Abstract
Ensuring the authenticity of food ingredients is a key aspect of food safety and quality control. High-quality raw materials are often replaced by cheaper ones and not declared. In fine bakery products such as baklava, pistachios are illegally replaced by cheaper nuts. In this study we introduce a Next-generation sequencing (NGS)-based DNA metabarcoding approach as a sensitive, reliable, and semi-quantitative method that enables a successfully detection of such adulterations, even in complex and highly processed food matrices. NGS offers increased depth, efficiency and further applications compared to conventional Sanger sequencing. In the present study, the mini-rbcL region of the chloroplast genome was used and sequencing was performed on an Illumina MiSeq® instrument. The method enabled the identification of six common pistachio adulterants, including nuts, seeds, and legumes. By preparing analytical control samples, matrix effects could be observed and included in the semi-quantitative analysis. We successfully applied the method and demonstrated the high potential of NGS technologies for routine food authentication, offering a cost- and time-efficient solution for high-throughput sample analysis.