News

This paper (open access) reports the development of a label-free electrochemical immunosensor for the detection of low quantities of porcine gelatin.  The sensor is based on a boron-doped diamond electrode modified with aryl diazonium salt. The diazonium electrografting enabled stable covalent immobilization of anti-porcine gelatin antibodies via protein A, preserving anti­body orientation and activity.

The optimised conditions were a 500× antibody concentration, 60 minute antibody incubation, and 15 minute gelatin incubation. Detection was performed using differential pulse voltammetry with [Fe(CN)₆]3-/4- as a redox probe, allowing label-free monitoring of anti­body-antigen interactions based on changes in current.

The authors report that the immunosensor demonstrated excellent analytical performance, with a detection limit of 142.15 pg mL-1. Specificity testing showed no cross-reactivity with bovine gelatin.

Although suitable validation would be required, the authors conclude that this immunosensor has potential to form the basis of a rapid, highly sensitive, and specific platform for porcine gelatin detection, offering great potential for food authentication and halal verification.

Researchers at Henley Business School (UK) are conducting a global research study on how organizations screen and evaluate new suppliers in food and agri-food supply chains.

Effective supplier screening is critical to managing risks such as food fraud, regulatory non-compliance, and unethical sourcing. Your insights will contribute to a broader understanding of current practices and help shape future standards.

If you have been involved in screening new suppliers in the past 5 years, please take part and share your valuable experience.

Survey Details:
Duration: 6–8 minutes
Anonymous and compliant with UK GDPR
Optional iPad draw
Option to receive a summary of findings
Take the survey now.

Your participation will help identify what’s working, what’s not, and what’s next in global supplier screening—ensuring that diverse industry voices are represented.

A new e-seminar pictorial guide for verification of previously frozen poultry has been published.

This e-seminar provides a guide for the implementation of a method for the verification of the labelling of previously frozen poultry by measurement of hydroxyacyl-coenzyme A dehydrogenase (HADH) activity.

When meat is frozen and then thawed, the muscle mitochondria (a type of intramuscular organelle) are damaged during the process and the enzyme HADH is released into the intracellular fluid. The relative increase in the amount of HADH found in the intracellular fluid before and after analytical method freezing procedure may be indicative as to whether the meat has previously undergone freezing. The measurement of HADH activity in the intracellular fluid, taken by pressing the meat and analysing the fluid using a spectrophotometer, is a simple, rapid and reliable procedure for a laboratory to undertake when evaluating the reported cryological history of raw chicken or turkey samples.

This e-seminar provides information and guidance relevant to understanding how to apply an HADH-based spectrophotometric method to differentiate between chilled and previously frozen poultry samples.

This e-seminar was produced by the Joint Knowledge Transfer Framework for Food Standards and Food Safety Analysis, funded by the Food Standards Agency, the Department for Environment, Food and Rural Affairs, Food Standards Scotland and the Department for Science Innovation and Technology via the Government Chemist.

The e-seminar has also been added to FAN's Training section.

Chlorogenic acids (CGAs) are phenolic compounds found in plant-based foods including coffee. This study (open access) aimed to evaluate the profile of three CGAs (5-CGA, 4-CGA, and 3-CGA )in medium-roasted Coffea arabica L. and Coffea canephora Pierre ex A.Froehner beans originating from diverse geographical regions.

The researchers reported that 5-CGA was the predominant compound across all samples analyzed.  C. canephora samples contained significantly higher and more variable levels of CGAs compared to C. arabica samples.

Statistical analysis using ANOVA, combined with Duncan, Tukey, and Dunn post hoc tests, confirmed species-related differences in CQAs content. Additionally, violin plots provided a clear visualization of these distinctions. Principal Component Analysis (PCA) further indicated that the geographical origin of the samples may influence the accumulation of chlorogenic acids.

The authors conclude that both botanical species and environmental factors influence the CGA composition of coffee. Understanding such variability could both give a useful authenticity marker and could guide the development of value-added coffee-based products tailored to consumer preferences and health-related expectations.

Photo by Clay Banks on Unsplash

Energy-Dispersive X-Ray Fluorescence (EDXRF) is a cheap non-destructive technique to measure metal and mineral content, typically operated as a laboratory benchtop method.

In this study (open access), researchers at the European Commission Joint Research Centre used market samples of oregano that had been previously tested under the EU co-ordinated official control plan to investigate whether EDXRF could be used as a screening technique.  This was a serendipitous extension of the use of EDXRF for checking compliance with EU limits for copper contamination.  After a relatively simple sample preparation, they measured a panel of 36 metals and minerals.

They found that, at it simplest level, the ratio of copper-to-zinc was a good indicator of adulteration with olive leaves without any need for modelling statistics.  Once multivariate statistics were used, samples could also be classified by geographic origin.  This classification required 2-stage modelling (SIMCA then PLS-DA) to achieve full potential, and then was limited because the reference dataset was not sufficiently comprehensive in terms of countries of origin.

The researchers concluded that their work demonstrates that EDXRF is a suitable screening method to detect oregano adulteration with other species, and to authenticate the geographical origin of the product. The method is clean, cheap and has a high sample throughput because it does not require sample digestion. For those reasons, the approach is ideal to be used by control laboratories.

SIMCA allowed the authentication of the geographical origin of oregano. The performance of the authentication could be improved with a combination of SIMCA with PLS-DA that provides sensitivities and specificities higher than 90 %. However, a database well populated with results obtained with samples coming from all the main producing countries, would be needed.

Issue 19 of the Food Authenticity Network Newsletter is now available.

This issue includes the following updates from FAN:

1. FAN Strategy 2025 - 2027
2. Global Food Fraud report 2024
3. Fundamentals of Food Fraud Prevention
4. New CEN Standards
5. Precision Breeding
6. Cultivated Meat
7. FAN Partnerships

As well as updates from the European Food Fraud Community of Practice project and our Food Authenticity Centre of Expertise.

Plus two interesting Guest Articles from the UK National Food Crime Unit and the Food Standards Agency on honey authenticity.

Our Food 2024: An annual review of food standards across the UK

The Food Standards Agency (FSA) and Food Standards Scotland (FSS) have published their annual ‘Our Food’ report, which reviews food safety and standards across the UK for 2024, which highlights ongoing food safety and standards challenges.

Overall, food safety and authenticity standards were stable in 2024, but several aspects of the food system remain under considerable pressure:

1. Local authorities still do not have enough resources to address the substantial backlog of inspections, nor deal with the growing number of new food businesses that should be inspected. 
2. There has been progress in implementing documentary and physical checks at our borders, however more comprehensive and accurate data would allow consumers to be better protected.
3. It is also still the case that too many households are struggling to afford food, and that more action is required to improve the healthiness of the food we eat.

The FSA and FSS are calling on government, industry, and regulators to work together to respond to these risks in our food system, to uphold high food standards, and to achieve a food system that works for everyone.  

Most test methods and research into the authenticity of edible oils are focussed on differentiating different plant species or on different grades of olive oil.  There has been relatively little focus on different grades of sunflower oil.  Commercial sunflower oil is sold as three different grades with increasing price premium; standard Sunflower Oil (SFO), Medium Oleic Acid (MOSFO) and High Oleic Acid (HOFSO).  HOFSO is more stable to repeated heating/cooling cycles and so is the grade typically required for fast food restaurants.  It is also available as a premium product sold direct to consumers.

In this paper (open access) the researchers used Spatially Offset Raman Spectrocopy (SORS, a portable non-invasive sensor) to build statistical models that could differentiate HOFSO from those that were not HOFSO (i.e. either MOSFO or SFO).  Although the reference samples used to build the model were purchased from commercial outlets rather than being of verified authenticity, the fact that two different unsupervised mathematical plus a number of supervised approaches all led to similar classification models, and that the models were validated with samples independent of the training sets, gave increased confidence in the model.

The authors conclude that the use of  SORS in combination with the developed chemometric models is an effective tool for the HOSFO authentication. The approach is simple and rapid, with instrumental fingerprints from portable analyser in less than 2 min and without requiring sample preparation.  This approach would class as Green Analytical Chemistry.

Image from the paper

The European Union has 13 flagship projects designed to tackle critical challenges in food safety, traceability and combatting fraud.  They are all under the funding umbrella of the Horizon R&D programme. FAN members will be familiar with the European Food Fraud Community of Practice (EFF-CoP) but this is just one project within the cluster.

All of the projects in the cluster are now indexed on the website of THEROS, one of the first of the projects to be launched.  The index includes project summaries and links.

• THEROS - An integrated toolbox for improved verification and prevention of adulterations and non-compliances in organic and geographical indications food supply chain
• EFF-CoP – the European Food Fraud Community of Practice
• Alliance – digital solutions for data veracity and transparency in food supply chaines
• CUES – consumers’ understanding of eating sustainably
• FishEUTrust - Increasing consumer trust and engagement in seafood products
• Sea2See - Blockchain traceability technology and stakeholders’ engagement strategy for boosting sustainable seafood consumption
• TealHelix – Inclusive and personalised food labelling
• Watson – digital and technical track-and-trace solutions, predominantly aimed to defend against counterfeiting
• Titan - Enabling transparency in food supply chains by implementing innovative solutions to boost health, sustainability, and food safety
• FOODGUARD - Microbiome applications and technological hubs as solutions to minimize food loss and waste
• ROSETTA - Reducing food waste due to marketing standards through alternative market access
• INfoodMATION - Optimising food information and communication towards healthier and more sustainable dietary patterns
• DRG4FOOD - Developing a European roadmap and a practical toolbox to guide policymakers, businesses, and civil society in designing food systems

The Food Industry Intelligence Network (fiin) was established in 2015 by industry technical leaders, in response to the recommendation of the ‘Elliott Review’ for the industry to create a ‘safe haven’ to collect, collate, analyse and disseminate information and intelligence relating to fraud risks. Fiin now has over 70 industry members, UK-based national and multinational food companies, who contribute their own testing data and insight which can then be anonymised, aggregated, and shared amongst the group.

Fiin has now launched a service to make some of this insight freely available to the wider food industry community, particularly to Small and Medium Enterprises (SMEs) which may have limited in-house technical expertise to mitigate food fraud risks.  The new SME hub requires users to register their details but there are no subsequent fees or restrictions.  Information and resources are listed in a clear and easy-to-navigate manner.

The hub offers

• Fiin's quarterly commodity watch-list - this is based on over 50,000 authenticity tests conducted by fiin's industry members, and so gives a different angle than data in the public domain (such as FAN's "most adulterated foods" collation) which are typically constructed from Official Reports.
•  Food fraud definitions and examples -  clear explanations and real-world illustrations
•  Food fraud prevention guides and training materials -  practical, SME-friendly tools
•  News & events -  updates and events relevant to food fraud
•  Food fraud reporting channels - know where and how to report concerns

All resources are free and tailored specifically to meet the needs of SMEs across the food sector.

We are proud, within FAN, that fiin has been a longstanding and supportive Partner.

Low Field (LF) Nuclear Magnetic Resonance (NMR) spectrometers have been used for routine inline quality control in the processed meat industry for many years.   Recent advancements have made the technology more accessible for other applications.

This proof-of-concept study (open access) demonstrates the potential of LF NMR for rapid oil authentication in an industrial setting. Their approach was based on solvent-free oil analysis using a single scan ¹H NMR measurement on a LF 80 MHz NMR instrument. The analysis identified the allylic signals at δ 2.0 ppm as a potential diagnostic region, effective in detecting adulteration in the oil samples. They limited the integration to this one spectral region in order to make data analysis rapid and easy to use in a food factory.

The authors demonstrated successful detection of adulteration in two types of vegetable oils rich in polyunsaturated fatty acids (PUFA), rapeseed and sunflower oil, at levels ranging from 5 % to 25 %. Specifically, the study found that adulteration in rapeseed oil could be detected at levels as low as 5 % when adulterated with soybean oil, 10 % when adulterated with sesame and cottonseed oils, and 25 % for corn oil and safflower oil. In the case of sunflower oil, cottonseed oil can be identified at 5 % adulteration, while corn, sesame, and safflower oils can be detected at 25 % adulteration.

The authors consider that the approach is fast, user-friendly, and ecological.  LF NMR could be a valuable tool for identifying adulteration in edible oils, with applications in various industries. This method would benefit from further research to validate the allylic region as a diagnostic region of oil adulteration.

Photo by Fulvio Ciccolo on Unsplash

This study (open access) used Nuclear Magnetic Resonance (NMR) ratios of key signals to differentiate the origin of Peppermint Essential Oil (PEO) as well as for the identification of adulterants in commercial PEO samples. Comprehensive analyses of 1D and 2D NMR spectra allowed for the identification of characteristic ¹H NMR signals associated with the key components of PEO.  Signals were assigned for 12 key components.  Significant compositional variations between PEOs from different geographical origins were revealed.

The US and India are the two primary production regions for PEO.  The model was built from authentic PEO samples of US origin (18),  India origin (15), twenty-seven blended PEO (US/India) samples and five de-mentholized cornmint (Mentha arvensis) oils.  All reference samples were collected by the National Center for Natural Products Research (NCNPR), University of Mississippi.

To facilitate differentiation, a straightforward indicator ratio method was developed to distinguish between PEOs from the United States and India.

A total of 50 commercial PEO samples were evaluated using the indicator model.  These included forty-three samples claiming to be pure PEO and seven claiming to be premium or therapeutic grade PEO.  They were purchased from various domestic and international suppliers of the US market

Results indicated a high adulteration rate (42 %). Adulterants, including synthetic chemicals, de-mentholized cornmint oil, and lower-cost oils, were identified.

The authors conclude that NMR is a useful tool for quality assessment and authenticity testing of essential oils. The methodology presented may also be extended to other essential oils to ensure product integrity.

For an explanation of the principles of NMR see FAN's introductory guide.

Photo by Anna Hliamshyna 💙💛 on Unsplash

This study (open access) aimed to identify the volatile compound components in chicken, beef, pork, and mixed (2-to-1 proportions) pork-containing satay, as well as determined the biomarker compounds for each type of satay meat.  The satay products were as commonly eaten in Indonesia, with cubes of meat barbequed on a skewer before adding the sauce.  Cooking in this manner gives the meat a distinct flavour, and the aim was to differentiate this by analysis of volatiles.

The volatile components in satay were extracted using the solid-phase microextraction (SPME) and analysed by gas chromatography-mass spectrometry (GC-MS). The data were processed using multivariate data analysis. 15 key volatile chemicals were measured.

Each type of satay meat exhibited good separation with the multivariate model. Beef and chicken satay were distinctly separated, whereas samples of pork and mixed pork-containing satay were positioned closely together.

The volatile compounds with the highest intensity in beef satay samples were nonanal, carbon disulfide, hexadecanal, and benzaldehyde. Chicken satay samples showed the highest levels of benzaldehyde, nonanal, hexadecanal, and hexadecane among the volatile compounds. In pork satay, the highest volatile compounds were cyclohexanol, 5-methyl-2-(1-methylethyl)-(1.alpha.,2.beta.,5.alpha.), hexanal, nonanal, benzaldehyde, and hexadecanal. Each type of satay meat was effectively separated, and mixed meat satay was positioned close to the pork satay group. The compounds identified as markers in beef satay were hexadecanal, nonanoic acid, ethylbenzene, pentadecanal, and heptadecanal. Chicken satay marker components included benzaldehyde; 2,3,5-trimethyl-6-ethylpyrazine; 2-nonenal, (E)-; linalool; 2-methylbutanal; and 3-methylbutanal. The marker components for pork satay and its mixtures were hexanal; thiophene, 2-methyl-; cyclodecene, (E)-; 2-methyl-2-butenal; and cyclodecene, (Z)-. These marker compounds present in each meat were highly correlated in the separation of satay samples.

The authors conclude that SPME-GC-MS successfully differentiated the satay meats and determined the compounds contributing most strongly to the separation.

Photo by Keriliwi on Unsplash

This blog, from consultancy group Forensic Risk Alliance, outlines the principles that a company must follow to demonstrate due diligence under the UK Failure to Prevent Fraud Act.  It is not specific to the food industry but the principles are generic,.  These same principles are good practice even for companies in countries that do not have similar legislation (i.e. a legal onus to take due diligence to prevent fraud) and for smaller UK companies not within the legal scope of the act.  The blog discusses how the principles can be implemented in practice:

• Implement a risk-based approach
• Incorporate fraud into other risk assessments
• Use existing data and technology
• Employee involvement and training
• Cross-industry collaboration

The blog contains links to other open-access blogs and articles on the same topic.

The authors of this study developed a targeted proteomics approach using LC–MS/MS and cross-species marker peptides with the potential to quantify meat in vegan and vegetarian foods. The method is designed to achieve the threshold of 0.1% w/w that is commonly applied for unintended cross-contamination.

 Protein extraction and digestion were optimized for rapid, simplified, and highly efficient sample preparation. Three matrix calibrations (0.1–5.0% w/w meat, each) were applied to vegan sausages and burger patties spiked with pork, chicken, or beef meat. The four markers DFNMPLTISR, DLEEATLQHEATAAALR, IQLVEEELDR, and LDEAEQLALK showed the highest accuracies for the determination of meat contents (recovery rates of 80–120%).

Although purchase is required for the full paper (here) the work builds upon previous publications and this supporting information is available free of charge (following the same link).  This includes detailed description of the statistical analysis; meat marker peptides before and after their re-evaluation; pea marker peptides; details of the LC runs; base materials and further ingredients for the vegan sausages and vegan burger patties; defatting/dehydration efficiencies of PLE and in-tube defatting/dehydration; comparison of extraction buffers and trypsin concentrations (matrix: vegan sausage with chicken meat); properties and comparison of different trypsins; chromatograms of the meat marker peptides from different matrixes; linear regressions derived from the quantifiers of the meat marker peptides in different matrixes; trueness and precision; mean signal-to-noise ratios at given meat contents.

Photo by LikeMeat on Unsplash

In this study (open access) researchers developed and piloted a single in-line sensor to classify yoghurt as either sheep, goat or milk origin and simultaneously check viscosity and pH Quality Attribute Specifications.  Their goal is a rapid in-line sensor that incorporates automated decision making, for routine use in the dairy industry.

Their reference dataset was sourced directly from two reputable Spanish companies and included both pasteurised and UHT yoghurts.

They found that the animal origin of milk could be predicted by building models based on the spectral data between 400 and 600 nm whilst viscosity and pH could be predicted by building models based on the spectral data between 800 and 1800 nm. To identify the animal origin of milk, they used Partial Least Squares-Discriminant Analysis (PLS-DA), achieving 100 % accuracy (95 % confidence interval). The model used to predict pH and viscosity was built with Partial Least Squares Regression (PLSR). The predictive power was generally very good (MSE=0.04–0.06; R²=0.94–0.96; MAE=0.16–0.17).

They conclude that their study demonstrates that the proposed spectroscopic method offers a more efficient approach for the simultaneous prediction of pH, viscosity, and milk origin in yogurt compared to existing methods, that require separate and slower analyses. Further work still needs to be carried out to optimize the model and achieve real-time monitoring that enables automated decision-making.

[picture – from the publication]

Are you interested in pursuing a PhD?

Would you like to tackle real-world challenges in food and nutraceutical analysis, using state-of-the-art instrumentation and advanced data handling, to uncover hidden adulteration and ensure consumer safety?

If you're passionate about science with impact, join this cutting-edge PhD project at the intersection of analytical chemistry and food integrity. The project is led by Prof Kate Kemsley and co-supervised by Dr Maria Marin (University of East Anglia) and Dr Lionel Hill (John Innes Centre), with joint funding from UEA and the UK Community for Analytical Measurement Science.

For further information and to apply visit: PhD Fast chemical profiling for detecting fraud in foods and nutraceuticals (KEMSLEYEK_U25SCICAMS) 2025/26 | UEA

The Food Fraud Prevention Think Tank is run out of Michegan State University by FAN Advisory Board member Professor John Spink.

It offers a series of regular blogs, plus training and other resources both online and in-person.

Professor Spink's latest blog is on the topic of the "Grief Cycle" - the progression of corporate emotions and responses when a fraud is uncovered.  This moves the thinking on from prevention to incident response and continual improvement.

We are grateful that Professor Spink has also collaborated with FAN to write a "back to basics" guide to the principles of fraud risk assessment and mitigation.  This valuable resource can be found on our website here.

The Food Authenticity Network works on a 3-year governance cycle of strategies and targets.  We have been working on our strategy for 2025-2027, and have published a summary here.  Please take a look.  The document summarises our achievements over the past 3-year period and lays our path for the next.

The strategy restates our commitment to being an open-access network, free to all global stakeholders, advancing and sharing best practice in food fraud prevention and detection.  We will leverage our impact by collaborating with other likeminded organisations.  We will seek to accelerate our successful membership growth (currently over 5,700 members), reducing our current bias towards UK members (currently 50%) by targeting membership growth particullarly within Europe and the "5-eyes" intelligence alliance countries.  We will continue to review the resources we offer and signpost, in order to provide maximum benefit and insight to our members, from multinational food companies and testing laboratories to local small businesses and enforcement officials.  The strategy relies upon a sustainable funding model, and includes targets to grow and diversify our valued funding partner organisations and to strengthen the resilience of our IT infrastructure.

As we approach our 10-year anniversary, our vision remains as a world where collaboration and shared best practices in food fraud detection and prevention creates a safer, more transparent, and trusted global food supply for all consumers.  It is as relevant now as it was at FAN's inception.

The Joint Research Centre of the European Commission have published their monthly collation of food fraud reports for March 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 where you can also access his other food safety infographics and services.

These collations from the JRC are based on global media reports, and so give a different picture to EU agri-food "suspicions" (as analysed in our most 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 and aggregates.