Cross-Platform Evaluation of Established NGS-Based Metabarcoding Methods for Detecting Food Fraud in Pistachio Products

对已建立的基于NGS的元条形码方法在开心果产品食品欺诈检测中的跨平台评估

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Abstract

Next Generation Sequencing is a constantly evolving technology whose applicability is increasingly expanding into the field of routine food analysis. In this context, metabarcoding has proven to be a powerful tool for detecting food fraud due to its ability to taxonomically classify even highly fragmented DNA from processed products. While Illumina sequencing platforms, representing second-generation sequencing technologies, are widely used for such applications, fourth-generation sequencing devices such as Oxford Nanopore Technologies' MinION offer advantages in terms of flexibility, scalability, and simplified handling. In this study, we evaluate the transferability of an established Illumina-based metabarcoding method for the detection of pistachio adulteration in processed foods to the MinION platform of Oxford Nanopore Technology. In more detail, we transferred the established method from Illumina on both MinION and Flongle flow cells to assess sequencing accuracy, quantification potential and practical aspects such as cost-efficiency and workflow. Our results highlight the applicability of the MinION sequencing platform as a reliable and cost-effective alternative to Illumina protocols for routine food authenticity testing, enabling faster processing and broader accessibility without significantly compromising accuracy.

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