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This study (USD$39.95 purchase required) reports a rapid and sensitive ultra-performance liquid chromatography-tandem triple quadrupole mass spectrometry (UPLC-MS/MS) method to detect adulteration of high-value camellia oil and olive oil with lower-cost sesame, soybean, and peanut oils.

Four characteristic markers-sesamin and sesamolin (sesame oil), 4′,7-dimethoxyisoflavone (soybean oil), and sativanone (peanut oil) were identified and quantified with high specificity.

The authors report limits of detection of 0.025%–0.10% for sesame oil, 1.0%–5.0% for soybean oil and peanut oil. Adulteration model experiments and method comparison analysis confirmed reliable multi-component adulteration detection in complex matrices.

Analysis of 106 commercial samples revealed adulteration rates of 16.0% (camellia oil) and 25.0% (olive oil), primarily with soybean oil. The analysis of two law enforcement samples confirmed adulteration with soybean oil, consistent with the official regulatory findings.

The authors conclude that this approach overcomes limitations of traditional methods.

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Conventional magnetic solid-phase extraction materials for DNA typically require multistep synthesis to coat functional layers onto an iron oxide core, which complicates their preparation and limits practical application.

In this study (USD$39.95 purchase required) the authors developed a magnetic ionic liquid-functionalized graphene adsorbent (G-MIL) that integrates the magnetic component and the functional modifier into a single material, thereby eliminating the need for a separate magnetic core and simplifying the synthesis process. This G-MIL material enabled the development of a rapid, one-step DNA extraction method that combines vortex-assisted dispersion and magnetic separation, effectively integrating isolation, enrichment, and purification without tedious centrifugation steps.

They optimised the method and applied it to the authentication of beef products.  They report good selectivity for bovine DNA in the presence of interfering proteins and amino acids. They report that their approach was successfully applied to the authentication of beef products, reliably distinguishing pure beef from adulterated counterparts.

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In 2025 the agency US Fopd and Drug Agency tested 102 honey samples, including 54 domestic samples and 48 import samples. Test methods were primarily stable-isotope testing, so testing was focussed upon detecting syrup adulteration rather than necessarily origin fraud or floral mislabelling.  They report a violation rate of about 4% for both domestic products (2 out of 54) and imported products (2 out of 48). In the 2022-2023 assignment, the agency collected and tested 107 imported honey samples and found 3% of those samples to be violative. In 2021-2022, the agency collected and tested 144 imported honey samples and found 10% of those samples to be violative.  

More details can be found here.

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In this paper (£29.95 purchase required) the authors report the development of a point-of-use test for chicken adulteration (down to 1% w/w) in meat products.  They report that the test takes 40 minutes with a per-test cost of around US$1.

They used a swab-based sampling protocol coupled with a dedicated HPV10 nucleic acid releaser. They report that this approach enables efficient DNA release from swab samples within a brief lysis step while minimizing subsequent amplification inhibition. This simplified sampling strategy was further integrated with loop-mediated isothermal amplification (LAMP) and naked-eye colorimetric detection, resulting in a fully integrated “swab-to-result” platform.

They report that validation using commercially available meat products confirmed consistent and reliable detection performance at 1% w/w adulteration.

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Italy on April 15 gave final approval to a food and agriculture protection bill that creates new crimes, tightens penalties tied to company revenue and expands controls across the supply chain..

The legislation also strengthening administrative sanctions and coordination among inspectors.  It creates a new offense of food fraud.. The law also creates a separate offense for the trade of foods with false signs, a category designed to catch misleading labels.

The bill adds specific aggravating circumstances that warrant increased penalties. Among them is “agropiracy,” a term used for organized and systematic illegal activity in the food sector. Penalties are linked to company turnover.

The law also increases penalties for counterfeiting PGI and PDO designations. It also strengthens traceability requirements, with tighter rules on how products are identified and monitored

To improve enforcement, the law creates a coordination body for inspections.

More details are in this media report.

This thought-provoking research was presented by Kwesi Boateng, a Nottingham University student, at the “Making Pharmaceuticals” show last month in Coventry, UK.  Contact details are on the poster.  It is a reminder that not all insight into food fraud risks comes from the insular bubble of the food industry, regulators and academics.

One premise of the research is that B-2-B end customers who specify “sustainable” production of botanicals to fulfil their orders, when they have no detailed knowledge of the supply chain, are almost making fraud inevitable.  At the bottom of the supply chain are small scale producers.  Sustainable supplies of botanicals are extremely limited.  If a small producer is given an order to fulfil, with no consultation and a quick delivery date, then there is a clear motive to make up any shortfall with “unsustainable” production, lying about the carbon accounting (or – even worst – bulk out the order with an adulterant).

The solution is for the end customer to understand, appreciate, and communicate with, their whole supply chain and not to introduce stresses by giving short notification orders that are difficult to fulfil.

Ground cinnamon bark (Ceylon cinnamon or “true” cinnamon) is vulnerable to substitution with the related species cinnamon camphora (cassia cinnamon) or to bulking with different parts of the plant such as roots and leaves.  There are a number of test methods, both published and proprietary, including some based on spectroscopic classification chemometrics.

 This paper (open access), from the Joint Research Centre of the European Commission, gives a robust justification for a recommended FT-Raman spectroscopic screening method. The researchers based their reference database on a much wider variety of “true” cinnamon samples on the market than other published methods.  They purchased over 100 market samples of cinnamon bark from a variety of countries and ground their own reference samples.  They also investigated the chemical explanation for all spectral features that underpinned their discriminatory models

 They compared all results with complementary techniques, including GC-MS and XRF, to ensure robustness and reliability. Both of these orthogonal techniques supported the FT-Raman classification results.  XRF is based on discriminatory features independent of FT-Raman i.e. the fact that the elemental content of cassia samples is generally lower than that of Ceylon cinnamon. The detection of certain elements (e.g., Al, Si, Ti, Cr, Fe, Zr, and Pb) was also used as an indication of substitution with organic matter and/or effect by the material used to mill the cinnamon sticks. GC-MS is based on the analysis of several volatile compounds (e.g., camphor, cinnamaldehyde, eugenol, coumarin, cinnamyl acetate) for the detection of substitution of Ceylon cinnamon with cassia as well as the substitution of bark with other parts of the cinnamon plant (leaves, flowers, roots, seeds), based on the difference in relative abundances of the selected compounds. 

 The authors conclude that FT-Raman combined with Principal Component Analysis provides a very efficient and fast approach to detect the substitution of Ceylon and cassia species by Cinnamon camphora, other parts of the plant (e.g., root), and/or inorganic matter, using only cinnamaldehyde as the main marker along p1. Complementary techniques such as GC-MS and XRF can then be used to confirm the type of substitution.

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The global market for herbs and spices is complex with diverse supply chains and products being sourced from a variety of businesses ranging from large scale producers to smallholders. Many herbs and spices grow wild and are farmed on a village or subsistence scale, and there are often many intermediaries in the supply chain from farmer, collector to middle-man before arrival at the origin processor / shipper, as shown in the Supply Chain Map in Annex II of guidance and shown here:

Protecting the authenticity of herbs and spices is of the utmost importance given that many are materials that may be of high intrinsic value. Food businesses need to ensure that they have appropriate controls and mitigation measures in place to prevent or detect product vulnerabilities. As with any raw material and its supply chain, the emphasis should always be on prevention rather than detection of issues. As each herb and spice is unique, this document concentrates on identifying and assessing general vulnerabilities.

The original guidance was developed by a Joint Industry Working Group comprised of representatives of the British Retail Consortium, Food and Drink Federation and Seasoning and Spice Association, in liaison with the Food Standards Agency and Food Standards Scotland.

This document provides Industry Best Practice Guidance on vulnerability assessment for culinary dried herbs and spices (including blends of)  and  it has been developed to help food business operators of all sizes strengthen preventative controls, enhance supply chain understanding, and collectively safeguard product integrity.

Download the guidance here. 

The document has also been added as a new guide in the 'Tools / Guides / Reports' part of our Food Fraud Prevention section.

The Royal Society of Chemistry’s “Advances in the Chemical Analysis of Food V” conference, last week, included a number of talks and posters on various aspects of food authenticity testing.  The keynote, from Professor Chris Elliot, was on the use of data fusion to improve untargeted classification models by aggregating information from multiple analytical approaches.

One presentation, from Nathan O’Neill at the University of East Anglia (a FAN Centre of Expertise) raised new suspicions about turmeric authenticity.

Conventional wisdom (and Seasoning & Spice Association guidance) is that a significant vulnerability point for turmeric adulteration is when the roots are ground.  However, in this case, Nathan sourced intact roots from both UK and overseas online sellers.  Only reputable sellers were used but there were no prior assumptions about sample authenticity.  Chemometric feature selection and modelling (using two orthogonal untargeted analytical techniques) highlighted some of the samples whch were clear outliers.  These outlying classifications were consistent between replicate analyses and between the two orthogonal test methods.

The next planned research stage is to build reference databases for each method, then check if these outliers are mislabelled or if it reflects honest variation within turmeric taxonomy and production.

Details of the conference programme and speakers can be found here

It is always interesting to compare insights from different sources that track food fraud trends.  As we repeatedly stress, different data sources collect and classify intelligence in different ways, are intended for different purposes, and sometimes give different (and even contradictory) warning signals about food fraud risks.  The best “Horizon Scanning” protocols look at data from multiple sources and always conclude with a “so what?” question in terms of their own supply chain.

Two very useful (and free) sources that are updated every 4-8 weeks are the EU JRC Monthly Food Fraud Report (a collation of global media reports) and the EU Monthly Agri-Food Suspicion Reports (a collation of EU regulatory reports).  The latest JRC report, covering February & March 2026, can be found here (although the data has yet to be added to the JRC’s online interactive Food Fraud Incidents Application) and FAN's own graphical trend analysis from the EU Suspicion Reports (February 2026 being the last published) is shown below.

Trends from our analysis include. 

• The highest proportion of suspicions continue to relate to illegal trade – for example, unlicenced operators or attempting to evade import checks. 
• There has been a spike in “suspicions” relating to colour enhancement of food.  (see caveats below about subjectivity within our trend analysis – we exclude colour additives illegal in the EU but which appear, from the classifications, to have been declared on-pack).  February 2026 suspicions included a wide range of food types where colour is viewed as a quality indicator – undeclared red dye in paprika, green dye in olives, yellow dye in cheese powder and blue dye in seaweed..
• Falsified documentation included horse passports and laboratory analysis certificates
• Frozen seafood and meat continues to be a watch-out, with net weight bulked by excessive glaze or water (or the pack simply being underweight).
• Pistachio cream adulteration is still watch-out, despite recent publicity and industry awareness.

FAN also 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.  Our 2025 summary can be found here.

Our interpretation of the Agrifood suspicion 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

This review (open access) evaluates isomer-resolved lipid fingerprints as a complementary approach to established screening methods to detect edible oil adulteration.  The review focusses on two underexploited structural dimensions: (i) double-bond positional and geometric isomerism and (ii) triacylglycerol (TAG) sn-regioisomerism, which encode biosynthetic specificity and processing “memory” that is less accessible to conventional compositional markers.

The authors compare analytical strategies (e.g., epoxidation-MS/MS and Paternò–Büchi reactions, ozone-based dissociation/ozonolysis, and ion mobility–mass spectrometry) highlighting their respective strengths, limitations, need for derivatisation, and fit-for-purpose roles in food-industry contexts.

The authors describe some specific examples relating to high-value oil adulteration, differentiation of native versus refined/reprocessed products, monitoring of thermal/oxidative history, and emerging nutrition-relevant structure–function questions. They recommend improvements and standardisation relating to reporting confidence and nomenclature, quantitation and reference materials, tiered workflows (screening-to-confirmatory), and defensible decision thresholds.  They identify key gaps in inter-laboratory comparability, controlled processing studies, and food-specific data infrastructure.

This study (open access) reviewed published food fraud incidents from 2015 – 2025 that were specific to South Africa.

The authors found multiple examples of instances that are high on global generic watchlists such as fish species mislabelling or meat species substitution.   They also report more “local” issues such as counterfeiting of brands, or food adulterated with chemical dyes being sold to impoverished communities.  One startling counterfeiting example was fire hydrant water being bottled and sold as branded mineral water.

They conclude that the incident history, particularly the relatively high occurrence of counterfeiting and illicit alcohol, highlights systemic regulatory shortcomings, including inadequate enforcement capacity, insufficient laboratory infrastructure, the absence of a national food fraud surveillance database, and outdated legislative penalties that fail to deter offenders.  They recommend establishing a national reporting and monitoring system, enhancing laboratory and inspection capacity, adopting advanced authentication tools, and implementing stricter regulations

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This review (open access) gives an overview of the role of sterols in ensuring olive oil quality and authenticity, current methodologies used for their analysis, as well as key markers for detecting fraudulent practices in olive oil.

The authors summarise the regulatory specifications for sterols in olive oil then discuss how – beyond this – sterols in different fractions can be used to classify oils.  They also list different sterol markers for adulteration with different vegetable oils.  They review analytical methods, and list published chemometric classification models based on sterol profiles.

This 1-page graphic summarises, and celebrates, some of our activities in 2025.  Download it here.

It includes links to conference and webinar recordings, to some of the key resources on the FAN website, and to partner organisations.  We hope that this accessible format is ideal for members to download and share.  This version is in English; we will publish translations into other languages soon.

FAN is a network for the benefit of our members.  Please take this opportunity let us know (secretary@foodauthenticity.global) which of our resources you find particularly useful or if there are things we could add or improve in order to make your life easier.

This systematic literature review (USD$49 purchase required) covers 60 years of scientific publications from 1965 – 2025.  It includes national and international regulatory specifications for edible oils, including food safety standards, but is restricted to documents in English language.

The review lists common and emerging adulterants in edible oils.

The authors critically evaluate available detection approaches, including chemical assays, chromatographic and spectroscopic techniques, sensor-based systems, and molecular biology-based methods. They discuss the advantages and limitations of each method.

The review highlights the complementary roles of low-cost screening tools and advanced analytical technologies and emphasizes the need for continuous methodological innovation and robust regulatory frameworks to ensure effective oil authentication, consumer protection, and public health safety. However, with the advent of new adulteration methods that are not detectable with conventional quality parameters, continuous improvements and regulations are essential.

FAN have recognised two new Centre of Expertise (CoE) laboratories:

Purity IQ is a Canadian laboratory specialising in the verification dietary supplements, botanicals, and nutraceuticals using advanced analytical platforms, primarily Nuclear Magnetic Resonance (NMR) spectroscopy and quantitative Polymerase Chain Reaction (qPCR). Their expertise includes strain-level verification and quantification of probiotics and postbiotics.

Imegen Agro is part of the Health in Code group, based in Spain.  Imegen specialise in analytical molecular biology, particularly the design and manufacture of reagents for commercial and customised kits.  Applications include tuna species verification, turkey species (premium varieties), and Spanish “bomba” rice.

We welcome them both to the CoE network.  For more details on all of the laboratories in the network browse through the tabs on our Centres of Expertise webpage.The network is intended as a valuable resource to connect FAN members with expert laboratories for highly specialist food authenticity testing and investigations. (it is not an endorsement of laboratories, nor is it exclusive, but it is a recognition of their expertise).

It is accepted that there is no “silver bullet” to check for honey authenticity.  There are a plethora of test methods and analytical approaches, each of which can increase suspicion of sophisticated fraud.  A weight of evidence approach is recommended, combining a range of analytical information with supply chain illumination, audit and traceability data.  One recent review (open access) found an astonishing 386 patents and 707 published methods relating to honey authenticity testing.  It can be difficult to judge which of these go beyond proof-of-concept to being a valid addition to a weight of evidence toolkit.

One approach which has generated much recent interest is Next Generation Sequencing (NGS).  In principle, the DNA in honey (including meta-data from the microbiome) should be indicative of the local environment and flora where the bees foraged.  There have been a number of proof-of-concept studies with researchers reporting high mislabelling rates based on their findings.

The EC Joint Research Centre have published a clear and accessible article in the popular science journal Nature - Of bees and buzz: towards validated NGS-based methods in honey authentication (open access link).  This explains the principles of NGS (“meta-genomics”) methods, their great potential, but also the complexity inherent in robust validation and verification for widespread use testing real market samples.  The source of DNA meta-data depends on many interlinked variables; floral seasonality, human activities such as agriculture and urbanisation, bees’ foraging behaviour variation over the seasons, physiological state of flora, the community diversity and the competition with pathogens or other pollinators. The environmental and pollen DNA found in a honey jar is derived from this dynamic interplay, leading to a DNA composition changing during a season rather than remaining static.  Add to this the fact that honey from different hives are legally mixed, filtered and processed and the validation required to underpin classification models becomes incredibly complex.

The authors recommend a coordinated strategy to realise the potential of metagenomic classification methods.  This begins with the creation of a dedicated honey‑DNA reference library. This library should be assembled from a large, well‑documented set of authentic honeys that captures the full spectrum of botanical origins, geographic regions, seasons and the typical blends found in commercial products. Each sample must be unquestionably authentic, either by sourcing from certified producers or by confirming authenticity with orthogonal methods.  They argue that existing databases such as BEEexact  and BeeRoLaMa demonstrate feasibility of shared and curated databases, but there needs to be comparability evidence of different laboratory workflows.  They give recommendations for achieving this, and conclude that this would enable reliable discrimination between natural variability and intentional adulteration.

Image from the JRC paper

Mixed-milk cheeses (cheese made with a mix of milk from different species) are common on the European market, particularly in Spain.  They present a motive to fraudulently increasing the proportion of the cheapest milk species above its maximum legal specification.  For example, Iberico cheese must contain a maximum of 50% cow's milk and a minimum of 15% each of goat's and sheep's milk. Verifying the proportions of milk in the final product by quantitative analytical testing is a challenge.

In this study (open access) the authors developed and validated a quantitative LC-MSMS method based on protein markers for each species.  They selected their markers using shotgun proteomics of 6 cheeses of known proportions that had been specially made in a pilot plant following the industrial process for manufacturing Iberico-type cheese.

They optimised a quantitative low-resolution LC-MSMS method for these markers and then validated it following AOAC guidelines.  They report that the method demonstrated linearity with detection limits less than 1% for all 3 species and showed good repeatability (CV = 8%), reproducibility (CV = 10%) and accuracy (99.6%),.

They applied the method commercial cheeses with diverse compositions and ripening times. They report that measurements were unaffected by either ripening or production process.

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Soybean farming—providing protein-rich feed for farm animals worldwide—is the third largest driver of tropical deforestation and expanding. Importing economies are considering regulating the trade of soybeans and other deforestation-driving commodities, and trading companies will be required to conduct due diligence to ensure compliance. 

One of the biggest challenges in tackling deforestation is simply knowing where a batch of soy actually came from.

In this new paper, by combining stable isotope ratios and multi element profiles with Gaussian Process modelling, Rsearchers pinpointed the harvest origin of soybeans to within ~193 km across the main soy growing areas of South America.

In this study (open access), the authors developed a classification model for shrimp (prawn) origin using fused data from Stable Isotope Ration Analysis (SIRA) and trace elemental profiling.  They built the model using reference samples from Ecuador (n = 191), Honduras (n = 118), and Thailand (n = 66).  Reference samples were not only shrimp meat, but also telson (part of the shell), pond water, and feed.  Reference samples were collected from different pond types in different sub-regional locations, but all over one season (winter 2024/25).

The authors report that random forest models demonstrated high accuracy for country-level classification of reference shrimp (out-of-bag error = 0.47%) and retained strong predictive power at subnational catchment levels for Ecuador and Honduras (OOB = 3.08–5.32%).  They subjected the reference shrimp to typical commercial processing (e.g. tumbling with polyphosphates or sulphites) and found that the treated shrimp retained chemical fingerprints comparable to their reference shrimp meat counterparts, achieving a 100% successful assignment to subnational areas.  Spearman tests among shrimp meat, telson, feed, and water revealed strong isotopic and elemental correlations. The telson samples were correctly classified to their country of origin when tested against reference models built from shrimp meat data, demonstrating that telson shell chemistry reliably mirrors the geographic signature of the edible tissue.

They applied their model to a survey of retail samples and report that these exhibited low assignment accuracy (16%), suggesting either post-processing alteration or false/fraudulent labeling of origin.

Photo by Fernando Andrade on Unsplash