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Non-targeted LC-MS metabolomics approach towards an authentication of the geographical origin of grain maize (Zea mays L.) samples

Zugehörigkeit
Hamburg School of Food Science, Institute of Food Chemistry, University of Hamburg, Grindelallee 117, Hamburg, Germany
Schütz, David;
Zugehörigkeit
Department Safety in the Food Chain, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Str. 8-10, Berlin, Germany
Achten, Elisabeth;
Zugehörigkeit
Hamburg School of Food Science, Institute of Food Chemistry, University of Hamburg, Grindelallee 117, Hamburg, Germany
Creydt, Marina;
ORCID
0000-0003-0916-7192
Zugehörigkeit
German Federal Institute for Risk Assessment (BfR), Department 8 Safety in the Food Chain, Unit 83 Product Identity, Supply Chains and Traceability, Germany
Riedl, Janet;
Zugehörigkeit
Hamburg School of Food Science, Institute of Food Chemistry, University of Hamburg, Grindelallee 117, Hamburg, Germany
Fischer, Markus

Safety along the food and feed supply chain is an emerging topic and closely linked to the ability to analytical trace the geographical origin of food or feed. In this study, ultra-performance liquid chromatography coupled with electrospray ionization quadrupole-time-of-flight mass spec-trometry was used to trace back the geographical origin of 151 grain maize (Zea mays L.) samples from seven countries using a high resolution non-targeted metabolomics approach. Multivariate data analysis and univariate statistics were used to identify promising marker features related to geographical origin. Classification using only 20 selected markers with the Random Forest algorithm led to 90.5% correctly classified samples with 100 times repeated 10-fold cross-validation. The selected markers were assigned to the class of triglycerides, diglycerides and phospholipids. The marker set was further evaluated for its ability to separate between one sample class and the rest of the dataset, yielding accuracies above 89%. This demonstrates the high potential of the non-polar metabolome to authenticate the geographic origin of grain maize samples. Furthermore, this suggests that focusing on only a few lipids with high potential for grain maize authentication could be a promising approach for later transfer of the method to routine analysis.

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