Publications

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Tankeu, S., Vermaak, I., Kamatou, G.P.P., Viljoen, A.M. 2014. Vibrational spectroscopy and chemometric modelling: an economical and robust quality control method for lavender oil. Industrial Crops and Products 59: 234–240.

Lavandula species (Lamiaceae), commonly known as lavender, ranks among the top ten medicinal plants used worldwide and is used and traded extensively in the flavour and fragrance, cosmetic and aromatherapy industries. Many studies continue to confirm the phytotherapeutic potential of lavender oil in the treatment of wounds, rheumatism, muscular pains, dermatitis, acne and eczema amongst many others. Gas chromatography coupled to mass spectrometry with a flame ionisation detector (GC-MS-FID) is the conventional method for the quality assessment of lavender oil. In this study, vibrational spectroscopy methods such as mid infrared (MIR) and near infrared (NIR) in tandem with chemometric data analysis are proposed as alternative methods for the routine quality control of this commercially important essential oil. Sixty lavender oil samples were purchased from a wide range of suppliers and six major and minor compounds (1,8-cineole, (E)-β-ocimene, (Z)-β-ocimene, camphor, linalool and linalyl acetate) were quantified using GC–MS–FID (reference data). Spectral data was acquired for both MIR (4000 – 550 cm-1) and NIR (10 000 – 4000 cm-1) wavelength regions and chemometric modelling applied to develop calibration models. The calibration models revealed good statistical performance where the coefficients of determination obtained for the major compounds of lavender oil were ≥ 0.82. Good coefficients of determination were observed for linalool R2 = 0.99 (MIR) and 0.98 (NIR) as well as linalyl acetate R2= 0.92 (MIR) and 0.90 (NIR). Linalool and linalyl acetate represented about 70% of the total composition of the essential oil. Low values (≤ 1.6) were obtained for the root mean square error of estimation (RMSEE) and root mean square error of prediction (RMSEP) and the predicted data obtained using the constructed calibration models corresponded closely with the reference data, validating the accuracy of the models.




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