López-Feria Silvia, Cárdenas Soledad, García-Mesa José Antonio, Valcárcel Miguel
Department of Analytical Chemistry, Marie Curie Building (Annex), Campus de Rabanales, University of Córdoba, E-14071, Spain.
Talanta. 2008 May 30;75(4):937-43. doi: 10.1016/j.talanta.2007.12.033. Epub 2007 Dec 31.
A headspace-mass spectrometry (HS-MS) coupling designed for the sensory characterization and classification of extra virgin olive oil on the basis of its protected designation of origin, olive variety and geographical origin is reported. The procedure involves the headspace generation and the direct injection of the homogenized gaseous phase into a mass spectrometer through a transfer line. The results obtained were chemometrically treated to achieve the best model capable of discriminating between the different olive oil categories. For this purpose, several procedures for variables selection, data pretreatments and unsupervised techniques were evaluated. In addition, K-nearest neighbor and soft independent modeling of class analogy algorithms were employed to the classification models building. Taking into account the prediction results obtained (ca. 87% of samples correctly classified and a specificity of ca. 97%), it can be concluded than the HS-MS coupling is, with an adequate chemometric treatment, an appropriate technique for routine control.
报道了一种顶空-质谱联用技术（HS-MS），该技术旨在基于特级初榨橄榄油的原产地保护名称、橄榄品种和地理来源对其进行感官表征和分类。该过程包括顶空生成以及通过传输线将均质化的气相直接注入质谱仪。对获得的结果进行化学计量学处理，以获得能够区分不同橄榄油类别的最佳模型。为此，评估了几种变量选择、数据预处理和无监督技术的程序。此外，采用K近邻算法和类类比软独立建模算法构建分类模型。考虑到所获得的预测结果（约87%的样品正确分类，特异性约为97%），可以得出结论，经过适当的化学计量学处理后，HS-MS联用技术是一种适用于常规控制的合适技术。
