Abstract
Parallel to the growing global interest in alternative medical therapies, high measures
of counterfeit pharmaceuticals enter the global market and, therefore, detection of
such marketed products is essential. This article throws an illuminating spot on the
adulteration of Cinnamomum verum (Cinnamomum zeylanicum) with Cinnamomum cassia and exhaustively extracted C. verum. A speedy and nondestructive near-infrared method in conjunction with the mathematical
tools of chemometrics was used to distinguish between genuine cinnamon and its common
adulterants. The principal component analysis and the hierarchical cluster analysis
models successfully discriminated between unadulterated and adulterated samples. In
the second part of the work, soft independent modeling of class analogy was implemented
to construct a chemometric model to authenticate C. verum samples. The constructed model could successfully predict and judge the quality of
C. verum powder without any misleading predictions. Finally, partial least squares regression
was approached to establish the correlation for adulterated samples regarding their
cassia and exhausted cinnamon content. The R2
of calibration and validation were all higher than 0.9, while the root mean square
errors were all lower than 0.05, indicating that the established models were successful.
Overall, the developed models were shown to have significant potential as time-saving
and accurate methods for identification of true cinnamon powder, which can help guarantee
both quality aspects of identity and purity of the herbal drug by avoiding its adulteration
and could be implemented as a routine screening in its quality control with no need
for any sample preparation.
Key words
NIR diffuse reflectance spectroscopy - chemometrics -
Cinnamomum verum
-
Cinnamomum cassia
- Laurareae - adulteration
