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In this study (open access), researchers set out to discriminate Royal Gala and Golden Delicious apples as being either Czech or Polish origin.  They built a reference database of 64 samples were collected in the years 2020–2022 from Central Bohemia  Eastern Bohemia, South Moravia, Lower Silesian Voivodeship, Łódź Voivodeship, and Masovian Voivodeship.  They measured phosphorus (P), potassium (K), magnesium (Mg), calcium (Ca), boron (B), zinc (Zn), manganese (Mn), and iron (Fe) as well as isotope ratios ¹⁰B/¹¹B and  ⁸⁷Sr/⁸⁶Sr.

They concluded that, with this data set, it was not possible to robustly differentiate Czech vs Polish origin.  The variation within individual regions, and the variation due to different agricultural inputs, was too significant compared to the variation between countries.  They concluded that differentiation would be possible in principle but a much more granular reference database would be needed.  Their findings contradicted previous published work that phosphorus was a suitable marker to differentiate Czech from Polish apples.

Photo by Priscilla Du Preez 🇨🇦 on Unsplash

Meat species identification has always been a challenge in highly processed foods, such as gelatines and stocks.

One approach is to measure proteins and protein patterns using mass spectrometry (MS).  A previous research project, under the UK Department of Environment, Food and Rural Affairs (Defra) Food Authenticity Programme, developed and in-house validated a method using proteomics.

That work has now been built upon by another 3 Defra projects to streamline the method to look for specific markers, in a format that can be used routinely by testing laboratories, and to fully validate the routine method including by interlaboratory trial.

All four research reports are now signposted on FAN’s Research pages.  Scroll through the table to find the appropriate report reference number:

• FA0166 – the original 2019 project – “Development, optimisation and validation of a non-targeted proteomics method for meat species identification”
• FA0165 – “Liquid chromatography targeted mass spectrometry method to determine the animal origin of gelatine - transfer to a high throughput, low cost platform with single lab evaluation”
• FA0177 – “Gelatine species determination, completion of method validation and determination of a quantitative method”
• FA0187 – “Interlaboratory trial of a mass spectrometry method for meat species determination”

Our December 2024 Newsletter is now available to download here.  In this issue:

• New resources – Authenticity test method explainers
• Updated resources – Laboratories with authentic food reference databases
• Updated resources – Honey reference sampling protocol
• Project launch – European Food Fraud Community of Practice
• Guest Article – Food fraud prevention US perspective
• Guest Article – Botanical adulterants prevention programme
• Centre of Expertise case study – Sugar detection in fruit juice

Plus we welcome Campden BRI and Natural Trace as FAN Partners, welcome five UK Public Analyst laboratories as new Centres of Expertise, and announce dates for our Analysis 4 Authenticity Conference 2025.

There is no single definitive test for dilution of honey with foreign sugar syrups.  An untargeted test, often used to contribute to an analytical weight of evidence, is proton NMR followed by chemometric pattern recognition based on variations in the sugars profile.  One disadvantage of this technique is a lack of sensitivity. 

LCMS is a more sensitive technique and could – in principle – be used in a similar untargeted manner to drive pattern recognition statistics based on the sugar profiles of a database of reference honeys.  The limiting factor has been the computing power that would be needed to “re-set” the database each time a new chromatographic peak is measured or data from different chromatographic systems are combined. (this is why untargeted LCMS is often used in authenticity testing as a 1-off development tool to identify marker compounds, which are then used as the basis for a more routine targeted test, rather than being used as a routine untargeted test).

In this paper (open access), the authors resolved the computing power limitation by using their Bucketing of Untargeted LC-MS Spectra (BOULS) data processing approach which they have previously published.  They demonstrated that untargeted LCMS testing (combining data from different systems, HILIC column with MS in both positive and negative ionisation mode) could discriminate a range of adulterated honeys (rice, beet and high-fructose corn syrups added at 5% to a reference set of 34 North German honeys) from their unadulterated counterparts.

As is the case with all untargeted analytical techniques, the key to using this method routinely would be building a robust reference database of verified authentic honeys that is fully representative of all types and origins on the market.

Photo by Roberta Sorge on Unsplash

Wines can be mimicked by the detailed addition of glycerol, sugars, colours, water and other additives.  Sometimes this is carefully balanced so that the fraud is difficult to detect by analysis of one parameter alone.

In this paper (open access conference presentation from researchers in Crimea) the authors propose a specification for “authentic” wines based upon 11 analytical indicators. 

This is based on in-house research where they prepared 3500 counterfeit wines adulterated in different ways, and studied the feedback effect of changing one analytical parameter upon another.  All parameters were measured using established and published test methods that are considered accessible to industrial laboratories.  They observed that every type of adulteration had an indirect effect on another analytical parameter, so if sufficient parameters were measured it was very difficult for fraudsters to mask their activity.  Specification ranges were established by training sets prepared from their in-house adulterated and unadulterated wines.

Table reproduced from the publication, Creative Commons licence

A weight of evidence approach is typically employed for food authenticity investigations in situations where screening tests do not provide a definitive answer, or where there is no applicable legal limit for what is being evaluated. In these types of situations, gathering and assessing several different forms of evidence may aid in coming to a conclusion on the authenticity of a sample/product.

This e-seminar is based on a “Toolkit to Support Weight of Evidence Approaches for Food Authenticity Investigations,” that has been published by Defra, and provides guidance and best practice on how to approach a weight of evidence assessment, in order to verify the authenticity of food and drink samples where no single confirmatory test result is currently available. It has been designed to support anyone who is required to make an assessment on the authenticity of a food or drink sample based on a combination of information from several independent sources but may also be of interest to anyone in the food and drink industry who undertakes supply chain audits and due diligence checks as part of any authenticity investigation.

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

This eSeminar has been added to the eSeminar tab of the FAN Training section and can also be viewed here:

The FAN annual call for new Centres of Expertise (CoEs) was launched in the last FAN Newsletter; the applications received were reviewed by FAN and recommendations for acknowledgement discussed and agreed with the UK Department for Environment, Food and Rural Affairs, the Food Standards Agency & Food Standards Scotland.  

We are delighted to announce that the following five organisations have been acknowledged as Food Authenticity CoEs:  

• Edinburgh Scientific Services 

• Glasgow Scientific Services 

• Hampshire Scientific Services 

• Isle of Man Government Laboratory 

• Tayside Scientific Services.  

These organisations are all Public Analyst laboratories and have a wealth of experience in food authenticity analysis in the context of official controls. Two Public Analyst laboratories were already recognised as CoEs, and now all seven will be listed as food authenticity CoEs in a separate category called ‘Public Analysts’. 

We are thrilled to announce that Campden BRI has become a FAN Partner!

With over 4,000 member companies in 90 countries, Campden BRI is the trusted, premier, independent technical partner of choice for the food and drink industry. Leveraging its 250-plus world-renowned technical experts, it helps to make food safer, tastier, healthier, affordable, sustainable, convenient, and innovative, underpinned by investment in meaningful research and science.

Campden BRI offers an extensive range of services including consultancy, analysis and testing, processing, contract research, manufacturing support and guidance, training, and regulatory and labelling advisory services. Members and clients benefit from industry-leading facilities for analysis, product and process development, and sensory and consumer studies. Campden BRI is ISO9001 certified and many of the analytical services are UKAS (United Kingdom Accreditation Service) ISO17025 accredited.  (www.campdenbri.co.uk )

FAN already acknowledges Campden BRI as a Food Authenticity Centre of Expertise; with Campden BRI’s industry knowledge and expertise, this partnership enhances our ability to offer even more robust and industry relevant resources to support members to combat hashtag#foodfraud and ensure hashtag#supplychainintegrity, furthering our mission to protect consumers and legitimate businesses worldwide.

This partnership is a significant step towards a safer and more authentic global food supply!

We're delighted to offer 𝗖𝗮𝗺𝗽𝗱𝗲𝗻 𝗕𝗥𝗜 𝗺𝗲𝗺𝗯𝗲𝗿 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝟱𝟬% 𝗼𝗳𝗳 𝘁𝗵𝗲 𝗿𝗮𝘁𝗲 𝗼𝗳 𝗙𝗔𝗡 𝗣𝗹𝗮𝘁𝗶𝗻𝘂𝗺 𝗮𝗻𝗱 𝗚𝗼𝗹𝗱 𝗣𝗮𝗿𝘁𝗻𝗲𝗿𝘀𝗵𝗶𝗽 (such Partners receive our quarterly global food fraud dashboard), for further information, please contact us at Secretary@foodauthenticity.global. Thank you.

The National Food Crime Unit (NFCU) of the UK Food Standards Agency has issued an AMBER Food Crime Alert on the Risk of Distribution Fraud Thefts from Food Businesses.

There has been a recent increase in the reporting of distribution fraud being used as a method of stealing high value food products from UK based companies.

The method of theft will include impersonating an existing business and using falsified documentation such as email addresses, invoices or even fake websites.

WHY HAS THE NFCU ISSUED THIS ALERT?
This alert is based on recent reports of this methodology being used in high profile thefts of food. Because of this NFCU is sharing this information via industry groups in England, Wales and Northern Ireland to encourage vigilance to this potential risk, and that food businesses update any risk assessments and processes to increase their resilience to this form of fraud.

           ACTION RECOMMENDED

1. Ensure that this information is used to inform any vulnerability or fraud risk assessments with appropriate actions in place.
2. Inform relevant colleagues with responsibility for sales and customer contracts to be aware of any unusual or suspicious activity such as changes to bank details from existing customers or new customers requesting extremely large orders of high value items.
3. If unsure whether a purchase is legitimate, do not reply directly to contacts via email or messages. Instead use publicly listed information for the company that are attempting the purchase and contact them directly to validate the details you are being given.

CONTACT NFCU - If you become aware of information relevant to this Food Crime Alert, please share with us via:
WEBSITE – visit food.gov.uk and click 'Report' at the top of the page.
TELEPHONE –08000 28 11 80.
EMAIL – foodcrime@food.gov.uk.
Please quote the alert number A002 in correspondence. Our processes enable us to handle information discreetly.

Read full alert.

More than 22 tonnes of three artisan award-winning cheddars worth more than £300,000 stolen from London cheese specialist in October 2024

The Food Authenticity Network is delighted to be a Partner in a new initiative: The European Food fraud Community of Practice: From Outset to Operation(EFF-CoP).

With €2 million funding under Horizon Europe Coordination and Support Actions, the EFF-CoP is led by Professor Saskia van Ruth, Professor of Food Supply Chain Integrity at UCD School of Agriculture and Food Science.

This new three-year project, starting in January 2025, will bring together a community of scientists, regulators, small- and large-sized businesses, laboratories and other stakeholders to create a research and innovation ecosystem to enhance food authenticity and traceability.

A page will be created on this website to link to the EFF-CoP website so that FAN members can keep abreast of progress.

In addition, you can become a member of the EFF-CoP community by emailing effcop@ucd.ie ✍️ and you can follow the EFF-CoP on LinkedIn.

Analytical Chemists / Scientists in Industry - please complete this short survey (using the QR code) on your data analysis experiences, your expert views are important for ensuring the right education and training. 

A reminder that the EU now publishes a monthly collation of "Agri-Food Fraud Suspicions".  A permanent link to these is also within FAN's Food Fraud Prevention reports listing. Such reports are a valuable aid to vulnerability assessment updates and reviews.

One example within the detail of September's "Suspicions" report is the potential for cause-and-effect between food safety risks and subsequent fraud risks.  Historically, the fumigant ethylene oxice (ETO) has been used to control salmonella risk in shipments of dry seeds/powder ingredients and additives, including xanthan gum.  With the EU ban on ETO, there have been recent RASFFs for residues of ETO in xantham gum.  The impact of the ban on salmonella risk is unclear.  We are now seeing cases of faked health certificates for xanthan gum.

Food Fraud Prevention - Understanding ISO 31000 and Consequence in 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 post expands on our earlier discussion of ISO 31000’s ‘likelihood’ component in risk assessment to explore the final key concept of ‘consequence.’ In our next post, we’ll complete the risk assessment process by applying COSO-based Enterprise Risk Management (ERM) to set a precise risk tolerance level.

To recap, a vulnerability in risk management combines ‘likelihood’ and ‘consequence’ to assess potential outcomes. Both elements are essential for comprehensive risk evaluation. Let’s consider this with a familiar example: the consequence of a 5% chance event varies widely depending on the context. A 5% chance of stubbing your toe at night might require no precautions beyond possibly turning on a light (‘risk acceptance’), while a 5% chance of drowning would prompt more significant measures, such as wearing a life jacket (‘risk treatment’) or finding an alternative way to cross the water (‘risk avoidance’).

To recap, a vulnerability is a type of risk. A risk is determined by the combination of ‘likelihood’ and ‘consequence.’ Remember:

Risk Assessment Essentials in ISO 31000

• Risk (ISO 31000): “effect of uncertainty on objectives; [Reference 2]
  • NOTE 1: An effect is a deviation from the expected — positive and/or negative.
  • 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.
  • NOTE 3: Risk is often characterized by reference to potential events (2.17) and consequences (2.18), or a combination of these.

ISO definitions are carefully crafted through years of review across disciplines, emphasizing the importance of structured and universal terminology in risk management.

• “Consequence (ISO 31000): outcome of an event affecting objectives
  • NOTE 1: An event can lead to a range of consequences.
  • NOTE 2: A consequence can be certain or uncertain and can have positive or negative effects on objectives.
  • NOTE 3: Consequences can be expressed qualitatively or quantitatively.
  • NOTE 4: Initial consequences can escalate through additional effects. [ISO Guide 73:2009, definition 3.6.1.3]”

These guidelines provide a thorough framework for organizations assessing risks, helping them identify and respond to various outcomes more effectively.

The Importance of Consequence vs. Severity in Risk Management

To help frame the problem in a broader business sense, ‘consequence’ considers a broader interpretation of the terms. Specifically the term ‘severity’ insinuates only a negative outcome. Some methods refer to other more neutral terms, such as ‘impact’ or ‘outcome.’ In a business, there is a need for some level of risk-taking to meet performance growth and financial goals. However, the term ‘consequence’ covers a broader range of possibilities, including positive, neutral, and negative results. In the context of food safety, for instance, risk isn’t just about avoiding undesirable outcomes—it’s about managing them to meet an organization’s goals. “Many Food Scientists and Food Safety managers use the term ‘risk’ to define an unacceptable or intolerable level.” [Reference 3] This aligns with business risk-taking, where managing risk appetite allows for opportunities that may bring rewards.

For example, buying a stock involves risk, but it’s a controlled risk with the potential for reward. Risk assessment, in this sense, includes both ‘likelihood’ and ‘consequence,’ ensuring that resource allocation aligns with both risk tolerance and potential outcomes.

The Formula for Risk: Likelihood x Consequence

Effective risk management must account for both likelihood and consequence to allocate resources wisely. While every event is bad and disruptive, the likelihood of an event is important ONLY in relation to the consquence, and vice versa. It should be noted that a food fraud incident – or known fraud in a supply chain – is illegal. Unless the operators are a criminal organization, the likelihood would be defined as ‘100%,’ and the consequence is ‘illegal product,’ so this situation is an ‘intolerable risk.’ In this case, addressing vulnerabilities shifts from reacting to incidents to eliminating root causes that could lead to fraud.

Adjusting terminology to align with ISO 31000 can simplify this process, but defining your organization’s risk tolerance threshold is crucial—and often complex.

Coming Next: Determining Your Risk Tolerance and Risk Appetite

Our next post will cover determining your organization’s risk tolerance, examining both likelihood and consequence. Traditional risk assessment frameworks often assign this threshold to an undefined “someone” within the organization. However, this step is both critical and complex in the risk assessment process and requires careful consideration.

If you have any questions on this blog, we’d love to hear from you in the comments box below.

References

1. (R1) 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
2. (R2) – ISO 31000 Risk Management, International Standards Organization (ISO), Updated 2023, https://www.iso.org/iso-31000-risk-management.html

3. Applying Enterprise Risk Management to Food Fraud Prevention (ERM2), 2017, Food Fraud Prevention Academy, https://foodfraudpreventionthinktank.com/wp-content/uploads/2021/05/BKGFF17-FFI-Backgrounder-2016-ERM-ERM2-v46-2.pdf

There is a price premium for tomato sauce labelled as “natural” or “no artificial additives”.  Citric acid (E330) is a common component of tomato sauces, and the cheapest form is biosynthetic (i.e. it is not “natural”).  There is therefore an incentive for deliberate misrepresentation on the label, and a consequential need for test verification methods as to whether the citric acid is “natural”.  Current reference specifications (e.g. AIJN) do not include tomato sauce.

In this conference presentation (open access) the authors report the successful use of Stable Isotope Ratio Analysis to discriminate the botanical source of the citric acid in tomato sauce  Biosynthesised citric acid is from cane or corn feedstock (C4 plants) whereas inherent tomato citric acid is C3.  The researchers established threshold values for citric acid carbon isotope ratios from authentic “natural” tomato sauces and used these to test a range of products on the market.

Photo by sentidos humanos on Unsplash

Differentiating gelatin species is an analytical challenge because of a lack of intact DNA.  Most speciation methods therefore target the profile of proteins.  Proteins are difficult to analyse - they are too large to measure directly by techniques such as LC-MS, without  prior breaking down, and their folded structure is also an important diagnostic parameter.  This structure is disrupted by many of the sampling and extraction procedures used in analytical method. Analysis of mixed gelatins is particularly difficult.

This method (open access) used a new approach based on the interaction of ethanol with amino acids inside a protein. Ethanol can denature globular proteins by disrupting intraprotein hydrogen bonds due to hydrophobic interactions. However, when added to solutions having proteins with considerable number of α-helices, ethanol can stabilize the protein structure and prevent aggregation. The specific effects of ethanol on protein structure and function can vary depending on the protein's composition and environment.

Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectroscopy was used to leverage ethanol's differential effects on gelatin's amide bands for quantifying pork gelatin contamination in bovine gelatin.

The authors report that the method showed a strong linear correlation between contamination levels and amide band transmission, with detection and quantification limits of 0.85 and 2.85 mg/100 mg (pork in bovine), respectively. It effectively identified pork gelatin in halal candy, with recovery rates from 50.05 % to 103.69 %.

The Food Safety Authority of Ireland (FSAI) 2023 Annual report, published last month, includes a summary of food fraud investigations and outcomes (see p61 onwards).

The FSAI Audits, Incidents and Investigations team conducted 57 investigations and 21 online investigations.  These ranged from warranted searches of premises to the monitoring of social media pages in cases where the online operation of unauthorised food businesses was suspected.  Outcomes included three Closure Orders, two Prohibition Orders and four Compliance Notices. Food safety concerns identified during these investigations necessitated the removal and disposal of more than 141,806 kg of products of animal origin.  The FSAI engaged with online platforms (such as Facebook and Instagram) where illegal food businesses were selling products online. This engagement resulted in two unregistered food businesses’ pages being taken down by the social media sites.

In overview, the report highlights a rise in “complex” food incidents.

Testing for honey authenticity often requires a panel of different analytical approaches, none of which is conclusive but each giving an increasing degree of suspicion.  Some of these approaches involve high cost specialist equipment and bespoke reference databases.

In this paper (purchase required) the authors propose a panel of three tests using relatively cheap and accessible equipment.  They developed a new high-performance liquid chromatography diode array detection (HPLC-DAD) method for the precise quantification of HMF, and coupled this with analysis of glucose, fructose, saccharose, and maltose using a HPLC with refractive index detection (HPLC-RI) plus diastase activity (DA) using the established Schade method.

They applied their approach to 65 commercial Spanish honey samples, reporting significant compliance with EU regulatory standards, yet also uncovering some suspicions of adulteration.

Photo by Roberta Sorge on Unsplash

The Indian Council of Agricultural Research Central Institute of Fisheries Technology (ICAR-CIFT) in Kochi has just hosted a national workshop on Food Authenticity and Traceability using Omics Techniques.

ICAR-CIFT has also signed a Memorandum of Understanding with Waters (a large laboratory instrument supplier) to act as a showcase laboratory and application development centre for authenticity testing.   The announcement is expected to boost research and builds on the regional hub in and around Kochi of laboratories with expertise in fish analysis.

The ICAR-CIFT announcement is here.

The UK government has issued guidance on the new Failure to Prevent Fraud corporate offence, which is due to come into force 1 September 2025.  This offence has the same “due diligence” defence principle as UK food safety law: if a company cannot show that they have a reasonable fraud defence/mitigation process in place then they become liable if an associate (which could be an employee or a contractor) commits a fraud offence to the company’s benefit.  Their mitigation procedure must be based on the principles typically espoused in food fraud mitigation best practice: they must show evidence of top level commitment, risk assessment, proportionate preventative measures, communication, training, monitoring and review.

The guidance clarifies a number of points, including the territorial scope (for example, a non-UK company can be prosecuted if a UK employee commits the fraud), and that the company can still be liable even if the associate is not prosecuted for the offence (provided that the offence can be proven to the standard required by a court of law).