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Ground cinnamon bark (Ceylon cinnamon or “true” cinnamon) is vulnerable to substitution with the related species cinnamon camphora (cassia cinnamon) or to bulking with different parts of the plant such as roots and leaves.  There are a number of test methods, both published and proprietary, including some based on spectroscopic classification chemometrics.

 This paper (open access), from the Joint Research Centre of the European Commission, gives a robust justification for a recommended FT-Raman spectroscopic screening method. The researchers based their reference database on a much wider variety of “true” cinnamon samples on the market than other published methods.  They purchased over 100 market samples of cinnamon bark from a variety of countries and ground their own reference samples.  They also investigated the chemical explanation for all spectral features that underpinned their discriminatory models

 They compared all results with complementary techniques, including GC-MS and XRF, to ensure robustness and reliability. Both of these orthogonal techniques supported the FT-Raman classification results.  XRF is based on discriminatory features independent of FT-Raman i.e. the fact that the elemental content of cassia samples is generally lower than that of Ceylon cinnamon. The detection of certain elements (e.g., Al, Si, Ti, Cr, Fe, Zr, and Pb) was also used as an indication of substitution with organic matter and/or effect by the material used to mill the cinnamon sticks. GC-MS is based on the analysis of several volatile compounds (e.g., camphor, cinnamaldehyde, eugenol, coumarin, cinnamyl acetate) for the detection of substitution of Ceylon cinnamon with cassia as well as the substitution of bark with other parts of the cinnamon plant (leaves, flowers, roots, seeds), based on the difference in relative abundances of the selected compounds. 

 The authors conclude that FT-Raman combined with Principal Component Analysis provides a very efficient and fast approach to detect the substitution of Ceylon and cassia species by Cinnamon camphora, other parts of the plant (e.g., root), and/or inorganic matter, using only cinnamaldehyde as the main marker along p1. Complementary techniques such as GC-MS and XRF can then be used to confirm the type of substitution.

Photo by Angelo Pantazis on Unsplash

This paper (open access) reports the development of a classification model for the geographic origin on black tea based upon measuring a panel of 15 trace elements by X-ray fluorescence (XRF).  XRF is a non-destructive technique.  The only sample preparation required is grinding the tea leaves into a fine powder.

The model could discriminate between 10 major tea-producing regions.  It was built using reference samples obtained, via tea industry contacts, directly from plantations or primary processing facilities.   791 black tea samples were collected in total: Assam (272 samples), Burundi (40 samples), Darjeeling (145 samples), Ethiopia (40 samples), Keemun (115 samples), Kenya region 1 (41 samples), Kenya region 2 (40 samples), Malawi (40 samples), Rwanda (10 samples), and Sri Lanka (48 samples).

Two unsupervised analysis techniques were used to visualize high-dimensional data, and six supervised models were employed to discriminate the ten GI regions.

The authors report that machine learning models, including random forest, support vector machine, k-nearest neighbours, linear discriminate analysis, and the deep learning multilayer perceptron (MLP) model, demonstrated superior predictive capabilities compared to the traditional partial least squares discriminant analysis model. The MLP model achieved the highest performance, with a 97.7 % overall F1 score in predicting the geographical origins of 532 authentic samples across ten GI regions.

The authors also Identified Rb, Sr, Mn, Si, and Cl as geographical markers for African region discrimination.

The conclude that their work could form the basis and foundation for an international database of tea Geographic Origin, enabling cheap and quick authenticity verification testing.

Photo by Oleg Guijinsky on Unsplash

This paper (open access) reports the outcome of a study in which 104 cinnamon samples purchased at retailers in EU countries, have been investigated. The study showed that a high share of samples, 66.3%, either did not fulfil quality criteria set by international standards, were not compliant with European food safety legislation, were suspicious of fraud, or could be toxic for children due to a high content of coumarin. 

Substitution of Ceylon by Cassia cinnamon, so far the most recognised type of fraud, was not the problem most frequently detected in this study.  Many samples were classified as either strongly suspicious or suspicious, based upon being statistical outliers, but further investigation would be needed to confirm if adulterated. 

The authors report that the use of multiple analytical techniques, namely Energy Dispersive X-Ray Fluorescence, Head Space-Gas Chromatography-Mass Spectrometry, q-PCR, and Termogravimetric Analyses, was needed to cover the full range of irregularities detected in the study. 

Photo by Angelo Pantazis on Unsplash