EBSI Team, Interdisciplinary Chemistry: Synthesis, Analysis, Modelling (CEISAM), University of Nantes-CNRS UMR 6230, 2 rue de la Houssinière, BP 92208, F-44322 Nantes Cedex 3, France; Research Unit: Technologies et Valorisation Agroalimentaire (TVA), Laboratory of Metrology and Isotopic Fractionation, Faculty of Science, Saint-Joseph University of Beirut, P.O. Box 17-5208 Mar Mikhaël, Beirut 1104 2020, Lebanon.
Research Unit: Technologies et Valorisation Agroalimentaire (TVA), Laboratory of Metrology and Isotopic Fractionation, Faculty of Science, Saint-Joseph University of Beirut, P.O. Box 17-5208 Mar Mikhaël, Beirut 1104 2020, Lebanon.
Food Chem. 2018 Apr 15;245:717-723. doi: 10.1016/j.foodchem.2017.12.005. Epub 2017 Dec 6.
In a previous work, we optimized and used a fast adiabatic C-INEPT (Insensitive Nuclei Enhanced by Polarization Transfer) experiment for the isotopomic analysis of olive oil samples, which allowed us quantifying individual fatty acids within triacylglycerols through multivariate linear regression models. The goal of this study was to validate these models and to evaluate the power of C-INEPT in the authentication of olive oils relative to gas chromatography (GC) and H NMR. In this respect, a new set of olive oil samples was analyzed by these three techniques. The analytical variables thus obtained as well as their corresponding long-term repeatability were compared. As a result, the reliability of the fatty acid quantification models was proven and the best classification of olive oils according to the altitude of the olive grove and to the morphological aspect (color) of the olives was achieved by means of C-INEPT.
在之前的工作中，我们优化并使用了一种快速绝热 C-INEPT（通过极化转移增强的不敏感核）实验，用于橄榄油样品的同位素分析，这使我们能够通过多元线性回归模型定量分析三酰基甘油中的单个脂肪酸。本研究的目的是验证这些模型，并评估 C-INEPT 在相对于气相色谱 (GC) 和 H NMR 对橄榄油进行认证方面的能力。在这方面，使用这三种技术分析了一组新的橄榄油样品。比较了由此获得的分析变量及其相应的长期重复性。结果证明了脂肪酸定量模型的可靠性，并通过 C-INEPT 实现了根据橄榄林的海拔高度和橄榄的形态（颜色）对橄榄油进行最佳分类。
