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

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 essent...

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Bibliographic Details
Published in:Phytochemical analysis 2006-03, Vol.17 (2), p.121-128
Main Authors: Juliani, H.R, Kapteyn, J, Jones, D, Koroch, A.R, Wang, M, Charles, D, Simon, J.E
Format: Article
Language:English
Subjects:
adulterated products
Africa
chemical analysis
chemical composition
Cinnamomum camphora
Cinnamomum verum
Cinnamomum zeylanicum
Drug Contamination
essential oils
Eugenia
GC-FID
Lauraceae
Lauraceae - chemistry
Lippia - chemistry
Lippia multiflora
Myrtaceae
near-infrared spectroscopy
Plant Oils - chemistry
qualitative analysis
Quality Control
Ravensara aromatica
Spectrophotometry, Infrared - methods
Syzygium - chemistry
Syzygium aromaticum
Verbenaceae
volatile oils
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Summary: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 greater than or equal to 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 rapid identification of individual essential oils, for product authentication, and for the detection of adulteration.
ISSN:0958-0344
1099-1565
DOI:10.1002/pca.895