classification method of rhubarb using simultaneous determination of bioactive compounds by HPLC was developed with 39 known samples of five different species and successfully applied to identify 57 unknown samples collected from Korea and China.
大黄是一种传统的中药,来源于三个物种的根茎:唐古特大黄、掌叶大黄和药用大黄。有几个物种经常被错误地鉴定为大黄。这些不同物种的分类鉴定可能具有挑战性。我们已经开发了一种基于 HPLC 的物种分类方法来鉴定大黄。
本研究的目的是开发一种简单的 HPLC 方法,用于同时测定生物活性化合物,并鉴定药用大黄根茎和非药用物种。
在 C₁₈ 柱上使用 0.05 M 磷酸水溶液和乙腈作为流动相,在梯度条件下进行定量分析,在 280nm 处进行紫外检测。该方法在线性、准确性、精密度和回收率方面进行了验证。统计分析用于对不同物种组进行分类。
所有校准曲线均表现出良好的线性(r≥0.9995)。该方法具有良好的重复性,日内和日间标准偏差均小于 1.13%和 1.32%。所有标记化合物的准确度和回收率均在 98.0%至 102.6%和 99.21%至 102.04%之间。选择了 17 个峰,基于线性判别分析,用 39 个已知的 57 个未知样本将其分为五个物种,准确率为 100%。
建立了一种基于大黄中生物活性化合物同时测定的 HPLC 化学物种分类方法,该方法用 5 个不同物种的 39 个已知样本进行了验证,并成功应用于鉴定从韩国和中国收集的 57 个未知样本。