Food authentication goes green: Determination of the geographical origin of grain maize (Zea mays L.) using direct analysis in real time mass spectrometry (DART-MS)

Abstract

Time savings, environmental friendliness and cost reduction are important criteria to determine the authenticity of feed and food in routine analysis. One analytical technique that is especially promising in terms of these criteria in metabolomics studies is Direct Analysis in Real Time Mass Spectrometry (DART-MS). In the present study, DART-MS is applied to 200 grain maize samples from seven geographical origins to develop a data processing workflow and an approach for origin analysis of grain maize. For the first time, such a large sample set was investigated using a DART-MS-based non-targeted lipidomics approach. Various open-source programs were used for pre-processing and random forest (RF) combined with repeated cross-validation was used for classification, resulting in an accuracy of 84.4%. Subsequently, the most important markers identified by RF, belonging to the classes of mono-, di- and triacylglycerols, were identified using DART-MS2. The chosen method significantly minimizes the time and solvent consumption compared to classic liquid chromatography electrospray ionization mass spectrometric (LC-ESI-MS) strategies and thus offers a more cost-effective and environmentally friendly alternative. Furthermore, the results show the high potential for determining the geographical origin of grain maize using DART-MS.