Jiménez-Carvelo Ana M, Pérez-Castaño Estefanía, González-Casado Antonio, Cuadros-Rodríguez Luis
Department of Analytical Chemistry, University of Granada, c/ Fuentenueva, s.n., E-18071 Granada, Spain.
Department of Analytical Chemistry, University of Granada, c/ Fuentenueva, s.n., E-18071 Granada, Spain.
Food Chem. 2017 Apr 15;221:1784-1791. doi: 10.1016/j.foodchem.2016.10.103. Epub 2016 Oct 24.
A new method for differentiation of olive oil (independently of the quality category) from other vegetable oils (canola, safflower, corn, peanut, seeds, grapeseed, palm, linseed, sesame and soybean) has been developed. The analytical procedure for chromatographic fingerprinting of the methyl-transesterified fraction of each vegetable oil, using normal-phase liquid chromatography, is described and the chemometric strategies applied and discussed. Some chemometric methods, such as k-nearest neighbours (kNN), partial least squared-discriminant analysis (PLS-DA), support vector machine classification analysis (SVM-C), and soft independent modelling of class analogies (SIMCA), were applied to build classification models. Performance of the classification was evaluated and ranked using several classification quality metrics. The discriminant analysis, based on the use of one input-class, (plus a dummy class) was applied for the first time in this study.
已开发出一种新方法，可将橄榄油（与质量类别无关）与其他植物油（菜籽油、红花油、玉米油、花生油、种子油、葡萄籽油、棕榈油、亚麻籽油、芝麻油和大豆油）区分开来。描述了使用正相液相色谱法对每种植物油的甲基酯交换馏分进行色谱指纹分析的分析程序，并应用和讨论了化学计量学策略。应用了一些化学计量学方法，如k近邻法（kNN）、偏最小二乘判别分析（PLS-DA）、支持向量机分类分析（SVM-C）和类类比软独立建模（SIMCA）来建立分类模型。使用几种分类质量指标对分类性能进行了评估和排名。基于使用一个输入类别（加一个虚拟类别）的判别分析在本研究中首次应用。
