Non-destructive quality assessment of herbal tea blends using hyperspectral imaging

In this study, hyperspectral imaging 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 and visualise spatial distribution of chemical constituents within a matrix. Certified raw materials (Sceletium tortuosum and Cyclopia genistoides) and herbal tea blends were acquired from Parceval Pty (Ltd). Hyperspectral images of the raw material and tea blends were captured on a SisuChema® SWIR (short wave infrared) hyperspectral pushbroom imaging system using ChemaDAQ® software. The images were analysed using Evince® multivariate analysis software 2.4.0. Principal component analysis (PCA) revealed 54.2% chemical variation between S. tortuosum and C. genistoides raw materials. A partial least squares-discriminant analysis (PLS-DA) model with predictive ability of 95.8% was developed. 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 (>97%) while S. tortuosum was present in lower amounts (<3%). The predictions confirm that HSI is a potentially favourable visual tool for the quality assessment of herbal tea blends. However, due to low instrument sensitivity quantitative determinations showed some deviation from the company formulation. Graphical abstract
Source: Phytochemistry Letters - Category: Chemistry Source Type: research