The European Food Fraud Community of Practice (EFF-CoP) is bringing together the food integrity community for the 1st Authentic Food Festival and Conference, taking place 27–28 May 2026 at University College Dublin, Ireland.

This two-day event combines scientific exchange, practical insights, and interactive experiences, creating a meeting point for researchers, regulators, industry experts, and students working to protect the authenticity of our food systems.

Participants will explore the latest developments in food fraud detection, prevention strategies, policy insights, and supply-chain transparency, while also engaging in interactive sessions, discussions, and collaborative activities. 

Key Dates to Remember

Abstract Submissions

📅 21 March 2026 – Deadline for oral and regular poster presentations
📅 20 May 2026 – Deadline for last-minute poster presentations

Registrations

📅 31 March 2026 – Early bird registration deadline (reduced fee)
📅 20 May 2026 – Regular registration deadline

 🎓 Student rate available: €25 (€20 early bird until 31 March 2026). Email effcop@ucd.ie (proof of university registration required).

Featured Speakers

The festival-conference will host leading voices from academia, industry, and policy who are shaping the fight against food fraud:

• Prof. Maarten Boksem: “Honestly Dishonest: Exploring the Cheating Brain”– Erasmus University Rotterdam.
• Dr Alex Kupatadze: “Detecting the Invisible: How Trade Data Exposes Illicit Activity in Supply Chains”– School of Politics and Economics, Kings College London, UK.
• Prof. Chris Elliott: “From the Lab to the Front Line” – Queen's University Belfast.
• Frank Cederhout: “How to become a Fraudster” – Forensic Accountant/Forensic Investigator, Deloitte.
• Roland Hassel: “Anti-Corruption Training in the Aid Sector: From Research to Practice” – German Red Cross Corruption Prevention Manager & Anti-Corruption Consultant.
• Prof. Alan Reilly: “From the Horse’s Mouth – The Scandal That Put Food Fraud on the EU’s Menu”– Adjunct Professor, UCD/Former Chief Executive of the Food Safety Authority of Ireland. 

Session Chairs and Moderators

The programme will also feature experienced moderators guiding discussions and interactive sessions:

• Dr Selvarani Elahi, Chair Session: Innovation meets Trust – LGC
• Dr Di Wu, Chair Session: Tech meets Trust – Queen's University Belfast
• Dr Hans van der Moolen, Moderator: Clinic “Under Pressure” – Eurofins Food Safety Solutions
• Prof. Saskia van Ruth, Moderator: Clinic “Under Pressure” – University College Dublin
• Frank Cederhout, Moderator: Clinic “Under Pressure” – Deloitte. 

Round Table: Good Practices, Shared Insights

A dedicated round table will bring together experts from public authorities and industry to share practical approaches to tackling food fraud:

• Dr Karen Gussow – Netherlands Food and Consumer Product Safety Authority - Intelligence and Criminal Investigations Unit (NVWA-IOD)
• Ivo Muller – QFS Risk Management Strategy Director, Danone Quality and Food Safety
• Quincy Lissaur – SSAFE, Moderator
• Ray Bowe – Director Food Safety & Quality, Musgrave Group. 

Interactive Workshop

Beverly Wenger-Trayner and Etienne Wenger-Trayner from Wenger-Trayner will moderate the workshop: “From Gaps to Action: Strengthening Food Fraud Education Across Europe.” 

Join the Community

The 1st Authentic Food Festival and Conference is designed not only to share knowledge but also to build connections across the food integrity community. From scientific presentations and expert panels to interactive workshops and networking opportunities, the event aims to inspire collaboration and new ideas in the fight against food fraud.

📍 Dublin, Ireland — 27–28 May 2026

For registration, abstract submission, and the preliminary agenda, visit: https://www.eff-cop.eu/festival  

Honey fraud, particularly the adulteration of honey with cheap sugar syrups and mislabelling of origin,remains a high-profile and contentious issue.

This article, by The Grocer, explores how investigations and testing programmes have flagged potential concerns in some imported, lower-cost and blended honeys, but also highlights significant disagreement over the reliability and interpretation of current analytical methods, including advanced techniques such as NMR. The Framework for interrogation of honey authenticity databases, jointly funded by the Government Chemist and Defra, is featured in this article.

The article also outlines how increasingly sophisticated fraud practices can evade detection, while also noting the role of complex global supply chains in obscuring traceability.

A clear divide emerges between stakeholders: retailers and industry bodies point to due diligence and existing controls, whereas beekeepers and campaigners argue these are insufficient and that fraud is undermining genuine producers and consumer confidence.

The article emphasises that while there are indicators of fraud, the variety of methods used and lack of harmonisation mean the true scale of honey fraud remains unresolved, reinforcing the need for improved testing, greater transparency, and stronger international alignment.

Food authentication and traceability in high-risk products: analytical approaches for regulatory control

Guest editors:

Marta Ferreiro González - University of Cadiz, Cadiz, Spain

Widiastuti Setyaningsih - Gadjah Mada University, Yogyakarta, Indonesia

Marco Ciulu - University of Verona, Verona, Italy

Special issue information:

Food fraud and adulteration continue to pose significant challenges to consumer protection, fair trade, and official control systems worldwide, including in the European Union. Foods such as honey, fruit juices, jams, powdered milk, and similar products (many of which are regulated by EU Breakfast Directives), as well as other globally relevant foods (olive oil, coffee, tea, wine, spices, among others), are particularly vulnerable to fraudulent practices such as misleading labelling, dilution, substitution, and false claims regarding the origin of the raw materials or their geographical provenance. Recent regulatory developments in the EU and globally have emphasized the need for robust, harmonized, and enforceable analytical strategies capable of supporting both official control and regulatory decision-making.

This Special Issue invites contributions that showcase cutting-edge analytical and data-driven approaches for food authentication and fraud detection, emphasizing rapid, sustainable, and practical methods relevant to both research and official control laboratories. We particularly encourage submissions on non-targeted analytical approaches, spectroscopic techniques, chemometrics, machine learning, and traceability frameworks. Topics covering method validation, harmonization, traceability, and origin verification are highly welcomed, providing a platform to discuss current challenges, scientific gaps, and future needs in regulatory contexts.

By combining innovative analytical methodologies with advanced computational and data analysis tools, this Special Issue seeks to bridge the gap between scientific research and practical regulatory applications. We aim to highlight emerging challenges, methodological gaps, and opportunities for enhancing food fraud detection and prevention, ultimately guiding both the scientific community and regulatory authorities toward more reliable, harmonized, and effective strategies. This Special Issue serves as a critical forum for advancing enforceable analytical solutions that ensure global food integrity and consumer trust.

Manuscript submission information:

Interested authors can submit their papers at https://www.editorialmanager.com/foodcont/default.aspx? before March 20th, 2027.

Please make sure to select the appropriate article type "VSI: Food authentication and traceability" while submitting.

In case of any questions please contact the above Guest Editors directly.

Check out the FAQs on special issues.

Learn more about the benefits of publishing in a special issue.

Interested in becoming a guest editor? Discover the benefits of guest editing a special issue and the valuable contribution that you can make to your field.

Many of FAN’s posts tend to deal with the detection or prevention of fraud from a technical viewpoint; either detection methods, fraud incidence reports or risk management techniques.  At a fundamental level, however, fraud is a crime committed by a person(s).  To understand the crime you need to understand the person.  We signpost relatively few resources on criminology.

This special edition of the European Journal of Criminal Policy and Research (open access) is devoted to food fraud.  It has six articles which give a criminological viewpoint on a range of different examples, and is an interesting read for technical specialists looking to approach the topic from a slightly different angle.

 “Preventing Illegal Enterprise in the Norwegian Fisheries Industry” by Svorken, Kvlakik and Lord

“Agri-Food Certifications in Latin America: Drivers of Accountability or Gateways to Fraud and Corruption?” by Marta Avesani

“The Paradox of Saving Fish by Eating them: Food Crime at the Intersection of Green Criminology and Political Ecology” by Rubio-Ramon and Pons-Hernandez

“Nature as victim: a vignette study on factors impacting perceived blameworthiness and harmfulness of manure pollution” by Wesselius et al

"Food Crime: Deterrence of a Potential Money Laundering Typology Through Block­chain and Generative Artificial Intelligence (Gen AI)” by Tiwari, Rathore and Jecklin

 “Understanding Blockchain Technology against Food Fraud: A Criminological Per­spective” by Rizzuti and Davies

This is the Food Standards Agency's first Incident Prevention Update and covers: 

• Recent incidents
• Rapid Alert System for Food and Feed (RASFF) incident summary
• Signals and emerging issues
• Root Cause Analysis (RCA): Animal feed and pet food incidents
• Did you know?
• New FSA and Institute for Grocery Distribution (IGD) incidents framework 
• Publications you may have missed

Figure 1 shows the total number and percentage (%) of the main hazard categories identified in signals; compositional issues was the highest reported hazard, [49%], followed by novel foods, [22%], pathogenic micro-organisms, [8%], labelling related non-compliances, [5%], non-compliance, [5%], other hazards, [5%], allergens, [4%] and heavy metals, [2%].

Between April 2025 and February 2026, 549 signals linked to food supplements were identified and processed by the FSA signal monitoring function. Hazards and issues identified in signals triaged by the FSA were compositional non-compliances, including excess vitamins and minerals, (notably vitamins D, B6, A and iron), unauthorised substances, labelling deficiencies and (unlabelled or incorrectly labelled ingredients). Other food safety concerns identified, albeit at a lower frequency but are potentially serious included pathogenic micro-organisms, [i.e. Salmonella spp.], undeclared allergens and heavy metals.

During this period, FSA observed an increase of non-compliance reports in supplements for compositional failures, non-compliant novel foods, and Salmonella spp. contamination, in particular botanical powders. The country of origin with the highest number of signals identified for supplements was the United States, primarily for composition and unauthorised substances.

The FSA has recently updated its supplement guidance for consumers.

Read full Incident Prevention Update here.

Given the diversity of traded bivalve molluscs (scallops, oysters, mussels etc), broad taxonomic coverage is essential for untargeted screening to verify species authenticity. 

To address this challenge, the authors of this paper (open access) developed and validated a DNA metabarcoding approach employing two PCR assays, a singleplex and a duplex, to amplify mitochondrial 16S rDNA fragments (160–203 bp) across seven families: Ostreidae, Pectinidae, Mytilidae, Pharidae, Veneridae, Glycymerididae, and Cardiidae.

Taxa were identified at the species or genus level in 38 reference samples and four model food samples, with individual species detected at concentrations as low as 0.008–0.014% (w/w).

They report that all main and most minor components were detected in 40 DNA extract mixtures, with a small number of false negatives which they hypothesise result from primer-template mismatches causing amplification bias.

In a follow-up surveillance exercise they tested 70 commercial food products. They concluded that 29% of samples were mislabeled (either adulteration or substitution), with scallops being the most frequently affected family.

They conclude that the method is suitable for detecting species substitution and adulteration. This study presents the first DNA metabarcoding method targeting a broad taxonomic range of bivalves. The validated approach is particularly-suited for qualitative screening in routine food authentication and can support laboratories and regulatory agencies in enforcing international monitoring strategies.

Thanks to FAN member, and author, Julia Andronache for flagging this paper.  If you have a publication that it would be useful to share with our members then please get in touch.

The EC-JRC manuscript entitled "Interlaboratory validation of thirteen qPCR methods to quantify adulterants in culinary spices and herbs”, has recently been published (open access) in the journal of European Food Research and Technology.

The paper describes the results of a recent inter-laboratory trial using 13 qPCR assays for the detection of  significant adulterants in  paprika/chili, turmeric, saffron, cumin, oregano and black pepper.  For paprika, adulterants tested were maize seed, tomato, and sunflower seed.  For saffron, adulterants were safflower and Mexican marigold.  For cumin, carroway seed.  For turmeric, maize seed, rice seed, oat seed and bell pepper.  For oregano, goose-foot leaf.  For black pepper, rice seed.

The thirteen qPCR methods had already passed in-house validation criteria (from an original pool of 30 methods – results previously published).  This study was an inter-laboratory trial involving fifteen European laboratories. For each method the participants received DNA templates of binary mixtures for five standard samples together with five test samples of unknown adulterant concentration. Interlaboratory validation parameters included repeatability, reproducibility and trueness. Measurement uncertainties, limits of detection and limits of quantification were also determined.

The authors report that, after data examination and outlier removal, relative repeatability standard deviation ranged from 4% to 25%, relative reproducibility standard deviation ranged from 6% to 25% and trueness bias ranged from − 11% to 27%.

They conclude that the thirteen qPCR methods are therefore fully validated and may be included in international standards for deployment in official control laboratories.

Photo by Tamanna Rumee on Unsplash

This paper (open access) proposes an approach to deal with surface scattering in the Near-Infrared (NIR) analysis of particulates.  The authors use coffee cultivarl testing as an example.

Surface scattering is a major confound in near-infrared (NIR) analysis of particulate foods. In roasted coffee powders, inhomogeneous scattering can obscure cultivar differences. Standard practice eliminates scattering (extended/multiplicative scatter correction) via reference-anchored polynomial projection.  The problem is that in heterogeneous matrices this is order-sensitive and can remove analyte-relevant variance.

The approach proposed in this paper is to encode scattering explicitly.  Per-spectrum polynomial slope, curvature and cubic baseline coefficients are determined and appended as descriptors and models are trained on the augmented matrix.

The authors reported that, using 300 diffuse-reflectance FT-NIR spectra (10 000–4000 cm⁻¹) from 25 lots covering 7 Arabica cultivars, this strategy improved test-set authentication.  Linear Discriminant Analysis (LDA) increased from 70.8% to 83.3%; Support Vector Machine (SVM)-linear from 63.9% to 84.7%, while Quadratic Discriminant Analysis (QDA) remained high (88.9%).

They conclude that the approach provides a quantitative scattering-aware method, treating it as information rather than aiming for its blind elimination. This method is an interpretable, easily implemented alternative and is applicable to other particulate and microstructured foods (e.g., cocoa, tea, spices)

The European Commission launched a new artificial intelligence (AI) platform on 10 March, TraceMap, to accelerate the detection of food fraud, contaminated food and foodborne disease outbreaks across the EU. TraceMap is accessible to national authorities in all Member States,.

TraceMap will use AI to:

• Improve food safety risk assessments by streamlining access and analysing critical data.
• Rapidly identify links between operators and consignments.  
• Monitor the entire agri-food supply chain, once a risk is identified, enabling faster recalls of unsafe or fraudulent products.

The intent is to enable national authorities to better target controls and carry out more thorough investigations, without requiring additional resources. It will use the extensive data in the existing EU agri-food systems to track trade patterns and production flows. The platform will improve screening accuracy, speed up the detection of suspicious operators and help investigators to detect food fraud and food borne outbreaks and remove non-compliant products from the market quickly. It will  enable better control of imported goods, in line with the strengthened measures set out in the Vision for Agriculture and Food.

TraceMap has been created by the Commission, using AI technology that processes, structures and interprets data from different food safety management platforms across the EU, including the Rapid Alert System for Food and Feed (RASFF) and Trade Control and Expert System (TRACES). A pilot version of TraceMap was recently used to support the identification and recall of infant milk formula made with contaminated ARA oil from China.

Photo by Mario Verduzco on Unsplash

In this study (open access) researchers developed and validated new new polymerase chain reaction (PCR) systems for detection of rapeseed in small samples of highly processed vegetable oils oils.

They designed primerss targeting the rapeseed acetyl-CoA carboxylase (ACCase; BnACCg8) gene, and optimised the PCR conditions after genomic DNA extraction from ground seeds and 700 µL aliquots of edible oils. DNA was isolated using two commercial kits, and PCR products were assessed by agarose gel electrophoresis.

They report that Uniplex PCRs demonstrated species specificity, producing 147-bp and 174-bp amplicons only in rapeseed DNA, with no amplification in soybean, sunflower, or maize. PCR bands from oils were weak or absent but implementing a double-PCR approach increased detection sensitivity in oils by approximately fivefold. Strong, expected-size amplicons were obtained from all oil extracts, confirming reliable detection of rapeseed in both cold-pressed and refined varieties, regardless of extraction method.

They conclude that this approach offers a sensitive, rapeseed-specific molecular tool for verifying the botanical origin of edible oils. It is suitable for routine authenticity testing and quality control of vegetable oils.

It is very difficult to verify, by testing honey, whether bees have been fed with C3-derived sugar syrups during the foraging season.  Sugar-feeding is not permitted unless over winter to keep the bees alive.

 In this study (open access), the researchers set out to show the potential for discrimination of sugar-fed hives using the non-exchangeable hydrogen isotope ratios on ethanol derived from honey, measured using mass spectrometry (ethanol isotope ratios are the same discriminator that underpin the proprietary SNIF-NMR databases that have been accepted for many years for fruit juice authenticity testing and have also been applied to honey)

 To generate reference samples, 36 genetically similar bee colonies, at a single geographical location and time point, were subject to different controlled sugar feeding regimes.  Four different sugar syrup types were used to represent distinct adulteration scenarios: fructose and glucose syrups derived from C4 plants, invert sugar derived from C3 plants (sugar beet), and sucrose syrup of unknown botanical origin.  Controls were in place to stop the colonies cross-feeding.

 The authors report that Ethanol δD_n values for adulterated samples differed significantly from controls, enabling clear discrimination.  This discrimination could form the basis of a potential classification database.

The application of high-throughput sequencing (HTS) of DNA barcodes can be hampered by technical challenges particularly in highly processed food.  Food pre-processing and differences in guanine/cytosine composition can lead to unequal amplification or complete loss of DNA barcode components.

To address this, the authors of this study (pre-publication, open access) used a multi-omic approach that coupled DNA barcode HTS analysis with proteomic analysis.  They applied it to the authentication of herbal beverages.

To resolve discrepancies between genomic and proteomic findings, the authors used traditional botanical morphology as an arbiter.

They applied their approach to a survey of herbal teas on the market in Russia.  They report two adulterations of Epilobium with Lythrum — a substitution potentially hazardous to consumers (Epilobium species are popular botanical drinks around the world, including Rosebay Willowherb, “Fireweed” and “Ivan Tea”).  They also found several minor substitutions, all confirmed by orthogonal methods.

They conclude that proteomic analysis provides enhanced confidence for verifying the presence or absence of plant components identified by HTS. However, its effective application is guided by prior sequencing to define specific targets for subsequent proteomic verification. A multimodal analytical approach is not only beneficial, but essential for the reliable and comprehensive characterization of components in complex plant mixtures.

Photo by Tamara Harhai on Unsplash

DNA-based verification that gelatin-containing foods and cosmetics do not contain pork products has always been a challenge due to DNA damage and destruction during gelatin production. 

In this study (open access) the authors report that – by careful optimisation of conditions – they could successfully apply a “traditional” PCR test to the problem.

They describe DNA extraction, post-isolation DNA analysis, annealing temperature and primer concentration optimization, specificity assay, amplification efficiency trial, sensitivity test, repeatability examination, and marketed sample analysis.

They report that the developed method demonstrated good specificity under optimized conditions. It achieved a good amplification efficiency of 101.2% with an R² of 0.994. The real-time PCR technique had a limit of detection of 1,316 pg in the sensitivity examination and a coefficient of variation of 0.81% in the repeatability testing.

They tested 10 retail samples (five facial mask cosmetics, food additive gelatin powder, two marshmallow products, and two gummy candy products), reporting that all of the samples displayed no amplification and were thus considered not to contain porcine DNA, consistent with the manufacturers’ labels.

The authors conclude that their real-time PCR method meets the validation criteria for qualitative analysis, including specificity, amplification efficiency, sensitivity, and repeatability.

Here is our latest monthly graphic from the EC Reports of Agri-Food Fraud Suspicions, showing a rolling 3-month trend. 

Our interpretation of the reports is subjective. In order to show consistent trends we have excluded cases which appear to be unauthorised sale but with no intent to mislead consumers (e.g. unapproved food additives, novel foods which are declared on pack), we have excluded unauthorised health claims on supplements, and we have excluded residues and contaminants above legal limits.  We have grouped the remaining incidents into crude categories.  Our analysis is intended only to give a high-level overview. 

The highest proportion of fraud continues to relate to falsified or unlicenced trade in high risk food (illegal operators, missing or falsified health certificates, attempts at illegal import) and relating to falsified or missing traceability documentation.  Beyond this, there has been a steady increase in examples of foods labelled as "preservative free" being found to contain preservatives.  There are also consistent - and high - numbers of the simple fraud of food being under the declared pack weight.  A high proportion of these cases are due to excessive water glaze on frozen seafood.

A small - but increasing - proportion of the cases of non-meat/fish products being low in a premium component relate to "nutraceuticals"; foods marketed on the basis of an ingredient or additive with a real or implied health benefit, and the ingredient/additive being at a lower quantity than declared.  For those formulating such products, it is a reminder that there is no "under-tolerance" in the enforcement guidelines for declared amounts of such ingredients (including vitamins and minerals) and that the declared quantity must remain valid throughout the shelf life.

These Agri-Food suspicions are just one of the incident databases available.  Different databases collect different information, in different ways, and therefore show a different angle on the true picture.  All of these sources are signposted on FAN.  Best practice is to use a combination of multiple sources.

• JRC – These are solely media reports.  They exclude cases not in the public domain, and can be biased by shocking but highly localised incidents in local food supply within poorly regulated countries.  They now incorporate a search and trending tool to produce graphs and charts
• EU Agri-Food Suspicions – These are solely EU Official Reports, and only suspicions.  The root cause of each incident is unknown.  The data include pesticide residues above their MRLs. unapproved supplements and novel foods, and unapproved health claims.
• Food Industry Intelligence Network Fiin SME Hub – These are aggregated anonymised results from the testing programmes of large (mainly UK) food companies.  The testing programmes are targeted and risk-based, not randomised, and the fraud risks within such suppliers of large BRC-certified retailers and manufacturers may be different than the companies supplying small manufacturing businesses or hospitality firms.  

Many testing laboratories also supply their own customers with incident collations, and there are many commercial software systems that scrape reports from the internet.  All collect and treat the data slightly differently.  FAN produce a free annual aggregate of "most adulterated foods" from three of the commercial providers, which gives very high level smoothed data based on official reports.

Wagyu beef's distinctive flavour and tenderness arise from its high levels of unsaturated intramuscular triglycerides. Although these compositional distinctions provide a unique Raman signature, extensive band overlap and background attenuation from packaging and frozen conditions hinder reliable in situ classification and constrain the interpretability of raw spectra.

This study (USD36 download fee) presents a label-free Raman spectroscopic and chemometric approach for authenticating Wagyu beef under realistic retail-like conditions. A supervised partial least squares discriminant analysis (PLS–DA) model was developed using spectra from unwrapped adipose tissue and evaluated with an independent validation set of frozen, plastic-wrapped samples from multiple breeds and suppliers.

The authors report that the model achieved 100% sample-level classification accuracy, To elucidate the molecular basis of discrimination and resolve spectral congestion, they used a two-stage decomposition combining singular value decomposition (SVD) and nonnegative matrix factorization (NMF), followed by nonnegative least squares (NNLS) fitting with pure triglyceride standards.

They found that analyses yielded chemically interpretable components, revealing enrichment of unsaturated triglycerides in Wagyu beef consistent with established compositional data. This could form the basis of a non-destructive test applicable directly through plastic packaging.

Photo by moreau tokyo on Unsplash

Undeclared lard in confectionary products is a significant concern for consumers in many parts of the world who avoid pork on religious grounds.

This study (GBP30 download fee) used gas chromatography with flame ionization detection (GC–FID) to measure fatty acids, then principal component analysis (PCA) to detect porcine fatty acid biomarkers in imported chocolates and biscuits.

The authors report that total fat content ranged from 11.5 to 32.5%, with palm kernel-based chocolates enriched in lauric (42–52%) and myristic acids (18–20%), while other chocolates were dominated by palmitic, stearic, and oleic acids. Biscuits contained high proportions of palmitic and oleic acids (> 75%).

PCA of the complete fatty acid dataset separated lard-adulterated samples.. Targeted PCA using porcine biomarkers palmitic-to-oleic acid ratio and eicosadienoic acid confirmed this clustering.

Calibration using simulated lard–palm oil mixtures (0–15% w/w; five replicates per level) enabled quantitative estimation of lard .

Photo by Pawel Czerwinski on Unsplash

Raman, and related techniques, have the potential to provide field-based rapid and non-destructive testing for dairy products and powders.

This review (open access) consolidates advances reported from 2015 to early 2025, covering conventional Raman, surface-enhanced Raman spectroscopy (SERS), Fourier-transform Raman, hyperspectral Raman imaging, confocal/mapping approaches, and portable systems.

The authors critically evaluate preprocessing and chemometrics as well as machine-learning and deep-learning pipelines for classification and quantification.

They compare species-specific applications including cow, buffalo, goat, camel, donkey, human breast milk (macronutrients, sex-linked profiles, microplastics, antibiotics), and milk powder workflows with respect to matrix effects, fluorescence interference, and validation practices.

They summarise that  Raman enables chemically specific fingerprints of proteins, lipids, and carbohydrates, whereas common adulterants present diagnostic bands. SERS substrates routinely extend sensitivity to ppm–ppb levels and suppress fluorescence, supporting rapid detection of melamine, urea, ammonium sulfate, thiocyanates, benzoate, and selected antibiotics. Hyperspectral imaging provides spatially resolved maps, differentiating multi-adulterant mixtures and thermo-structural behavior in powders.

Chemometric models achieve high accuracy for classification and concentration prediction, whereas deep-learning architectures improve robustness under nonlinear matrix variation and instrument drift.

They conclude that challenges persist in substrate reproducibility, calibration transfer, fluorescence in lipid-rich systems, and detection of emerging adulterants and trace preservatives under field conditions. Future progress will hinge on multi-excitation instruments with adaptive laser power control, universal SERS substrates integrating plasmonic metals, dielectric shells, and molecular recognition, and standard operating procedure grade preprocessing. They highlight that industrial reliability requires calibration-transfer strategies, rigorous validation, and explainable artificial intelligence to link decisions to chemically meaningful features, supporting regulatory acceptance and auditability.

Portable Raman and SERS systems can aid nutritional profiling and contaminant surveillance in breast milk, whereas Fourier-transform Raman and hyperspectral imaging mitigate fluorescence and map heterogeneity in powders.

Verifying the origin of garlic has risen up the risk rankings in recent years.  Approximately 70% of the world’s garlic originates from China.  Volatility in trade tariffs (and the anticipation of tariffs) and anti-dumping measures mean that there could be financial incentive to trans-ship Chinese garlic through a third country and mis-state the country of origin, particularly if importing into the US.

In this proof of concept study (USD32 download fee) the authors show that microbiota profiling provides an alternative to conventional chemometric approaches for garlic origin authentication. They characterized the surface bacterial communities of 153 garlic samples collected between 2021 and 2024 from China (n = 60), the United States (n = 50), and multiple other countries (n = 43) using 16S rRNA gene amplicon sequencing.

They report that comparative analyses revealed significant differences in alpha and beta diversity across countries, with U.S. samples exhibiting the highest microbial richness and Chinese samples the lowest. Dimensionality reduction methods showed clear clustering by country of origin, supporting the presence of distinct microbial signatures. Machine-learning classifiers trained on 16S profiles achieved >0.87 accuracy across Random Forest, k-nearest neighbours, logistic regression, and support vector machine models using only five genus-level microbial features.

Multi-year sampling confirmed that these microbial signals remained stable across harvest seasons. Differential abundance analyses further identified ecologically relevant taxa driving country-level separation.

Photo by team voyas on Unsplash

FAN is pleased to highlight a newly published peer-reviewed article presenting a recommended framework designed to support more structured and consistent implementation in practice: Towards harmonisation in food authentication: How to establish maximum tolerable levels of food adulterants? - ScienceDirect. This link is open access until 3 April.

The authors are keen to move this beyond publication and into practical dialogue. They are particularly interested in understanding whether the proposed framework is realistically implementable across regulatory, industry, laboratory and supply-chain contexts.

We would value FAN members’ perspectives on:

• Is the framework practical in real-world food system settings?

• What barriers might limit implementation?

• What adaptations would make it more usable?

• Where does it align — or conflict — with existing guidance and standards?

Your experience is critical in testing whether recommended approaches are workable beyond theory.

Please share your reflections, either via the comments, on the FAN discussion board or directly with the authors: nixb@fvst.dk

Let’s ensure that emerging frameworks are not just academically robust, but operationally deliverable.

Thank you!

This technical report from the FAO (free to download) provides a detailed overview of food fraud in the aquatic sector, outlining its types, causes and impacts. It demonstrates that species substitution and mislabelling are the most common forms of fraud, with studies indicating that up to 20 percent of fishery and aquaculture products globally are mislabelled. Fraud is especially prevalent in restaurants and catering services, where visual identification is challenging, and in processed products, where the species identity can be masked.

A series of international case studies illustrates the extent and consequences of food fraud in the aquatic sector and provides an overview of the most common cases and the available tools to fight food fraud in the sector.

The report reviews international regulatory frameworks and standards designed to mitigate fraud risk, including Codex Alimentarius, FAO guidelines, and GFSI‑benchmarked schemes (such as BRCGS, FSSC 22000, International Featured Standards, and Safe Quality Food), as well as national laws in Australia, Canada, the United States of America and the European Union.

It advocates for harmonized labelling requirements, the mandatory inclusion of scientific names, and better traceability systems. Raising consumer awareness and

increasing industry transparency are also highlighted as critical steps to reduce fraud and support sustainable practices in the aquatic sector.

The report also includes summaries of the most common testing methods used to identify different types of fraud.