PMID: 16634289Apr 26, 2006Paper

Application of near-infrared spectroscopy in quality control and determination of adulteration of African essential oils

Phytochemical Analysis : PCA
Hector R JulianiJames E Simon

Abstract

An evaluation has been made of the potential of near-infrared (NIR) technologies in the assessment of essential oil components and in the identification of individual essential oils. The results showed that cross-validation models are able to predict accurately almost all of the components of essential oils. In different cinnamon (Cinnamomum zeylanicum) and clove (Syzygium aromaticum) essential oils, which showed a similar composition, 23 components (representing 97.8-99.9% of the oil) were accurately predicted, as well as 20 components (93.0-99.1%) in Cinnamomum camphora (ravintsara), 32 components (92.3-98.1%) in Ravensara aromatica (ravensara), and 26 components (96.6-98.4%) in Lippia multiflora. For almost all of the components, the modelled and reference values obtained by GC-FID were highly correlated (r2 > or = 0.985) and exhibited a low variance (less than 5%). The model was also able to discriminate between the ravintsara and ravensara essential oils. It was shown that two commercial oils labelled as R. aromatica were actually ravintsara (C. camphora), revealing the misidentification of these essential oils in the marketplace. The study demonstrates the application of NIR technology as a quality control tool for the ra...Continue Reading

References

Feb 24, 2001·The Journal of Pharmacy and Pharmacology·N D WilsonA C Moffat
May 15, 2002·Journal of Pharmaceutical and Biomedical Analysis·I RagerK-A Kovar
Jun 19, 2002·Analytical Chemistry·Magali LaasonenHeikki Vuorela

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Citations

Jul 28, 2015·Natural Product Research·Sara CannasPaola Molicotti
Aug 13, 2013·Phytochemical Analysis : PCA·Sidonie TankeuAlvaro Viljoen
Jul 31, 2019·Phytochemical Analysis : PCA·Cristiane I CerceauFyaz M D Ismail

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