Cebi Nur
Department of Food Engineering, Faculty of Chemical and Metallurgical Engineering, Yıldız Technical University, İstanbul 34210, Turkey.
Foods. 2021 Aug 11;10(8):1848. doi: 10.3390/foods10081848.
essential oil is an essential oil that has the greatest industrial importance due to its unique quality properties. The study used ATR-FTIR (attenuated total reflectance-Fourier transform infrared) spectroscopy coupled with chemometrics of PLSR (partial least squares regression) and PCR (principal component regression) for quantification of probable adulterants of geranium essential oil (GEO), palmarosa essential oil (PEO) and phenyl ethyl alcohol (PEOH). Hierarchical cluster analysis was performed to observe the classification pattern of essential oil, spiked samples and adulterants. essential oil was spiked with each adulterant at concentrations of 0-100% (/). Excellent R (regression coefficient) values (≥0.96) were obtained in all PLSR and PCR cross-validation models. The SECV (standard error of cross-validation) values ranged between 0.43 and 4.15. The lowest SECV and bias values were observed in the PLSR and PCR models, which were built by using the raw FTIR spectra of all samples. Hierarchical cluster analysis through Ward's algorithm and Euclidian distance had high potential to observe the classification pattern of all adulterated and authentic samples. In conclusion, the combination of ATR-FTIR spectroscopy with multivariate analysis can be used for rapid, cost-effective, easy, reliable and high-throughput detection of GEO, PEO and PEOH in essential oil.
精油是一种因其独特的品质特性而具有最大工业重要性的精油。该研究使用衰减全反射傅里叶变换红外(ATR-FTIR)光谱结合偏最小二乘回归(PLSR)和主成分回归(PCR)化学计量学来定量天竺葵精油(GEO)、玫瑰草精油(PEO)和苯乙醇(PEOH)的可能掺假物。进行层次聚类分析以观察精油、加标样品和掺假物的分类模式。精油中分别加入浓度为0-100%(/)的每种掺假物。在所有PLSR和PCR交叉验证模型中均获得了优异的R(回归系数)值(≥0.96)。交叉验证标准误差(SECV)值在0.43至4.15之间。在使用所有样品的原始FTIR光谱建立的PLSR和PCR模型中观察到最低的SECV和偏差值。通过Ward算法和欧几里得距离进行的层次聚类分析具有很高的潜力来观察所有掺假和正品样品的分类模式。总之,ATR-FTIR光谱与多变量分析相结合可用于快速、经济高效、简便、可靠且高通量地检测精油中的GEO、PEO和PEOH。
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