Taylan Osman, Cebi Nur, Sagdic Osman
Department of Industrial Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
Department of Food Engineering, Faculty of Chemical and Metallurgical Engineering, Yıldız Technical University, İstanbul 34210, Turkey.
Foods. 2021 Jan 20;10(2):202. doi: 10.3390/foods10020202.
essential oil (EO) has high economic importance because of its wide usage area and health-beneficial properties. Besides health-beneficial properties, EO has great importance in the flavor and food industries because of its unique sensory and quality properties. High-valued essential oils are prone to being adulterated with economic motivations. This kind of adulteration deteriorates the quality of authentic essential oil, injures the consumers, and causes negative effects on the whole supply chain from producer to the consumer. The current research used fast, economic, robust, reliable, and effective ATR-FTIR spectroscopy coupled chemometrics of hierarchical cluster analysis(HCA), principal component analysis (PCA), partial least squares regression (PLSR) and principal component regression (PCR) for monitoring of EO and L-menthol adulteration in EOs. Adulterant contents ( and L-menthol) were successfully calculated using PLSR and PCR models. Standard error of the cross-validation SECV values changed between 0.06 and 2.14. Additionally, bias and press values showed alteration between 0.06 and1.43 and 0.03 and 41.15, respectively. Authentic was successfully distinguished from adulterated samples, and L-menthol, by HCA and PCA analysis. The results showed that attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, coupled with chemometrics could be effectively used for monitoring various adulterants in essential oils.
由于精油(EO)的广泛使用领域和有益健康的特性,它具有很高的经济重要性。除了有益健康的特性外,由于其独特的感官和品质特性,精油在香料和食品工业中也具有重要意义。高价值的精油容易因经济动机而被掺假。这种掺假会降低纯正精油的质量,损害消费者利益,并对从生产商到消费者的整个供应链产生负面影响。当前的研究使用了快速、经济、稳健、可靠且有效的衰减全反射傅里叶变换红外光谱(ATR-FTIR)结合层次聚类分析(HCA)、主成分分析(PCA)、偏最小二乘回归(PLSR)和主成分回归(PCR)等化学计量学方法来监测精油中精油和L-薄荷醇的掺假情况。使用PLSR和PCR模型成功计算出掺假物含量(和L-薄荷醇)。交叉验证标准误差SECV值在0.06至2.14之间变化。此外,偏差和预测残差平方和值分别在0.06至1.43和0.03至41.15之间变化。通过HCA和PCA分析,成功地将纯正的与掺假样品、和L-薄荷醇区分开来。结果表明,衰减全反射傅里叶变换红外光谱(ATR-FTIR)结合化学计量学可有效地用于监测精油中的各种掺假物。