Evidence map›Paper›PMID 41517190›Full record

ArticleFoods (Basel, Switzerland)2026

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

Sina Rammouz, Jochen Riehle, Ansgar Ferner, Markus Fischer, Christian Schäfers

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Sina RammouzInstitute for Hygiene and Environment, Marckmannstraße 129 b, 20539 Hamburg, Germany.
Jochen RiehleInstitute for Hygiene and Environment, Marckmannstraße 129 b, 20539 Hamburg, Germany.
Ansgar FernerInstitute for Hygiene and Environment, Marckmannstraße 129 b, 20539 Hamburg, Germany.
Markus FischerHamburg School of Food Science, Institute of Food Chemistry, University of Hamburg, Grindelallee 117, 20146 Hamburg, Germany.ORCID 0000-0001-7243-4199
Christian SchäfersInstitute for Hygiene and Environment, Marckmannstraße 129 b, 20539 Hamburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

illuminametabarcodingmethod comparisonoxford nanopore technologiespistachio

Identifiers

PMID41517190
PMCPMC12785918

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.