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Hyperspectral Imaging and Chemometric Modeling of Echinacea — A Novel Approach in the Quality Control of Herbal Medicines

机译:紫锥菊的高光谱成像和化学计量学建模—一种草药质量控制的新方法

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摘要

Echinacea species are popularly included in various formulations to treat upper respiratory tract infections. These products are of commercial importance, with a collective sales figure of $132 million in 2009. Due to their close taxonomic alliance it is difficult to distinguish between the three Echinacea species and incidences of incorrectly labeled commercial products have been reported. The potential of hyperspectral imaging as a rapid quality control method for raw material and products containing Echinacea species was investigated. Hyperspectral images of root and leaf material of authentic Echinacea species (E. angustifolia, E. pallida and E. purpurea) were acquired using a sisuChema shortwave infrared (SWIR) hyperspectral pushbroom imaging system with a spectral range of 920–2514 nm. Principal component analysis (PCA) plots showed a clear distinction between the root and leaf samples of the three Echinacea species and further differentiated the roots of different species. A classification model with a high coefficient of determination was constructed to predict the identity of the species included in commercial products. The majority of products (12 out of 20) were convincingly predicted as containing E. purpurea, E. angustifolia or both. The use of ultra performance liquid chromatography-mass spectrometry (UPLC-MS) in the differentiation of the species presented a challenge due to chemical similarities between the solvent extracts. The results show that hyperspectral imaging is an objective and non-destructive quality control method for authenticating raw material.
机译:紫锥菊物种普遍包含在各种制剂中,以治疗上呼吸道感染。这些产品具有商业重要性,2009年的总销售额为1.32亿美元。由于它们紧密的分类学联盟,很难区分这三种紫锥菊属物种,而且据报道,错误地标记了商业产品。研究了高光谱成像作为一种快速质量控制方法对含有紫锥菊属物种的原料和产品的潜力。使用sisuChema短波红外(SWIR)高光谱推扫式成像系统获取了真实紫锥菊属物种(洋紫锥菊,淡色大肠杆菌和紫叶菊)的根和叶材料的高光谱图像,其光谱范围为920-2514 nm。主成分分析(PCA)图显示了三种紫锥菊属植物的根和叶样品之间的明显区别,并进一步区分了不同物种的根。构建具有高确定系数的分类模型,以预测商业产品中所包含物种的身份。令人信服地预测,大多数产品(20种产品中的12种)都含有紫癜大肠杆菌,安氏紫癜大肠杆菌或两者兼有。由于溶剂萃取物之间的化学相似性,在物种的区分中使用超高效液相色谱-质谱(UPLC-MS)提出了挑战。结果表明,高光谱成像是一种客观,无损的原料鉴别质量控制方法。

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