In this study (purchase required) the researchers used bioinformatics methods to identify specific sequences of cattle, pig, chicken, and duck, and designed primers and probes accordingly.

They developed a method based on recombinase polymerase amplification (RPA) combined with lateral flow dipstick (LFD) for rapid visual authentication of beef and beef products. The RPA reaction was conducted at 37℃ for 20 min. The amplification products were then diluted and applied to the sample pad of the LFD. Results were visible to the naked eye within 5 minutes.

They report that the results demonstrated the method could specifically differentiate components of bovine, porcine, chicken, and duck origin, with a limit of detection (LOD) of approximately 20 copies for each species.

They applied the method to 10 commercially available beef products. Of which, five samples were detected with porcine-derived components. The results of the RPA–LFD method were verified using PCR and observed to be consistent between the methods.

The researchers conclude that this method is easy to use, requires no specialized equipment, and delivers results in about 30 min from amplification to detection, making it suitable for rapid visual detection on-site.

This study (open access) proposes a strategy to verify the authenticity of Mozzarella di Bufala Campana (MdBC).  MdBC is, a Protected Designation of Origin (PDO) cheese, Buffalo breeds are highly similar genetically, so detecting foreign buffalo milk in commercial cheese is more complicated than identifying cow, goat, or sheep milk. Fraud involving cow milk is particularly concerning because it is cheaper and more widely available, especially during peak MdBC production seasons

The researchers used a reference set of sixty-four anonymized PDO MdBC and foreign mozzarella samples provided by the Italian Central Inspectorate for Fraud Repression and Quality Protection of the Agrifood Products and Food, Ministry of Agricultural and Forestry Policies (Rome, Italy).  They used a sequential approach to verifying foreign milk species in buffalo mozzarella.  As a first screen, the casein was separated on a polyacrylamide gel.  This was generally sufficient to identify extraneous cows’ milk proteins.  In a second stage, the isolate casein was then digested with trypsin and the peptides analysed by MALDI-ToF-MS.

In cases requiring confirmation, nano-liquid chromatography coupled to electrospray tandem mass spectrometry (nano-LC-ESI-MS/MS) is used in central state laboratories for the highly sensitive detection of extraneous milk proteins in PDO buffalo MdBC cheese. The researchers report that analysis of the pH 4.6 soluble fraction from buffalo blue cheese identified 2828 buffalo-derived peptides and several bovine specific peptides, confirming milk adulteration.

They conclude that, despite a lower detection extent in the pH 4.6 insoluble fraction following tryptic hydrolysis, the presence of bovine peptides was still sufficient to verify fraud. This integrated proteomic approach, which combines electrophoresis and mass spectrometry technologies, significantly improves milk adulteration detection.

Photo by Audric Wonkam on Unsplash

In common with most jurisdictions, India has regulatory analytical criteria for authentic honey.  This includes various stable isotope ratios.

In this study (open access) the researchers set out to construct an analytical database of fully traceable authentic honeys in order to verify the criteria set by the Food Safety and Standards Authority of India.

They collected 98 authentic samples (covering 19 botanical sources, 42% multifloral and 58% monofloral).  They covered 17 states and provinces.  Sample were from collection centres of the All-India Coordinated Research Project on Honey Bees and Pollinators (AICRP, HB&P), under the auspices of the Indian Council of Agricultural Research (ICAR).   In addition, beekeepers registered with the National Bee Board (NBB) were also identified for sample collection. All samples were fully traceable.

The researchers generated a database of stable carbon isotope ratios (¹³C/¹²C) by Elemental Analyzer/Liquid Chromatography–Isotopic Ratio Mass Spectrometry (EA/LC-IRMS). The samples were analyzed for the parameters δ¹³C_Honey(δ¹³C_H), δ¹³C_Protein(δ¹³C_P), δ¹³C individual sugars, ∆δ¹³C_{Protein-Honey}(δ¹³C_P-H), C4 sugar, ∆δ¹³C_{Fructose-Glucose}(δ¹³C_Fru-Glu), ∆δ¹³C_max, and foreign oligosaccharides as per the official methods of analysis of the Association of Official Analytical Chemists (AOAC 998.12) and the FSSAI.

The results were evaluated against the published literature and Indian regulatory criteria for authentic honey. The δ¹³C value for honey (δ¹³C_H) ranged from −22.07 to −29.02‰. It was found that 94% of samples met the criteria for Δδ¹³C_P-H (≥−1.0‰), Δδ¹³C_Fru-Glu (±1.0‰), and C4 sugar content (7% maximum), with negative C4 sugar values treated as 0% as prescribed by the AOAC method.  86% of samples met the accepted foreign oligosaccharide criteria (maximum 0.7% peak area).

They conclude that the data of this study provide scientific backing for these four parameters as per the FSSAI regulation. However, the non-compliance of a high number (47%) of authentic honey samples for Δδ¹³C_max (±2.1‰) compels further systematic investigation with a special focus on bee feeding practices. Further, they found that honey samples with a Δδ¹³C_P-H greater than +1‰ and a C4 sugar content more negative than −7% also did not comply with the Δδ¹³C_max criteria. They suggest that Δδ¹³C_P-H values (>+1‰ equivalent to C4 sugar < −7%) could be an indicator of C3 adulteration to some extent.

One of the limiting factors in developing any untargeted analysis is sourcing samples for the reference database.  The samples labelled as “authentic” in the model developed must be of absolute trustworthiness (fully traceable back to authentic production) and also fully representative of every variable within the “authentic” scope (e.g. different permitted agricultural inputs, harvest seasons, species, variety and geographic origin).

This pilot study (open access) uses a statistical approach to circumvent this need.  The authors still attempted to source reference samples that were representative of an “authentic” scope but they made no attempt to verify the samples; all reference samples were purchased from online direct-to-consumer vendors.  They then built a results dataset of 38 different fatty acid methyl esters, tocopherols and phytosterols measured by GC-MS and LC-MS.  They selected from within this dataset using Monte Carlo sampling to choose different “reference databases” and build a large number of One Class Classification models.  They then used statistical analysis to see if each of these models appeared internally consistent (i.e. suggestive that all of the reference samples had been “authentic”) or not (i.e. suggestive that some of the reference samples had been “inauthentic”).  They chose the model with best internal consistency.

They piloted this approach on 40 avodado oils, identifying 6 of them a potentially adulterated.  Subsequent targeted chemical analysis showed that these 6 adulterated samples had been correctly identified.

This publication (open access) describes the launch of FISH-FIT.  FISH-FIT is a biobank of seafood species samples which are linked to an authentic database of morphology, genetic information, and other physical characteristics. It also contains a library of PCR analytical methods.   It was developed under an EU-funded project and free access is currently only available to EU regulatory bodies, although wider access is planned.  The databank is hosted by the Max Ruber Institute.

FISH-FIT has been added to FAN’s index of authenticity reference databases, a useful search tool for existing databanks or commercial testing services..

(image from the paper)

This study (open access) used the fingerprint of trace elements (measured by inductively-coupled plasma – mass spectrometry, ICP-MS) as a marker for the use of mineral vs organic fertilisers, and hence as a marker for the mislabelling of Organic apple juice.  The concept was proven on juices made from apples grown in two regions of Northern Germany.

Reference data sets were generated from juices made by the researchers from apples of known provenance.  59 apple juice samples (31 organic and 28 conventional) from four crop years (2020–2023) were analyzed regarding their element profiles and used for model creation. All samples were from Schleswig-Holstein, Germany. Afterwards, the model was expanded using 24 apple juice samples (11 organic and 13 conventional) from Hamburg, Germany (crop year 2020–2023). Prior to analysis, the whole apple samples were washed with deionized water and then dried. Afterwards, the samples were processed to apple juice using a commercial juice extractor.

The authors report that, using an environment-friendly sample preparation strategy and a ratio-based evaluation approach in combination with a random forest classification model, it was possible to distinguish between the cultivation methods of processed apples.  The results were verified by analyzing samples from local supermarkets. Furthermore, the detection of adulterated mixtures of conventional juice to organic juice was studied using a regression analysis (5–50 % adulteration). Adulteration could reliably be detected from a proportion of 20 % Thus, falsification of the cultivation method can be detected even in mixtures.

The authors conclude that the study shows great potential towards sustainability, reducing sample preparation time, hazardous chemicals and energy consumption.  The identified molybdenum as a potential routine marker for organic apple juice.

Authentication of mushroom commodities often relies on visual identification, including microscopy. The methods usually involve physical observation with high subjectivity, which may lead to mushroom-product fraud and mislabelling.

This review (purchase required) covers molecular methods and “chemical” methods coupled with chemometrics and/or artificial intelligence. These include DNA barcoding, which is an identification strategy based on the DNA sequence of the mushroom sample, specifically the internal transcribed spacer (ITS) region. The review discusses the advancements in the usage of both DNA barcoding and chemometrics-coupled methods in the authentication of mushrooms and their derivative products; and how these can solve some major hurdles relating to mushroom products.

Photo by Damir Omerović on Unsplash

This study (purchase required) reports a direct method to verify the purity and authenticity of commercial sweetener raw materials; erythritol, xylitol, and stevia.  Analysis is by near- and mid-infrared spectroscopy combined with a DD-SIMCA classification model. The model was enhanced with virtual samples created by adding PCA residuals and noise.  The authors report that this improved the model's robustness and accuracy. Validation was performed using independent sample sets, including commercial natural sweeteners and in-house samples adulterated with saccharin, sucrose, acesulfame, and silicon dioxide.

The authors conclude that the approach was efficient for xylitol and erythritol authentication.  Efficiency rates were 90 % or higher for xylitol, erythritol, and stevia, but stevia sampling is challenging due to stevia's variable composition and needs improvement before the model could be applied with confidence.

Photo by rama purnama on Unsplash

In recent years the responsibility for enforcing food sustainability claims in the Netherlands has been unclear.  It has now been agreed that the Authority for Consumers and Markets (ACM) will take the lead, but will consult the Netherlands Food and Consumer Product Safety Authority (NVWA) before taking action.  Both are designated as Competent Authorities.

The ACM has announced a focus on sustainability claims in the food sector in 2025.  It has recently run successful similar campaigns in the energy and clothing sectors.  The ACM does not have the power to directly impose fines, but previous warnings to companies making unsubstantiated claims (including major brands such as H&M and Greenchoice) have resulted in changes to packaging, advertising, and substantial corporate donations to sustainability charities in lieu of a fine.

The ACM’s sustainability claims guidelines can be found here.

In this study (open access) the authors made a reference dataset of comminuted meat mixtures by dicing and mixing 140 commercially-purchased steaks of beef, duck and chicken.  They built a classification model to discriminate between the three species in the mixtures.

They used a hand-held Hyperspectral Imaging (HSI) (with a Raspberry Pi controller, which has real-time image acquisition and processing covering  a spectral range from 400 nm to 800 nm) to develop a discrimination model for chicken/duck adulteration in diced beef. The portable push broom HSI was designed with the spectral resolution of 5 nm and spatial resolution of 0.1 mm. To improve generalization, a model transfer method was also developed to achieve model sharing across instruments

The authors report that their model transfer method can effectively correct the spectral differences due to instrument variation and improve the robustness of the model. The support vector machine (SVM) classifier combined with spectral space transformation (SST) achieved a best accuracy of 94.91%. Additionally, a visualization map was proposed to provide the distribution of meat adulteration.

They conclude that the portable HSI enables on-site analysis, making it an invaluable tool for various industries, including food safety and quality control.

There is an increasing market of mildly processed chilled Not-From-Concentrate (NFC) orange juices, preserved by methods such as high pressure processing (HPP) and pulsed electric fields (PEF).

To protect consumers from food fraud, analytical methods to differentiate such juices from thermally pasteurized juices are required.

This paper (open access) sought to identify volatile chemical markers specific to the preservation process.  To screen for appropriate candidate markers, the authors applied a complementary non-targeted volatilomics and sensomics approach.  This identified 58 candidate markers, among which 20 were quantitated and nine were statistically confirmed.

Extension of the quantitations to stored and doubly-treated juices finally resulted in the identification of (S)-carvone and vanillin as promising candidate markers. In combination, the two compounds could distinguish the HPP-treated juice from thermally treated juices and could even identify an HPP-treated juice that had received an additional thermal pasteurization.

Photo by ABHISHEK HAJARE on Unsplash

The authors of this study (purchase required) report that they systematically separated and authenticated the triacylglycerols composition of milks from holstein cattle, goats, mongolian horses, bactrian camels, yaks and buffaloes,  using supercritical fluid chromatography coupled to high-resolution mass spectrometry (SFC-Q-TOF-MS). Subsequently, the fingerprinting of triacylglycerols from different livestock milks was modelled using chemometric methods. The results showed that the statistical grouping of different livestock milks was consistent with the species taxonomy, and the accuracy of internal as well as external validation was satisfactory.

They conclude that this work not only provides an innovative strategy for authentic traceability of livestock milk, but also offers potential for the establishment of nutritional databases.

Photo by Polina Kuzovkova on Unsplash

This paper (open access) reports the construction of a classification model to detect the adulteration of white pepper with mung bean flour utilizing Fourier Transform Infrared (FTIR) spectroscopy combined with chemometric techniques.

The authors prepared their own reference samples in-house by grinding locally sourced white pepper (Malaysian origin) with bean flour ranging from 3 – 50%.

They report that adulterants can be detected even at the lowest concentration prepared using the Partial Least Squares (PLS) method and chemometrics.. The second derivative FTIR spectrum in the range of 3712-650 cm⁻¹ was identified as the optimal calibration model.  The PLS Discriminant Analysis (PLS-DA) method also successfully classified pure white pepper samples from those adulterated with various concentrations of mung bean flour.

This study (purchase required) reports the development of a novel recombinase aided amplification (RAA) assisted Cas12a assay to authenticate the commercially important Pacific oyster.

The COI gene was selected as a genetic marker for primer design. The authors report that the developed species-specific RAA assay was optimal at 40 °C for 25 min. The Cas12a assay successfully detected the target Pacific oyster DNA sequence in RAA products using 0.05 μM gRNA and 0.05 μM Cas12a enzyme within 40 min at 37 °C. The developed RAA primers and gRNA for CRISPR-Cas12a assay showed no cross-amplification and high specificity for C. gigas compared with C. belcheri and C. iridalei. The sensitivity test showed the ability of the assay to detect DNA concentrations as low as 10 fg/reaction. In addition, the developed assay successfully authenticated oyster samples in all processed forms, including boiled, steamed, fried, and canned samples.

A small follow-up survey found that 1 of the 15 commercial samples tested was mislabeled.

The authors conclude that the developed assay was a valuable technique with high potential for food safety authorities and stakeholders in ensuring authenticity, in which substitution and adulteration of seafood products can be detected.

This study (open access) applies both the Situational Crime Prevention (SCP) framework and the Enterprise Model to the Norwegian cod fishing industry.  It makes consequential recommendations for improving fraud prevention.  Although the SCP model has been used previously in Norway, the authors discuss whether previously adopted strategies adequately address the enterprise conditions that facilitate or drive unreported fishing.  They aim to provide new insights that can be used to reduce fisheries crime in particular and contribute to the understanding and analysis of food crime prevention in general.

The prevention frameworks and models used in this study focus on opportunities.  Five general prevention strategies are considered: increase the risk of detection, increase the effort, reduce the rewards, reduce provocations, and remove excuses. SCP focuses on the decision-making process of the offender, based on the principle that all crimes involve costs and benefits and that the decisions depend on these.

The authors analyse how the current prevention mechanisms in Norwegian fisheries address the enterprise environment that affects industry actors’ behaviour and misreporting practices by applying an integrated framework of combining the enterprise model with SCP.. They discuss why the existing prevention strategies are (in)sufficient for preventing unreported fishing.

The study shows that existing prevention mechanisms mainly address supply and regulation dimensions. Despite their significant role in driving and facilitating unreported fishing, less emphasis is given to market and competition. The analysis reveals the limitations of the heavy reliance of the current prevention strategy on fisheries resource control, as many of the motivating conditions are outside the realm of the control authorities.

The authors recommend that the authorities should expand the perspective to encompass contextual challenges such as competitive conditions and low profitability.

They conclude that the framework proves helpful for analysing fisheries crime prevention, offering insights into addressing food fraud in legitimate supply chains, but the analysis would have benefited from a more apparent distinction between the different conditions that influence criminal behaviour.

Photo by Fredrik Öhlander on Unsplash

In this paper (open access) the authors developed and validated a novel sample introduction mechanism (a new configuration of Solution Glow Cathode Discharge, SGCD) to enable heated and diluted honey to be directly analysed by Optical Emission Spectroscopy (OES).  This provided a relatively low-cost and bespoke platform for the routine testing of trace metals in honey.

They measured the concentrations of five metals – Na, K, Rb, Mg and Ca – in a reference set of authentic honeys and honeys adulterated with syrups.  The paper concentrates more on the analytical technique validation than the reference database and so it is unclear how all the reference samples were sourced and prepared, and two reference results were removed from the dataset as unexplained outliers.  Nonetheless, the authors present multivariate statistics showing that the metal profile can be used as an indicator of adulteration, with syrup-adulterated honey having higher Na content and “natural” honeys having higher K, Mg and Ca content.

This could form the basis of another classification technique which, whilst being a long way from definitive, could add to that analytical arsenal in a weight-of-evidence approach to determining honey authenticity.

The Joint Research Centre of the European Commission have published their monthly collation of food fraud reports for February 2025 here Thanks again to FAN member Bruno Sechet who has turned these into an infographic.  The original infographic, along with his commentary, is on Bruno's LinkedIn feed.

These collations are based on global media reports, and so give a different picture to EU official "suspicions" (as analysed in our recent blog), which is different again to annual collations of official reports as aggregated in our annual summaries.  It is important, when conducting your own risk assessments, to appreciate what a specific data source includes and what it does not.  It is helpful to look at multiple, complementary, data sources.

Fluorescence spectroscopy utilizing benchtop and portable spectrometers with light-emitting diodes (LEDs) as a fixed excitation source has been used as a method for detecting food adulteration in various products, including honey, extra virgin olive oil, tea, and coffee  It is cost-effective, rapid, and sensitive, allowing for intact measurement. LED-based fluorescence spectroscopy is fast, accurate, and cheaper than using a laser.. Recent advancements in semiconductor technology have enabled the delivery of LEDs with commercially available wavelengths ranging from 370 to 470 nm, exhibiting significant light intensity.

In this paper (purchase required), the authors used the technique to develop a classification model to detect ground soy in ground-roasted Arabica coffee, and to differentiate Robusta and Liberica varieties.  The abstract gives no details of the reference samples used to construct or validate the model but it was limited to 2024 season samples harvested in Indonesia.

Photo by Nathan Dumlao on Unsplash

The EC Monthly Reports of Agri-Food Fraud Suspicions reports are a useful tool for estimating fraud incidents, signposted on FAN’s Reports page.  The February 2025 report can be found here.

As with all incident collation reports, interpretation must be drawn with care.  The EC collation is drawn from the iRASSF system – these are not confirmed as fraud, and the root cause of each issue is usually not public.  There are important differences in the data sources, and thus the interpretation that can be drawn, of these data compared to other incident collations.  For example:

• JRC Monthly Food Fraud Summaries (which underpin the infographics produced monthly by FAN member Bruno Sechet) - these are unverified media reports, rather than official reports, but hugely valuable in giving an idea of which way the fraud winds are blowing
• Official reports (as collated from commercial databases such as Fera Horizonscan or Merieux Safety Hud, which underpin FAN's annual Most Adulterated Foods aggregation) - these are fewer in number and give a much more conservative estimate of fraud incidence, and may miss some aspects which have not been officially reported
• Verified reports (where the root cause has been scrutinised and interpreted by a human analyst, for example the FoodChainID commercial database) - these are also few in number, less suitable for drawing overall trends, but give specific insight and information.

If looking at trends over time, you must also be wary of step-changes due to new data sources.  For example, Turkey's public "name-and-shame" database of foods subject to local authority sanctions went online in January 2025 and has had a big impact on the data captured by all commercial incident databases.

In FAN’s graphical analysis of the Agri-Food Fraud Suspicions, shown here, we have excluded cases which appear to be unauthorised sale but no intent to mislead consumers of the content/ingredients of a food pack (e.g. unapproved food additives, novel foods), excluded unauthorised health claims on supplements, and we have excluded residues and contaminants above legal limits.  Our analysis is subjective but intended to give a high-level overview.

We have grouped the remaining cases into crude categories.  It can be seen that the majority are either unregistered trade (e.g. illegal import, or unlicenced premises), falsified certification or traceability records, or substandard meat quality/content in processed foods (what used to be termed “QUID”).  It can be useful to compare a series of consecutive months to see if there is any evidence for materialisation of frauds flagged as risks by supply-and-demand pressures (e.g. the recent increase in cocoa prices).  So far, we only have two months of analysis but we will continue to publish these trends over the year..

In this paper (purchase required) the authors developed an LC-MSMS method to identify and quantify fourteen illegal dyes in chili products, including chili powder, chili sauce, chili flavour, and snacks. They validated the method following the guidelines of CIR EU 2021/808 (the prescriptive requirements for methods for veterinary drug residues in animal products) at four concentration levels ranging from 5 to 70 µg/kg,. The method's applicability was further confirmed through successful proficiency testing (PT) participation.

An analysis of 2350 samples purchased on the Egyptian market over four years revealed that 18.62 % of chili powders, 14.05 % of sauces, 12.87 % of flavorus, and 11.32 % of snacks contained illegal dyes. Sudan IV and Red B were the most frequently found dyes in chili powders (15.86 % each), while Sudan I was the most common in sauces (13.72 %), flavours (12.54 %), and snacks (9.36 %).

Photo by Min Ling on Unsplash