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Food Fraud Records: Summary of Data 1980-2022

12368302465?profile=RESIZE_400xGlobal 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.

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12367433864?profile=RESIZE_400xThis 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.

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Spink’s Snippet – Food (Fraud) for Thought

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.

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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)

 

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12366097699?profile=RESIZE_180x180A 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

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12365940678?profile=RESIZE_400xThe 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.   

Photo by on

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12365384453?profile=RESIZE_584xThe 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.

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12365337854?profile=RESIZE_584xThe 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 

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Explainer video - how to find an authenticity test

12365321666?profile=RESIZE_400xFAN 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).

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Edible insects: supply chain vulnerability map

12364307091?profile=RESIZE_400xThis study (open access) used literature reviews and stakeholder interviews to construct a generic supply chain map and identify fraud and food safety vulnerabilities for edible insects.  Safety concerns discussed include novel allergenicities and the effect of different processing methods on microbiological safety.  The main fraud risk discussed is the artificial enhancement of apparent protein content by adding an adulterant rich in nitrogen (as per the motivation for melamine adulteration of milk powder).

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12364306094?profile=RESIZE_400xConventional DNA authenticity analyses (RT-PCR) requires samples to be sent to a laboratory. Point-of-use tests, using isothermal amplification, are well characterised but are not in routine use (mainly due to cost and lower sensitivity).  This study (purchase required) compared four such amplification techniques for the identification of chicken DNA: loop-mediated isothermal amplification (LAMP), denaturation bubble-mediated strand exchange amplification (SEA), cross-priming amplification (CPA), and recombinase polymerase amplification (RPA).  The researchers focussed on the limit of detection, simplicity, amplification time and cost. The LAMP, CPA, and RPA primers all targeted the chicken mitochondrial cytochrome b gene. The SEA primers were provided by the SEA kit. The authors found that all methods showed good specificity to chicken.   0.1% chicken in mutton could be detected using LAMP and RPA methods. The authors considered that, although RPA costs 10 times more than LAMP, the system and primers of LAMP are far more complex. Therefore, they concluded that RPA is the most suitable method in multiplex detection, and LAMP is much better than the other three methods in single-plex detection.

Photo by Braňo on Unsplash

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12360746468?profile=RESIZE_180x180As the world's human population grows and climate change impacts food security, digital technologies are becoming increasingly critical for ensuring transparency, resilience, and fairness across the food system.

However, technology and digitalisation are often expensive and can be out of reach for small-scale farms and businesses. So, how can we ensure these technologies are available to all stakeholders, and the associated food is affordable for all consumers?

Here are four ways that technology can increase food system transparency, resilience and fairness (FAO report: Five ways science, technology and innovation are helping to transform the world's agrifood systems): 

  1. Track food supply chains and collect secure data
  2. Increase access to information and enable communication between stakeholders and with consumers
  3. Monitor and predict changes to reduce and prevent risk
  4. Connect small-scale producers and increase access to networks and services.

Read EIT-Food's blog on how can digital technologies increase food system transparency, resilience, and fairness?

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12360374060?profile=RESIZE_400xThe Agricultural and Food Chain Supply Act established a new regulator in the Republic of Ireland which came into force in December 2023.  The remit is to protect against unfair commercial terms in the Agri-food supply sector.  Some of the new industry obligations will make fraud mitigation mass-balance checks easier; for example the requirement for all buyers and suppliers within scope of the regulations to record sales volumes, costs and discounts and to supply them to the regulator on request.  The regulations apply when the buyer has large commercial muscle in comparison to the supplier (defined as a buyer turnover of < 2 million Euro when the supplier has a lower turnover).

Key prohibitions in the act include short notice cancellations (less than 30 days) for perishable products, acts of commercial retaliation against suppliers seeking to invoke their legal rights, buyers using suppliers’ trade secrets, late payment, refusal to confirm supply agreements in writing, and unilateral contract changes by the buyer.

Photo by PHÚC LONG on Unsplash

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12360158858?profile=RESIZE_710xFAO, in partnership with Wageningen Food Safety Research (WFSR), has developed this technical background document to raise awareness of predictive early warning tools that can identify imminent and emerging food safety issues, and contribute to the prevention of food safety emergencies, while supporting the development of capacities for their use. 

The report also includes tools (Annex 3) that could be helpful in the prevention of food fraud - we are delighted that our blogs of the JRC's Monthly Food Fraud Reports, presented as visuals (created by our Member Bruno Séchet) gets a mention!.

Access the FAO report here.

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12360126259?profile=RESIZE_400xIn this study (open access), headspace solid-phase microextraction for sample extraction followed by untargeted gas chromatography coupled to high-resolution mass spectrometry (HS-SPME-GC-HRMS) for volatile compounds was used to build a classification model to discriminate saffron, safflower, calendula, capsicum and turmeric. (the latter four being potential adulterants of saffron).  The model was based on reference analysis of 38 authentic saffron (Crocus sativus L.) samples from different origins (Iran, Spain, Greece and Italy) 6 samples of turmeric (Curcuma longa L), 9 of calendula (Calendula officinalis L), 6 of capsicum (Capsicum annum L) and 4 of safflower (Carthamus tinctorius L., n = 4).  The instrument software was used to normalise the signals from the less concentrated or less responsive volatile compounds.  Unsupervised PCA and supervised PLS-DA gave a chemometric model that could clearly differentiate pure samples of all 5 species.

The researchers then sought specific volatile markers for each species using the pattern search function of MetaboAnalyst software. This function uses a template matching method and the results are expressed as a ranked list of variables with the Spearman correlation coefficient and p-value. They short-listed any compound with a Spearman correlation coefficient ≥ 0.80.  Tentative Identification of short-listed ‘markers’ was performed using mass spectra NIST 17 library. Only compounds with match factor ≥ 750 and relevant Kovats retention indexes (RI) relative to n-alkanes (C7–C30) were considered. The compliance of exact mass of detected ions (mass error < 5 ppm) and isotopic pattern were used to confirm the identification.

Once markers were identified they were used to build specific classification models to differentiate pure saffron from saffron adulterated with each specific species.  Models were built using in-house prepared mixes at 20, 10, 4 and 2% adulteration in each case.  The authors could successfully detect 2% adulteration with each of the 4 species modelled.

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12358156464?profile=RESIZE_710xThe 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 December 2023.  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.

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12358146260?profile=RESIZE_584xIn March 2023, Dr Malcolm Burns, Head of the GMO Analytical Unit at the National Measurement Laboratory at LGC presented presented at the International Conference on GMO and New Genomic Techniques on 'Analytical strategies for detection of GMO's and NGT products- status and challenges'. The presentation explored some of the opportunities and challenges for the development of methods for the detection of NGT products.

You can now view Malcolm's presentation here.         
Note: all information given in the presentation was correct at the time of the presentation in March 2023.

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12357125469?profile=RESIZE_400xThis paper (purchase required) reports a proof-of-concept study to detect, with a point-of-use NIR scanner, the adulteration of ground almonds with apricot kernels .  The authors built a classification model by preparing their own ground almond from different almonds (120 samples) purchased at local markets and then preparing blends (up to 50%, in 2% intervals) with ground apricot kernel. They collected NIR spectra using a portable and benchtop spectrometer and analyzed the data by Soft Independent Modeling of Class Analogy (SIMCA) and Conditional Entropy (CE) with machine learning algorithms to generate a classification model. They used Partial Least Square Regression (PLSR) and CE with machine learning algorithms to predict the levels of apricot kernel in ground almonds. The authors reported that both SIMCA and CE algorithms combined with spectral data obtained from the spectrometers provided very distinct clusters for pure and adulterated samples (100% accuracy). Both units also performed well in predicting apricot kernels using PLSR with rval>0.96 with a standard error prediction (SEP) 3.98%. They conclude that, based on the SIMCA, PLSR, and CE-based models, NIR spectroscopy showed great potential for real-time surveillance to detect apricot kernel adulteration.

Photo by Marcia Cripps on Unsplash

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12356844870?profile=RESIZE_400xSpectrometric classification models are usually constructed by multivariate analysis of measurements from multiple samples from authenticated reference database.  In this study (open access) the authors used a simplified approach.  They tood a single measurement: the integrated IR spectrum between 3000-2800 cm2.  They used factorial mixture design, on an Excel spreadsheet, to construct a calibration curve based only upon 3 reference samples: 100% Arabica, 100% Rustica and a 50/50 mix.  They then validated the curve using a range of other mix proportions, and concluded that it was suitable for detecting Rustica adulteration in “pure Arabica” down to 2.5%.  The authors propose this as a useful and cheap strategy for building specific classification models for the routine checking of adulteration in individual coffees that purportedly come from a consistent and well-characterised source.

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12356486865?profile=RESIZE_400xIn this publication (open access) the authors reviewed the potential frauds that could be applied to cultured meat, which of them could be detected by existing “conventional” meat test methods and controls, and which would require new authentication standards or testing.  They highlighted some threats which would require a new risk-management approach such as

  • Use of conventional chicken meat in cultivated chicken nuggets
  • Use of mouse myoblasts for cell sheet-based porcine meat
  • 3D-printed steak produced by Company A using Wagyu-sourced muscle cell imitated by Company B with non-Wagyu-sourced muscle cells labelled as “Wagyu”
  • Imitation of a plant protein scaffold-based cultivated meat by mixing conventional meat mush with extruded plant protein

The authors propose a scheme for establishing cultured meat authentication standards (pictured)

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