Detecting Plant-Based Food Fraud Using Nanopore Metabarcoding: A Proof-of-Concept Study

Food products containing plant ingredients are particularly vulnerable to economically motivated adulteration (EMA), which poses risks to consumer trust and regulatory compliance. While traditional methods-such as microscopy, chemical profiling or targeted PCR-struggle to detect adulterants in processed food products or complex mixes, DNA metabarcoding offers a non-targeted, high-throughput alternative. This study presents a nanopore sequencing-based technique that is easy to implement, cost-effective and sufficiently sensitive to detect substitutions, with a focus on spices and herbal teas as model matrices. The method was evaluated using eight single-species reference samples and five commercial multi-ingredient products. It reliably detected undeclared contaminants (e.g., mint in oregano) and species substitutions. Compared to single-barcode approaches, the combination of ITS2 + matK + trnH-psbA markers achieved higher sensitivity. The proposed workflow requires minimal infrastructure and a 2-4-day turnaround time. However, factors such as DNA degradation in highly processed foods, database gaps, and biological diversity limited detection in some cases. These findings demonstrate the workflow's potential as a first-line screening tool for food authenticity testing, aligning with requirements such as EU regulation 1169/2011 on food labelling or the FDA's Economically Motivated Adulteration (EMA) program. Future work should validate the method against regulatory thresholds and expand testing to a broader variety of species and matrices.