Search

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 (calledDNAbarcodes) 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 analyzedwith 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 thatmetabarcoding 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. [ABSTRACT FROM AUTHOR]

Fruit juice and wine are important beverages that are consumed all over the world. Due to their constantly increasing demand and high value, fruit juice and wine are one of the most frequent targets of adulteration. Since adulterated foods are proven to have harmful effects on health, several approaches have been utilized for the detection of fruit juice and wine adulteration. Based on the requirement for sample destruction, analytical techniques to assess food authenticity can be classified into 2 main categories, i.e., destructive and non-destructive techniques. This paper provides an overview on the principle of adulteration detection, its application and performance, and the advantages and limitations of various analytical techniques. Destructive approaches, such as physicochemical methods, isotope analysis, elemental analysis, chromatographic techniques, and DNA-based techniques, are reviewed. Furthermore, non-destructive approaches, including spectroscopic-based techniques, nuclear magnetic resonance spectroscopic technique, electronic techniques, and imaging-based techniques, are discussed. [ABSTRACT FROM AUTHOR]

Machine learning has been extensively used for analyzing spectral data in food quality management. However, collecting high-quality spectral data from miniature spectrometers outside the laboratory is challenging due to various factors such as distortions, noise, high dimensionality, and collinearity. This paper presents an in-depth analysis of food datasets collected from miniature spectrometers to evaluate the data quality and characteristics, by focusing on a case study of olive oil quality check, where various machine learning models were applied to differentiate pure and adulterated olive oil. Furthermore, the impact of pre-processing techniques on data distortions was studied. It presents a comprehensive pipeline, including data pre-processing, dimension reduction, classification, and regression analysis, and deploys different algorithms for comparative classification and regression analysis. The model performances were assessed using 2 separate methods: tenfold cross-validation on an entire dataset with 10% random testing, and an entire test set collected in different environments (multi-session validation). The first validation approach reached classification rates of up to 96.73%, while the second achieved 83.32%. These results demonstrate that cost-effective miniature spectrometers augmented with a suitable machine learning pipeline could execute classification tasks on par with non-portable and more expensive spectrometers. Furthermore, the study highlights the requirement of specialized algorithms to handle different ambient conditions affecting data acquisition and to eliminate performance gaps, making miniature spectrometers suitable for in situ scenarios. This work extends previous research to enable consumers becoming the first line in the defense against food fraud. [ABSTRACT FROM AUTHOR]

This study develops a three-party evolutionary game model among upstream raw material producers, midstream food producers, and downstream distributors in the food supply chain, and investigates food fraud and fraud emulation among companies in the same group based on a food safety social co-governance framework. Moreover, the equilibrium points are divided into four scenarios according to the number of groups of companies committing fraud in the supply chain and whether companies in the same group emulate each other's fraudulent behavior. The stability conditions of these scenarios are also discussed and verified by numerical simulation in MATLAB. The results show that the behavioral strategy choices of different groups of food companies in the supply chain are closely related to the level of social co-governance involving the government, market, and consumers. Government regulation, supervision between companies, and consumer reporting can all change companies' behavioral strategies. Although the level of fraud emulation among companies in the same group does not change their behavioral strategy choice, it affects the time it takes for their behavioral strategy to evolve to a stable state. Moreover, the level of social co-governance directly affects companies' behavioral strategy choices at different emulation levels.

Pericarpium citri reticulatae (PCR) is the dried mature fruit peel of Citrus reticulata Blanco and its cultivated varieties in the Brassicaceae family. It can be used as both food and medicine, and has the effect of relieving cough and phlegm, and promoting digestion. The smell and medicinal properties of PCR are aged over the years; only varieties with aging value can be called “Chenpi”. That is to say, the storage year of PCR has a great influence on its quality. As the color and smell of PCR of different storage years are similar, some unscrupulous merchants often use PCRs of low years to pretend to be PCRs of high years, and make huge profits. Therefore, we did this study with the aim of establishing a rapid and nondestructive method to identify the counterfeiting of PCR storage year, so as to protect the legitimate rights and interests of consumers. In this study, a classification model of PCR was established by e-eye, flash GC e-nose, and Fourier transform near-infrared (FT-NIR) combined with machine learning algorithms, which can quickly and accurately distinguish PCRs of different storage years. DFA and PLS-DA models were established by flash GC e-nose to distinguish PCRs of different ages, and 8 odor components were identified, among which (+)-limonene and γ-terpinene were the key components to distinguish PCRs of different ages. In addition, the classification and calibration model of PCRs were established by the combination of FT-NIR and machine learning algorithms. The classification models included SVM, KNN, LSTM, and CNN-LSTM, while the calibration models included PLSR, LSTM, and CNN-LSTM. Among them, the CNN-LSTM model built by internal capsule had significantly better classification and calibration performance than the other models. The accuracy of the classification model was 98.21 %. The R2P of age, (+)-limonene and γ-terpinene was 0.9912, 0.9875 and 0.9891, respectively. These results showed that the combination of flash GC e-nose and FT-NIR combined with deep learning algorithm could quickly and accurately distinguish PCRs of different ages. It also provided an effective and reliable method to monitor the quality of PCR in the market.

Food fraud prevention and detection remains a challenging problem, despite recent developments in regulatory and auditing requirements. In 2012, the United States Pharmacopeial Convention created a database of food ingredient fraud. The objective of this research was to report on updates made to the database structure and to provide an updated analysis of food fraud records. The restructured database was relational and included four tables: ingredients, adulterants, adulteration records, and references. Four adulteration record types were created to capture the variety of information that can be found in public food fraud reports. Information was searched and extracted from the peer-reviewed scientific literature, media publications, regulatory reports, judicial records, trade association reports, and other public sources covering 1980-present. Over an almost seven-year data entry period, a total of 15,575 records were entered, sourced primarily from the peer-reviewed literature and media reports. The percentage of records that included at least one potentially hazardous adulterant ranged from 34% to 60%, depending on the record type. The ingredients with the highest number of incident and inference records included fluid cow’s milk, extra virgin olive oil, honey, beef, and chili powder. The ingredient groups with the highest number of incident and inference records included Dairy Ingredients, Seafood Products, Meat and Poultry Products, Herbs, Spices, and Seasonings, Milk and Cream, and Alcoholic Beverages. This database was created to serve as a standardized source of information about publicly documented occurrences of food fraud and other information relevant to fraud risk to support food fraud vulnerability assessments, mitigation plans, and food safety plans. These data support the contention that food fraud presents a public health risk that should continue to be addressed by food safety systems worldwide.

ABSTRACTThe presence of impurities in roasted ground coffee interferes with its quality. This Systematic Literature Review (SLR) aimed to identify and evaluate the different types of analytical techniques published in the last 20 years for the detection of adulterants in roasted coffee. The SLR was performed on StArt software in three stages: Planning, Executing, and Summarization. Eighty-three studies were selected for this review. The type of coffee most frequently studied was roasted ground coffee and Coffea arabica, while among the adulterants, Coffea canephora, coffee wastes, and corn. There was a trend toward applications of chromatographic, spectroscopic, and multi-adulterant techniques. Suitable techniques to detect/quantify adulterations in coffee and particularly as multi-detection approaches are crucial to improve coffee quality worldwide.

Snow Lotus Seed (SLS), esteemed for its nutritional and market value, faces challenges of authentication due to the absence of appropriate testing standards and methods. This results in frequent adulteration of SLS sourced from Gleditsia sinensis (G. sinensis) with other plant seeds endosperm. Traditional chloroplast DNA barcoding methods are inadequate for species identification due to the absence of chloroplasts in G. sinensis seeds endosperm. In this study, the homology of 11 ITS genes among 6 common Gleditsia species was analyzed. Universal primers suitable for these species were designed and screened. A DNA barcoding method for distinguishing SLS species was developed using Sanger sequencing technology, leveraging existing GenBank and Barcode of Life Data System (BOLD) databases. Optimized sample pretreatment facilitated effective DNA extraction from phytopolysaccharide-rich SLS. Through testing of commercial SLS products, the species origin has been successfully identified. Additionally, a novel instance of food fraud was uncovered, where the Caesalpinia spinosa endosperm was used to counterfeit SLS for the first time. The study established that the developed DNA barcoding method is effective for authenticating SLS species. It is of great significance for combating food fraud related to SLS, ensuring food safety, and promoting the healthy development of the SLS industry.

Abstract The issue of food fraud, safety and contaminants remains a topic of public concern, as it has been aligned to potential food scarcity. However, nanotechnology presents a promising opportunity for improving various industries, including food, agriculture, and health. This article aims to examine the potential of nanotechnology in enhancing food safety in Ghana, and its efficacy in addressing prevalent food safety challenges. Nano‐based approaches, such as nano‐packaging, nano‐sensing, nano‐additives, and other nano‐techniques, are discussed as effective methods for addressing major and emerging food safety issues in Ghana, such as food contaminants, antimicrobial resistance, food fraud and adulteration, and poor sanitary conditions. Additionally, the ethical and safety implications of these nano‐based approaches and particles are also deliberated.

Food authentication is a growing concern with rising complexities of the food supply network, with fish being an easy target of food fraud. In this regard, NIR spectroscopy has been used as an efficient tool for food authentication. This article reviews the latest research advances on NIR based fish authentication. The process from sampling/sample preparation to data analysis has been covered. Special attention was given to NIR spectra pre-processing and its unsupervised and supervised analysis. Sampling is an important aspect of traceability study and samples chosen ought to be a true representative of the population. NIR spectra acquired is often laden with overlapping bands, scattering and highly multicollinear. It needs adequate pre-processing to remove all undesirable features. The pre-processing technique can make or break a model and thus need a trial-and-error approach to find the best fit. As for spectral analysis and modelling, multicollinear nature of NIR spectra demands unsupervised analysis (PCA) to compact the features before application of supervised multivariate techniques such as LDA, PLS-DA, QDA etc. Machine learning approach of modelling has shown promising result in food authentication modelling and negates the need for unsupervised analysis before modelling.

Global demand for food has increased over the years owing to the growing world population size. However, the growing demand has created an avenue for fraudsters to invade the food market with sub-standard products. Therefore, this study sought to synthesise and comprehensively review the available literature on food fraud. Three themes were generated from the 118 papers retrieved from Scopus. The data were analysed using Ms Excel, VOS-viewer and Bibliometrix (Biblioshinny). The results revealed that food fraud had gained increasing concern over the years. Countries like the USA, the UK, Canada and China have been relevant in combating the rising incidence of food fraud. Food products such as organic food, sseafood, food supplements and olive oil are the primary target for perpetrators. The complexity of modern and conventional marketing channels has a significant correlation with food fraud. Lack and inadequate enforcement and supervision of local and international trade regulations have exacerbated the incidence of food fraud in marketing. Again, low levels of countermeasures and technological tools for instant authentication of agricultural products have also negatively increased the global implications of food fraud. From the analysis, it is recommended that countries collaborate to adopt holistic food safety standards and rigorous intervention approaches to detect, dissuade, and prevent fraud activities of individuals and companies.

In Brussels in February 1840, Piotr Kopczynski published a series of three newspaper articles that caused a commotion because they took seriously the rumors about bread that caused gastrointestinal problems. Journalists, city administrators, doctors, chemists, bakers, and two health boards reacted to the articles, which led to a controversy that lasted a couple of months. The paper analyzes this episode, paying meticulous attention to the views and doings of all actors. It emphasizes the need to know the chronology of food fears to learn when, how, and why people and institutions react. The Kopczynski affair allows to suggest the phases of food fears, that may go beyond time and place. Sources of the paper include reports, magazines, treatises, and especially newspapers, which are carefully read with consideration not only of what was written but also of how. [ABSTRACT FROM AUTHOR]

Laboratory testing methods to confirm the identity of meat products and eliminate food fraud regularly rely on PCR amplification of extracted DNA, with most published assays detecting mitochondrial sequences, providing sensitive presence/absence results. By targeting single-copy nuclear targets instead, relative quantification measurements are achievable, providing additional information on the proportions of meat species detected. In this Methods paper, new assays for horse, donkey, duck, kangaroo, camel, water buffalo and crocodile have been developed to expand the range of species that can be quantified, and a previously published reference assay targeting the myostatin gene has been modified to include marsupials and reptiles. The accuracy of this ratio measurement approach was demonstrated using dPCR with mixtures of meat DNA down to 0.1%. However, the limit of detection (LOD) of this approach is not just determined by the assay targets, but by the samples themselves, with food or feed ingredients and processing impacting the DNA yield and integrity. In routine testing settings, the myostatin assay can provide multiple quality control roles, including monitoring the yield and purity of extracted DNA, identifying the presence of additional meats not detected by the suite of species-specific assays and potentially estimating a sample-specific LOD based on measured copy numbers of the myostatin target. In addition to the myostatin positive control assay, a synthetic DNA reference material (RM) has been designed, containing PCR targets for beef, pork, sheep, chicken, goat, kangaroo, horse, water buffalo and myostatin, to be used as a positive template control. The availability of standardised measurement methods and associated RMs significantly improves the reliability, comparability and transparency of laboratory testing, leading to greater confidence in results. [ABSTRACT FROM AUTHOR]

Thermal desorption direct analysis in real‐time high‐resolution mass spectrometry (TD‐DART‐HRMS) approaches have gained popularity for fast screening of a variety of samples. With rapid volatilization of the sample at increasing temperatures outside the mass spectrometer, this technique can provide a direct readout of the sample content with no sample preparation. In this study, TD‐DART‐HRMS's utility for establishing spice authenticity was examined. To this aim, we directly analyzed authentic (typical) and adulterated (atypical) samples of ground black pepper and dried oregano in positive and negative ion modes. We analyzed a set of authentic ground black pepper samples (n = 14) originating from Brazil, Sri Lanka, Madagascar, Ecuador, Vietnam, Costa Rica, Indonesia, Cambodia, and adulterated samples (n = 25) consisting of mixtures of ground black pepper with this spice's nonfunctional by‐products (pinheads or spent) or with different exogenous materials (olive kernel, green lentils, black mustard seeds, red beans, gypsum plaster, garlic, papaya seeds, chili, green aniseed, or coriander seeds). TD‐DART‐HRMS facilitated the capture of informative fingerprinting of authentic dried oregano (n = 12) originating from Albania, Turkey, and Italy and those spiked (n = 12) with increasing percentages of olive leaves, sumac, strawberry tree leaves, myrtle, and rock rose. A predictive LASSO classifier was built, after merging by low‐level data fusion, the positive and negative datasets for ground black pepper. Fusing multimodal data allowed retrieval of more comprehensive information from both datasets. The resultant classifier achieved on the withheld test set accuracy, sensitivity, and specificity of 100%, 75%, and 90%, respectively. On the contrary, the sole TD‐(+)DART‐HRMS spectra of the oregano samples allowed construction of a LASSO classifier that predicted the adulteration of the oregano with excellent statistical indicators. This classifier achieved, on the withheld test set, 100% each for accuracy, sensitivity, and specificity. [ABSTRACT FROM AUTHOR]

Using China's milk scandal as a natural experiment, this paper explores whether the countries of origin and export destinations have the same responses to the original country's food scandal. Our difference‐in‐difference estimation shows that the outbreak of China's milk scandal had asymmetric impacts on China's total imports (increased by 23.4%) and exports (sharply dropped by 65.8%). The results further show that China's milk scandal contributed to import increases from European and Oceanian countries. Moreover, China's milk scandal worsened exports, mainly those going to neighbouring Asian regions but increased exports to Oceania. A product quality index is constructed to explain this finding. Intuitively, consumers' perceived quality of Chinese products declined, and they tended to consume products from other countries. The lower the product quality was with those in China, the lower the perceived quality and safety, thereby affecting demand. During the scandal, Chinese consumers tended to buy high‐quality dairy products from Europe and Oceania rather than the perceived unreliable dairy products produced by China or neighbouring countries. We conclude that product quality plays a key role in imports and exports when facing food scandals. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Recent food fraud incidents have highlighted the need to manage fraud risks in food supply chains. However, there is little research on how to manage these risks. Our study helps to alleviate this issue by examining food fraud risk management in the Asia–Pacific honey supply chain. We conducted interviews about existing food fraud risk management practices. We then used the Gioia method to generate a framework of these management practices, which expanded the "Six Ts" framework by adding a seventh dimension of Tolerance to this extant framework. Next, we empirically examined this novel Seven Ts framework. We found that managers treat many of these risk management practice dimensions as substitutes rather than complements. Our findings and managerial guidance are practically relevant for food companies. Lastly, we believe that, by implementing some of these suggestions theoretically generated and empirically validated by our framework, food supply chains may become more sustainable. [ABSTRACT FROM AUTHOR]

The rapid globalization of seafood trade over the past few decades has triggered heightened vulnerability for fraud within the seafood supply network. Consumer perceptions of these vulnerabilities are not limited to imported seafood products, as spillover effects are likely to influence purchasing behavior for domestically produced seafood as well. Using a between-sample survey experiment with 1,272 respondents in differing informational settings, we investigate whether consumer WTP for local seafood is impacted by information regarding seafood fraud. Consistent with previous studies, our results indicate that consumers broadly derive positive utility from consuming locally sourced relatively to imported seafood. Upon further disaggregation, however, we find that for one consumer segment, which we term the price-sensitive group, localness does not command a significant positive premium. Most importantly, we demonstrate that information regarding international seafood fraud largely did not alter local seafood demand. That said, we find some evidence of a negative spillover effect of the information treatment on US-labeled seafood in one of the consumer subgroups. [ABSTRACT FROM AUTHOR]

The price of Cinnamomum verum (Ceylon cinnamon) is around twice as high as that of the other cinnamon varieties commonly grouped under the name cassia cinnamon, making the former spice an attractive target for fraudsters. This work demonstrates that elemental profiles obtained by energy-dispersive X-ray fluorescence in combination with multivariate analyses can be used as a screening method to detect Ceylon cinnamon adulteration. Thirty-six elements were analysed in 52 commercially available cinnamon samples, 29 Ceylon, 8 cassia, and 15 for which no indication about variety was provided. Fifty-eight percent of the samples were either adulterated or did not meet international quality criteria. Four of the ground cinnamon samples labelled as Ceylon cinnamon were found to be pure cassia or a mixture with a high cassia content, and 26 samples were suspected of other types of adulteration including replacement of bark with other parts of the cinnamon tree. Headspace gas chromatography–mass spectrometry and ash determination by thermogravimetric analysis confirmed the conclusions reached by elemental analysis. Only one sample labelled as Ceylon cinnamon and that according to its volatile composition was cassia cinnamon was not flagged as suspicious by elemental analysis. [ABSTRACT FROM AUTHOR]

Extra virgin olive oil (EVOO) and avocado oil (AVO) are recognized for their unique sensory characteristics and bioactive compounds. Declared blends with other vegetable oils are legal, but undeclared mixing is a common type of fraud that can affect product quality and commercialization. In this sense, this study explored strategies to mitigate the influence of lighting in order to make digital image colorimetry (DIC) using a smartphone more robust and reliable for predicting the soybean oil content in EVOO and AVO blends. Calibration models were obtained by multiple linear regression using the images' RGB values. Corrections based on illuminance and white reference were evaluated to mitigate the lightness effect and improve the method's robustness and generalization capability. Lastly, the prediction of the built model from data obtained using a distinct smartphone was assessed. The results showed models with good predictive capacities, R2 > 0.9. Generally, models solely based on GB values showed better predictive performances. The illuminance corrections and blank subtraction improved the predictions of EVOO and AVO samples, respectively, for image acquisition from distinct smartphones and lighting conditions as evaluated by external validation. It was concluded that adequate data preprocessing enables DIC using a smartphone to be a reliable method for analyzing oil blends, minimizing the effects of variability in lighting and imaging conditions and making it a potential technique for oil quality assurance. [ABSTRACT FROM AUTHOR]

The adulteration of goat milk powder occurs frequently; cattle-derived and soybean-derived ingredients are common adulterants in goat milk powder. However, simultaneously and rapidly detecting cattle-derived and soybean-derived components is still a challenge. An efficient, high-throughput screening method for adulteration detection is needed. In this study, a rapid method was developed to detect the adulteration of common cattle-derived and soybean-derived components simultaneously in goat milk powder by combining the CRISPR/Cas12a system with recombinant polymerase amplification (RPA). A dual DNA extraction method was employed. Primers and crRNA for dual detection were designed and screened, and a series of condition optimizations were carried out in this experiment. The optimized assay rapidly detected cattle-derived and soybean-derived components in 40 min. The detection limits of both cattle-derived and soybean-derived components were 1% (w/w) for the mixed adulteration models. The established method was applied to a blind survey of 55 commercially available goat milk powder products. The results revealed that 36.36% of the samples contained cattle-derived or soybean-derived ingredients, which revealed the noticeable adulteration situation in the goat milk powder market. This study realized a fast flow of dual extraction, dual amplification, and dual detection of cattle-derived and soybean-derived components in goat milk powder for the first time. The method developed can be used for high-throughput and high-efficiency on-site primary screening of goat milk powder adulterants, and provides a technical reference for combating food adulteration.

This paper discusses the development of rapid, reliable, and accurate polymerase chain reaction (PCR) assays for detecting opium poppy (Papaver somniferum L.) in food. Endpoint, quantitative, and digital PCRs were compared based on the amplification of a newly developed DNA marker targeting the NADPH-dependent codeinone reductase (COR) gene. Designed assays were shown to be highly specific and sensitive in discriminating opium poppy from other plant species, even in heat-treated and food samples. Digital PCR was the most sensitive, with a detection limit of up to 5 copies, i.e., approximately 14 pg of target DNA per reaction. Quantitative and digital PCR further allowed the quantification of opium poppy in up to 1.5 ng and 42 pg (15 copies) of target DNA in a sample, respectively. In addition, two duplex PCRs have been developed for the simultaneous detection of opium poppy DNA and representatives of (i) the Papaveraceae family or (ii) the Plantae kingdom. Finally, all designed assays were successfully applied for analysis of 15 commercial foodstuffs; two were suspected of being adulterated. The study results have an important impact on addressing food fraud and ensuring the safety and authenticity of food products. Beyond food adulteration, the study may also have significant implications for forensics and law enforcement.

World health is increasingly threatened by the growing number of spice-related food hazards. Further development of reliable methods for rapid, non-targeted identification of counterfeit ingredients within the supply chain is needed. ENEA has developed a portable, user-friendly photoacoustic laser system for food fraud detection, based on a quantum cascade laser and multivariate calibration. Following a study on the authenticity of saffron, the instrument was challenged with a more elusive adulterant, olive leaves in oregano. The results show that the reported method of laser sensing and chemometric analysis was able to detect adulterants at mass ratios of at least 20% in less than five minutes. [ABSTRACT FROM AUTHOR]

Ten years ago, in 2012, the Global Food Safety Initiative (GFSI) led the food industry when it created a standardized way to assess and manage food fraud incidents. GFSI adopted an interdisciplinary approach to not only detect food fraud but to understand and reduce the root causes. A series of crucial milestones guided the GFSI work, starting with creating their GFSI Food Fraud Think Tank through the Technical Working Group benchmark development, the adoption by the GSFI Board of Directors, and then development, implementation, and management by the food industry. This research presents the key GFSI food fraud prevention strategy development milestones from the historical records and a member of the original GFSI Food Fraud Think Tank. GFSI achieved momentum by establishing a food industry-wide definition and scope of the problem. Further, focusing on all types of fraud and for all products – not just incoming goods and adulterant-substances – created a holistic and all-encompassing approach. The new topic of food fraud prevention is moving through the 'hype cycle' and is now in the 'Scope of Enlightenment' (e.g., processes and systems are simplified and optimized) and moving to the 'Plateau of Productivity' (e.g., standard operating procedures are adopted). GFSI, itself is maturing and evolving through the 'hype cycle.' The next ten years will include a more rigorous and thorough adoption of management systems with a continuous improvement process. The foundation is very theoretically and practically sound. • In 2022, the GSFI food fraud prevention activities were ten years old. • GFSI followed a methodical process to create food fraud prevention requirements. • Momentum was achieved by taking a holistic approach that addressed the root cause. • GFSI has helped create a food industry-wide approach to the problem. • The development continues along the hype cycle as true management systems are adopted. [ABSTRACT FROM AUTHOR]

Accurate methods for meat speciation and quantification are essential for ensuring the supply of safe and wholesome meat and composite products with animal origins to negate the potential associated hazards, aid classification of consignments at the import control system, and thwart food fraud committed for financial gain. To better enhance meat safety control and combat food fraud, this study developed two duplex real-time polymerase chain reaction (real-time PCR) systems specifically designed for chicken, pork, sheep, and beef, using single-copy, chromosomally encoded, species-specific gene sequences to accurately measure the content of each meat type in meat products. DNA extracted from the raw and boiled reference materials prepared in varying proportions (ranging from 1% to 75%) were used in the development of the duplex assay to derive calibration factors to determine the meat content in different meat products. The method was further validated using proficiency test samples and market monitoring samples. Our findings showed that this method exhibits high specificity and sensitivity, with a significant accuracy range of 0.14% to 24.07% in quantifying the four meat types in both raw and processed meat products. Validation results further confirmed the effectiveness of our method in accurately quantifying meat content. Thus, we have demonstrated the duplex qPCR assays as promising approaches for implementation in routine analysis to strengthen meat safety control systems and combat meat fraud, thereby safeguarding consumer health and trust in the meat industry. [ABSTRACT FROM AUTHOR]

Nutmeg is a popular spice often used in ground form, which makes it highly susceptible to food fraud. Therefore, the aim of the present study was to detect adulteration of ground nutmeg with nutmeg shell via Fourier transform near-infrared (FT-NIR) spectroscopy. For this purpose, 36 authentic nutmeg samples and 10 nutmeg shell samples were analyzed pure and in mixtures with up to 50% shell content. The spectra plot as well as a principal component analysis showed a clear separation trend as a function of shell content. A support vector machine regression used for shell content prediction achieved an R2 of 0.944 in the range of 0–10%. The limit of detection of the prediction model was estimated to be 1.5% nutmeg shell. Based on random sub-sampling, the likelihood was found to be 2% that a pure nutmeg sample is predicted with a nutmeg shell content of >1%. The results confirm the suitability of FT-NIR spectroscopy for rapid detection and quantitation of the shell content in ground nutmeg. [ABSTRACT FROM AUTHOR]

Foreign amylase addition to honey in an effort to disguise diastase activity has become a widespread form of food fraud. However, since there is no report on the investigation in Japan, we investigated foreign amylases in 67 commercial honeys in Japan. First, the α-glucosidase and diastase activities of honeys were measured, which revealed that only α-glucosidase activity was significantly low in several samples. As both enzymes are secreted from honeybee glands, it is unlikely that only one enzyme was inactivated during processing. Therefore, we suspected the presence of foreign amylase. α-Amylase in honey were assigned using protein analysis software based on LC-QTOF-MS. As a result, α-amylases from Aspergillus and Geobacillus were detected in 13 and 6 out of 67 honeys, respectively. To detect foreign amylases easily, we developed a cost-effective method using native PAGE. Conventional native PAGE failed to separate the α-amylase derived from honeybee and Geobacillus. However, when native PAGE was performed using a gel containing 1 % maltodextrin, the α-amylase from honeybee did not migrated in the gel and the α-amylase could be separated from the other two α-amylases. The results from this method were consistent with those of LC-QTOF-MS method, suggesting that the novel native PAGE method can be used to detect foreign amylases. [ABSTRACT FROM AUTHOR]

To prevent food fraud, products can be monitored by various chemical-analytical techniques. In this study, we present a CRISPR-Cpf1 DETECTR-based assay for the differentiation of plant ingredients in sweet confectionary like fine and bulk-cocoa, or bitter and sweet almonds. To enable rapid in-field analysis, the trans-cleavage activity of the Cpf1 enzyme was used to develop a DETECTR (DNA endonuclease-targeted CRISPR trans reporter) assay for simple, highly specific fluorometric detection of single nucleotide polymorphisms (SNPs). The endonuclease Cpf1 requires the protospacer adjacent motif (PAM) 5'-TTTV-3' for activation, but the recognition sequence is freely programmable. The SNPs were selected to alter the Cpf1 specific PAM sequence. As a result, sequences that do not carry the canonical PAM sequence are not detected and thus not cut. The optimized system was used for both raw material and processed products such as cocoa masses or marzipan with a limit of detection of 3 ng template DNA. In addition, we were able to implement the system in the context of an LFA (lateral flow assay) to serve as a basis for the development of rapid test systems. [ABSTRACT FROM AUTHOR]

The broader implications of food fraud are global and can affect consumers across the religious line. In Islamic belief, meat is considered the most strictly regulated food product. The awareness of seeking authentic halal meat is the highest among Muslim consumers because it is an essential part of their faith. It is devastating for Muslims that they might have consumed meat considered halal, which actually was not. For example, a meat-fraud scandal was uncovered in December 2020 by the local newspaper in Malaysia, which also involved a few other countries. Fraudulent advertising by food companies clearly spells doom for the Muslim community as they would want to know who the legitimate dealers of halal meat products are. The discussion on halal meat unavoidably boils down to animal rights and the way animals are slaughtered to comply with the requirements of halal meat. Muslims argue that the practices of traditional Islamic slaughter are humane. However, many animal rights campaigners argue that religious slaughter causes animals unnecessary suffering and should adopt stunning before slaughter. This article uncovers various types of fraud relating to halal meat globally with specific reference to European and Malaysian laws to analyse the legal rights available to consumers and their protection. The analysis in this article reveals that authorities should further strengthen their role in enforcing consumer laws and continuously seek ways to educate consumers about halal food fraud. [ABSTRACT FROM AUTHOR]

Economic profit-driven food adulteration has become widespread in the dairy industry. One of the most common forms of dairy adulteration is the substitution of low-priced milk for high-priced milk. This has prompted regulatory authorities to focus on various means of authenticity testing. So far, many methods have been developed. Since milk adulteration has been upgraded, which has forced the testing methods to meet the needs of detection, which include DNA-based PCR methods. PCR and PCR-derived methods exhibit multiple advantages for authenticity testing, such as high stability, fast speed, and high efficiency, which meet the needs of modern testing. Therefore, it is important to develop rapid, reliable, and inexpensive PCR-based assays for dairy adulteration identification. In order to provide perspectives for improving adulteration identification methods, this review first summarizes the DNA extraction methods, then compares the advantages and disadvantages of various PCR authenticity testing methods, and finally proposes the directions for improving dairy product adulteration identification methods. [ABSTRACT FROM AUTHOR]

Mozzarella di Bufala Campana (MdBC) cheese is a Protected Designation of Origin (PDO) product that is important for the economy and cultural heritage of the Campania region. Food fraud can undermine consumers' trust in this dairy product and harm the livelihood of local producers. The current methods for detecting adulteration in MdBC cheese due to the use of buffalo material from foreign countries could exhibit limitations associated with the required use of expensive equipment, time-consuming procedures, and specialized personnel. To address these limits here, we propose a rapid, reliable, and cost-effective genotyping method that can detect foreign buffalo milk in a counterpart from the PDO area and in MdBC cheese, ensuring the quality and authenticity of the latter dairy product. This method is based on dedicated allele-specific and single-tube heminested polymerase chain reaction procedures. By using allele-specific primers that are designed to detect the nucleotide g.472G>C mutation of the CSN1S1Bbt allele, we distinguished an amplicon of 330 bp in the amplification product of DNA when extracted from milk and cheese, which is specific to the material originating from foreign countries. By spiking foreign milk samples with known amounts of the counterpart from the PDO area, the sensitivity of this assay was determined to be 0.01% v/v foreign to PDO milk. Based on a rough estimate of its simplicity, reliability, and cost, this method could be a valuable tool for identifying adulterated buffalo PDO dairy products. [ABSTRACT FROM AUTHOR]

The molecular approach of DNA barcoding for the characterization and traceability of food products has come into common use in many European countries. However, it is important to address and solve technical and scientific issues such as the efficiency of the barcode sequences and DNA extraction methods to be able to analyze all the products that the food sector offers. The goal of this study is to collect the most defrauded and common food products and identify better workflows for species identification. A total of 212 specimens were collected in collaboration with 38 companies belonging to 5 different fields: seafood, botanicals, agrifood, spices, and probiotics. For all the typologies of specimens, the most suitable workflow was defined, and three species-specific primer pairs for fish were also designed. Results showed that 21.2% of the analyzed products were defrauded. A total of 88.2% of specimens were correctly identified by DNA barcoding analysis. Botanicals (28.8%) have the highest number of non-conformances, followed by spices (28.5%), agrifood (23.5%), seafood (11.4%), and probiotics (7.7%). DNA barcoding and mini-barcoding are confirmed as fast and reliable methods for ensuring quality and safety in the food field. [ABSTRACT FROM AUTHOR]

In recent years, due to the globalization of food trade and certified agro-food products, the authenticity and traceability of food have received increasing attention. As a result, opportunities for fraudulent practices arise, highlighting the need to protect consumers from economic and health damages. In this regard, specific analytical techniques have been optimized and implemented to support the integrity of the food chain, such as those targeting different isotopes and their ratios. This review article explores the scientific progress of the last decade in the study of the isotopic identity card of food of animal origin, provides the reader with an overview of its application, and focuses on whether the combination of isotopes with other markers increases confidence and robustness in food authenticity testing. To this purpose, a total of 135 studies analyzing fish and seafood, meat, eggs, milk, and dairy products, and aiming to examine the relation between isotopic ratios and the geographical provenance, feeding regime, production method, and seasonality were reviewed. Current trends and major research achievements in the field were discussed and commented on in detail, pointing out advantages and drawbacks typically associated with this analytical approach and arguing future improvements and changes that need to be made to recognize it as a standard and validated method for fraud mitigation and safety control in the sector of food of animal origin. [ABSTRACT FROM AUTHOR]

The use of different mixtures of products and the addition of cheap raw materials such as chicory, corn and soy alter the sensory and functional characteristics of the beverage based on roasted and ground coffee beans, defects that call into question the quality of the beans imported by the producing countries in Algeria and threaten the environment through the quantities of coffee grounds produced. The objective of our study is the detection of fraud on coffee beans, the differentiation between pure coffee and coffee with sugars, the determination of the antioxidant power of some coffee powders selected in the Algerian trade, and finally to select the best consumable coffee. The physico-chemical analysis of the coffee extracts, gave an acid pH, which varies between 5.71 and 6.19, a moisture content not exceeding 5%, an ash content varying between 4.38 and 5.52%, polyphenols between 11.54 and 34.32 (mg GAE/g MS), an antiradical activity between 26.33 and 81.77% and total sugars varying between 1.156 and 4.38%. At the end of this study, the choice of consumption was made for a type of coffee with superior physico-chemical characteristics and the use of sugar content for their formula below the permitted limit, which results in a low level of regenerated acrylamide with an unpolluted environment. [ABSTRACT FROM AUTHOR]

In Poland, food supplements have been popular among consumers for many years. Their sale brings producers huge profits. The interest in these products, especially in vitamin and mineral preparations and in immunity-supporting products increased dramatically due to the COVID-19 pandemic. Self-medication with untested dietary supplements may be health hazardous. Since in Poland and in other countries the procedures of quality control of food supplements are imperfect, this situation raises serious concerns about the risks of their unrestricted use and food fraud. The article briefly presents important problems in the safety of food supplements from the point of view of experts involved in their evaluation.

Oregano (Origanum vulgare and O. onites) is one of the most frequently counterfeited herbs in the world and is diluted with the leaves of a wide variety of plants. In addition to olive leaves, marjoram (O. majorana) is often used for this purpose in order to achieve a higher profit. However, apart from arbutin, no marker metabolites are known to reliably detect marjoram admixtures in oregano batches at low concentrations. In addition, arbutin is relatively widespread in the plant kingdom, which is why it is of great relevance to look for further marker metabolites in order to secure the analysis accordingly. Therefore, the aim of the present study was to use a metabolomics-based approach to identify additional marker metabolites with the aid of an ion mobility mass spectrometry instrument. The focus of the analysis was on the detection of non-polar metabolites, as this study was preceded by nuclear magnetic resonance spectroscopic investigations of the same samples based mainly on the detection of polar analytes. Using the MS-based approach, numerous marjoram specific features could be detected in admixtures of marjoram >10% in oregano. However, only one feature was detectable in admixtures of >5% marjoram. This feature was identified as blumeatin, which belongs to the class of flavonoid compounds. Initially, blumeatin was identified based on MS/MS spectra and collision cross section values using a database search. In addition, the identification of blumeatin was confirmed by a reference standard. Moreover, dried leaves of olive, myrtle, thyme, sage and peppermint, which are also known to be used to adulterate oregano, were measured. Blumeatin could not be detected in these plants, so this substance can be considered as an excellent marker compound for the detection of marjoram admixtures. [ABSTRACT FROM AUTHOR]

Because of the serious adulteration of goat milk, the rapid on-site detection of goat milk powder adulteration is needed. In this study, the CRISPR/Cas12a detection system combined with recombinase polymerase amplification (RPA) was employed to qualitatively detect the adulteration of goat milk powder with cattle-derived components. Specific primers and crRNA were designed and screened. After the optimization of RPA and the Cas system, the RPA-CRISPR/Cas12a detection method was established. The detection can complete the rapid identification of cattle-derived components in 45 min, without the assistant of large equipment. The absolute detectability of the RPA-CRISPR/Cas12a assay could reach 10−2 ng/μL for cattle genomic DNA, and 1% (w/w) for cattle milk powder, which is suitable to meet the testing requirements for on-site detection. In total, 55 commercial goat milk powder products were collected for blind testing. The results showed that 27.3% of the samples were adulterated with cattle ingredients, revealing a serious adulteration situation in goat milk powder market. The RPA-CRISPR/Cas12a assay established in this research exhibited its potential for practical use of on-site detection to detect cow milk powder in goat milk powder and can provide reliable technical reference for combating food fraud of adulteration of goat milk products. [ABSTRACT FROM AUTHOR]