The authors of this study (open access) developed a chemometric classification model to distinguish true cinnamon from its potential adulterants, Cassia or Saigon cinnamons. The model is based on simple and low-cost LC-UV analysis of four marker chemicals: eugenol, cinnamaldehyde, coumarin and cinnamic acid. Sample pre-treatment was vortexing/sonicating with methanol followed by centrifugation. Reference samples for the model were purchased from retail outlets rather than fully traceable sources; 25 samples of each type of cinnamon, including both sticks and powder. The model was first constructed to differentiate pure powders. Then the authors used an experimental design on a training set of in-house prepared mixtures (down to 1%/99% mixes) and a Partial Least Squares algorithm to model the classification of mixtures. They found the model was linear and – in the case of true cinnamon mixed with either of the two adulterants – could discriminate adulteration down to 1%. The model could not discriminate Cassia from Saigon cinnamons but the authors consider this a less important question.
Image from the published study.
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