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- W2334016728 abstract "The quality control of complex herbal medicines is an ongoing process for which simple and rapid analysis methods are required. Hyperspectral imaging (HSI) has been used as a quality control method in the food, agricultural and pharmaceutical industries. HSI acquires both spectral and spatial information through an amalgamation of conventional spectroscopy and imaging. In combination with chemometric analysis, HSI displays compositional differences in an image. As a result, non-destructive analyses can be performed in a much shorter time compared to conventional analysis methods. This study investigated the potential of shortwave infrared (SWIR) hyperspectral imaging and chemometric data analysis as a rapid quality control method for commercially important herbal medicines including; Chinese star anise (Illicium verum), skullcap (Scutellaria laterifolia) and Echinacea spp. The sisuChema SWIR hyperspectral pushbroom imaging system was used to acquire images. Principal component analysis (PCA) was used to investigate compositional differences in the images. Classification models using partial least squares discriminant analysis (PLS-DA) were constructed, optimised and used for prediction of the external datasets. Model 1: toxic Illicium anisatum (Chinese star anise) and Illicium verum (Japanese star anise) (Fig. 1a); Model 2: Echinacea angustifolia, Echinacea pallida and Echinacea purpurea (Fig. 1b); Model 3: Scutellaria laterifolia (Skullcap), Teucrium canadense (American germander) and toxic Teucrium chamaedrys (European germander) (Fig. 1c). The classification models exhibited good R2X_cum and R2Y_cum values and accurately predicted external datasets. Clearly, hyperspectral imaging is ideally suited for the quality control of herbal raw materials as it is a rapid, accurate and non-destructive method with high prediction ability." @default.
- W2334016728 created "2016-06-24" @default.
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- W2334016728 date "2014-10-30" @default.
- W2334016728 modified "2023-10-18" @default.
- W2334016728 title "Making the invisible visible: The application of hyperspectral imaging to the quality control of herbal medicines" @default.
- W2334016728 doi "https://doi.org/10.1055/s-0034-1394494" @default.
- W2334016728 hasPublicationYear "2014" @default.
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