News

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

The final report has been published from the German “DIGICHECK” project, which aims to strengthen and verify Organic traceability by utilising Internet-of-Things sensors and digital traceability systems.

The project aimed to achieve

1. The digital collection of real-time land, yield and certification data (from certifiers) and product transaction data (from companies of trading, processing, etc.) as well as the linking of this data as information for authorised users;
2. the calculation of mass balances along product chains calculated from land, income and transactions;
3. the use and linking of geographical information systems (GIS) and data collected by sensors to the certification data in order to provide control bodies with additional tools for their control activities, including independently of an on-the-spot visit;
4. the optimisation of control activities and quality assurance measures along the cereal product chain through the exchange of information between the operators involved;
5. clarifying which instruments and measures are permitted under the EU Organic Regulation and the German Organic Farming Act and could be implemented as required;
6. the evaluation of which tools can be usefully used by control authorities and which information should be made available in the event of fraud or monitoring;
7. the evaluation of the extent to which data can be evaluated for statistical purposes.

This review (open access) presents a comprehensive summary of the principles and recent advancements in the application of stable isotope techniques for authenticity assessment. It examines their use in detecting fraud (e.g., identifying edible alcohol, exogenous water, carbonylation, and trace compounds), vintage identification, and geographical origin determination across various alcoholic beverages, with a particular focus on wine, Chinese baijiu, and beer.   It cites over 100 publications from the past 15 years.

The authors conclude that stable isotope analysis is a powerful tool for verifying the authenticity of alcoholic beverages, offering effective solutions to combat counterfeiting, mislabeling, and adulteration. They recommend that future studies should focus on understanding the ecological, biological, and hydrometeorological factors influencing isotope signatures and develop advanced multi-isotope and chemometric approaches to improve reliability. Expanding global databases and integrating emerging technologies such as artificial intelligence (AI) and machine learning will further enhance the effectiveness and accessibility of stable isotope techniques, ensuring safer and higher-quality alcoholic beverages for consumers worldwide.

Photo by Ibrahim Boran on Unsplash

Tenet Law are a FAN partner.  They have kindly provided this best-practice guide to protect your business against Cyber Crime.  You can find out more at Tenet's website.

Cyber Risk: Who’s Really Prepared?

Cyber threats are evolving rapidly, yet many organisations remain unprepared for the risks they face and uncertain about how to respond in the event of an incident. No organisation is immune to the risks, making proactive cybersecurity measures essential.

From safeguarding sensitive data to managing third-party risks and responding to ransomware attacks, businesses must first identify vulnerabilities and gaps in their systems and processes.

Adding to the challenge, regulatory requirements impose additional complexity on our already demanding roles. Ensuring compliance and managing policies, procedures, and vendor relationships are crucial.

This article offers practical advice and strategies, helping organisations to feel confident in their approach, emphasising the importance of everyone in the business supporting and building resilience against cybercrime.

Large Organisations Vs Small Organisations

• Large firms invest heavily in cybersecurity due to greater risks and assets, but their systems are complex and harder to patch.
• Smaller firms may assume they are not targets or rely on outdated practices, making them vulnerable.
• Businesses of all sizes should conduct regular audits, training and software updates to avoid vulnerabilities in legacy systems and to comply with the latest regulation.
• At a minimum, carry out a basic cyber hygiene check annually to review software updates, access controls and incident response plans.
• Many businesses treat certifications like Cyber Essentials as a tick-box exercise, but these basic measures do not stop advanced cyber threats.
• The best security tools can be expensive, making them inaccessible for small businesses.
• ISO 27001 is the international standard for information security, requiring organisations to:
  • Identify security risks.
  • Select appropriate controls to mitigate risks.
  • Establish an internal process to handle incidents.

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Protecting Data & Third-Party Risks

• Fraudsters often target smaller vendors to gain access to bigger companies.
• Vendor risk assessments are essential—ask suppliers about their cybersecurity controls before sharing data.
• Review supplier contracts for security clauses and require them to meet cybersecurity best practices.
• Monitor third-party access—limit vendor access to only what they need, for the time they need it.
• Effective cybersecurity is about setting clear parameters—knowing what data is coming in, what is going out, identifying risks and defining actions to take when threats arise.
• Ensure your staff know how to escalate an incident to the appropriate person or team to determine whether a breach has occurred.

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Strengthening Defences

• Many businesses avoid cybersecurity because it feels too technical.
• Asking "Why do we do it this way?" can reveal security gaps.
• Get the Board interested by asking “What happens if we lose access to X system for 24 hours?”
• Cyber risk is now treated like health and safety—it’s no longer optional.
• Many businesses assume, “It won’t happen to us,” leading to poor preparation and rushed decisions during an attack.
• Have an incident response plan that includes:
  • Who is involved (internal/external)?
  • What steps must be followed?
  • Who makes key decisions?
  • How are systems restored and regulators informed?
• Be open and honest about breaches—notify affected parties promptly and follow legal reporting obligations (e.g., GDPR’s 72-hour rule).
• Transparency is key - I can recover from the truth I can’t recover from a lie!

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Real and Relevant Cyber Threats

• The cybersecurity industry often spreads fear rather than offering practical solutions.
• Many businesses struggle to identify which threats are real and relevant.
• Instead of overwhelming staff with too many security policies, focus on keeping it simple.
  • Protect your perimeter (firewalls, network monitoring).
  • Control what goes in and out (limit USB drives, monitor email attachments, downloads).
  • Training and education (unusual payment requests, phishing emails, passwords).
• AI tools create new risks, such as data leaks, deepfake scams and employees sharing confidential information with AI chatbots.
• Educate staff on AI risks and set clear guidelines on what can/cannot be shared.
• Many breaches occur because employees don’t report suspicious activity due to fear of blame.
• Build a non-blame reporting culture where employees feel safe reporting potential security issues.

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Ransomware Dilemmas

• Many companies quietly pay ransoms instead of reporting breaches.
• The government is moving toward banning ransomware payments for critical infrastructure sectors.
• NEVER pay a ransom—it does not guarantee data return and invites further attacks.
• Have offline backups to restore data if ransomware locks your systems.
• Some industries must report cyber incidents (e.g., financial firms under DORA regulations) and more mandatory breach disclosure laws may follow.
• Keep an action log—document every step of your cyber response (who was notified, what actions were taken) for legal and compliance purposes.
• Stay informed about new cyber security laws (e.g. the UK’s upcoming "King’s Resilience Bill").

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Preparing for a Cyber Attack

• The best way to prepare is to practice before it happens.
• Run a cyber attack simulation using real-life threats:
  • A fake invoice email with malware.
  • A ransomware attack locking business files.
  • A data breach where customer information is stolen.
  • An employee clicking on a phishing link.
• Measure response time, decision-making and gaps in your plan.

To understand more about Cybercrime watch the latest ‘At the Coalface’ webinar back on YouTube. Tenet’s Arun Chauhan - an accomplished lawyer specialising in fraud investigations and disputes, is joined by leading cyber security expert and consultant Adrian Jolly. Together, they cut through the noise and have an unfiltered conversation about cyber risk, what businesses are getting right, what they’re getting wrong, and how to stay resilient against evolving threats. Click here:

Tenet are a multi-award winning law firm specialising in complex fraud disputes, investigations and financial crime compliance. Our experience and sole focus is our expertise of dealing with a range of financial crime and fraud issues and applying that detailed and experienced knowledge to certain sectors, including food. For more information on how you can better prevent or investigate fraud within your business visit our website or sign up to receive articles, events and insights straight to your inbox

🌍🔍 EFF-CoP Editorial Board📝💡

The European Food Fraud Community of Practice (EFF-CoP) Editorial Board has been created to ensure knowledge flows freely to help experts unite, and members to shape the conversation!

The EFF-CoP  Editorial Board is comprised of a team of passionate professionals 🏆 dedicated to delivering insightful, high-quality content tailored to our members' interests. Each article will be written by specialists in their fields, ensuring accuracy, depth, and practical insights. All EFF-CoP members are invited to actively participate in shaping our content by engaging with our LinkedIn page.

This Editorial Board isn’t just about writing - it’s about listening and collaborating! Using LinkedIn polls 📊, EFF-CoP will ask YOU, our community, to vote on the topics that matter most. This way, every article will reflect real needs, real concerns, and real expertise!

All these articles will be uploaded to the upcoming EFF-HUB, a dynamic digital platform designed to connect minds, foster innovation, and provide invaluable resources. Only registered members will have access to Good Practice Recommendations, factsheets, case studies, educational content and a forum - all aimed at strengthening the global fight against food fraud.

EFF-CoP invites YOU to be part of this journey! Engage with our polls, suggest topics, and help shape the future of EFF-CoP!

Together, we can build a thriving, knowledge-rich community and strengthen our global fight against food fraud!

🎉 Stay tuned for the launch of the EFF-CoP website and HUB, upcoming articles, and let’s shape the future of food fraud detection and prevention together! 🙌

Please visit the the FAN for EFF-CoP for all EFF-CoP updates.

Jaggery is one of the most popular foods in India.

 This research (purchase required) presents a classical, novel colour-based method for detecting  adulteration in jaggery. A colour sensor is used to detect the colour of melted jaggery samples, and an Arduino Uno (opensource microcontroller board) is used to further analyse the colour. This research exploits the direct relationship between the captured pixel intensities of the jaggery and its purity in order to develop a linear regression model. The developed product is validated using samples having varying percentages of adulterations (10% to 70%) caused due to single and multiple adulterants (sugar and food colour) in jaggery. The abstract does not describe how these reference samples were sourced or prepared. 

The authors report that their machine learning approach gave promising results with accuracy of 94.67% and precision as 92.6%. The developed method for identifying tampered jaggery is user friendly, affordable, portable and non-destructive.

Photo by Prchi Palwe on Unsplash

Cocoa is high on many companies’ current risk radar for authenticity threats, due to recent supply pressures and price increases. Carob has legitimate uses as a cocoa replacement, and carob flour has been cited as a potential cocoa adulterant.

 A number of chemometric classification methods to differentiate cocoa from carob recently have been proposed, including one featured in our blogs in January based on DART-MS.  In a more recent publication (purchase required) the authors use the alternate method of near and mid-infrared spectroscopy before applying various chemometric approaches.

Spectral data were collected using four different infrared spectrometers: a benchtop FT-NIR system, two portable NIR instruments, and a benchtop FT-MIR-ATR. Reference samples included pure cocoa, pure carob, and their mixtures with carob concentrations ranging from 0 % to 60 %. Both classification and regression models were developed to detect and quantify the presence of carobs in cocoa powder. Classification models, including Random Forest (RF), Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), k-Nearest Neighbors (kNN), Linear Discriminant Analysis (LDA), and Soft Voting Classifiers, demonstrated superior performance for discriminating between cocoa powder, carob powder, and cocoa-carob mixtures, particularly using the benchtop FT-NIR. Similarly, regression models - RF, SVM, MLP, kNN, Partial Least Squares Regression, and Voting Regressor- exhibited robust predictive capabilities, particularly, FT-MIR and portable NIR.

Overall, these findings highlight and prove the potential of NIR and MIR spectroscopy as rapid, robust, and non-destructive tools for screening and quality control in food authentication.

Photo by lindsay Cotter on Unsplash

A2 cows’ milk is from selective breeds that produce a higher ratio of the A2/A1 form of β-casein in the milk.  It is sold mostly in Australia, New Zealand, China, and the United States and commands a price premium over conventional milk.  Authenticity testing has been difficult, typically requiring genetic techniques.

In this study (purchase required) the researchers piloted portable NIR to differntiate A2 milk versusnon-A2 milk and their mixtures using a portable NIR spectrometer.  They built a 1-class classification model.  63 samples of whole A2 milk were selected (authentic set), and 40 samples (fraudulent set) composed of non-A2 milk and mixtures in 3 different proportions (10, 25, and 50% v/v) of non-A2 milk in A2 milk. The abstract gives no further details of the reference samples in terms of production systems or seasonality.  For spectra collection, a MicroNIR was used.

Full data were pre-processed using different methods, but they found the most effective approach was the combination of the first derivative with Savitzky-Golay smoothing and Standard Normal Variate (SNV). A Data-driven Soft Independent Modeling of Class Analogy (DD-SIMCA) was applied. Using the Kennard-Stone algorithm, the authentic samples were split into two sets (45 for calibration and 20 for external validation). The non-A2 and fraudulent samples were added to the external validation set, and the model’s performance was evaluated using the metrics of sensitivity, specificity, accuracy, and precision.

They report that the DD-SIMCA model, utilizing 2 PCs, showed 100% results in all metrics, indicating no errors in the recognition of authentic samples.

They conclude that the model is suitable for use with portable equipment. Additionally, this fast and non-invasive technique can be optimized for applications in industrial management, food control, and A2 product authentication.

This study (open access) examined how variations in δ²H and δ¹⁸O values of cooking water affect the isotopic fingerprint of noodles with different gluten-to-starch formulations.

Eight differently formulated noodles were boiled using waters with six distinct isotopic compositions ranging from of −160‰ to +50‰ for δ²H and from −22.9‰ to +99.9‰ for δ¹⁸O, respectively.

It was found that formulation and water isotopic composition significantly affected the δ²H in cooked noodles. Additionally, the δ²H values of noodles changed with the isotopic signatures of the cooking water. Conversely, δ¹⁸O in the noodles remained stable despite boiling processing and was also not changed by the water's isotopic signature.

The authors derived an equation for determining the exchange factor (f(H)ex) between noodles and cooking water. The fraction of hydrogen atoms in different noodles for exchange was highest at 19.3% in noodles with the formulation of 45:55(gluten-to-starch) and the lowest at 11.1% in noodles with 100% gluten.

The authors conclude that cooking water systematically alters the isotopic signatures of noodles, underscoring the necessity of considering this type of effect in food authentication and traceability practices.

Photo by M. W on Unsplash

In this paper (open access) the authors demonstrate an optical, contactless method to discriminate different types of commercial milk (whole, partially skimmed and skimmed) and identify its adulteration with water and 12.5% water-glucose solution.  This adulterant was selected since it exhibits a refractive index comparable to that of whole milk, rendering such adulteration unnnoticed when performing a routine quality test based on refractive index measurements.

The prototype sensor employs a CMOS digital camera to acquire speckle pattern images generated by shining the beam of a red semiconductor laser onto milk samples placed in a plastic cuvette. The collected data are then analyzed to extract informative parameters, such as the average intensity and the speckle grain size.

The authors report that the system can distinguish between different types of milk and detect diluted samples with both water and glucose.

There is a growing market for the use of insect protein in feed.  The cricket species Gryllus assimilis. is approved in the EU for feeding farmed animals whilst the closely-related G. locorojo is only permitted for pets. The two are difficult to distinguish analytically in a highly processed product.

This paper (purchase required) reports a method developed on the basis of the cytochrome oxidase I gene, (COI), which was sequenced with thoroughly characterised G. locorojo and G. assimilis samples. The method is highly sensitive, detecting 0.8 pg G. locorojo-DNA or 0.1% G. locorojo incurred in feed, respectively. Authentic G. assimilis specimens were used to ensure that the G. locorojo method (Gloco-PCR) discriminates this closely related sister taxon, with a comfortable Ct-difference of 10-15. For cross analysis of true G. assimilis, similar primers with another probe were employed (Gassim-PCR) and the annealing temperature was increased from 60 °C to 62 °C.

Under these conditions, authentic G. assimilis crickets were detectable with Ct-values around 20, while G. locorojo samples showed a low detection at cycles around Ct 35. An investigation of ten ‘G. assimilis’ samples collected from Germany and four other European countries revealed that all of them were of the G. locorojo type.

The authors conclude that this small preliminary survey proves the usefulness of the method and supports the assumption that many G. assimilis crickets marketed in the EU indeed belong to the species G. locorojo. Consequently, European legislation, currently based on a white list of allowed insect species, is critically questioned.

Photo by Ivan Ivanovič on Unsplash

Laser Induced Breakdown Spectroscopy (LIBS) is a technique that can provide fast multi-elemental analysis , and hence food authenticity “fingerprints”, without requiring any sample preparation. It is an under-utilized technology in the food sector because of its high setup cost and lack of LIBS expertise in this sector.

This review (subscription required) gives an outline of LIBS fundamentals and instrumentation alongside published scope and capabilities of LIBS for detecting adulteration in various food samples.  The authors consider that LIBS is a pre-existing tool within the authenticity testing armoury which could be better utilised in the food sector..

The Food Authenticity Online Conference – Analysis for Authenticity, was held online on February 11-12 2025.

Over the two days, the >800 attendees, had the opportunity to listen to the keynote speeches of the Chief Scientific Advisers for Defra (Professor Gideon Henderson) and FSA (Professor Robin May) who both emphasised the importance of science and evidence in underpinning government policy and decision making. They also highlighted government’s critical role in supporting the development of new technology and innovation, allowing us to address future challenges in the food system.

Our speakers from day one explained untargeted testing and machine learning in engaging & understandable terms, showing that AI applications have been in use for decades. We also learned just how much authenticity research Defra and FSA is doing to try and stay ahead of fraudsters to protect legitimate businesses and consumers.

On day two, speakers highlighted the importance of authenticity reference databases/ datasets, their reliability and the accessibility of such data. We also heard how we need to have greater and continued cross sector collaboration to be more effective in detecting and preventing food fraud in the global food supply chain.

The conference recordings are now available here.

Presentations from both days are also available at the links below.

For anyone who attended and hasn't yet completed the very short feedback survey, we'd love to hear your views please.

Thank you

Selvarani

FAN Executive Director

FAN has been delighted over the past year to have collaborated with Professor John Spink to produce a stepwise guide through the fundamentals and terminology of food fraud prevention - Spink's Food (Fraud) for Thought.

We have now published the final two sections (here - within our Food Fraud Prevention menu) - "ISO31000 and COSO-Based Enterprise Risk Management (ERM)" and "Diagnosis treatment prognosis and conclusion ". 

The guide takes you through the whole risk assessment and risk management thought process.

We hope you find it useful.  Watch for the star of the next “Spink’s Food (Fraud) for Thought” blog post series on the Food Authenticity Network (FAN) website in 2025.

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 January 2025 report has been published 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.

In FAN’s graphical analysis, 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.

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) or substandard meat quality/content in processed foods (what used to be termed “QUID”).  Olive oil is the most adulterated specific product, including both substitution with other vegetable oils or mislabelling of Lampeter oil as EVOO.  Document forgery is a current watch-out in the UK, and the EU cases include a forged Health Certificate.

On February 12th, a virtual gathering of experts, researchers, and policymakers took place at the Analysis 4 Authenticity Online Food Authenticity Conference, hosted by the Food Authenticity Network.

Among the key speakers was Professor Saskia van Ruth, coordinator of EFF-CoP, who took the stage and introduced the project, a collaborative initiative designed to strengthen cooperation in the fight against fraudulent food practices. She emphasized how EFF-CoP is working to bridge the gaps - bringing experts together and reinforcing food integrity across global supply chains.

Updates will also be added to the FAN EFF-CoP page.

In the heart of Amsterdam, on January 15-16 2025, a group of passionate partners[1] came together to officially embark on an important journey - the fight against food fraud. This moment marked the beginning of EFF-CoP, a collective effort dedicated to making food systems more transparent, authentic, and resilient. With a shared vision, the partners made a powerful commitment to:

🌍 Enhance collaboration and knowledge sharing
📖 Develop and disseminate best practices
🚀 Promote innovative learning and capacity building
🔍 Strengthen food authenticity, traceability, and transparency
🤝 Expand and sustain a vibrant community through EFF-HUB
🌱 Ensure long-term viability and impact

Over the course of two inspiring days, Work Package Leaders and partners, took the stage, presenting their ideas, brainstorming strategies, and setting ambitious goals - not just for the project’s success, but for its lasting legacy beyond its official duration. But it wasn’t all work; they also cooked together, danced together, and built the kind of trust and camaraderie that turns a group of professionals into a true team.

In the coming months, EFF-CoP will launch its official website and EFF-HUB, a dynamic digital platform designed to connect minds, foster innovation, and provide invaluable resources. Members will have access to Good Practice Recommendations, factsheets, case studies, educational content and a forum - all aimed at strengthening the global fight against food fraud.

But learning won’t be confined to static resources. EFF-CoP is set to revolutionize engagement with interactive activities like food fraud festivals, gamified training sessions, living labs, webinars, podcasts, and hands-on workshops.

Whether you’re an expert, a researcher, a policymaker, or simply someone who cares about the integrity of the food on your plate - you are welcome to join. The fight against food fraud needs a community, and that community starts here.

[1] UNIVERSITY COLLEGE DUBLIN, AGROKNOW IKE, SMART AGRO HUB, NOFIMA AS, WAGENINGEN UNIVERSITY, REZOS BRANDS, LGC LIMITED, 8D GAMES BV, DELOITTE LIMITED, RETE INTERNAZIONALE PER LE PICCOLEE MEDIE IMPRESE, EUROFINS ANALYTICS FRANCE SAS, WENGER-TRAYNER UNIPESSOAL LDA, AUTORIDADE SEGURANCA ALIMENTAR E ECONOMICA, SSAFE, International Federation of Organic Agriculture Movements - EU Group, FIIN LTD, UDRUGA DIH AGRIHRANA HRVATSKA, Food Fraud Prevention Think Tank LLC, Stichting Fraude Film Festival, Stichting FSSC.

Updates will also be added to the FAN EFF-CoP page.

This study (open access) advances the field of “natural” vanilla flavour authentication, and of geographic origin of vanilla pods, by investigating minor volatile organic compounds and their isotopic ratios. Vanilla pods from the two main vanilla species, V. planifolia and V. tahitensis, were investigated using GC-MS/MS to analyze their aromatic profile and GC-C/Py-IRMS to determine compound-specific isotope ratios, providing, for the first time, detailed and authentic isotopic and aromatic profiles.

The researchers quantified more than 50 volatile compounds in different vanilla pods.

A key finding was the confirmation—through UHPLC-HRMS analysis—that ethyl vanillin and its glucoside precursors were absent in genuine vanilla extracts, reinforcing that the detection of ethyl vanillin remains a reliable marker of fraud.

The authors conclude that their study provides new insights into the natural pathways of biosynthesis in vanilla. For the first time, compound-specific isotope analysis has been applied to minor aromatic compounds in vanilla pods, opening new avenues for their use in authentication and botanical and geographical traceability of vanilla flavours. The study pioneers the application of isotope analysis to authentic vanilla extracts spiked with synthetic ethyl vanillin, enabling a more precise assessment of the impact on the isotopic composition of foods flavoured with natural vanillin following fraudulent augmentation with small amounts of ethyl vanillin.

Photo by Jocelyn Morales on Unsplash