food fraud (188)

Fighting food frauds on the frontline

12322855490?profile=RESIZE_180x180Our Secretary, John Points, has written an article for a special edition of the Institute of Food Science and Technology's Journal of Food Science and Technology focussed on 'food safety and authenticity', in which he emphasises the pervasive impact of food fraud, spanning from brand risks to safety risks, advocating rigorous risk assessment, vigilance, and the use of tools like analytical testing to effectively detect and mitigate fraudulent activities in the food industry.

The article is open access.

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12164813283?profile=RESIZE_710xA new vacancy for a Senior Intelligence Analyst has arisen at the Food Standards Agency's National Food Crime Unit (NFCU).

The role will be focussing on the delivery and assurance of NFCU's tactical and strategic intelligence analysis to better understand and communicate the food crime threat, as well as the support and development of NFCU's analyst and researcher cadre.

You'll be playing your part in keeping food safe and what it says it is, and protecting UK consumers from deceptive practices in the food sector. 

Home or hybrid working is available for this post.

The deadline is 6th August 2023.

For further information / to apply: Senior Intelligence Analyst - Civil Service Jobs - GOV.UK


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This 52 minutes documentary "The Criminals Running Our Food Chain - Food Fraud: An Organised Crime? ", published in 2021, is now publicly available - see below.

The documentary covers some well known food fraud issues encountered in recent years and includes an account of some of the food fraud prevention activities that have been deployed to combat food fraud.

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Is our food safe? An article by Which?

12125140090?profile=RESIZE_710xThis article by Which? states that recent food fraud revelations show we can't take food safety for granted, and that careful oversight is essential for food safety and security.

The article focuses on the following areas:

  • Why food safety laws need saving.
  • Lack of border checks and staff cuts make life easy for fraudsters.
  • Which foods are most at risk of food fraud?
  • The human cost of food fraud.

Using examples, Which? show, why we can't take food safety for granted, and it's vital we take the opportunity to review and strengthen food safety laws, via a transparent process that allows both consumers and legitimate businesses to have confidence in the system.

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11824541898?profile=RESIZE_710xNew publication using outputs of MedISys-FF finds that:

  • Meat and meat products were the most reported fraudulent food products.
  • Adulterated food commodities are mainly associated with the expiry date and tampering.

The MedISys-FF tool developed by Bouzembrak and colleagues (Bouzembrak et al., 2018) uses the MedISys portal of the European Media Monitor (EMM), a system that uses text mining to collect media articles worldwide.

Read the full article.

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The NFCU (National Food Crime Unit) part of the Food Standards Agency is investigating allegations of mislabelling of the origin of pork and sometimes selling rotten meat to retailers at least up to the end of 2020. Meat produced by the supplier, as yet unnamed, is reported to have ended up in products such as ready meals, quiches, sandwiches and other produce sold to the UK major retailers. The alleged supply chain fraud was investigated by the journal the "Farmers Weekly".

Read the article here  

In addition, please looked at the LinkedIn entry about this fraud as it discusses the significance of it to food businesses and "What It Means For Me".

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Review of the Adulteration of Cow Milk


The common adulterants used in cow milk are water, starch, flour, urea, formalin, sodium hydroxide and cane sugar. Extension of milk with added water is the most common. These adulterants have effect on the nutritional quality of cow milk by decreasing the concentration of ingredients found and wholesomeness of the milk. This review examines the occurence of adulteration, as well as the methods to detect it.

Read the full review paper here

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Global demand for soyabeans has increase dramatically especially over the past 30 years, which has led to concerns about lower-than-expected product quality, adulteration, illegal trade, and deforestation. Therefore, development of effective analytical regimes to determine geographical origin and hence traceability, have become a priority. This is the first review that investigates current analytical techniques coupled with multivariate analysis for determining the geographical origin of soybeans. The 10 analytical techniques in 3 main groups outlined above are assessed, compared, and discussed in terms of their operating specifics, advantages, and shortcomings. The contribution of chemometrics in in analysing complex data is also covered. Each of these methods has advantages and disadvantages of its own. For example, the major drawback of geochemical techniques is their instrumental and operational costs, which can be mitigated by spectroscopic methods at the expense of sensitivity. Gaps in application of some analytical techniques are also identified. 

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10949009861?profile=RESIZE_400xAquacultured prawns were the second highest export of Bangladesh, but have now been renegated to seventh place. In the period from July to December 2022, 1,660kg of prawned were seized and destroyed by authorities because they were found to have been injected by a jelly-like substance to increase the water content. The injection was carried out after harvest, and by some traders in the supply chain. Exporters are worried that these incidents may reduce exports even more.

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This paper proposes an innovative method based on AI, to reinforce traceability systems in detecting possible counterfeiting by product substitution. It is an item-based mass balance method that analyses the agreement of the traceability data flows not by using explicit (even stochastic) rules, but by exploiting the learning capabilities of a neural network. The system can then detect suspect information in a traceability data flow. The AI-based method was applied to a pork slaughtering and meat cutting chain case study, and used the weights of different cuts of a pork carcase as the training phase of AI. Any analogous carcase information along the supply line might indicate substitution or modification of the pork carcase cuts. 

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Chris Elliott on BBC Radio 4 - Fighting Food Fraud

10930141894?profile=RESIZE_400x Chris Elliott was the the guest on BBC's Radio 4 programme - The Life Scientific talking about his life and his work on food fraud. The recording of the programme will be available for over a year from 10 January 2023. Chris was a founding director of the Institute for Global Food Security (IGFS) at Queens University Belfast. After the horsemeat fraud incident in 2013, he conducted an independent review of the UK food system. Following Recommendation 4 in the review report, LGC set up the Food Authenticity Network with funding from Defra. Chris also goes into details of the latest developments in fighting food fraud.

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Saffron is a high value spice and hence susceptible to adulteration and fraud. In this study, a machine vision system based on smartphone image analysis and deep learning was used to detect saffron authenticity and quality. A dataset of 1869 images was created of 6 types of saffron/adulterants including: dried saffron stigma using a dryer; dried saffron stigma using pressing method; pure stems of saffron; sunflower; saffron stems mixed with food colouring; and corn silk mixed with food colouring. The deep learning system developed for grading and authenticity determination of saffron in images captured by smartphones and applied to these images, was a Learning-to-Augment incorporated Inception-v4 Convolutional Neural Network (LAII-v4 CNN). After applying further data augmentation and comparison against regular CNN-based methods and traditional classifiers, the results showed that the proposed LAII-v4 CNN approach gave an accuracy of 99.5%.

 Read the paper preview here

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Food Fraud: a Joint Nordic Threat Assessment

10885049698?profile=RESIZE_400xThis publication examines the joint threats arising from criminal activity in the Nordic food production chain. The countries participating in the project are Norway (leader), Denmark, Iceland and Sweden. It summarises and draws from the discussions which took place at a methodology seminar for participants in December 2018, the purpose of which was to discuss what a threat assessment is, and what is known about fraud and deception in the Nordic market. International experts from the UK and the USA, as well as experts from the Nordic customs authorities and the police, also participated in this seminar. In 2019, Denmark, Norway and Sweden carried out national threat assessments as a contribution to this Nordic report. Finally, a seminar for Icelandic Food and Veterinary Authority inspectors and local inspectors was arranged in Iceland and was also attended by US participants.

Read the full report here

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10884938055?profile=RESIZE_400xThis review is a chapter in a book entitled "Blockchain in Finance, Marketing and Others". It explains the workings of blockchain, and its applicability in monitoring and verifying the data and information in the food chain from farm to fork. It covers how blockchain can address the challenges faced in ensuring food supplies deal with food safety, food fraud and food waste issues, as well as its benefits.

Read the full chapter here

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This review conducted by an expert group of ILSI (International Life Science Institute) Europe details the numerous activities by authorities undertaken within different regions (Europe, North America, Asia, Latin America, and Africa) to counter food fraud. It defines "food inauthenticity" in terms of misrepresentation of a food within a contractual agreement, and/or misrepresentation of a food within a legal obligation (i.e non-compliance of the law). It also describes the guidance available to the food industry to understand how to assess the vulnerability of their businesses, and implement the appropriate mitigation.

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Addition of cheese whey to raw milk is an extension fraud, and this paper develops a rapid method for its detection. FTIR (Fourier-transform infrared) spectroscopy of milk produces a large amount of data, which can treated by machine learning methods such as classification tree and multilayer perceptron neural networks (MPNN) the two methods used in this study. A total of 520 samples of milk adulterated with cheese whey in concenrations from 1-30% were prepared, and 65 samples were taken as the control. These were stored at different times and temperatures, and analysed by FTIR. A further 520 samples of authentic raw milk were used, and selected components (fat, protein, casein, lactose, total solids, and solids nonfat) and freezing point (°C) were predicted using FTIR, then used as input features for the machine learning algorithms. Performance metrics included accuracy as high as 96.2% for CART (classification and regression trees) and 97.8% for multilayer perceptron neural networks, with precision, sensitivity, and specificity above 95% for both methods. The authors make a caveat on these results that the samples were all prepared from bulk raw milk, not individual milk, whose composition is more variable.

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This study looked at verification of egg production method from organic, free range, barn and caged produced eggs, all of which are defined in EU legislation. A total of 84 eggs were bought from local supermarkets in northern Spain (18 each of organic and free range eggs, and 24 each of barn and caged eggs). The egg contents were homogenised and centrifuged to separate the plasma from the granules, and the UV-VIS-NIR spectra of the plasma measured in a spectrophotometer, and different chemometric models applied to the spectra variables . As two samples were detected as outliers and removed, the 82 samples were divided into two groups: 62 for model calibration and 20 for validation. Spectra analysis with QDA (quadratic discriminant analysis) gave a higher accurate categorisation of the four production systems, with a sensitivity of 100% in the calibration set. The validation set scored 87.5% sensitivity and 94.07% specificity using the visible spectra. 

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10837224682?profile=RESIZE_400xThis is Tenet's quarterly publication (Issue 5), which discusses the various methods of tackling food fraud, from food safety and quality legislation, and consumer protection legislation, to contract law and trade practices. It also examines the importance of auditing your suppliers and look deeper into non-party disclosure and ‘Norwich Pharmacal’ orders.

If you work in the food and drinks industry and take an interest in fraud and financial crime impact in the sector, please take a look at the Secret Ingredient -Issue 5.


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Wild-caught seafood is vulnerable to illegal, unreported, and unregulated fishing, which often leads to overfishing and destruction of marine environments. A recent study has developed a method to determine the geographical origin of seafood using oxygen isotope (δ18O) composition imprinted in the shells and bones of seafood (δ18Obiomin). This value is determined by ocean composition and temperature rather than the seafood's biology.  Global ocean isoscapes of predicted δ18Obiomin values specific to fish (otoliths), cephalopod (statoliths) and shellfish (shells), and a fourth combined “universal” isoscape, were evaluated in their ability to derive δ18Obiomin values among known-origin samples. After validation and testing of the method, it was  demonstrated that this global isoscape can be used to correctly identify the origins of a wide range of marine animals living in different latitudes. After removing tuna species from the analyses, a prediction rate of up to 90% in classifying fish, cephalopods, and shellfish between the tropical waters of Southeast Asia and the cooler waters of southern Australia was obtained. Further research is planned to incorporate other chemical markers into improving the prediction of geographical origin. 

Read the full open access paper and the corresponding article here

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