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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
- (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
- (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).
This publication, by the Food Safety Authority of Ireland (FSAI), identifies a range of analytical techniques that, when performed by expert laboratories incorporating suitable controls, could identify anomalies within a food which may help to determine the authenticity of that food.
This report has been prepared in response to a request for advice from the FSAI to its Scientific Committee. The report indicates specific or general analytical controls and criteria that are required to ensure that the results obtained are reliable and reproducible.
The report also emphasises that to be fit for purpose, laboratory techniques and their application must incorporate various critical controls at the sampling, processing, and analysis stages.
The report addresses two important questions:
- What are the essential criteria (e.g. specificity, linearity, range, accuracy, reproducibility, precision, etc.) for unaccredited analytical techniques to be acceptable and reliable tools in examining the food chain, particularly in assessing food authenticity?
- For the different categories of analytical tests (e.g. spectroscopic, molecular, omics etc.), what are the analytical controls feasible or necessary to ensure that methods are fit for purpose and results are accurate, reliable, and reproducible?
This report has also been added to the Quality section of this website.
Paper-based analytical devices (PADs) have the potential for low-cost, rapid point-of-use testing with easier and cheaper fabrication than (for example) 3D laser-printed microfluidics.
This review states that it covers cutting edge applications for food authenticity analysis and includes a section on how close some of the applications are to commercialisation. There is no detail in the publicly-available abstract as to what topics or applications the review covers. Purchase of the article would be needed to ascertain its use or relevancy. It is published in a reputable peer-reviewed journal.
DNA analysis will not help if a processed meat product has been adulterated with offal from the same species. The traditional test approach is microscopy but this is challenging for highly processed products and requires expert interpretation. Analysis of protein profiles can also be used, but proteins may not be stable to food processing.
In this study (purchase required) the authors propose using a molecular diagnostics method, testing for the messenger RNA (mRNA) that drives the protein production, rather than for the proteins themselves. They scanned through a bovine gene expression database for mRNAs expressed at elevated levels in 10 unwanted offal tissues but not in muscle or adipose tissue. Out of 27,095 candidate transcripts, 3 were eventually selected as markers. Primers and probe sets for RT-PCR analysis of each transcript were designed. Two of the transcripts were shown to be detected by the developed RT-PCR method. The method was validated by specificity, sensitivity, repeatability, and reproducibility parameters
Photo by Laura Ohlman on Unsplash
Food Fraud Prevention - ISO 31000 and Likelihood
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 ISO 31000 Risk Management to dive into the risk assessment concept of “likelihood.” The next blog post will review the second half of a risk assessment, which is “consequence.” Likelihood alone is only half of the risk assessment.
For example, the concern about an event with a 5 percent chance of occurring is based on the consequence. A 5-percent chance of stubbing your toe at night may not require you to take any precautions, even as simple as turning on the light (“risk acceptance”). A 5-percent chance of drowning while swimming would lead you to at least wear a life jacket (“risk treatment”) or find another way to cross a river (“risk avoidance”).
To recap, a vulnerability is a type of risk. A risk is determined by the combination of “likelihood” and “consequence.” Remember:
- Risk (ISO 31000): “effect of uncertainty on objectives;
- 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.
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)."
The likelihood is covered in this blog post, and a future blog post will cover the consequences in detail. It is interesting to examine the level of detail and insight that went into the ISO definitions. The use of “likelihood” even considers the information interpretation of the terms. Specifically, the term “probability” often insinuates a statistical or mathematical determination.
- Likelihood (ISO 31000): “chance of something happening” (Note: yes, that is the exact text) [Reference 1]
- NOTE 1: In risk management terminology, the word “likelihood” is used to refer to the chance of something happening, whether defined, measured, or determined objectively or subjectively, qualitatively or quantitatively and described using general terms or mathematically (such as a probability or a frequency over a given time period).
- NOTE 2: The English term “likelihood” does not have a direct equivalent in some languages; instead, the equivalent of the term “probability” is often used. However, in English, “probability” is often narrowly interpreted as a mathematical term. Therefore, in risk management terminology, “likelihood” is used with the intent that it should have the same broad interpretation as the term “probability” has in many languages other than English.”
Why the Likelihood concept was preferred to Probability
When food fraud prevention was first being considered as a specific concept, some experts estimated it would take five years to complete a formal assessment. This was unacceptable, especially since the GFSI requirements were due in 12 months. It was efficient and supported by ISO 31000 concepts to focus on a “vulnerability assessment” rather than a “probabilistic risk assessment.” A key fundamental concept was to start by focusing on the more informal and qualitative “likelihood” than “probability.”
“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 there may not be details provided (at least not yet).” (Reference 2)
It is very important and of great value that ISO 31000 Risk Management provides a common set of terms that have been created through an international and government-endorsed consensus-based process.
Watch out for the next blog, which will review the application of ISO 31000 Risk Management based on the term “consequence” and the basis for not using “severity.”
If you have any questions on this blog, we’d love to hear from you in the comments box below.
References:
1 ISO 31000 – Vocabulary, definition of ‘Likelihood, URL: https://www.iso.org/obp/ui/#iso:std:iso:31000:ed-1:v1:en
2 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
Canada operates a statutory list of permitted supplemental ingredients (e.g. vitamins, minerals, amino acids) in food. In addition, there is a temporary marketing approval (TMA) framework by exception, to use a specific supplement in a specific food. The ongoing approval status of some of these TMA substances had been unclear.
This has now been clarified by a Health Canada notice. It addresses this gap by issuing a table which provides information relevant to the use of these ingredients as conventional food ingredients and in supplemented foods, along with any data gaps that must be filled to establish safety as proposed supplemental ingredients.
In some cases, an ingredient has a history of safe use in food and is permitted as an ingredient (including in supplemented foods) on that basis. These ingredients may be used in all foods, including supplemented foods, according to the relevant provisions of the Food and Drug Regulations. Examples include certain food additives and flavourings. If use is proposed at levels higher than those with a history of safe use or if an ingredient has no such history, the ingredient would be considered a supplemental ingredient and require a pre-market assessment by Health Canada.
This review (purchase required) and its associated recommendations is primarily aimed at regulators and competent authorities, but also has implications for food businesses.
The aim of was to consider food-related fraud prevention initiatives, understand what has worked well, and develop a series of recommendations on preventing food fraud, both policy related and for future research.
The authors found that reactive (including intelligence based) food fraud detection dominates over prevention strategies, especially where financial, knowledge, and time resources are scarce. First-generation tools have been developed for food fraud vulnerability assessment, risk analysis, and development of food fraud prevention strategies. However, examples of integrated food control management systems at food business operator, supply chain, and regulatory levels for prevention are limited.
They conclude that the lack of hybrid (public/private) integration of food fraud prevention strategies, as well as an effective verification ecosystem, weakens existing food fraud prevention plans. While there are several emergent practice models for food fraud prevention, they need to be strengthened to focus more specifically on capable guardians and target hardening.
This review (open access) covers technological and digital solutions to mitigate food fraud risk, concentrating on recent developments. It categorises solutions as either systematic interventions (e.g. risk prioritisation databases, digital fraud prediction tools), fraud detection techniques (analytical test methods) or package-level technologies (e.g. traceability systems, anti-counterfeiting markers, RFID tags).
It concludes that a notable gap exists in converting laboratory based sophisticated technologies to tools in high-paced, live industrial applications. New frontiers such as handheld laser-induced breakdown spectroscopy (liBS) and smart-phone spectroscopy have emerged for rapid food authentication. Multifunctional devices with hyphenating sensing mechanisms that are combined with deep learning strategies to compare food fingerprints can be a great leap forward in the industry. Combination of different technologies such as spectroscopy and separation techniques will also be superior where quantification of adulterants are preferred. with the advancement of automation these technologies will be able to be deployed as in-line scanning devices in industrial settings to detect food fraud across multiple points in food supply chains.
The UK Food Standards Agency (FSA) have published a survey of 1025 samples purchased at retail in the 2nd half of 2023. Samples were targeted on a risk-basis, and the survey included authenticity testing of some samples.
The survey found:
- There was a considerable increase in compliance for olive oil year on year 75% in 2022/23 to 87% (26 out of 30) 2023/24
- Food authenticity rates for samples tested were 97% compliant for the areas of authenticity tested
- There are no overall geographical hotspots for non-compliance
From the small number of samples tested, two potentially widespread authenticity issues were flagged which will be used to inform future enforcement priorities.
- 40% (16 out of 40) of frozen raw chicken was non-compliant due to undeclared, or excess, added water and labelling issues
- 42% (10 out of 24) of frozen beef burgers were non-compliant, with eight samples having less meat content than declared, and 4 samples containing higher fat levels than stated.
DNA analysis is rarely used for the verification of edible oil species, because of the low amount of intact DNA in the refined oil and the genetic similarities between different oil varieties. In this study (open access pre-print, not yet peer-reviewed) the authors compared different DNA extraction kits and PCR protocols and new genetic markers to try and resolve the issue. They reported that DNA extraction kits such as NucleoSpin Food, DNeasy mericon Food, and Olive Oil DNA Isolation as well as modified CTAB method were found to be able to isolate amplifiable genomic DNA from highly processed oils. Novel uniplex, double, and nested PCR systems targeting the sunflower-specific helianthinin gene were developed for efficient identification of sunflower. New sunflower DNA markers were revealed by uniplex PCRs.
They concluded that a combination of modified CTAB and nested PCR gave the best performance, and was demonstrated as a reliable, rapid, and cost-effective technology for detecting traces of sunflower in highly processed oil, including refined and used cooking oil.
The UK Food Standards Agency (FSA) and Food Standards Scotland (FSS) have been awarded a £1.6M grant as part of round one of the Engineering Biology Sandbox Fund, which aims to test innovative regulatory approaches for products like cultivated meat. Cell-cultivated products are foods created through the isolation of cells from meat, seafood, fat, offal or eggs which are grown in a controlled environment. It could result in food production which is more environmentally friendly and sustainable, using just 1% of the land used for animal equivalents, while increasing food security. Programmes like this will help bring innovative food products to shop shelves safely but without unnecessary delay and at lower costs, giving consumers more choice. There are a number of challenges to address in the regulatory approval, and subsequent enforcement, of cell cultivated products, not least of which is authenticity verification (how to ensure that the product on sale has been produced only using the regulatory-approved process, scaffolds and starting materials)
Synthetic technologies allow companies to ‘print’ DNA and RNA. Applications are cross-sector, and include nucleic acids that are used as the basis of selective analytical test methods. This voluntary best-practice guidance emphasises the UK government’s intent for a pro-innovation culture in the engineering biology ecosystem through providing well-defined guardrails for customers and producers of synthetic nucleic acid.
This link has been added to FAN’s Quality page, which contains links to a range of other best-practice guidance for both laboratories and for customers looking to choose a laboratory
