Hyperspectral imaging: a visual tool for quality control of herbal raw material

Hyperspectral imaging (HSI) integrates conventional spectroscopy and imaging to obtain spectral and spatial information from a sample. This non-destructive method can provide species identification in less than a (New York) minute; lightning fast compared to conventional analysis methods such as liquid chromatography. The potential of near infrared (NIR) hyperspectral imaging in combination with chemometric data analysis as a rapid quality control method for commercially important herbal medicines such as Illicium and Echinacea species was investigated. Hyperspectral images of authenticated botanical specimens were acquired using a sisuChema short wave infrared (SWIR) hyperspectral pushbroom imaging system with a spectral range of 920–2514nm. Principal component analysis (PCA) was applied to the images to reduce the high dimensionality of the data, remove background pixels and to visualise the data. The score images and plots were used to interactively assign classes to the data. Classification models were developed using partial least squares discriminant analysis (PLS-DA) and the models were subsequently used to accurately predict the identity of the species introduced as an external dataset, producing a visually interpretable result. Clearly, hyperspectral imaging is ideally suited as a qualitative tool for the quality control of herbal raw material as it is a rapid, accurate, non-destructive method with high prediction ability.