News

The UK Department for Environment, Food and Rural Affairs (Defra) is running a campaign to recruit three new members to the Food Authenticity Methodology Working Group (AMWG). 

Applications are welcomed from any candidate who has the knowledge, skills and experience required for the role and who meets the essential criteria. More information about the role can be found in the Candidate Pack. The deadline for applications is 12 noon on Friday 15^th November 2024.

Information about the vacancies is given below: 

 The AMWG is a non-statutory expert committee of the Department for Environment, Food and Rural Affairs (Defra). The Committee provides expert advice on research carried out under Defra’s Food Authenticity Programme and is accountable to the Agri-Food Science Team within Defra’s Agri-Food Chain Directorate.  

The Chairs of expert committees meet annually with Defra’s Chief Scientific Advisor; and provide an annual summary of the work of the Committee to the Science Advisory Council (SAC) for Defra's Annual Report.     

Defra wants to attract high-calibre and forward-thinking applicants from diverse backgrounds to its expert committees. Applicants will need to demonstrate they are able to carry out a full range of non-executive responsibilities and have relevant skills, knowledge and expertise. Defra is seeking to appoint up to three new members to AMWG to cover the broad range of expertise required.  

Applications will be assessed against the following general essential criteria: 

• Experience in dealing with complex technical authenticity challenges, recognised expertise in food analysis and an understanding of fitness for purpose requirements and validation concepts for authenticity methods. 
• Demonstrable collaborative working and a willingness to enhance the UKs standing in the field of authenticity testing as well as the ability to understand and value different perspectives and to build productive relationships both within and outside the Committee.  
• Ability to think analytically and creatively and to contribute effectively to the formulation of sound scientific-based advice and decisions.   
• Ability to express views cogently and clearly, to represent views to the Committee and the Committee’s views to Government and other stakeholders.  

In addition to the above general food authenticity expertise and skills, we are seeking new members who have a good understanding or experience of at least one of the following:  

• Physical and chemical methods in particular spectroscopic and screening methods   
• Food Industry experience, supply chain assurance and traceability  
• AI/digital technology  
• Molecular Biology and Genetic technologies   
• A qualified Public Analyst with experience of Food analysis in a legal setting.    

 If you have any queries by email AMWGSecretariat@defra.gov.uk.  

This Masters’ degree project developed a predictive algorithm to categorize butter, butter spreads, and margarine/vegetable oil spreads according to their fatty acid profile, moisture, and total fat content based on the spectra collected by using handheld FT-NIR and portable FT-MIR devices. FT-NIR infrared and FT-MIR performances were similar, with a strong correlation (Rep >0.94) and low standard error of prediction for different analyzed parameters. SIMCA classification model based on FT-NIR and FT-MIR spectra effectively differentiated between butter, butter spread, and margarine/vegetable oil spreads.

The results were benchmarked against “classical” analysis.  Moisture and total fat content were determined using reference methods AOAC 920.116 and AOAC 938.06-1938, respectively. FA profile was determined using Gas Chromatography with flame ionization detector (GC-FID) (AOAC 996.06, 1996.). The FA profile showed that butter-containing products distinguished from margarine/vegetable oil spreads based on the presence of trans fats (TFA) (C18:1t) and butyric acid (C4:0).

The author concludes that portable FT-MIR and handheld FT-NIR technologies offer real-time and in situ analysis capabilities, enabling the dairy industry and regulatory agencies to make actionable decisions regarding FA, moisture, and total fat content and for nutrition, authentication, claims, and labeling purposes of these products.

The abstract and author contact details are available here.  The full text is being withheld until May 2026 at the author’s request. For an overview of FT-NIR see FAN's analytical techniques explainer for spectroscopy.

Photo by Sorin Gheorghita on Unsplash

Flow injection analysis (FIA) is a laboratory-based technique which is faster than liquid chromatography (HPLC) but less selective.

This paper (open access) builds on previous work to use high-throughput FIA-mass spectrometry (FIA-MS) fingerprinting of polyphenols to discriminate chicory from tea of various varieties,  This previous work had failed to discriminate chicory adulteration in the cases of black or green tea.

The authors have repeated the approach but this time using tandem mass spectrometry (MS/MS).  They built a database of the polyphenol fingerprint (55 polyphenols) from 100 tea samples (black, green, oolong, red and white) and from 20 chicory samples.  Database samples were purchased from local markets, so were of unverified source or provenance.  It is likely that this exercise of building the database would need to be repeated with verified samples if the test were to be validated for routine use.  The authors reported excellent chemometric discrimination between the “fingerprints” from tea and chicory, which they were then able to use to detect down to 15% adulteration of tea with chicory.

The authors recommend a workflow where FIA-MS/MS is used as an initial high-throughput screen, with polyphenols in “suspicious” samples then confirmed by LC-MSMS.

For an overview of the difference between MS and MS/MS, see FAN’s analytical techniques explainer pages.

Photo by charlesdeluvio on Unsplash

This paper (open access) reports a survey of 62 retail samples of processed whitefish products from British, Italian and Albanian retailers (mainly high-street supermarkets).  24 samples, spanning all regions, were reported as mislabelled using the criteria below.

The researchers used Next Generation Sequencing following DNA extraction using commercial kits.  Full details of the primers are given in the paper.  They prepared in-house positive and negative controls by blending various proportions of white fish species (from whole, identifiable, fillets) that are not used in commercial fish product manufacturing into mixtures of “authentic” species.

Since commercial designations of seafood species vary greatly both across and within countries, the researchers compared the ingredients provided for each product to the official list of commercial designation of the country where the product was purchased.. If a common name was declared on the label, the relevant species name was obtained searching FishBase , while if a scientific name was provided, it was contrasted directly with the molecular results.

Using matches and mismatches between label information and DNA-based identification, the researchers classified the examined products into the following categories: (i) “green” (correctly labelled product): when the proportion of reads of the declared species was at least twice as large as the second most abundant species and constitutes the majority of the bulk; (ii) “amber” (misleading product): when the proportion of the declared species was higher than any other species, but not necessarily amounting to the majority of the bulk; (iii) “red” (mislabelled product): when the declared species was either absent or not the most abundant in the mix; (iv) “grey” (undetermined product): when the declared species couldn’t be genetically identified with certainty.

Food Fraud Prevention – ISO 31000 Risk Management

Welcome! In support of the Food Authenticity Network (FAN), this blog series reviews key topics related to food fraud prevention. Watch here for updates that explore the definitions of food fraud terms and concepts.

This blog post builds on our previous review of the definition of risk and vulnerability as well as mitigation and prevention to review the International Standards Organization publication ISO 31000 Risk Management. The next blog post will shift focus to the ISO 31000 Risk Management concepts of the likelihood and then a separate blog post on the consequences.

International Standards – and specifically the International Standards Organization (ISO) – are efficient places to start when considering terms, definitions, and basic management system standards. Specifically, ISO 31000 Risk Management provides a crucial fundamental reference. Also, it is crucial to review what is published in this type of consensus-based, government-endorsed, official publication or what is part of informal documents or meeting notes (several of the widespread food fraud-related terms were published in workshop reports or even just meeting invitations). ISO 31000 Risk Management was published as a formal standard in 2009 after many years of a contensious consensus-driven process involving national standards organizations. This superseded more informal reports or informal guidance such as ISO Guide 73 Risk Management Vocabulary.

The publication of ISO 31000 was often contentious since some industries used terms in different applications. With the publication of ISO 31000, some people would need to change to achieve harmonization. Fortunately, food fraud prevention was developed after ISO 31000 was published (e.g., ISO 31000 significantly impacted my research and projects). Thus, from the start, food fraud prevention has focused on vulnerability and presenting the assessment in terms of “likelihood” rather than “probability” and “consequence” rather than “severity.”

ISO 31000 and Risk

In ISO 31000, a risk or vulnerability is defined in terms of likelihood AND consequence. It is critical to note that the assessment must cover both if the event occurs but also this impact. For example, jaywalking and murder are both clearly crimes, but the risk response is more based on a function of the consequence. An interesting – and often uncomfortable - realization for food safety professionals is that ‘risk’ does not only have negative consequences. Admittedly, food safety almost exclusively uses ‘risk’ for situations where there is an ‘unacceptable risk’ or a “hazard that requires a preventive control.” Understanding that, in the big picture, ‘risk’ does have an upside, such as financial investments.

• Risk (ISO 31000): “effect of uncertainty on objectives;”
  • NOTE 1: An effect is a deviation from the expected — positive and/or negative.
  • NOTE 3: Risk is often characterized by reference to potential events (2.17) and consequences (2.18) or a combination of these.
  • NOTE 4: Risk is often expressed in terms of a combination of the consequences of an event (including changes in circumstances) and the associated likelihood (2.19) of occurrence.

Then, a type of risk is a vulnerability.

• Vulnerability (ISO 31000 citing Guide 73): “intrinsic properties of something resulting in susceptibility to a risk source (3.3.10) that can lead to an event (3.3.11) with a consequence (3.3.18)."

“ISO 31000 includes a consideration for the preliminary or general assessments that may not require data that is very detailed, accurate, precise, certain, or robust decisions. What is often important is that ‘a’ risk assessment is conducted as long as the specification of the low certainty and low robustness is clearly defined. For food fraud prevention decisions, there may not be a lot of detail needed for a decision, or details may not be provided (at least not yet).” (Reference 1)

It is very important and of great value that ISO 31000 Risk Management provides a common set of terms.

Watch out for the next blog, which will review the application of ISO 31000 Risk Management topics of “likelihood versus probability” to “consequence versus severity.”

We’d love to hear from you in the comments box below if you have any questions on this blog.

References:

1. Spink, John W (2019). Food Fraud Prevention – Introduction, Implementation, and Management, Food Microbiology and Food Safety series, Springer Publishing, New York, URL: https://www.springer.com/gp/book/9781493996193

This September, Food Integrity Global 2024 saw the return of, ‘The Apples’, New Food’s industry awards created to recognise and celebrate some of the amazing and industry-leading talents within the food and beverage sector.

Our very own Executive Director, Selvarani Elahi was crowned ‘Food Defender of the Year’ for embodying the spirit of food integrity and consistently protecting our food system, through one or more actions in 2023/24!  There was an extremely strong field; leading food safety expert Darin Detwiler, and Giles Chapman of the UK's National Food Crime Unit.

Selvarani told us: “I’m honoured to have won this prestigious industry award. We built FAN to provide a public service to help stakeholders resiliently navigate food fraud in times of continuing global uncertainty. We are passionate about food safety standards and ensuring consumers can continue to have confidence in the food they buy. FAN is an open access website and over the past nine years, we have curated information on food authenticity testing and food fraud prevention promoting good practices that help improve food standards around the world; building more resilient global food supply chains. We’re proud of what we’ve achieved and our contribution to science for a safer world. FAN is very much a team effort and I am incredibly grateful to my excellent colleagues, past and present (Stephen Ellison, Gary Bird, Merry Rivas, Mark Woolfe, Sterling Crew and John Points) for always making time for FAN despite their workloads!”

In this paper (purchase required) a reversed-phase thin-layer chromatography (RP-TLC) method was developed to quantify the flavour enhancer monosodium glutamate (E-621) in various food samples following ultrasound-assisted extraction.

RP-TLC layers were precoated with RP-18 modified silica gel 60 F_254s. The mobile phase was ethanol‒water‒isopropanol (5:2.5:2.5, V/V).  The method used densitometric detection at 570 nm with an R_F value of 0.57.

The authors report that Monosodium glutamate (MSG) showed linearity in 500–1500 ng/spot range. RP-TLC separation was optimized, and the most influential and interacting parameters were identified using central composite design. Validation study was performed as per the International Council for Harmonisation (ICH) recommendations, which demonstrated all the parameters are within acceptable limits. MSG showed recovery of 93.12–101.42% among various food samples.

This test method was specifically designed to be sustainable and “green”, both in the extraction technology and the solvents used.  Its development used Analytical Quality by Design (AQbD) methodology, and various sustainability metrics are reported as favourable.

The authors conclude that the method provides a fast and environmentally friendly alternative to traditional procedures used to analyse MSG in foods.

This paper (purchase required) reports an electroanalytical approach for measuring apple juice or apple cider in white wine.

After addition of LiClO₄ as electrolyte and deoxygenation, reference samples were analysed using a screen-printed carbon electrode modified with gold nanoparticles (cyclic voltammetry).

The authors report that cyclic voltammograms (CVs) of white wine samples displayed consistency regardless of their grape variety, mono-, bi- or multi-varietal status as well as geographical origin. In contrast, CVs of apple juice and apple cider exhibited similarities but were distinct from those of white wine. They were particularly characterized by the presence of a cathodic peak at about -0.50 V, attributed to sugars and organic acids, predominantly malic acid.

The authors then exported these reference, cyclic voltammograms into data points and classified them using chemometric analysis. Principal Component Analysis effectively grouped samples into two clusters: white wine and apple juice/ apple cider. Class-modelling demonstrated the ability to detect adulteration in white wine samples, with a detection threshold of 5% v/v or lower, contingent upon the adulterant type (apple juice or apple cider). Partial Least Squares regression facilitated approximate quantification of the adulteration level.

They conclude that this approach is both cost-effective and straightforward, involving minimal sample preparation.

Photo by Jp Valery on Unsplash

This book (purchase required, either hardcover or e-book) includes a dedicated chapter “Quality Assessment and Authentication of Coconut Milk: Recent Technologies and Prospects”.  It also has equivalent chapters on authentication of coconut oil and authentication of virgin coconut oil, as well as a chapter on non-destructive testing applied to coconut products.

In this study (purchase required) the researchers build a classification model for differentiate freshwater from seawater shrimp (prawns), Litopenaeus vannamei, based on fatty acid (FA) profiling in muscle and hepatopancreas.

They built an untargeted model, using k-nearest neighbor (KNN) and random forest (RF), to identify discriminatory variables.

They then identified, using orthogonal partial least squares-discriminant analysis (OPLS-DA) specific FAs to create their classification model: six (C22:6n3, C20:3n3, C17:0, C18:3n3, C20:5n3, and C20:2) from the muscle and seven (C22:6n3, C16:0, C18:3n3, C18:2n6, C20:2, C20:1, and C18:1n9) from the hepatopancreas.

They report that, using FA profiles from the two tissues, both KNN and RF had initial and cross-validated classification rates >93%, while the predictive classification rates of the models based on muscle FA profiles were higher than that of the models based on hepatopancreas FA profiles. They conclude, therefore, that FA profiles in muscle were more effective than hepatopancreas FAs for this promising classification method.

Photo by Dan Dennis on Unsplash

The Joint Research Centre of the European Commission have published their latest collation of food fraud reports here. They have combined the reports from July and August 2024 into a single summary.  Thanks to FAN member Bruno Sechet who has again collated these as an infographic.  The original infographic, along with his commentary, is on Bruno's LinkedIn feed.

The JRC collation uses global media reports, and this always gives a slightly different picture than collating official reports.  FAN's recent report gives a high-level annual overview for 2023 from official reports. 

The NFCU have published their quarterly update for industry.

It covers the UK's updated Strategic Food Crime Assessment (described more fully in a FAN blog earlier this month), a specific warning about counterfeit vodka and a more general warning about meat composition and labelling, plus includes a section on best practice for goods-in checks.  Specific ingredients that are suffering current price or availability volatility are highlighted; UK lamb and pork, tea, edible oils, and lemon.

Two open access, E-learning resources from the International Atomic Energy Agency (IAEA) have been added to the E-Seminars section of our Training section:

• Elemental Analysis for Isotope Ratio Mass Spectrometry Course: Elemental Analysis for Isotope Ratio Mass Spectrometry (iaea.org) 
• Food Authenticity and Stable Isotopes Course: Food Authenticity and Stable Isotopes (iaea.org) 

In order to access these free courses, you need to register for an IAEA Nucleus account first here. 

In this study (open access) the authors used the fingerprint profile of fats and their metabolites to classify the cultivar (as either Tonda di Giffoni, TG, or as non-TG) and origin (either Chile CHL, Spain ESP, Italy ITA or Georgia GEO) of hazelnuts.  They propose a systematic workflow (see graphical abstract, below) first examining the Triacylglycerol profiles (TAG) as a screen and then testing the Unsapnifable Fraction (UF), if needed, for further classification.

The reference database was constructed from 309 traceable hazelnut samples collected from 2019 to 2022 directly from producers. Analyses was by gas chromatography–mass spectrometry.

PLS-DA classification models were developed to discriminate hazelnuts by cultivar and origin. The authors report that external validation results demonstrated the suitability of the UF fingerprint as a hazelnut authentication tool.  Both tested models showing a high efficiency (>94 %). The correct classification rate of the TAG fingerprinting method was lower (>80 %), but due to its faster analysis time, it is recommended as a complementary screening tool to UF fingerprinting.

The European Commission has published its 2023 report on the Alert and Cooperation Network, which facilitates cooperation and information exchange between Member States on official controls in the agri-food chain. The report reveals a significant increase in notifications compared to 2022 – a sign of the growth in cooperation between Member States in this area.

The Alert and Cooperation Network is composed of four sub-networks, each with an individual focus.

The Rapid Alert System for Food and Feed (RASFF) facilitates the rapid exchange information between food safety authorities on health risks related to food, feed or food contact materials. In 2023, there was an 8% rise in RASFF notifications, with a total of 4695 notifications. As in previous years, the most reported issue in RASFF concerned pesticide residues, followed closely by pathogenic micro-organisms. The top notifying countries continued to be Germany, the Netherlands, and Belgium.

The Administrative Assistance and Cooperation component (AAC) allows Member States to notify violations of EU food safety legislation which do not constitute a health risk. In 2023, there was a 24% increase in AAC notifications, with 3166 notifications.

The majority of AAC notifications in 2023 were linked to non-compliant fruits and vegetables, again mainly due to pesticide residues, followed by cases of mislabelling, such as unauthorised health claims for food supplements.

The Agri-Food Fraud Network (FFN) registered a 26% rise in notifications, with 758 fraud suspicions. The illegal trade of cats and dogs remained a major issue, with 414 notifications. Other suspicions related to meat substitution, honey adulteration, and mislabelled olive oil. Additionally, 1075 AAC notifications and 1625 RASFF notifications were flagged as potential fraud, prompting deeper inspections or investigations by Member States.

In its first operational year, the Plant Health Network (PHN) generated 128 notifications, as Member States shared details about non-compliant consignments of plants, plant products, and other items (such as seeds, fruits, vegetables, wood, and flowers) and other plant health concerns.

In this study (purchase required), 14 widely commercialized GM soybean events, including GTS40-3-2, MON89788, CV127, A2704-12, A5547-127, 305423, 356043, MON87701, MON87705, MON87708, MON87769, SYHT0H2, FG72, and DAS-444Ø6-6 were utilised as targets for event-specific identification. A high-throughput detection method was established by integrating a single universal primer multiplex PCR (SUP-M-PCR) with capillary electrophoresis  The authors report that this method enables the identification of 14 soybean events in a single PCR reaction, addressing the limitations of conventional multiplex PCR such as self-inhibition and amplification variations between different primers. Furthermore, it significantly enhances the sensitivity and accuracy of previous multiple detection methods, achieving a detection sensitivity of 0.05% (w/w). They conclude that this approach improves detection efficiency and holds promising potential for the identification and detection of the 14 targeted GM soybean events and their derivatives.

Photo by Meredith Petrick on Unsplash

The Food Standards Agency and Food Standards Scotland have published their joint Food Crime Strategic Assessment (FCSA) for 2024.

The FCSA supports the protection of consumers and the reputation of the UK food and drink industry through the following strategic objectives:
● Setting out a current assessment of the threats posed to the UK food system from food crime
● Identifying opportunities to detect, tackle and prevent food crime
● Taking a collaborative approach with local authorities, regulators and law enforcement agencies
● Alerting the UK food and drink sector to the threat of food crime and how it could impact on their supply chains

Specific threats identified and discussed include:
● Misrepresentation of red meat and poultry, with regards to status, origin or durability date
● Waste diversion, including links to Animal By-Products (ABP) handling within red meat and poultry supply chains
● The servicing of consumer demand for culturally preferred products through the slaughter, unlawful processing or importation of lamb and pork
● Authenticity challenges in the supply chains of commodities posing notable or persistent fraud risks to UK consumers arising from upstream, overseas adulteration and misrepresentation

There are areas of clear change from the assessment of 2020, including a significant reduction in the entry of illicitly gathered shellfish into the UK food chain (likely driven by changes to exports after EU Exit) and the rise in the retail availability of a broad spectrum of illicit imports in the UK, referred to as ‘grey market goods’.  UK responsibilities for enforcing 2,4-dinitrophenol (DNP) prohibition now sits with the police rather than food agencies, but this ongoing risk is also discussed

The servicing of consumer demand for specific, culturally preferred products, mainly relating to meat, both through illicit domestic production and through importation, remains a prominent theme, presenting in several different forms.

This review (open access) covers a range of topics relating to insect-protein safety and quality including a substantial section on authentication.  It is an output of the Czech-Slovenian bilateral project: Quality, Safety and Authenticity of Insect Protein-based Food and Feed (INPROFF).  It references studies to map the insect supply chain as well as analytical techniques to verify either the species or the substrate in which it has been reared.  Published techniques are largely based on stable isotope ratio analysis.  The review concludes that there have been relatively few authenticity studies, with a significant literature gap, and that without the necessary tools, a nascent insect farming industry is ripe for economic fraud.  The authors highlight a gap in metrological traceability for insect ingredient quality and authenticity analysis.  They report that the INPROFF programme is addressing this by developing a reference dataset based on genuine samples.

Photo by oktavianus mulyadi on Unsplash

This is posted on behalf of Demi Ellis - she is seeking survey respondants to complete a research project:

Calling all UK or Irish honey consumers

My name is Demi Ellis and I’m currently completing a research project as part of an MSc in International Business within Ulster University Business School, under the supervision of Dr Damian Gallagher. 

As part of this, I’m conducting a survey to obtain the perspectives of consumers on organic honey, which employs an exciting, innovative technology referred to as blockchain. Specifically, it will examine factors which impact consumer WTPP for blockchain-enabled organic honey. Your responses are pivotal in enabling me to gather as much data for the analysis of this research. If you have any colleagues or contacts that you feel would also be interested in undertaking this survey, I would appreciate if you could share where appropriate.

To partake, you must meet the following criteria:

• Aged 18 years old or older
• Live in the UK, Northern Ireland or Ireland
• Consume honey

 Your decision to participate is entirely voluntary and you have the ability to withdraw at any stage. If you wish to take part, the estimated completion time is about 10 minutes.

As a token of appreciation, on completion of the questionnaire, you will have the opportunity to enter a draw for one of five One-4-All e-Vouchers worth £10 each.

Please be assured that your responses will remain completely anonymous and are strictly used for research purposes. All data collected will be stored safely and securely.

To obtain further details and to participate, please click on the either of the two links displayed below:

📌 TOPIC OF STUDY: Factors affecting consumers’ Willingness-To-Pay-Premiums (WTPP) for blockchain-enabled organic honey
👉 TARGET AUDIENCE: Honey consumers in United Kingdom, Northern Ireland or Ireland
⏳ DURATION: 8 – 10 minutes
🔗 ORIGINAL LINK: https://qualtricsxmprnlqvfzp.qualtrics.com/jfe/form/SV_6s4Fr0wdByrgHgG

This review (purchase required) explores the recent advancements and applications of portable and miniature sensors, including portable/miniature near-infrared (NIR) spectroscopy, e-nose and colorimetric sensors based on nanozyme, for food authentication within the supply chain. After presenting the architecture and mechanism, the review discusses the application of these portable and miniature sensors in food authentication, addressing the challenges and opportunities in integrating and deploying these sensors to ensure authenticity. The review reveals the enhanced utility of portable/miniature NIR spectroscopy, e-nose, and nanozyme-based colorimetric sensors in ensuring food authenticity and enabling informed decision-making throughout the food supply chain

Photo by William Hook on Unsplash