期刊
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
卷 409, 期 16, 页码 3933-3942出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s00216-017-0338-2
关键词
GC-IMS; Olive oil; Geographical origin; VOC fingerprints; Non-targeted analysis; Principal component analysis (PCA); k-nearest neighbor; Linear discriminant analysis (LDA)
资金
- Center for Applied Research in Biomedical Mass Spectrometry Mannheim, Germany (ZAFH-ABIMAS)
A prototype gas chromatography-ion mobility spectrometry (GC-IMS) system, hyphenating temperature-ramped headspace GC to a modified drift time IMS cell, was evaluated and compared to a conventional, isothermal capillary column (CC)-IMS system on the example of the geographical differentiation of extra virgin olive oils (EVOO) from Spain and Italy. It allows orthogonal, 2D separation of complex samples and individual detection of compounds in robust and compact benchtop systems. The information from the high-resolution 3D fingerprints of volatile organic compound (VOC) fractions of EVOO samples were extracted by specifically developed chemometric MATLABA (R) routines to differentiate between the different olive oil provenances. A combination of unsupervised principal component analysis (PCA) with two supervised procedures, linear discriminant analysis (LDA) and k-nearest neighbors (kNN), was applied to the experimental data. The results showed very good discrimination between oils of different geographical origins, featuring 98 and 92% overall correct classification rate for PCA-LDA and kNN classifier, respectively. Furthermore, the results showed that the higher resolved 3D fingerprints obtained from the GC-IMS system provide superior resolving power for non-targeted profiling of VOC fractions from highly complex samples such as olive oil.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据