This PhD thesis (request a copy here) describes the application of a previously-published LC-MS analytical method for triglycerides in fats to build an authenticity classification model for oils and fats based upon their triglyceride profile. The author reports good discrimination between different pure oils and also good discrimination when oil or sesame oil were adulterated with lower value oils. The model was also used to discriminate aged and degraded oils, and those which had been heat-processed. The author concludes that this fast, simple, robust and reliable method offers significant benefits in authenticating edible oils, evaluating oil degradation, and differentiating meat products from their fats. The method has excellent potential for universal use.
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Part II - Food Fraud Prevention and Types of Fraud
Welcome! In support of the Food Authenticity Network, 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 and scope of food fraud.
Food fraud was first clearly defined in 1820 by Frederick Accum in ‘A Treatise on Adulteration of Food and Culinary Poisons.’ Over the next two hundred years, the subject continued to be reviewed as a food science or food safety problem, as by Wiley and other pillars of scholarship. Along the way, ‘someone else’ was relied upon to actually prevent the problem. The ‘someone else’ was never assigned.
Interdisciplinary areas of study converged over time, to enable the shift to focus on prevention. In the 1970s, criminology theory expanded from focusing on the criminal and punishment to prevention. In the 1980s, quality management became a separate area of business theory with a shift to understanding and reducing the root causes of problems. In the 2000s, risk management became more formalized, such as in ISO 31000 Risk Management, which focused on likelihood and consequence as well as risk and vulnerability. In the 2010s, Enterprise Risk Management expanded the resource allocation decision-making to evaluate not only how to mitigate but also to prevent problems.
This holistic view of vulnerability applied criminology concepts to all criminal acts and all possible targets. For food products, that led to the need to define the ‘types of food fraud’ and the ‘types of products.’ If we are going to prevent food fraud, we need to consider all types of actions and products. This led to the holistic and all-encompassing definitions:
Type of Food Fraud & Definition (From various sources including GFSI and SSAFE):
- Adulterant-Substances (Adulterant/ Adulteration):
- Dilution: The process of mixing a liquid ingredient with a high value with a liquid of a lower value.
- Substitution: The process of replacing an ingredient or part of the product of high value with another ingredient or part of the product of lower value.
- Concealment: The process of hiding the low quality of a food ingredient or product.
- Unapproved enhancements: The process of adding unknown and undeclared materials to food products in order to enhance their quality attributes.
- Mislabeling or Misbranding: The process of placing false claims on packaging for economic gain.
- Grey market production/ diversion:
- Gray Market: A market employing irregular but not illegal methods.
- Theft: Something stolen and then covertly re-entered into commerce.
- Diversion/ Parallel Trade: The act or an instance of shifting a product from one intended market to another, which is unauthorized but either legal or illegal.
- Counterfeiting (IPR): The process of copying the brand name, packaging concept, recipe, processing method, etc., of food products for economic gain.
The types of food fraud are intentionally broad – holistic and all-encompassing - to frustrate the criminal against action of any kind.
Watch out for the next blog in March, which will review fraud susceptibility of different types of products (e.g., raw materials or ingredients to finished goods in the marketplace).
If you have any questions on this blog, we’d love to hear from you in the comments box below.
References:
- https://publicdomainreview.org/collection/a-treatise-on-adulteration-of-food-and-culinary-poisons-1820
- Spink, J, and Moyer, DC, (2011) Defining the Public Health Threat of Food Fraud, Journal of Food Science, Volume 75 (Number 9), p. 57-63. (ISI 1.791; SJR 0.378), URL: https://ift.onlinelibrary.wiley.com/doi/full/10.1111/j.1750-3841.2011.02417.x
- Spink, John, Bedard, Brian, Bruner, Leon, Keogh, John, Scimeca, Joseph, Goodridge, Lawrence, Moyer, Douglas C, & Vasan, Akila (2019). International Survey of Food Fraud and Related Terminology: Preliminary Results and Discussion, Journal of Food Science, 84(10), 2705-271800, URL: https://ift.onlinelibrary.wiley.com/doi/full/10.1111/1750-3841.14705
The EC Knowledge Centre for Food Fraud and Quality (the Joint Research Centre, “JRC”) have published their monthly collation of global food fraud media reports for January 2024. Thanks, as always, for FAN member Bruno Sechet for formatting these into this infographic. If you would like to join the JRCs mailing list to sign up for these monthly summaries then the link is here. You can follow Bruno's LinkedIn feed here.
The authors of this study (open access) developed a chemometric classification model to distinguish true cinnamon from its potential adulterants, Cassia or Saigon cinnamons. The model is based on simple and low-cost LC-UV analysis of four marker chemicals: eugenol, cinnamaldehyde, coumarin and cinnamic acid. Sample pre-treatment was vortexing/sonicating with methanol followed by centrifugation. Reference samples for the model were purchased from retail outlets rather than fully traceable sources; 25 samples of each type of cinnamon, including both sticks and powder. The model was first constructed to differentiate pure powders. Then the authors used an experimental design on a training set of in-house prepared mixtures (down to 1%/99% mixes) and a Partial Least Squares algorithm to model the classification of mixtures. They found the model was linear and – in the case of true cinnamon mixed with either of the two adulterants – could discriminate adulteration down to 1%. The model could not discriminate Cassia from Saigon cinnamons but the authors consider this a less important question.
Image from the published study.
A Toolkit to Support Weight of Evidence Approaches for Food Authenticity Investigations has been published by Defra.
Applying a weight of evidence approach for food authenticity investigation is relevant in situations where screening tests which do not give a definitive answer are used, for example with non-targeted fingerprinting approaches for food authenticity testing which rely on probability-based interpretation of the data. In these situations, gathering and assessing the weight of evidence can help in drawing a conclusion on the authenticity of a sample/product.
This document provides a structured outline on how to approach a weight of evidence assessment to verify the authenticity of food and drink samples where there is no single confirmatory test result available.
It has been developed by a sub-group of Defra’s Authenticity Methods Working Group (AMWG), drawing on analytical testing, enforcement, and food industry expertise.
Access the Weight of Evidence Toolkit. This report has also been added to the 'Guides' tab of the 'Tools_Guides_reports' part of our Food Fraud Prevention section.
A recent criminal conviction in the UK highlights the fraud risk from rogue employees. Two Despatch Managers at 2Sisters Food Group, the country’s largest poultry supplier, were supplying another company, Townsend Poultry, with chicken. Townsend Poultry was not a customer of 2 Sisters Food Group and there were no records of any deliveries. The fraud was uncovered during an audit when Townsend Poultry appeared incongruous on the customer records. Enquiries made with local hauliers used by the 2 Sisters Food Group confirmed there had been 84 deliveries from the 2 Sisters Food Group to Townsend Poultry, worth hundreds of thousands of pounds. The Despatch Managers had destroyed the records of those deliveries.
2 Sisters suffered the theft of £300K of stock over an extended period between 2019 and 2021. This stock was then fed into the UK market with falsified or non-existent traceability records; a food safety risk.
Read the FSA statement here
Read the story here.
This paper (purchase required, free to IFST members) reports a quick, non-destructive technique to add to the panel of analytical tools needed to detect olive oil adulteration or mis-labelling. This test is to detect addition of sunflower, rapeseed or corn oils. It is based on electrochemical examination of the peak of alpha-tocopherol oxidation on a pencil graphite electrode (PGE). There is no sample pre-treatment needed. The authors prepared in-house oil mixes and were able to confidently discriminate “adulterated” samples at around 10% added non-olive oil. The method's relative standard deviation (RSD) was 20%, and the α-tocopherol in cold pressed olive oil cut-off value was 30.98 ± 12.57 nA. The authors believe this is the first publication on utilisation of voltammetric techniques for the detection of olive oil adulteration using a PGE.
The European Parliament and Council agreed to review and strengthen the existing marketing standards applicable to honey, fruit juices, jams and milk. The so-called Breakfast Directives lay down common rules on the composition, sales names, labelling and presentation of these products to ensure their free movement within the internal market and help consumers make informed choices.
The revised Directives agreed upon by the co-legislators will introduce the following changes:
- Mandatory origin labelling for honey: the countries of origin in honey blends will have to appear on the label in descending order with the percentage share of each origin. Member States will have the flexibility to require percentages for the four largest shares only when they account for more than 50% of the blend. The Commission is empowered by the co-legislators to introduce harmonised methods of analysis to detect honey adulteration with sugar, a uniform methodology to trace the origin of honey and criteria to ascertain that honey is not overheated when sold to the final consumer. A Platform will be set up to advise the Commission on those matters. This will limit fraudulent practices and increase the transparency of the food chain.
- Innovation and market opportunities for fruit juices in line with new consumers demands: Three new categories will become available: ‘reduced-sugar fruit juice‘, ‘reduced-sugar fruit juice from concentrate‘ and ‘concentrated reduced-sugar fruit juice‘. This way consumers can choose a juice with at least 30% less sugars. It will be possible for fruit juices to indicate on their labels that “fruit juices contain only naturally occurring sugars” to clarify that, contrary to fruit nectars, fruit juices cannot by definition contain added sugars – a feature that most of the consumers are not aware of.
- Higher mandatory fruit content in jams: an increase of the minimum fruit content in jams (from 350 to 450 grams per kilo) and in extra-jams (from 450 to 500 grams per kilo) will improve the minimum quality and reduce the sugar content of these products for EU consumers. Member States will be allowed to authorise the term ‘marmalade' as a synonym of ‘jam', to take into account of the name commonly used locally for these products. The term “marmalade” was authorised until now only for citrus jams.
- Simplified labelling for milk: the distinction between ‘evaporated' and ‘condensed' milk will be removed, in line with the Codex Alimentarius standard. Lactose-free dehydrated milk will also be authorised.
The political agreement reached by the European Parliament, Council and Commission is now subject to formal approval by the co-legislators. From entry into force 20 days after publication of the final text, Member States will have 18 months to transpose the new provisions into national law and 6 more months before it applies throughout the European Union.
Read full press release.
A survey is being undertaken as part of a project which is jointly funded by FSA and Defra to better-understand the capabilities and challenges related to the verification of geographical origin of food and feed to inform on future direction (Project Reference FS900435). The project is being undertaken by Fera Science Limited in York, UK.
The insight of all stakeholders with an interest in the geographical origin of food and feed is welcomed and will be invaluable to the project outcomes. Your participation in this project is invited by means of completing the questionnaire at the link below:
Legal firm Hogan Lovells have published their predictions for US Food Law changes in 2024. Whilst there is nothing specific to authenticity or claims, they do foresee a step-change in the extent of State level regulatory divergence and a step-change increase in class actions. The headlines are
- FDA Setting Nutritional Guardrails for Foods on Multiple Fronts
- State Laws Run Amok
- Post-market Food Chemicals Surveillance: Can FDA Reassert Leadership and Stem the Rising Tide of State Action?
- Significant New Rulemakings Could Mean Operational Changes for Meat & and Poultry Processors
- Heavy Focus on Heavy Metals to Continue Unabated
- FSMA Implementation Will Continue, But at a Slower Pace
- Some Inspections, With a Dash of Enforcement
- Guidance and Enforcement by the Federal Trade Commission (FTC)
- The Supreme Court Could Rewrite Administrative Law
- Class Action Litigation and Proposition 65
The European Commission's Joint Research Centre (JRC) has published guidance on the selection and use of DNA extraction methods.
Extracting DNA of suitable quality and quantity from a test sample is a fundamental upstream step that underpins the confidence in a number of downstream analytical molecular biology based methods (e.g., qPCR. dPCR, NGS, etc.,).
This official guidance document provides advice on the selection and use of fit for purpose DNA extraction methods. Whilst this guidance uses the example of DNA extraction in the context of official controls for the analysis of genetically modified organisms (GMOs), the principles it describes are universally applicable to all DNA based methods including those for food authenticity.
Advice is provided on the selection of different protocols and decision support systems, and guidance provided on validation approaches and the assessment of DNA quality parameters, further illustrated with practical examples/solutions based on extensive collective experiences.
Access guidance: DOI: 10.2760/76162 (online)
This guidance has also been added to the Quality section of this website.
In this conference proceeding (free Computer Society membership needed plus USD19 article download fee) the authors use “big data” commodity price analysis as an indicator of possible food fraud incidence. They calculate the expected price vs the actual price of each commodity and plot trends over time. Where there is a sustained differential (e.g. “price is too good to be true”, or “price is over-inflated”) then the authors assume fraud. They report surprisingly clear trends, and differences in different European countries. For example, for oils and fats, there was evidence of price disparity in Belgium, Germany and Poland from 2021 until November 2022 when it was sharply corrected. There was no such disparity in Italy and Spain. They report correlations between different industry sectors within specific countries, most markedly illustrated by price disparities within Portugal.
Photo by Blogging Guide on Unsplash
Global reports of food fraud have been collated for over 40 years on the USP database under various ownership iterations (Decernis, FoodChainID). The owners have always taken the approach that media reports, official reports or literature surveys are assessed by a team of analysts before logging, to ensure that fraud is genuinely the cause. Thus the database holds relatively few entries but with relatively high confidence in the categorisation of each entry.
A summary of all entries has now been published in the open access literature. Top of the list of “most adulterated foods” is dairy products. This chimes with the recent annual summaries of “most adulterated foods” published on FAN’s website. Patterns of food fraud do not appear to have changed over the past four decades.
This review article is primarily a literature search and list of relevant publications from the past 5 years rather than a critical or comparative review. The authors cite publications that use a relatively rapid test method (either lab-based or point-of-use) coupled with chemometrics for categorising food. They explain the principle of each analytical technique including spectroscopic techniques, ambient ionisation mass spectrometry, electronic sensors and isothermal amplification DNA techniques. They then subdivide each into applications to categorise species/variety, quality attributes, or geographical origin of food. They devote less time to listing different chemometric methods but do include a basic explanation of different methods such as PCA, HCA, PLS-DA, OPLS-DA, SVM, KNN, and PLSR.
Welcome! This new blog series[1] reviews key topics related to food fraud prevention. The first blog explores the definition of food fraud terms and concepts.
When considering any new subject, the most important starting point is to define the terms and the scope.
- 2011: Food fraud was first defined in a scholarly journal article in 2011 (Spink and Moyer, 2011).
- 2014: The Global Food Safety Initiative (GFSI), foundation for most of the world’s food safety management system standards, provided a similar key definition and scope.
- 2018: The International Standards Organization (ISO) published a definition of:
- product fraud: “wrongful or criminal deception that utilizes material goods for financial or personal gain.” (ISO 22300:2018 updated from ISO 12931:2012)
- 2018: ISO 22000 Food Safety Management added a note that food fraud was to be considered as a root cause of food hazards.
- 2019: Spink et al conducted an International Survey of Food Fraud and Related Terminology
- 2023: The Food Authenticity Network published a review of global definitions of food fraud
- Active: CEN and Codex Alimentarius have working groups that are actively developing their definitions of food fraud and related terms.
The simple definition is:
Food fraud is “intentional deception for economic gain using food”.
The scope of product fraud and food fraud is intentionally broad in order to cover all types of fraud.
Watch out for the next blog, which will review types of food fraud…...
If you have any questions on this blog, we’d love to hear from you in the comments box below.
About the author
John W Spink, Ph.D., is the Director and Lead Instructor for the Food Fraud Prevention Academy. Also, he is an Assistant Professor in the Department of Supply Chain Management (SCM) in the College of Business at Michigan State University (MSU). His food fraud prevention research focuses on policy and strategy to understand and prevent these supply chain disruptions and implement procurement best practices. He is widely published in leading academic journals and has helped lead national and global regulatory and standards activity. More recently, his teaching and research have expanded to supply chain disruption management and procurement best practices. He is also on the Advisory Board of the Food Authenticity Network. For more information please visit: www.FoodFraudPrevention.com
[1] Collaboration between Dr John Spink of Michigan State University and the Food Authenticity Network (FAN)
A scientific paper entitled ”Authenticity Assessment of Ground Black Pepper by Combining Headspace Gas-Chromatography Ion Mobility Spectrometry and Machine Learning” has now been published in Food Research International (Elsevier journal)
The study assessed a broad variety of authentic samples originating from eight countries and three continents. The method uses head-space gas-chromtaography ion mobility spectrometry (HS-HC-IMS), combined with machine learning. It requires no sample preparation and is rapid. In this proof-of-concept study, the methos successfully classified samples with an accuracy of >90% with a 95% level of confidence.
Access the paper for free until the end of March 2024.
Photo by Anas Alhajj on Unsplash
The UK National Food Crime Unit have a useful page "Food crime - guidance for businesses" which we have now added as a permanent link in FAN's "Guides" list, here. The NFCU guidance is particularly aimed at small businesses. It includes how to spot the signs of food fraud, what you can do to protect your own business, staff and customers, and how to report incidents. There are links from the page to other useful resources.
The European Parliament Research Service has published briefing document on geographical indications for wine, spirit drinks and agricultural products.
The note states that the Parliament and Council reached a provisional agreement on the Commission's proposal for a regulation on geographical indications for wine, spirit drinks and agricultural products. The text still has to be formally adopted by the Parliament and Council.
The agreed text would bring together in a single legal document the provisions setting out the procedures for registering geographical indications (GIs) for wine, spirit drinks and agricultural products that are currently spread over three regulations. It would increase the powers and responsibilities of producer groups, lay down rules on sustainability practices, clarify rules on the use of GI products as ingredients, and improve the protection of GI products online.
Access the briefing note.
The Food Integrity Unit of the European Commission’s Joint Research Centre (JRC), is looking for laboratories with expertise in beeswax analyses, interested in participating in a method validation study by inter-laboratory comparison according to ISO 5725-2.
The goal is to evaluate repeatability and reproducibility of the gas chromatography based analytical method for quantifying paraffin n-alkanes respectively stearin/stearic acid in beeswax with the aim to identify potential adulteration of beeswax.
The participants will receive a set of beeswax test samples, the detailed analytical protocol of the method, and the necessary consumables, free of charge.
If you interested in being part of this important project that will lead to the future standardisation of the method by an international standardisation organization, please contact: Christina.CHRISTIA@ec.europa.eu
FAN are planning a series of short explainer videos to help you better navigate our website. The first, on finding organisations that curate specific authenticity testing databases, was launched on social media today. You can access or download the video here (hosted on a my own website because of file size limitation on FAN site).
