Identification and quantification of herbal tea blend raw materials using hyperspectral imaging spectroscopy

The consumption of herbal teas is increasing as consumers become more appreciative of the health benefits. Herbal tea blends, comprising of two or more plant species, are produced with the intention of improving taste and health effects through synergistic actions. As with foods, cosmetics and pharmaceutical products, quality control of herbal teas is important to ensure safety and efficacy. Chromatography-based techniques that are commonly used in quality control require sample preparation using solvents; thus, they are destructive. In this study, hyperspectral imaging spectroscopy is applied as a fast and non-destructive method for the quality control of herbal tea blends. The technique combines conventional spectroscopy and digital imaging to gather chemical information (spectral data) and visualise spatial distribution of chemical constituents within a matrix. Certified raw materials (Sceletium tortuosum and Cyclopia genistoides) and herbal tea blends were sourced from a local supplier. Hyperspectral images of the raw materials and tea blends were captured separately on a sisuChema SWIR (short wave infrared) hyperspectral pushbroom imaging system. The images were analysed using Evince® multivariate analysis software 2.4.0. Principal component analysis (PCA) revealed 52.9% chemical variation between S. tortuosum and C. genistoides raw materials. Partial least squares-discriminant analysis (PLS-DA) models were developed to predict the plant species present in the blend and determine the relative proportions. Based on pixel classification it was possible to visualise the tea blend constituents as S. tortuosum and C. genistoides and quantitatively predict C. genistoides as the major constituent (> 95%) while S. tortuosum was present in relatively lower amounts (< 5%). The observed predictions are close to the company formulation and thus HSI in tandem with multivariate data analysis tools present a useful alternative in the quality control of herbal products.