A review of food fraud and food authenticity across the food supply chain, with an examination of the impact of the COVID-19 pandemic and Brexit on food industry

Identifying the botanical origin of alcohol using 2H SNIF NMR: A case study of "polish vodka" PGI

In this study, we utilized 2H SNIF NMR and chemometric techniques to differentiate the botanical origin of raw materials used in vodka production in Poland, specifically focusing on plants with C3 metabolism such as grain, potato, and sugar beet. Additionally, for the first time, mixtures of alcohols from different C3 plants were analysed to detect adulteration. Our goal was to determine if it is possible to detect the addition of a different raw material in vodka made from a mixture of alcohols derived from C3 plants. Significant isotopic differences were confirmed using analysis of variance and Tukey's tests. Linear relationships in grain-potato, grain-sugar beet, and beet-potato mixtures enabled composition determination. The detectability threshold for adulterants ranged from 10 % to 50 %, depending on the type of raw material. Our findings suggest that 2H SNIF-NMR is an effective tool for authenticating vodka and detecting adulteration in products marketed as "Polish vodka."

Food authenticity and the interactions with human health and climate change

Food authenticity and fraud, as well as the interest in food traceability have become a topic of increasing interest not only for consumers but also for the research community and the food manufacturing industry. Food authenticity and fraud are becoming prevalent in both the food supply and value chains since ancient times where different issues (e.g., food spoilage during shipment and storage, mixing decay foods with fresh products) has resulted in foods that influence consumers health. The effect of climate change on the quality of food ingredients and products could also have the potential to influence food authenticity. However, this issue has not been considered. This article focused on the interactions between consumer health and the potential effects of climate change on food authenticity and fraud. The role of technology and development of risk management tools to mitigate these issues are also discussed. Where applicable papers that underline the links between the interactions of climate change, human health and food fraud were referenced.

Food Fraud Conceptualization: An Exploratory Study with Portuguese Consumers

Food fraud refers to deceptive practices conducted for economic gain, and incidents of such fraud are often reported in the media and scientific literature. However, little is known about how European consumers perceive food fraud. To address this gap, a study explored Portuguese consumers' knowledge and perceptions of food fraud using qualitative methods such as free word association and semi-structured interviews. For this research, 340 participants were recruited, providing 911 valid words, classified into categories, major categories, and dimensions. Differences between consumers' previous exposure to food fraud and sociodemographic characteristics were explored. Additionally, other thirty-six participants were selected and interviewed, following a semi-structured guide. Interviews were transcribed, coded, and analyzed using a thematic analysis procedure. The results suggest that Portuguese consumers view food fraud as a morally reprehensible deception and are aware of its causes and impacts. However, not all consumers know the different forms of food fraud or the types of products vulnerable to fraud. Among the most repeated words were "deception", "expiration date", and "falsification". Despite this food fraud awareness, most consumers believed they were not exposed to food fraud and stated that they do not conduct daily practices to reduce exposure to it. Following the chi-square and Mann-Whitney tests, significant differences (p ≤ 0.05) were identified between participants exposed and not exposed to food fraud. The study also found that consumers with higher education and self-reported exposure to food fraud had a better understanding of the issue. This study provides insights for quantitative research on consumer perceptions and beliefs about food fraud to explore further vulnerable food categories and types of food fraud in real-world scenarios.

Application of machine learning approach on halal meat authentication principle, challenges, and prospects: A review

Meat is a source of essential amino acids that are necessary for human growth and development, meat can come from dead, alive, Halal, or non-Halal animal species which are intentionally or economically (adulteration) sold to consumers. Sharia has prohibited the consumption of pork by Muslims. Because of the activities of adulterators in recent times, consumers are aware of what they eat. In the past, several methods were employed for the authentication of Halal meat, but numerous drawbacks are attached to this method such as lack of flexibility, limited application, time,consumption and low level of accuracy and sensitivity. Machine Learning (ML) is the concept of learning through the development and application of algorithms from given data and making predictions or decisions without being explicitly programmed. The techniques compared with traditional methods in Halal meat authentication are fast, flexible, scaled, automated, less expensive, high accuracy and sensitivity. Some of the ML approaches used in Halal meat authentication have proven a high percentage of accuracy in meat authenticity while other approaches show no evidence of Halal meat authentication for now. The paper critically highlighted some of the principles, challenges, successes, and prospects of ML approaches in the authentication of Halal meat.

Food fraud threats in UK post-harvest seafood supply chains; an assessment of current vulnerabilities

Seafood fraud is commonly reported on food fraud databases and deceptive practices are highlighted by numerous studies, with impacts on the economy, health and marine conservation. Food fraud assessments are a widely accepted fraud mitigation and prevention activity undertaken to identify possible points of deception within a supply chain. This study aims to understand the food fraud vulnerability of post-harvest seafood supply chains in the UK and determine if there are differences according to commodity, supply chain node, business size and certification status. The SSAFE food fraud vulnerability assessment tool was used to assess 48 fraud factors relating to opportunities, motivations and controls. The analysis found seafood supply chains to have a medium vulnerability to food fraud, with the highest perceived vulnerability in technical opportunities. Certification status was a stronger determinant of vulnerability than any other factor, particularly in the level of controls, a factor that also indicated a higher perceived level of vulnerability in smaller companies and the food service industry. This paper also reviews historic food fraud trends in the sector to provide additional insights and the analysis indicates that certain areas of the supply chain, including uncertified prawn supply chains, salmon supply chains and food service companies, may be at higher risk of food fraud. This study conducts an in-depth examination of food fraud vulnerability relating to the UK and for seafood supply chains and contributes to a growing body of literature identifying areas of vulnerability and resilience to food related criminality within the global food system.

Food authentication, current issues, analytical techniques, and future challenges: A comprehensive review

Food authentication and contamination are significant concerns, especially for consumers with unique nutritional, cultural, lifestyle, and religious needs. Food authenticity involves identifying food contamination for many purposes, such as adherence to religious beliefs, safeguarding health, and consuming sanitary and organic food products. This review article examines the issues related to food authentication and food fraud in recent periods. Furthermore, the development and innovations in analytical techniques employed to authenticate various food products are comprehensively focused. Food products derived from animals are susceptible to deceptive practices, which can undermine customer confidence and pose potential health hazards due to the transmission of diseases from animals to humans. Therefore, it is necessary to employ suitable and robust analytical techniques for complex and high-risk animal-derived goods, in which molecular biomarker-based (genomics, proteomics, and metabolomics) techniques are covered. Various analytical methods have been employed to ascertain the geographical provenance of food items that exhibit rapid response times, low cost, nondestructiveness, and condensability.

Exploring Key Barriers of HACCP Certification Adoption in the Meat Industry: A Decision-Making Trial and Evaluation Laboratory Approach

Food safety management represents an important concern in contemporary society. The Hazard Analysis Critical Control Point (HACCP) system is a crucial tool for meat producers, preventing and controlling major food safety concerns in the process. This research investigates key barriers to HACCP implementation in the meat industry, employing the Decision-Making Trial and Evaluation Laboratory (DEMATEL) model to identify and categorize these obstacles. Using the insights of 18 experts, a cause-and-effect relationship diagram is generated through which twelve barriers are categorized in terms of their cause and effect and then analyzed. Threshold value is calculated as 0.299. The findings reveal poor management as the primary impediment, followed by challenges in training, knowledge, and dedication. Categorizing the barriers into four groups emphasizes the critical role of effective management and human resources. The study contributes valuable insights to food safety management literature, serving as a practical resource for industry practitioners. Despite limitations in relying on expert opinions and the industry-specific focus, the research lays a foundation for informed decision-making, stressing the importance of effective management in successful HACCP implementation. Future research directions include diversifying geographical representation, exploring practical solutions, and integrating emerging technologies for a better understanding of HACCP adoption challenges.

Anticounterfeiting and Fraud Mitigation Solutions for High-value Food Products

Globalization and the increasing complexity of supply chains have allowed food fraud to expand to a great extent. Some of the most serious effects of these deceitful activities are damage to a brand's reputation and trust, economic losses, and public health risks. The usual victims of food fraud are dairy, meat, fish, and seafood products, as well as fats/oils and alcoholic drinks. The purpose of this review paper is to present an updated analysis of the currently available anticounterfeit technologies and their application to the four most fraud-affected food supply chains. An assessment that was conducted to determine when the adoption of a combination of technologies could enhance food safety and brand protection is also provided. The obtained results indicate that electronic and data-driven technologies (RFID devices and digital traceability systems) are still in their infancy in the food sectors that are subjected the most to fraudulent activities. Research is necessary to develop innovative digital and physical technologies to "outsmart" such fraudsters and to prevent their illicit actions in the food sector.

Safe Food Supply Chain as Health Network: An Evolutionary Game Analysis of Behavior Strategy for Quality Investment

There is a natural relation between human health and the quality of their food and drinks, and elevating the quality input level of food production for all enterprises within the food supply chain system forms the foundation for preventing various potential food safety risks that may be encountered. Unlike the previous research on quality investment of food production by enterprises, this paper probes into the evolutionary routes of the behavior strategy selection of subjects in the food supply chain and the preconditions for the equilibrium points of the social co-governance system. It takes the approach of establishing a tripartite evolutionary game model of food suppliers, food manufacturers and consumers on the basis of the social co-governance framework, in view of the above, this paper focuses on the influence of the reputation mechanism and the market contracts among supply chain subjects on the selection of a behavior strategy for quality investment by enterprises under the condition of lawful regulation by government. The results show that every subject selects their own behavior strategy on the basis of the balance of their respective interests. The net disbursement incurred by enterprises for quality investment and the costs of participation in governance by consumers constitute the dominant factors that influence both enterprises' selection of a behavior strategy and the level of social co-governance. Compared with the increase in economic punishment imposed on suppliers for production of risky food raw materials, it is more efficient to control food safety risks by lowering the costs of quality investment by suppliers. Accordingly, this paper proposes advice on policy in an attempt to provide inspiration for preventing and controlling food safety risks.

Is the metabarcoding ripe enough to be applied to the authentication of foodstuff of animal origin? A systematic review

Food authentication using molecular techniques is of great importance to fight food fraud. Metabarcoding, based on the next-generation sequencing (NGS) technologies, allowing large-scale taxonomic identification of complex samples via massive parallel sequencing of fragments (called DNA barcodes) simultaneously, has become increasingly popular in many scientific fields. A systematic review to answer the question "Is the metabarcoding ripe enough to be applied to the authentication of foodstuff of animal origin?" is presented. The inclusion criteria were focused on the selection of scientific papers (SPs) only applying metabarcoding to foodstuff of animal origin collected on the market. The 23 included SPs were first analyzed with respect to the metabarcoding phases: library preparation (target genes, primer pairs, and fragment length), sequencing (NGS platforms), and final data analysis (bioinformatic pipelines). Given the importance of primer selection, the taxonomic coverage of the used primers was also evaluated. In addition, the SPs were scored based on the use of quality control measures (procedural blanks, positive controls, replicates, curated databases, and thresholds to filter the data). A lack of standardized protocols, especially with respect to the target barcode/s and the universal primer/s, and the infrequent application of the quality control measures, leads to answer that metabarcoding is not ripe enough for authenticating foodstuff of animal origin. However, the observed trend of the SP quality improvement over the years is encouraging. Concluding, a proper protocol standardization would allow a wider use of metabarcoding by both official and private laboratories, enabling this method to become the primary for the authentication of foodstuffs of animal origin.

Harnessing the power on our plates: sustainable dietary patterns for public and planetary health

Globally, diet quality is poor, with populations failing to achieve national dietary guidelines. Such failure has been consistently linked with malnutrition and poorer health outcomes. In addition to the impact of diet on health outcomes, it is now accepted that what we eat, and the resulting food system, has significant environmental or planetary health impacts. Changes are required to our food systems to reduce these impacts and mitigate the impact of climate change on our food supply. Given the complexity of the interactions between climate change, food and health, and the different actors and drivers that influence these, a systems-thinking approach to capture such complexity is essential. Such an approach will help address the challenges set by the UN 2030 Agenda for sustainable development in the form of the sustainable development goals (SDG). Progress against SDG has been challenging, with an ultimate target of 2030. While the scientific uncertainties regarding diet and public and planetary health need to be addressed, equal attention needs to be paid to the structures and systems, as there is a need for multi-level, coherent and sustained structural interventions and policies across the full food system/supply chain to effect behaviour change. Such systems-level change must always keep nutritional status, including impact on micronutrient status, in mind. However, benefits to both population and environmental health could be expected from achieving dietary behaviour change towards more sustainable diets.

Low-cost electronic-nose (LC-e-nose) systems for the evaluation of plantation and fruit crops: recent advances and future trends

An electronic nose (e-nose) is a device designed to recognize and classify odors. The equipment is built around a series of sensors that detect the presence of odors, especially volatile organic compounds (VOCs), and generate an electric signal (voltage), known as e-nose data, which contains chemical information. In the food business, the use of e-noses for analyses and quality control of fruits and plantation crops has increased in recent years. Their use is particularly relevant due to the lack of non-invasive and inexpensive methods to detect VOCs in crops. However, the majority of reports in the literature involve commercial e-noses, with only a few studies addressing low-cost e-nose (LC-e-nose) devices or providing a data-oriented description to assist researchers in choosing their setup and appropriate statistical methods to analyze crop data. Therefore, the objective of this study is to discuss the hardware of the two most common e-nose sensors: electrochemical (EC) sensors and metal oxide sensors (MOSs), as well as a critical review of the literature reporting MOS-based low-cost e-nose devices used for investigating plantations and fruit crops, including the main features of such devices. Miniaturization of equipment from lab-scale to portable and convenient gear, allowing producers to take it into the field, as shown in many appraised systems, is one of the future advancements in this area. By utilizing the low-cost designs provided in this review, researchers can develop their own devices based on practical demands such as quality control and compare results with those reported in the literature. Overall, this review thoroughly discusses the applications of low-cost e-noses based on MOSs for fruits, tea, and coffee, as well as the key features of their equipment (i.e., advantages and disadvantages) based on their technical parameters (i.e., electronic and physical parts). As a final remark, LC-e-nose technology deserves significant attention as it has the potential to be a valuable quality control tool for emerging countries.

Application of Microsatellites to Trace the Dairy Products Back to the Farm of Origin

The increasing number of food frauds, mainly targeting high quality products, is a rising concern among producers and authorities appointed to food controls. Therefore, the development or implementation of methods to reveal frauds is desired. The genetic traceability of traditional or high-quality dairy products (i.e., products of protected designation of origin, PDO) represents a challenging issue due to the technical problems that arise. The aim of the study was to set up a genetic tool for the origin traceability of dairy products. We investigated the use of Short Tandem Repeats (STRs) to assign milk and cheese to the corresponding producer. Two farms were included in the study, and the blood of the cows, bulk milk, and derived cheese were sampled monthly for one year. Twenty STRs were selected and Polymerase Chain Reactions for each locus were carried out. The results showed that bulk milk and derived cheese express an STR profile composed of a subset of STRs of the lactating animals. A bioinformatics tool was used for the exclusion analysis. The study allowed the identification of a panel of 20 markers useful for the traceability of milk and cheeses, and its effectiveness in the traceability of dairy products obtained from small producers was demonstrated.

Classification of Vietnamese Cashew Nut (Anacardium occidentale L.) Products Using Statistical Algorithms Based on ICP/MS Data: A Study of Food Categorization

Fingerprinting techniques, which utilize the unique chemical and physical properties of food samples, have emerged as a promising approach for food authentication and traceability. Recent studies have demonstrated significant advancements in food authentication through the use of fingerprinting methods, such as multivariate statistical analysis techniques applied to trace elements and isotope ratios. However, further research is required to optimize these methods and ensure their validity and reliability in real-world applications. In this study, the inductively coupled plasma mass spectrometry (ICP-MS) analytical method was employed to determine the content of 21 elements in 300 cashew nut (Anacardium occidentale L.) samples from 5 brands. Multivariate statistical methods, such as principal components analysis (PCA), were employed to analyze the data obtained and establish the provenance of the cashew nuts. While cashew nuts are widely marketed in many countries, no universal method has been utilized to differentiate the origin of these nuts. Our study represents the initial step in identifying the geographical origin of commercial cashew nuts marketed in Vietnam. The analysis showed significant differences in the means of 21 of the 40 analyzed elements among the cashew nut samples from the 5 brands, including 7Li, 11B, 24Mg, 27Al, 44Ca, 48Ti, 51V, 52Cr, 55Mn, 57Fe, 60Ni, 63Cu, 66Zn, 93Nb, 98Mo, 111Cd, 115In, 121Sb, 138Ba, 208Pb, and 209Bi. The PCA analysis indicated that the cashew nut samples can be accurately classified according to their original locations. This research serves as a prerequisite for future studies involving the combination of elemental composition analysis with statistical classification methods for the accurate establishment of cashew nut provenance, which involves the identification of key markers for the original discrimination of cashew nuts.

Volatile markers as a reliable alternative for the correct classification of citrus monofloral honey

The pollen analysis to classify monofloral honey is an unresolved challenge specially when the pollen is under-represented as the case of citrus honey. Thus, this study assesses the validity of the volatile fraction to differentiate types of honey, with special attention to markers compounds of citrus honey that could permit their distinction. Unsupervised analysis (PCA and HCA) showed that the volatile fraction of honey containing Citrus sp. pollen, undoubtedly differentiates it from other types of honey. An OPLS model focused on citrus honey selected 5 volatile compounds (of the 123 found in all samples by GC-MS) as significant predictors of the currently used value of methyl anthranilate obtained by HPLC. The joint detection of 4 lilac-aldehydes and the volatile methyl-anthranilate has the advantage of providing more precise information. Therefore, it could be proposed as a consistent marker to ensure the correct classification of citrus honey, fostering its labelling reliability.

Food fraud and mitigating strategies of UK food supply chain during COVID-19

Covid-19 had shown the vulnerability of the food supply chain and fraudsters may take advantage of the pandemic whilst the population needed a continuous supply of safe and quality food. The lack of monitoring and policing in the food supply chain may encourage fraudsters to upscale their operations. Previous studies had warned of a surge in fraudulent products due to COVID-19. This raised the question on whether food fraud had increased during the pandemic? This study aims to investigate food fraud during COVID-19 and how the food supply chain develops mitigating strategies against fraudulent activities. A mixed-method approach including survey and semi-structured interviews were conducted among UK food businesses. Two hundred and two agri-food businesses responded to the survey and 15 semi-structured interviews were conducted. The majority of the food businesses did not experience an increase of food fraud activities during COVID-19. Two thematic domains and ten sub-themes were identified from the data set. There was a heightened sense of anticipation and preparation for increased fraudulent activities during the pandemic. The main risk mitigating strategies included horizon scanning; developing and maintaining supplier relationship and assurance; understanding product characteristics, testing capabilities, conducting vulnerability assessments and training. Practical and cost-effective strategies for small and medium food businesses were recommended. This is the first empirical study on food fraud and mitigating strategies of the UK food supply chain during the pandemic. Our findings provide evidence for informing the policies and practices of the food regulatory authorities as well as best practices to protect the UK food supply chain against food fraud during exogenous shocks like COVID-19.

Implementation of relevant fourth industrial revolution innovations across the supply chain of fruits and vegetables: A short update on Traceability 4.0

Food Traceability 4.0 refers to the application of fourth industrial revolution (or Industry 4.0) technologies to ensure food authenticity, safety, and high food quality. Growing interest in food traceability has led to the development of a wide range of chemical, biomolecular, isotopic, chromatographic, and spectroscopic methods with varied performance and success rates. This review will give an update on the application of Traceability 4.0 in the fruits and vegetables sector, focusing on relevant Industry 4.0 enablers, especially Artificial Intelligence, the Internet of Things, blockchain, and Big Data. The results show that the Traceability 4.0 has significant potential to improve quality and safety of many fruits and vegetables, enhance transparency, reduce the costs of food recalls, and decrease waste and loss. However, due to their high implementation costs and lack of adaptability to industrial environments, most of these advanced technologies have not yet gone beyond the laboratory scale. Therefore, further research is anticipated to overcome current limitations for large-scale applications.

Metabolomics integrated with machine learning to discriminate the geographic origin of Rougui Wuyi rock tea

The geographic origin of agri-food products contributes greatly to their quality and market value. Here, we developed a robust method combining metabolomics and machine learning (ML) to authenticate the geographic origin of Wuyi rock tea, a premium oolong tea. The volatiles of 333 tea samples (174 from the core region and 159 from the non-core region) were profiled using gas chromatography time-of-flight mass spectrometry and a series of ML algorithms were tested. Wuyi rock tea from the two regions featured distinct aroma profiles. Multilayer Perceptron achieved the best performance with an average accuracy of 92.7% on the training data using 176 volatile features. The model was benchmarked with two independent test sets, showing over 90% accuracy. Gradient Boosting algorithm yielded the best accuracy (89.6%) when using only 30 volatile features. The proposed methodology holds great promise for its broader applications in identifying the geographic origins of other valuable agri-food products.

Mechanisms and Health Aspects of Food Adulteration: A Comprehensive Review

Food adulteration refers to the alteration of food quality that takes place deliberately. It includes the addition of ingredients to modify different properties of food products for economic advantage. Color, appearance, taste, weight, volume, and shelf life are such food properties. Substitution of food or its nutritional content is also accomplished to spark the apparent quality. Substitution with species, protein content, fat content, or plant ingredients are major forms of food substitution. Origin misrepresentation of food is often practiced to increase the market demand of food. Organic and synthetic compounds are added to ensure a rapid effect on the human body. Adulterated food products are responsible for mild to severe health impacts as well as financial damage. Diarrhea, nausea, allergic reaction, diabetes, cardiovascular disease, etc., are frequently observed illnesses upon consumption of adulterated food. Some adulterants have shown carcinogenic, clastogenic, and genotoxic properties. This review article discusses different forms of food adulteration. The health impacts also have been documented in brief.

Impact of food safety supervision efficiency on preventing and controlling mass public crisis

Food safety has received unprecedented attention since the COVID-19 outbreak. Exploring food safety regulatory mechanisms in the context of cluster public crises is critical for COVID-19 prevention and control. As a result, using data from a food safety regulation survey in the Bei-jing-Tianjin-Hebei urban cluster, this paper investigates the impact of food safety regulation on the prevention and control of COVID-19. The study found that food safety regulation and cluster public crisis prevention and control have a significant positive relationship, with the ability to integrate regulatory resources acting as a mediator between the two. Second, industry groups argue that the relationship between regulatory efficiency and regulatory resource integration should be moderated in a positive manner. Finally, industry association support positively moderates the mediating role of regulatory re-source integration capacity between food safety regulatory efficiency and cluster public crises, and there is a mediating effect of being moderated. Our findings shed light on the mechanisms underlying the roles of regulatory efficiency, resource integration capacity, and industry association support in food safety, and they serve as a useful benchmark for further improving food safety regulations during the COVID-19 outbreak.

CRISPR-Cas systems mediated biosensing and applications in food safety detection

Food safety, closely related to economic development of food industry and public health, has become a global concern and gained increasing attention worldwide. Effective detection technology is of great importance to guarantee food safety. Although several classical detection methods have been developed, they have some limitations in portability, selectivity, and sensitivity. The emerging CRISPR-Cas systems, uniquely integrating target recognition specificity, signal transduction, and efficient signal amplification abilities, possess superior specificity and sensitivity, showing huge potential to address aforementioned challenges and develop next-generation techniques for food safety detection. In this review, we focus on recent progress of CRISPR-Cas mediated biosensing and their applications in food safety monitoring. The properties and principles of commonly used CRISPR-Cas systems are highlighted. Notably, the frequently coupled nucleic acid amplification strategies to enhance their selectivity and sensitivity, especially isothermal amplification methods, as well as various signal output modes are also systematically summarized. Meanwhile, the application of CRISPR-Cas systems-based biosensors in food safety detection including foodborne virus, foodborne bacteria, food fraud, genetically modified organisms (GMOs), toxins, heavy metal ions, antibiotic residues, and pesticide residues is comprehensively described. Furthermore, the current challenges and future prospects in this field are tentatively discussed.

Investigating how COVID-19 has challenged the Eurocentric concept of 'development': a case for sustainable food systems in the UK

The COVID-19 health crisis has imposed extensive shocks to many global systems, particularly the UK food production chains, further challenging Eurocentric development discourses and stereotypes. Thus, this paper investigates how the pandemic has challenged the UK's development status by analysing how the pandemic has impacted the country's food industry. A literature review was conducted and used to identify, select and critically appraise publications between 2000 and 2021 discussing the challenges in the UK food system. The findings reveal that the UK's food industry is unsustainable as there are significant flaws in the system, that is food insecurity and food waste that go unaddressed. The impact of the pandemic has exacerbated the social and economic impacts of operating with such a system. Compounded with the geopolitical adjustments caused by Brexit, the UK is faced with the challenge of restructuring and developing new frameworks such as policies, regulations, schemes and partnerships to support the food industry's sustainability. Lastly, the findings reinforce that 'developed' and 'developing' nations encounter similar food challenges, which manifest differently in various landscapes and contexts. Therefore, the world (not just the UK) needs to shift away from Eurocentrism, moving towards a universal but equally personalised development outlook. This review provides an outline of the major problem areas in the UK food system and presents potential solutions aimed at helping guide the government's decision-making process.

Food traceability 4.0 as part of the fourth industrial revolution: key enabling technologies

Food Traceability 4.0 (FT 4.0) is about tracing foods in the era of the fourth industrial revolution (Industry 4.0) with techniques and technologies reflecting this new revolution. Interest in food traceability has gained momentum in response to, among others events, the outbreak of the COVID-19 pandemic, reinforcing the need for digital food traceability that prevents food fraud and provides reliable information about food. This review will briefly summarize the most common conventional methods available to determine food authenticity before highlighting examples of emerging techniques that can be used to combat food fraud and improve food traceability. A particular focus will be on the concept of FT 4.0 and the significant role of digital solutions and other relevant Industry 4.0 innovations in enhancing food traceability. Based on this review, a possible new research topic, namely FT 4.0, is encouraged to take advantage of the rapid digitalization and technological advances occurring in the era of Industry 4.0. The main FT 4.0 enablers are blockchain, the Internet of things, artificial intelligence, and big data. Digital technologies in the age of Industry 4.0 have significant potential to improve the way food is traced, decrease food waste and reduce vulnerability to fraud opening new opportunities to achieve smarter food traceability. Although most of these emerging technologies are still under development, it is anticipated that future research will overcome current limitations making large-scale applications possible.

The Russia-Ukraine Conflict: Its Implications for the Global Food Supply Chains

Food is one of the most traded goods, and the conflict in Ukraine, one of the European breadbaskets, has triggered a significant additional disruption in the global food supply chains after the COVID-19 impact. The disruption to food output, supply chains, availability, and affordability could have a long-standing impact. As a result, the availability and supply of a wide range of food raw materials and finished food products are under threat, and global markets have seen recent increases in food prices. Furthermore, the Russian-Ukrainian conflict has adversely affected food supply chains, with significant effects on production, sourcing, manufacturing, processing, logistics, and significant shifts in demand between nations reliant on imports from Ukraine. This paper aims to analyze the impacts of the conflict between Russia and Ukraine on the effectiveness and responsiveness of the global food supply chains. A PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach, including grey literature, was deployed to investigate six key areas of the food supply chains that would be impacted most due to the ongoing war. Findings include solutions and strategies to mitigate supply chain impacts such as alternative food raw materials, suppliers and supply chain partners supported by technological innovations to ensure food safety and quality in warlike situations.

COIBar-RFLP Molecular Strategy Discriminates Species and Unveils Commercial Frauds in Fishery Products

The DNA analysis is the best approach to authenticate species in seafood products and to unveil frauds based on species substitution. In this study, a molecular strategy coupling Cytochrome Oxidase I (COI) DNA barcoding with the consolidated methodology of Restriction Fragment Length Polymorphisms (RFLPs), named COIBar-RFLP, was applied for searching pattern of restriction enzyme digestion, useful to discriminate seven different fish species (juveniles of Engraulis encrasicolus and Sardina pilchardus sold in Italy as “bianchetto” and Aphia minuta sold as “rossetto”; icefish Neosalanx tangkahkeii; European perch, Perca fluviatilis and the Nile Perch, Lates niloticus; striped catfish, Pangasianodon hypophthalmus). A total of 30 fresh and frozen samples were processed for DNA barcoding, analyzed against a barcode library of COI sequences retrieved from GenBank, and validated for COIBar–RFLP analysis. Cases of misdescription were detected: 3 samples labeled as “bianchetto” were substituted by N. tangkahkeii (2 samples) and A. minuta (1 sample); 3 samples labeled as “persico reale” (P. fluviatilis) were substituted by L. niloticus and P. hypophthalmus. All species were simultaneously discriminated through the restriction pattern obtained with MspI enzyme. The results highlighted that the COIBar-RFLP could be an effective tool to authenticate fish in seafood products by responding to the emerging interest in molecular identification technologies.

Assessing the Food Safety and Quality Assurance System during the COVID-19 Pandemic

This study aims to develop and test a methodological approach to assess the system of food quality and safety in the COVID-19 pandemic. To achieve the study objectives, a multi-country research project was implemented with 425 enterprises from Russia, Azerbaijan, Ukraine, and Belarus. The application of the developed methodological approach resulted in comparable assessments of the various criteria of the food safety and quality assurance system in supply chains. This makes it possible to implement continuous monitoring of the state of the food safety and quality assurance system in the enterprises. In addition, the study identified critical weaknesses in the safety system, including a very low level of assessment by enterprises of the impact of WHO advisory protocols. This greatly increases the risks associated with food safety in the COVID-19 pandemic. Urgent action is required to increase the confidence of food supply chain actors in WHO recommendations and national food safety and quality protocols. The conducted assessments showed that a significant proportion of enterprises did not implement a food safety system. One out of five of the respondents claimed to have implemented safety systems at an enterprise in accordance with the standards recognized by the Global Food Safety Initiative. Only 2% declared the introduction of HACCP at an enterprise, which is logical given the high mistrust of WHO recommendations. The proposed approach can be used in the real sector of the economy to monitor the food safety and quality assurance system in the supply chain at the regional, sectoral and national levels.

The cold chain and the COVID-19 pandemic: an unusual increase in histamine content in fish samples collected in Southern Italy during lockdown

Objectives

We analysed 900 samples of fresh (250) and processed (650) fish products collected in Sicily (Southern Italy) in 2020 during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic (hereafter: COVID-19).

Materials and methods

The samples were divided temporally based on five phases relating to the various restrictions imposed by the Italian government in this period. The validated method of ultra-high performance liquid chromatography (UHPLC) combined with a diode array detector (DAD) was then employed for the analysis.

Results

The samples collected during the Phase I lockdown period and after it had ended (Phase II) revealed significant increases in the mean histamine levels: 41.89±87.58 mg/kg ^-1 and 24.91±76.76 mg/kg ^-1, respectively. The 11 (1.3% of the total) fresh fish samples that were identified as being non-compliant with EC Reg. 2073/2005 were only found during these two periods. All the processed samples were always compliant. The histamine values decreased as the restrictions eased, achieving a mean value of 11.16±9.3 mgkg ^-1 (Phase III).

Conclusions

There was an increase in the incidence of fish samples that were non-compliant with EC Reg. 2073/2005 compared to previous surveillance data. These results provide a first report on the effect of lockdown measures on food safety and the cold chain. Our findings must cause food safety operators to intensify their controls over fresh fish products in such periods to safeguard consumer health. Further studies are required to evaluate whether the same trend would be observed with other food contaminants.

A Taxonomy of Food Supply Chain Problems from a Computational Intelligence Perspective

In the last few years, the Internet of Things, and other enabling technologies, have been progressively used for digitizing Food Supply Chains (FSC). These and other digitalization-enabling technologies are generating a massive amount of data with enormous potential to manage supply chains more efficiently and sustainably. Nevertheless, the intricate patterns and complexity embedded in large volumes of data present a challenge for systematic human expert analysis. In such a data-driven context, Computational Intelligence (CI) has achieved significant momentum to analyze, mine, and extract the underlying data information, or solve complex optimization problems, striking a balance between productive efficiency and sustainability of food supply systems. Although some recent studies have sorted the CI literature in this field, they are mainly oriented towards a single family of CI methods (a group of methods that share common characteristics) and review their application in specific FSC stages. As such, there is a gap in identifying and classifying FSC problems from a broader perspective, encompassing the various families of CI methods that can be applied in different stages (from production to retailing) and identifying the problems that arise in these stages from a CI perspective. This paper presents a new and comprehensive taxonomy of FSC problems (associated with agriculture, fish farming, and livestock) from a CI approach; that is, it defines FSC problems (from production to retail) and categorizes them based on how they can be modeled from a CI point of view. Furthermore, we review the CI approaches that are more commonly used in each stage of the FSC and in their corresponding categories of problems. We also introduce a set of guidelines to help FSC researchers and practitioners to decide on suitable families of methods when addressing any particular problems they might encounter. Finally, based on the proposed taxonomy, we identify and discuss challenges and research opportunities that the community should explore to enhance the contributions that CI can bring to the digitization of the FSC.

COVID-19 frauds: An exploratory study of victimization during a global crisis

RESEARCH SUMMARY

The COVID-19 pandemic threated public health and safety and led to a number of virus-related fraud schemes. We surveyed over 2,200 American adults to investigate their experiences with COVID-19-related frauds. Our goals were to better understand fraud targeting and victimization, as well as the impacts of fraud on victims. Over a quarter of our sample reported purchasing either a COVID-19-related product or a service, yet 42.5% reported feeling targeted for fraud. Being a target of COVID-19 frauds is significantly linked to one's routine activities, however it is one's level of self-control that more strongly predicts victimization. COVID-19 anxieties mediate the impact of self-control on purchasing.

POLICY IMPLICATIONS

Legal interventions and increased regulations surrounding advertising are a potential mechanism for protecting consumers, yet "soft" interventions that interrupt routine activities might be more useful and applicable. The use of white-lists and publicly available websites that allow e-commerce sites and sellers to be verified would help enable higher levels of self-guardianship. It is also important to provide continuous and clear messaging about what is being done to protect consumers.