News

The UK National Food Crime Unit's self-assessment questionaire has recently been revised.  This 20-minute prompt to check for best practice in fraud resilience is particularly aimed at Small and Medium Enterprises (SMEs)

A curated link to the NFCU self-assessment is within the "Tools" list on the "Food Fraud Prevention" FAN pages.  It is always worth a quick check for other tools on the list which might be a good fit for your own organisation.

This white paper is from the Institute of International and European Affairs, a non-profit charity that is Ireland’s leading international affairs think tank.

The paper tracks the suspicions of honey fraud and subsequent investigations and surveillance monitoring plans over the past decade, leading up to the EU legislation changes in the Breakfast Directive.  The paper makes the case that without this large-scale co-ordinated action and evidence-gathering, the possibility of wide scale fraud might never have been taken sufficiently seriously. It reviews the effectiveness of the current EU regulations and international cooperation efforts that are designed to detect and prevent honey adulteration and asks what technological and legislative improvements can be deployed to protect consumers and support EU honey producers.  It concludes by looking to the future and how honey fraud might be tackled on a local, national, and international level

The Joint Research Centre (JRC) of the European Commission have published a report that includes an overview of food fraud information sharing networks and incident data held around the world.  (including both the Food Industry Intelligence Network, Fiin, and the 2022 Defra report FA0175 into food fraud drivers and mitigation tools).

The report recommends the funding of a new predictive analytics model to try and prioritise future fraud risks based on historic patterns of reported incidents.  This would be predicated on improved data sharing between different countries and between industry and governments.  The report recommends a public-private partnership model to develop the concept.

The authors of this paper (open access) used Fourier-Transform Ion-Cyclotron Resonance Mass Spectrometry (FT-ICR) to accurately profile and classify thousands of chemical components within different types of coffee.  They are making their list of components publicly available alongside the paper.

Their reference set of 130 coffees were purchased at market, rather than being of traceable origin, but were verified by documentation from the manufacturers along with morphological examination and classification using the German standard NMR method.

From this list of markers, the authors investigated those with the potential to discriminate based on the complex Maillard reactions of roasting processes and those that could discriminate coffee varieties.  They propose a group of 25 tryptophan conjugates of hydroxycinnamic acids that could be measured by conventional high-resolution LC-MS and used as specific markers for rustica coffee vs arabica.

The latest edition of the Foods Standards Agency's National Food Crime industry newsletter has been published.

This edition covers:

• 2024 FSA and FSS Food Crime Strategic Assessment.
• Counterfeit Vodka.
• Sustainability Claims. 
• Good practice for ‘goods in’ stock. 
• Meat composition and labelling. 
• Horizon scanning. 

Read the bulletin.

You can contact the NFCU Prevention team to feedback, raise a concern or possibly contribute to a future update.

Measuring the profile of trace metals in food is one approach to discriminating its geographic origin.  Analytical tools for trace-metal measurement tend to be laboratory-based with expensive capital equipment.

There has been recent research to develop point-of-use sensors for metal ions using specific chemical binders (often based on the chemistry of human olefaction) with fluorescent markers.  This paper (purchase requires) takes the work a significant step forward.  Their sensor is based upon the principle that different metal ions induce different degrees of aggregation in perylene diimide derivative based supramolecular nanoaggregates.  This enabled the construction of a multi-analyte sensor which they report as having ease of preparation, rapid response, and high sensitivity originating from large specific surface areas.  The authors report that they used the sensor to build a successful classification model of geographic origin for both drinking water and apples.

The AIJN (European Fruit Juice Association) Codes of Practice are analytical identity standards for fruit juices which are internationally agreed and also cross-refererred within some legislation.  They are available here behind a subscription paywall.

The Codes of Practice have just been updated with new identity standards for blueberry and bilberry juices.  Thanks to Mikko Hofsommer of GfL, one of FAN’s Centre of Expertise Laboratories, for flagging this.

Photo by Jeremy Ricketts on Unsplash

'Our Food 2023: An annual review of food standards across the UK.' has been published today by the UK Food Standards Agency (FSA) and Food Standards Scotland (FSS).

This is the third in a series of annual reports since the UK left the EU. Our Food 2023 is an evidence-based assessment of food standards across all four nations of the UK.

The analysis conducted suggests that food standards in the UK remained stable during 2023. Yet there are questions about the resilience of our food system for the future. So, FSA and FSS are highlighting three areas that government, businesses and regulators need to work together to address.

1️⃣ More needs to be done to ensure that consumers can access safe, nutritious food against a backdrop of rising prices.

2️⃣ After a long-term decline in numbers, pressure on the local authority workforce continues, with a significant backlog in the number of food businesses awaiting inspection.

3️⃣ Without a reliable and secure resourcing model for Official Veterinarians, there is increased risk of disruption to the UK meat chain in the years ahead due to staff shortages, as well as increasing costs that will be passed on to businesses and consumers.

FSA and FSS are asking government, industry and regulators to work together on these and the other challenges highlighted in this report. The cooperation of everyone in the food system, from government departments and food businesses, to our colleagues in local authorities, remains essential for ensuring people have access to safe, healthy and sustainable food.

Read the full report.

This guide is being developed by the Codex Alimentatius Committee on Food Import Inspection and Food Export Certification Systems (CCFICS).  The draft is in 8 sections: (Preamble; Scope/Purpose; Definitions; Types of food fraud; Principles; Roles and Responsibilities of Competent Authorities and Food Business Operators; Relevant Activities for Competent Authorities; and Cooperation, Collaboration, and exchange of Information Between Competent Authorities). It includes working definitions of food fraud, food integrity and food authenticity, noting that they are not yet approved. 

The document has been drafted by an Electronic Working Group (EWG), led by the US, with China, EU, Iran, Panama, and the UK.  Selvarani Elahi, FAN's Executive Director, was UK co-chair for the ealier drafts and FAN have also fed into Codex discussions on fraud definitions.  The draft was brought back to the 27^th meeting of CCFICS, held in Cairns, Australia, in September.  It is now ready to go to the next Codex plenary meeting on 25^th November, before returning to another EWG for resulting edits then back to the 28^th meeting of CCFICS next year.

The 27^th CCFICS also discussed other standards and guidelines relevant to food fraud prevention, including modernising the Codex principles on traceability and product tracing (CXG60), digitisation of national food control systems, and new work on principles and guidelines to harmonize the use, development and implementation of (food-producing) establishment listing

A full report of the meeting can be found here, including contact details for each country’s representative on the committee.  The draft Food Fraud Prevention guide is included as Appendix II.

Photo by Nathan Cima on Unsplash

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.