| Title: | Resolution-optimized headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) for non-targeted olive oil profiling |
| Author(s): | Gerhardt N; Birkenmeier M; Sanders D; Rohn S; Weller P; |
| Address: | "Institute for Instrumental Analytics and Bioanalysis, Mannheim University of Applied Sciences, Paul-Wittsack-Strasse 10, 68163, Mannheim, Germany. Gesellschaft fur Analytische Sensorsysteme mbH, Otto-Hahn-Strasse 15, 44227, Dortmund, Germany. Hamburg School of Food Science, University of Hamburg, Grindelallee 117, 20146, Hamburg, Germany. Institute for Instrumental Analytics and Bioanalysis, Mannheim University of Applied Sciences, Paul-Wittsack-Strasse 10, 68163, Mannheim, Germany. p.weller@hs-mannheim.de" |
| DOI: | 10.1007/s00216-017-0338-2 |
| ISSN/ISBN: | 1618-2650 (Electronic) 1618-2642 (Linking) |
| Abstract: | "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 MATLAB(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. Graphical abstract Principle of the determination of geographic origins of olive oils by chemometric analysis of three-dimensional HS-GC-IMS fingerprints" |
| Keywords: | Discriminant Analysis Food Analysis/methods Gas Chromatography-Mass Spectrometry/*methods Ion Mobility Spectrometry/*methods Italy Olive Oil/*chemistry/classification Principal Component Analysis Spain Volatile Organic Compounds/analysis Gc-ims Geographic; |
| Notes: | "MedlineGerhardt, Natalie Birkenmeier, Markus Sanders, Daniel Rohn, Sascha Weller, Philipp eng Germany 2017/04/19 Anal Bioanal Chem. 2017 Jun; 409(16):3933-3942. doi: 10.1007/s00216-017-0338-2. Epub 2017 Apr 17" |
