Food Fraud Cases Research Articles

ADULTERATION IN FOOD INDUSTRY IN 2023 - OVERVIEW

This review focuses on food fraud and shows a picture of the most critical notifications reported by the Knowledge Centre for Food Fraud and Quality worldwide during the year 2023. Knowledge4Policy (K4P) is the EU Commission's platform for evidence-based policymaking. This study aims to provide an overview of the cases of food fraud focused on specific food groups - (fish and seafood, oils and fats, fruit and vegetables, honey and sugar, meat and meat products, wine, alcohol, milk and dairy products, spices and herbs, grain-based food – cereals - bakery products, eggs, snacks, coffee, tea, cocoa, non-alcoholic beverages, dietic foods supplements, fortified food). The data on food fraud was divided based on world continents (Asia, Africa, South America, North- Central America, Australia, and Europe). The next part of our overview shows the count of food fraud incidents separately each month for 2023. Overall, 419 cases were registered worldwide in 66 countries in 2023. Most cases were registered in Europe, South America, Africa, North-Central America, and Australia. Based on our findings, we can conclude that the highest number of cases were registered in Pakistan, followed by Italy, Brazil, Nigeria, the Dominican Republic, and Australia. The most abundant was alcohol-beverages adulteration (18.13 % of the total number of cases reported in 2023 worldwide), followed by meat and meat products (15.03 %), fish and seafood (13.60 %), and grain-based food, cereals, and bakery products (11.69 %). Analysis of notification data showed that the most used type of fraud was grey market trading, mislabeling, document forgery, dilution/mixing, substitution, and unapproved enhancement. Food fraud databases serve as valuable tools for the food industry and regulatory bodies, aiding in mitigating food fraud risks.

Incidents and Potential Adverse Health Effects of Serious Food Fraud Cases Originated in Asia.

Food fraud has long been regarded as a major issue within the food industry and is associated with serious economic and public health concerns. Economically motivated adulteration, the most common form of food fraud, has consequences for human health, ranging from mild to life-threatening conditions. Despite the potential harm and public health threats posed by food fraud, limited information on incidents causing illness has been reported. Enhancing the food control system on the Asian continent has become crucial for global health and trade considerations. Food fraud databases serve as valuable tools, assisting both the food industry and regulatory bodies in mitigating the vulnerabilities associated with fraudulent practices. However, the availability of accessible food fraud databases for Asian countries has been restricted. This review highlights detrimental food fraud cases originating in Asian countries, including sibutramine in dietary supplements, plasticizer contamination, gutter oil, and the adulteration of milk. This comprehensive analysis encompasses various facets, such as incident occurrences, adverse health effects, regulatory frameworks, and mitigation strategies.

The Status and Trends of Food Fraud in Tamale, Ghana

Despite its seriousness, food fraud has not received the necessary attention in Ghana’s discourse on food safety. Food fraud is generally considered as the intentional misrepresentation of the contents or identity of food for economic gain. The study was aimed at assessing the food fraud awareness level of participants as well as the foods most likely to be implicated in food fraud cases in Tamale, Ghana. Data was collected from 385 participants, including food business operators and consumers, via a simple random sampling technique using a structured questionnaire. Most participants (54%) were not aware of food fraud and its related activities before the study. Beverages and juices, fruits and vegetables, spices, oils, meat and fish, baked foods, honey, milk, and semi-processed local foods such as groundnut paste, "Dawadawa," “Kulikuli zim,” and “Agushi powder” were all revealed to be implicated in food fraud by respondents. Adulteration was the most common food fraud action, but tampering, substitution, and mislabeling were also identified as ongoing in the study area. “Moora” (Bixa orellana seeds) was revealed as the key adulterant used in most foods. Food fraud, which is a threat to consumer health and well-being, is active in the region and is predicted to increase without strict regulation and increased sensitization about its dangers. The fight against food fraud should be refocused on making food defense systems like vulnerability analysis and critical control points (VACCP) a key aspect of food safety systems to tackle food fraud.

Parvalbumin: A Major Fish Allergen and a Forensically Relevant Marker.

Parvalbumins (PVALBs) are low molecular weight calcium-binding proteins. In addition to their role in many biological processes, PVALBs play an important role in regulating Ca2+ switching in muscles with fast-twitch fibres in addition to their role in many biological processes. The PVALB gene family is divided into two gene types, alpha (α) and beta (β), with the β gene further divided into two gene types, beta1 (β1) and beta2 (β2), carrying traces of whole genome duplication. A large variety of commonly consumed fish species contain PVALB proteins which are known to cause fish allergies. More than 95% of all fish-induced food allergies are caused by PVALB proteins. The authentication of fish species has become increasingly important as the seafood industry continues to grow and the growth brings with it many cases of food fraud. Since the PVALB gene plays an important role in the initiation of allergic reactions, it has been used for decades to develop alternate assays for fish identification. A brief review of the significance of the fish PVALB genes is presented in this article, which covers evolutionary diversity, allergic properties, and potential use as a forensic marker.

Identification of Fish Species and Targeted Genetic Modifications Based on DNA Analysis: State of the Art

Food adulteration is one of the most serious problems regarding food safety and quality worldwide. Besides misleading consumers, it poses a considerable health risk associated with the potential non-labeled allergen content. Fish and fish products are one of the most expensive and widely traded commodities, which predisposes them to being adulterated. Among all fraud types, replacing high-quality or rare fish with a less valuable species predominates. Because fish differ in their allergen content, specifically the main one, parvalbumin, their replacement can endanger consumers. This underlines the need for reliable, robust control systems for fish species identification. Various methods may be used for the aforementioned purpose. DNA-based methods are favored due to the characteristics of the target molecule, DNA, which is heat resistant, and the fact that through its sequencing, several other traits, including the recognition of genetic modifications, can be determined. Thus, they are considered to be powerful tools for identifying cases of food fraud. In this review, the major DNA-based methods applicable for fish meat and product authentication and their commercial applications are discussed, the possibilities of detecting genetic modifications in fish are evaluated, and future trends are highlighted, emphasizing the need for comprehensive and regularly updated online database resources.

Environmental and Economical Impact of Blockchain

Traditional food supply chains are centralised and have problems with variable product quality, missing data, and irregular product production. As seen by the countless cases of food fraud and adulteration that are reported on a daily basis from various parts of India, an improved decentralised supply chain model is urgently needed. India is a developing nation whose demographic dividend is its greatest advantage; it cannot afford to eat contaminated dairy products. We suggest a blockchain-enabled dairy supply chain platform for the sector as a result of this predicament. Blockchain is a technology that is starting to be widely employed in a variety of commercial areas. Traditional supply chains can be turned into decentralised, robust, transparent, impermeable networks with the use of blockchain technology. The suggested supply chain platform intends to increase food safety, maintain the nutritional value of dairy products, identify adulteration and contamination in dairy products, and stop the creation of fake dairy products. This platform offers more than just food traceability. The suggested platform for the dairy supply chain integrates smart contracts, and blockchain technology and has a positive effect on the environment.

Food inauthenticity: Authority activities, guidance for food operators, and mitigation tools.

Historically, food fraud was a major public health concern which helped drive the development of early food regulations in many markets including the US and EU market. In the past 10 years, the integrity of food chains with respect to food fraud has again been questioned due to high profile food fraud cases. We provide an overview of the resulting numerous authoritative activities underway within different regions to counter food fraud, and we describe the guidance available to the industry to understand how to assess the vulnerability of their businesses and implement appropriate mitigation. We describe how such controls should be an extension of those already in place to manage wider aspects of food authenticity, and we provide an overview of relevant analytical tools available to food operators and authorities to protect supply chains. Practical Application: Practical Application of the provided information by the food industry in selecting resources (guidance document, analytical methods etc.).

Blockchain-Enabled Supply Chain platform for Indian Dairy Industry: Safety and Traceability.

Conventional food supply chains are centralized in nature and possess challenges pertaining to a single point of failure, product irregularities, quality compromises, and loss of data. Numerous cases of food fraud, contamination, and adulteration are daily reported from multiple parts of India, suggesting the absolute need for an upgraded decentralized supply chain model. A country such as India, where its biggest strength is its demographic dividend, cannot afford to malnutrition a large population of its children by allowing them to consume contaminated and adulterated dairy products. In view of the gravity of the situation, we propose a blockchain-enabled supply chain platform for the dairy industry. With respect to the supply chain platform, the dairy products of choice include milk, cheese, and butter. Blockchain is one of the fastest growing technologies having widespread acceptance across multiple industry verticals. Blockchain possesses the power to transform traditional supply chains into decentralized, robust, transparent, tamper proof, and sustainable supply chains. The proposed supply chain platform goes beyond the aspect of food traceability and focuses on maintaining the nutritional values of dairy products, identification of adulteration and contamination in dairy products, the increasing economic viability of running a dairy farm, preventing counterfeit dairy products, and enhancing the revenue of the dairy company. The paper collates the mentioned functionalities into four distinct impact dimensions: social, economic, operations, and sustainability. The proposed blockchain-enabled dairy supply chain platform combines the use of smart contracts, quick response code (QR code) technology, and IoT and has the potential to redefine the dairy supply chains on socio-economic, operational, and sustainability parameters.

Quality risk and responsive actions in sourcing/procurement: an empirical study of food fraud cases in the UK

It is never an easy task to govern contemporary food systems and prevent contaminated foods from reaching further down the chains. This study aims to investigate how UK managers in food supply chains have perceived food fraud risk in their supply chain and to identify what their actions could be in response to the threat of food fraud. The study adopts the psychometric paradigm approach to measure risk perception and uses the data collected from 113 UK food practitioners to identify the determinants of their responsive actions. The results highlight that most managers have perceived high uncertainty in the food supply chain and considered the disruption of information flow as a major concern in dealing with food fraud. Therefore, this study suggests that putting effort into practices to improve supply chain visibility and facilitate the flow of information are weighted as important in the food fraud mitigation journey. Policy makers should also make better use of the current quality assurance schemes for proactive food quality control and fraud prevention; government agencies should improve the risk communication systems for trustworthy information dissemination.

Global media as an early warning tool for food fraud; an assessment of MedISys-FF

Food fraud is a serious problem that may compromise the safety of the food products being sold on the market. Previous studies have shown that food fraud is associated with a large variety of food products and the fraud type may vary from deliberate changing of the food product (i.e. substitution, tampering, dilution etc.) to the manipulation of documents. It is therefore important that all actors within the food supply chain (food producers, authorities), have methodologies and tools available to detect fraudulent products at an early stage so that preventative measures can be taken. Several of such systems exist (i.e. iRASFF, EMA, HorizonScan, AAC-FF, MedISys-FF), but currently only MedISys-FF is publicly online available. In this study, we analyzed food fraud cases collected by MedISys-FF over a 6-year period (2015–2020) and show global trends and developments in food fraud activities. In the period investigated, the system has collected 4375 articles on food fraud incidents from 164 countries in 41 different languages. Fraud with meat and meat products were most frequently reported (27.7%), followed by milk and milk products (10.5%), cereal and bakery products (8.3%), and fish and fish products (7.7%). Most of the fraud was related to expiration date (58.3%) followed by tampering (22.2%) and mislabeling of country of origin (11.4%). Network analysis showed that the focus of the articles was on food products being frauded. The validity of MedISys-FF as an early warning system was demonstrated with COVID-19. The system has collected articles discussing potential food fraud risks due to the COVID-19 crisis. We therefore conclude that MedISys-FF is a very useful tool to detect early trends in food fraud and may be used by all actors in the food system to ensure safe, healthy, and authentic food.

A holistic approach to food fraud vulnerability assessment

The increase in fraudulent incidents has resulted in a change of focus in theory related to investigating food fraud from risk mitigation to vulnerability reduction. While the literature provided a framework from which to identify possible areas of vulnerability to food fraud, it does not provide a methodology that would allow food producers and processors to quantify and assess their vulnerability to food fraud more accurately. This paper developed a holistic approach to analyse food fraud vulnerability factors using a Bayesian Network (BN) approach based on the Decernis food fraud database incidents. Food fraud incidents related to seafood, dairy, alcoholic beverages and meat products were reviewed as they cover more than 50 % of the Decernis incident records (as in June 2018). 580 cases of food fraud were included in the development of the BN model. SPSS Modeler 18.2 was used to construct two BN model, and fraud vulnerability factors were directly linked to seven criteria of the country of origin, country of detection, year, food fraud types, product types, the weight of evidence, and types of adulterants. Possible food fraud vulnerability factors related to each case retrieved from Decernis database, combined Barrier Analysis technique and Routine Activity Theory, and additional sources from the literature. Two Bayesian Networks of Tree Augmented Naïve (TAN) and Markov were selected to determine the most reliable holistic model. Based on the analysis result, the TAN model assessed the vulnerability to food fraud with a higher accuracy rate of 86 %. The country of origin (76 %), food product types (9 %), types of adulterants (counterfeiting) (9 %), and country of detection (China) (6 %) were the main predictors of food fraud vulnerability factors. This model helps authorities in border protection, policymakers, and quality assurance agencies assess fraud vulnerability for a range of food products for incoming (imported) food products, mainly if they know the country of origin and type of food products.

Identifying food fraud vulnerability factors in food fraud incidents – a review of global incidents 2000–2018

PurposeGlobal food fraud incidents are regularly reported and are on the rise due to the ineffectiveness of traditional food safety intervention strategies. The increase in food fraud opportunity is prevalent in the state of the COVID-19 pandemic as well. Food fraud vulnerability assessment (FFVA) is acknowledged as a critical requirement by the Global Food Safety Initiatives (GFSIs) and the World Health Organisation for an effective food fraud mitigation plan. However, there is no clear direction or ways to identify and analyse food fraud vulnerability factors based on real-data.Design/methodology/approachCombining the barrier analysis technique and the routine activity theory to review the 580 cases of food fraud recorded in the Decernis database, this paper identified new food fraud vulnerability dimensions and insights pinpointed to three categories of opportunity, motivation and countermeasures.FindingsNew dimensions of food fraud vulnerability factors are identified in this paper over the period 2000–2018. Where possible, new insights related to each food fraud vulnerability factor and dimension were identified, and literature evidence was used to confirm their contribution.Originality/valueThere is a gap observed in the first step of FFVA in the literature. This paper is the first study to undertake a FFVA based on evidence recorded in a global food fraud database. This paper offers critical insights into global food fraud regulations by exploring the new emerging root causes of food fraud and analysing them, supporting developing effective food fraud prevention plans (FFPPs).

Rapid Analysis and Authentication of Meat Using the MasSpec Pen Technology.

Food authenticity and safety are major public concerns due to the increasing number of food fraud cases. Meat fraud is an economically motivated practice of covertly replacing one type of meat with a cheaper alternative raising health, safety, and ethical concerns for consumers. In this study, we implement the MasSpec Pen technology for rapid and direct meat analysis and authentication. The MasSpec Pen is an easy-to-use handheld device connected to a mass spectrometer that employs a solvent droplet for gentle chemical analysis of samples. Here, MasSpec Pen analysis was performed directly on several meat and fish types including grain-fed beef, grass-fed beef, venison, cod, halibut, Atlantic salmon, sockeye salmon, and steelhead trout, with a total analysis time of 15 s per sample. Statistical models developed with the Lasso method using a training set of samples yielded per-sample accuracies of 95% for the beef model, 100% for the beef versus venison model, and 84% for the multiclass fish model. Predictors of meat type selected included several molecules previously reported in the skeletal muscles of animals, including carnosine, anserine, succinic acid, xanthine, and taurine. When testing the models on independent test sets of samples, per-sample accuracies of 100% were achieved for all models, demonstrating the robustness of our method for unadulterated meat authentication. MasSpec Pen feasibility testing for classifying venison and grass-fed beef samples adulterated with grain-fed beef achieved per-sample prediction accuracies of 100% for both classifiers using test sets of samples. Altogether, the results obtained in this study provide compelling evidence that the MasSpec Pen technology is a powerful alternative analytical method for meat analysis and investigation of meat fraud.

Food adulteration and safety regarding detected market cases and consumer opinions

Food fraud is one of the long-standing causes of scandals attracting particular attention for a long time. This study aimed to monitor food fraud in the European Union and to identify the relationships among the countries where the cases were reported, adulterated commodities (seafood, eggs, milk, meat, fish, and their products) and types of fraud. The secondary data were covered by the survey focused on consumer knowledge about fraudulent activities, ingredient substitution, masking of origin, mislabeling, placing on the market of foods not fit for human consumption within Slovak inhabitants. Primary and secondary data were used to achieve this aim. Primary data were obtained from the Food Fraud and Quality Knowledge Center (KCFFQ) and secondary data from the questionnaire survey from 354 respondents. During the period from 2017 to 2019, 163 cases of food fraud were reported, most of which originated from Italy and mainly concerned fish and fish products. Based on primary data and one-way ANOVA statistical tests, we confirmed five hypotheses. There was found no statistical impact of the country on the type of food fraud (p = 0.0067), but the significant effect was determined on which food was adulterated (p = 0.000001). There was no statistical correlation among years and countries where the cases were reported (p = 0.110), but the statistically significant correlation was confirmed among years and commodities (p = 0.0043) and types of fraud reported (p = 0.009). Based on the processed secondary data from the questionnaire, we can conclude some information or public interest in food fraud problems.

Detection of pork in processed meat products by species-specific PCR for halal verification: food fraud cases in Hat Yai, Thailand

Consumer confidence in halal integrity of the unique and various food products provides Hat Yai, Thailand a great potential for a global destination of Muslim-friendly tourism. Islam prohibits the consumption of pork and its derivatives in any food products. The issue of food adulteration and contamination, particularly in the processed halal meat products with pork and its derivatives, greatly concern Muslim consumers. The aim of this study was to detect the presence of pork DNA from processed meat products collected from self-proclaimed “halal” Muslim street food stalls at Hat Yai, Thailand. Thirty-six samples of various processed meat products were randomly collected from seven Muslim street food stalls including patties, meatballs, and sausages containing processed chicken, beef, or a mixture of various meats. The detection of the presence of pork and its derivatives was performed by a conventional polymerase chain reaction (PCR) technique based on the pork-specific primers for a conserved region in the mitochondrial (mt) 12S ribosomal RNA (rRNA) gene. The results revealed that three out of the thirty-six samples (8.3%) were positively identified to contain porcine DNA by the detection of the expected single band of size 387 bp. The DNA method conveniently provides reliable results for routine food analysis for halal requirement. Overall, the study highlights the importance of halal integrity between the producers, suppliers, and street food business owners to provide halal food products particularly to Muslim consumers.

A PCR-based lateral flow assay for the detection of Turkey ingredient in food products

A simple PCR-based lateral flow assay (LFA) was developed to detect turkey ingredient in foods. We developed this assay based on PCR amplification of turkey DNA, followed by detecting labeled amplicon by LFA. The results could be observed by the naked eye within 5 min following PCR. The reliability of this assay was confirmed by gel electrophoresis. Specificity tests validated no cross-reactivity with 21 other animal and plant samples. As low as 0.1% (w/w) of turkey in mixed meats were detected by the proposed PCR-LFA. Heat treatment did not affect the sensitivity of this assay for detecting turkey ingredient. The reproducibility of PCR-LFA was confirmed by the fully consistent intra-laboratory tests and acceptable inter-laboratory tests. Finally, this assay was successfully used to authenticate 24 commercial turkey products. No turkey ingredient was identified in two frozen turkey rolls, indicating food fraud cases. PCR-LFA provides an accurate, sensitive and cost-effective approach for turkey authentication. It is a promising tool for species authentication, food quality assurance and traceability.

How to tackle food fraud in official food control authorities in Germany

Food Fraud has been a problem for as long as food trade exists in human history. Recent food fraud scandals have attracted particular attention of the public and authorities. The fight against food fraud is still hampered by a lack of a clear definition stating which facts constitute a legal case of food fraud. Against this background, an online survey was conducted in the official food control authorities of the German federal states to obtain an overview of the facts considered as food fraud and to identify factors which, according to the respondents, could be used for the early detection of food fraud. The study was carried out in autumn 2017 with the online software tool Sosci Survey. The data collected was analysed descriptively using Microsoft Excel. The following facts are classified as food fraud by almost all participants: substitution of substances/liquids, imitation of foodstuff, omission of substances/liquids and the concealment of inferior quality of a product. The origin of the foodstuff is considered to be the most important factor in predicting possible food fraud, followed by the product category and price fluctuations. The results of this study show similarities and differences in the understanding of the term food fraud in the official institutions of Germany. Therefore they might be used for the development of a legal definition, which eliminates the identified ambiguities and is a prerequisite for a stringent and congruent fight against food fraud. The identified factors for predicting possible cases of food fraud could be used to develop an early warning system and could thus be part of an overall prevention concept.

Valid machine learning algorithms for multiparameter methods

In the light of recent food fraud cases, the issue of food authenticity is receiving increasing attention. New analytical methods and evaluation approaches are currently being proposed. In this framework, the evaluation of mass spectral profiles constitutes a promising avenue, e.g. for the determination of food origin. Relevant evaluation approaches include principal component analysis, artificial neural networks, random forests, support vector machines, etc. The aim is to derive decision rules for the assignation of unknown samples to different classes. These decision rules are derived on the basis of samples whose origin is known—the training set. Typically, a reliable evaluation requires that the number of samples should be considerably larger than the number of features. However, in the framework of multiparameter mass spectrometry methods, the required ratio between sample and parameter numbers is inverted, with, e.g. 100 samples versus 10 000 features. In this paper, two approaches for the establishment of reliable decision rules in spite of low sample numbers are discussed.

Gap analysis of the Canadian food fraud regulatory oversight and recommendations for improvement

The Canadian regulatory framework prohibits selling adulterated food or selling food in a false, misleading or deceptive manner. Although the number of prosecutions for food fraud cases in Canada has steadily decreased in the last decade, except for a spike in 2017, penalties are becoming more severe (i.e. 12-fold increase in fine amount between 2008 and 2018). The majority of cases are in violation with the Food and Drugs Act, Section 5(1), which prohibits “labelling, packaging, treating, processing, selling or advertising food in a manner that is false, misleading or deceptive or is likely to create an erroneous impression.” In the cases presented in this study, violators having been found guilty were fined between $25,000 and $1.5 million, but none were sentenced to imprisonment.To improve control over food fraud incidents, the Canadian government should clearly define food fraud and include a definition and description of the different types of fraudulent activities. To support this, the Government of Canada should raise awareness about food fraud among members of the food industry, while requiring expanded testing of raw ingredients and final products for authenticity. A critical step is for the Canadian government to conduct a country-wide food fraud vulnerability assessment to identify the most problematic types of food fraud and then create a country-wide food fraud prevention strategy. Once the prevention strategy is in place, then the most efficient countermeasures and control systems can be considered. The holistic and all-encompassing food fraud prevention focus would be on a coordinated and optimized reduction of the entire fraud opportunity. The creation of government-industry-academia partnerships would also play an essential role in preventing and combating food fraud. It is possible that few – if any – additional government allocation will be required to put the plan in place and begin to make significant improvements.

Warunki bezpieczeństwa żywnościowego Polski (ze szczególnym uwzględnieniem województwa podlaskiego)

Purpose – The article aims to define main tendencies concerning the structure of food safety within the economy of Poland with special consideration of the Podlasie Voivodeship.Research method – The analysis was conducted on the basis of data obtained from the Central Statistical Office of Poland (GUS), the State Sanitary Inspectorate, the Office of the Chief Inspector of Food and Agricultural Products as well as the study of literature related to the issue being considered.Results – The analysis established that on account of decreasing levels of population and the growing capabilities for food production its physical availability is not threatened. The Podlasie Voivodeships plays a significant role in food production. The condition of economic availability of food both nationally as well as in the Podlasie Voivodeship has not been met. Health related quality of agriculturally produced food is varied and does not display a steady tendency for improvement which requires appropriate institutions to remain vigilant in monitoring it. The last several years have seen a rise in the number of food fraud cases. The tendencies concerning food safety presented in the article prove that the subject remains important and valid. Despite the lack of a clear threat to the level of that safety in Poland, it must be remembered that this situation is not stable or unchangeable, a condition which also concerns the future.