METABOLOTMIC APPROACH FOR GEOGRAPHICAL ORIGIN DISCRIMINATION OF HAZELNUTS (CORYLUS AVELLANA) BY UPLC-QTOF-MS
S. Klockmann, E. Reiner and M. Fischer
Hamburg School of Food Science, University of Hamburg
Grindelallee 117, 20146 Hamburg, Germany
Ultraperformance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) was used for geographical origin discrimination of hazelnuts (Corylus avellana L.). After initial evaluation different LC-MS methods (non-polar or polar, each in positive or negative ion mode) with samples from harvest year 2014, the LC-MS method analyzing the non-polar metabolome in positive ion mode using Isopropanol/Chloroform 2/1 + 0,1 % BHA as extraction solvent and a 150 x 2.1 mm; 2.6 µm AccucoreTM RP-MS UPLC column was chosen to be best suited for origin differentiation. 196 authentic hazelnut samples from harvest years 2014 and 2015 (Germany, France, Italy, Turkey, Georgia) were analyzed in a non-targeted approach, followed by selecting and identifying 20 key metabolites with significant differences in abundancy, represented by triacylglycerides, diacylglycerides, phosphatidylcholines, phosphatidylethanolamines with varying fatty acid side chains as well as gamma-tocopherol. Three classification models were created using linear discriminant analysis (PCA-LDA), support vector machine classification (SVM) and a customized statistical model based on confidence intervals of selected metabolite levels, all three combined with soft independent modeling of class analogy (SIMCA) as surveillance analysis for the reduction of false positive assignments, yielding 99.5 % training accuracy at its best. Additionally, 40 hazelnut samples for confectionary industry were subsequently used to estimate as realistic as possible the prediction capacity of the previously developed models.
Sven Klockmann is a third year PhD student at the Hamburg School of Food Science (University of Hamburg). In 2014 he finished his study of food chemistry with first state examination and diploma. His research focuses on developing analytical methods for origin discrimination of hazelnuts using LC-MS and NIR applications.