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利用高光谱成像技术进行草药质量控制的新方法:鉴别南非钩麻和南非钩麻。

A novel approach in herbal quality control using hyperspectral imaging: discriminating between Sceletium tortuosum and Sceletium crassicaule.

机构信息

Department of Chemistry, Tshwane University of Technology, Private Bag X680, Pretoria, 0001, South Africa.

出版信息

Phytochem Anal. 2013 Nov-Dec;24(6):550-5. doi: 10.1002/pca.2431. Epub 2013 Apr 17.

Abstract

INTRODUCTION

Sceletium tortuosum is the most sought after species of the genus Sceletium and is commonly included in commercial products for the treatment of psychiatric conditions and neurodegenerative diseases. However, this species exhibits several morphological and phytochemical similarities to S. crassicaule.

OBJECTIVES

The aim of this investigation was to use ultrahigh-performance liquid chromatography (UPLC) and hyperspectral imaging, in combination with chemometrics, to distinguish between S. tortuosum and S. crassicaule, and to accurately predict the identity of specimens of both species.

METHODS

Chromatographic profiles of S. tortuosum and S. crassicaule specimens were obtained using UPLC with photodiode array detection. A SisuChema near infrared hyperspectral imaging camera was used for acquiring images of the specimens and the data was processed using chemometric computations.

RESULTS

Chromatographic data for the specimens revealed that both species produce the psychoactive alkaloids that are used as quality control biomarkers. Principal component analysis of the hyperspectral image of reference specimens for the two species yielded two distinct clusters, the one representing S. tortuosum and the other representing S. crassicaule. A partial least squares discriminant analysis model correctly predicted the identity of an external dataset consisting of S. tortuosum or S. crassicaule samples with high accuracy (>94%).

CONCLUSIONS

A combination of hyperspectral imaging and chemometrics offers several advantages over conventional chromatographic profiling when used to distinguish S. tortuosum from S. crassicaule. In addition, the constructed chemometric model can reliably predict the identity of samples of both species from an external dataset.

摘要

简介

龟甲草是弯龟甲草属中最受欢迎的物种,通常包含在用于治疗精神疾病和神经退行性疾病的商业产品中。然而,该物种与大龟甲草在形态和植物化学上有几个相似之处。

目的

本研究旨在利用超高效液相色谱(UPLC)和高光谱成像结合化学计量学,区分弯龟甲草和大龟甲草,并准确预测这两个物种标本的身份。

方法

采用 UPLC 结合光电二极管阵列检测对弯龟甲草和大龟甲草标本的色谱图谱进行了测定。使用 SisuChema 近红外高光谱成像相机获取标本的图像,并对数据进行化学计量学计算处理。

结果

对标本的色谱数据表明,这两个物种都产生了用于质量控制生物标志物的精神活性生物碱。对两种参考物种的高光谱图像的主成分分析得到了两个明显的聚类,一个代表弯龟甲草,另一个代表大龟甲草。偏最小二乘判别分析模型对由弯龟甲草或大龟甲草样本组成的外部数据集的身份进行了准确预测,准确率>94%。

结论

高光谱成像与化学计量学的结合在区分弯龟甲草和大龟甲草方面优于传统的色谱分析。此外,构建的化学计量学模型可以可靠地从外部数据集预测这两个物种样本的身份。

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