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 essential oils.
Hector R. Juliani1, Jeremy Kapteyn1, Dayton Jones2, AdolFIna R. Koroch1, Mingfu Wang1, Denys Charles3, James E. Simon1 *
1New Use Agriculture and Natural Plant Products Program, Rutgers, The State University of New Jersey, New Brunswick, New Jersey, USA
2Analytical Spectral Devices Inc., Boulder, Colorado, USA
3Frontier Natural Products, Co-Op, Norway, Iowa, USA
email: James E. Simon (jesimon@aesop.rutgers.edu)
*Correspondence to James E. Simon, New Use Agriculture and Natural Plant Products Program, Rutgers, The State University of New Jersey, New Brunswick, New Jersey, USA.
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 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. Copyright © 2006 John Wiley & Sons, Ltd.
Received: 28 April 2005; Revised: 5 May 2005; Accepted: 20 May 2005
Application of near-infrared spectroscopy in quality control and determination of adulteration of african essential oils (full paper)