Department of Pharmaceutical Sciences, Faculty of Science, Tshwane University of Technology, Private Bag X680, Pretoria, 0001, South Africa.
Phytochem Anal. 2014 Jan-Feb;25(1):81-8. doi: 10.1002/pca.2470. Epub 2013 Aug 10.
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.
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.
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.
High correlation coefficients (R(2) ) 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 (R(2) = 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.
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.
茶树油（TTO）是一种重要的商业用油，已在香料、香精和化妆品行业得到应用。其质量由其主要成分的相对浓度决定：1,8-桉叶素、松油烯-4-醇、α-萜品醇、α-萜品烯、萜品油烯、γ-萜品烯和柠檬烯。气相色谱法与质谱联用（GC-MS）传统上用于定性和定量分析，但成本高且耗时。
评估振动光谱与化学计量数据分析相结合作为 TTO 质量控制的快速、低成本替代方法的用途。
在中红外（MIR）和近红外（NIR）波长区域获取光谱数据，并使用带有火焰离子化检测（FID）的 GC-MS 获得参考数据。主成分分析（PCA）用于通过观察聚类和识别异常值来研究数据。偏最小二乘（PLS）多元校准模型用于对七种主要成分进行定量。
对于七种主要化合物，均获得了相关性系数（R(2)）≥0.75 的高值，并且 1,8-桉叶素在 MIR 和 NIR 数据中均表现出最佳的相关性系数（R(2)分别为 0.97 和 0.95）。估计的均方根误差（RMSEE）和预测的均方根误差（RMSEP）值较低，从而确认了准确性。
在将外部数据集引入模型后进行准确预测，证实了 MIR 和 NIR 光谱法在与使用 GC-MS 获得的参考数据相比时，是定量 TTO 主要化合物的有价值方法。版权所有©2013 年 John Wiley & Sons, Ltd.
