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Food Authentication: Multi-elemental analysis of white asparagus for provenance discrimination

Author:
Richter, Bernadette, Gurk, Stephanie, Wagner, Deniz, Bockmayr, Michael, Fischer, Markus
Source:
Food chemistry 2019
ISSN:
0308-8146
Subject:
asparagus spears, atomic absorption spectrometry, cobalt, lithium, prediction, product authenticity, provenance, rare earth elements, rubidium, strontium, support vector machines, uranium, China, Germany, Greece, Netherlands, Peru, Poland, Spain
Abstract:
Prediction of the geographic origin of white asparagus was realized using inductively coupled plasma mass spectrometry (ICP-MS) and machine learning techniques. The elemental profile of 319 asparagus samples originating from Germany, Poland, the Netherlands, Greece, Spain, China and Peru was determined. Using a support vector machine (SVM) combined with nested cross-validation, a prediction accuracy of 91.2% was achieved when classifying the country of origin. Accuracy can be increased up to 98% on subsets of samples with high SVM prediction scores. Most relevant elements for provenance discrimination were lithium, cobalt, rubidium, strontium, uranium and the rare earth elements. In addition, the multi-elemental method provided specific fingerprints of asparagus cultivation sites as German samples could be assigned correctly with an accuracy of 82.6%. Asparagus variety and harvest year had no significant influence on provenance distinction, which further underlines the robustness of this study.
Agid:
6285186