Vibrational Spectroscopy as a Rapid Quality Control Method for Melaleuca alternifolia Cheel (Tea Tree Oil)

Authors

  • Sidonie Tankeu,

    1. Department of Pharmaceutical Sciences, Faculty of Science, Tshwane University of Technology, Pretoria, South Africa
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  • Ilze Vermaak,

    Corresponding author
    1. Department of Pharmaceutical Sciences, Faculty of Science, Tshwane University of Technology, Pretoria, South Africa
    • Correspondence to: I. Vermaak, Department of Pharmaceutical Sciences, Faculty of Science, Tshwane University of Technology, Private Bag X680, Pretoria, 0001, South Africa. E-mail: vermaaki@tut.ac.za

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  • Guy Kamatou,

    1. Department of Pharmaceutical Sciences, Faculty of Science, Tshwane University of Technology, Pretoria, South Africa
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  • Alvaro Viljoen

    1. Department of Pharmaceutical Sciences, Faculty of Science, Tshwane University of Technology, Pretoria, South Africa
    2. Department of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmacy, King Abdulaziz University, Jeddah, Saudi Arabia
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ABSTRACT

Introduction

Tea tree oil (TTO) is an important commercial oil which has found application in the flavour, fragrance and cosmetic industries. The quality is determined by the relative concentration of its major constituents: 1,8-cineole, terpinen-4-ol, α-terpineol, α-terpinene, terpinolene, γ-terpinene and limonene. Gas chromatography coupled to mass spectrometry (GC–MS) is traditionally used for qualitative and quantitative analyses but is expensive and time consuming.

Objective

To evaluate the use of vibrational spectroscopy in tandem with chemometric data analysis as a fast and low-cost alternative method for the quality control of TTO.

Methods

Spectral data were acquired in both the mid-infrared (MIR) and near infrared (NIR) wavelength regions and reference data obtained using GC–MS with flame ionisation detection (FID). Principal component analysis (PCA) was used to investigate the data by observing clustering and identifying outliers. Partial least squares (PLS) multivariate calibration models were constructed for the quantification of the seven major constituents.

Results

High correlation coefficients (R2) of ≥ 0.75 were obtained for the seven major compounds and 1,8-cineole showed the best correlation coefficients for both MIR and NIR data (R2 = 0.97 and 0.95, respectively). Low values were obtained for the root mean square error of estimation (RMSEE) and root mean square error of prediction (RMSEP) values thereby confirming accuracy.

Conclusion

The accurate prediction of the external dataset after introduction into the models confirmed that both MIR and NIR spectroscopy are valuable methods for quantification of the major compounds of TTO when compared with the reference data obtained using GC–MS. Copyright © 2013 John Wiley & Sons, Ltd.

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