Discriminating cinnamon species and geographic origin using HPLC-UV and chemometrics

The aim of this study was to evaluate biomarkers for the differentiation and classification of cinnamon species and geographical origin. A reverse phase high performance liquid chromatography method with UV-Vis detection was used to quantify the following biomarkers: coumarin, cinnamic acid, cinnamaldehyde and eugenol. A total of 23 cinnamon samples were analysed and processed using chemometric methods. Besides commonly used principal component analysis, uniform manifold approximation and projection was also used for exploratory analysis. Next, combination of dimensions reduction and classification algorithms were used for the development of 16 classification models. The models were validated using the bootstrapping resampling method. The best classification was achieved with the combination of principal component analysis - regularised discriminant analysis model with an overall accuracy of 84.0% and 89.2% in discriminating cinnamon species and their geographical origin, respectively. In addition, the samples were successfully classified according to their shape and whether the cinnamon samples were certified as "bio" organic.