Provenance profiling: SN- and LA-ICP-MS based authentication of strawberries.

Abstract

Depending on their origin, strawberries can vary greatly in price. For example, fruit from Germany may be costly compared to imported goods, encouraging financially motivated food fraud. In this study, two different sample preparation techniques - acid digestion and laser ablation - were applied to determine the provenance of strawberries using ICP-MS and multivariate data analysis. 403 samples from six countries (Egypt, Germany, Greece, the Netherlands, Poland and Spain) were used to develop classification models. German and imported strawberries were distinguished with an accuracy of 91.7 % using solution nebulization. Strawberry seeds were identified as optimal matrix for the alternative laser ablation method. With laser ablation, a two-class classification model with an accuracy of 88.0 ± 12.1 % provided the best result. The classical SN-ICP-MS provides a very good classification result; however, it requires more reagents and time compared to the innovative and resource-efficient LA-ICP-MS, making it a realistic tool for food fraud detection.