News

The US FDA has issued guidance for Small and Medium Enterprises to comply with the upcoming (1 January 2024) Standard of Identity rules for yoghurt.  Such guidance is a reminder to any laboratory testing compliance with a food’s “legal name” that the legal specification will vary depending on the country of sale.

The new US rules cover pH, minimum counts of active cultures or vitamins (if claimed). and minimum requirements for milk fat and milk solids.  There are specific labelling requirements for lower fat yoghurts.

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

The article is open access.

This article (open access) reports the development of a classification model for the country of origin of black tea.  The authors collected both FTIR and NIR spectral data from a reference library of 360 black tea samples sourced from prominent tea cultivation regions across the world, including China, Darjeeling (India), Assam (India), Sri Lanka, Kenya, Ethiopia, Burundi, and Malawi.  They compared different machine learning models to build a predictive classification system.  They found that the best results were obtained when  SNV and ¹DER spectral pre-processing methods were also used. They concluded that all of the machine learning models gave superior prediction performance compared to traditional PLS-DA modelling, with the best giving a classification accuracy of 100 %. They also identified and validated a set of significant wavenumber regions in FTIR and NIR spectra for discriminating black tea GI regions. The authors conclude that the developed workflow is a novel, rapid, easy to operate, cost-efficient, and non-destructive method, and  can be regarded as a “green analytical technique” since no solvents and reagents are used during the process. It has the potential to form the basis of an on-site, real-time solution for Geographic Origin inspections throughout the entire supply chain, particularly within developing countries where tea cultivation is prominent. However, further work is required to enhance the size and diversity of the database and validate the model’s transferability between devices.

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This article (open access) provides an overview of the Nigerian meat industry, explores specific cases of meat fraud, and discusses authentication methods used in neighbouring African countries.  It offers insights for Nigerian researchers and the government.  The meat industry in Nigeria encompasses a range of sources, with beef taking precedence and also including chicken, chevon, mutton and pork.  Reported frauds are frequent, particularly the deliberate sale of meat unfit for consumption.  Frequent frauds also include the undeclared tenderising of processed meat using paracetamol (a food safety hazard) or soda drinks. The authors conclude that Nigerian meat products are highly vulnerable to fraudulent practices, stemming in part from consumer preferences for cost-effective items and the limited coordination within the meat sector due to the absence of robust enforcement in areas such as product metrology, sales, and packaging.  They recommend that the Nigerian regulatory authorities adopt best practice from other countries, including neighbouring African countries.

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This conference paper (purchase required) describes the development of a successful non-destructive test to discriminate 20 varieties of Indian wheat as either hard or soft wheat.  The authors used near-infrared (NIR) hyperspectral imaging (spectral range 900–1700 nm) on a reference set of authentic samples. Data images were taken from both sides of the seed (ventral and dorsal side). The dataset included images of 20,160 seeds. The authors compared results from 5 different machine learning models. The models were trained using the mean spectral values extracted from the hyperspectral images. They also tried 5 different pre-processing techniques.  They evaluated each model’s performance for both raw and preprocessed data.  They found that the optimum model achieved a classification accuracy rate of 95.01% for amalgamated data (encompassing both ventral and dorsal side data), 95.05% for exclusively ventral side data, and 95.37% for exclusively dorsal side data.

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This review (open access) highlights serious detrimental food fraud cases originating in Asian countries, including sibutramine in dietary supplements, plasticizer contamination, gutter oil, and the adulteration of milk. The analysis encompasses various facets, such as incident occurrences, adverse health effects, regulatory frameworks, and mitigation strategies.  It is intended to be of particular use to readers in Asia who do not have access to subscription-based fraud databases or insight trends.  It concludes that establishing a global real time alert system is critical for safeguarding the food industry from fraud and adulteration, and reducing public health and safety risks. To foster long-term prevention, it would be beneficial for underlying economic issues to be addressed and resolved at the national and/or international level.

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A direct link to the newsletter is here.

The modern food industry is a rapidly evolving sector with complex supply chains that utilises a wide variety of analytical tools to support food integrity and authenticity.

Next Generation Sequencing (NGS)-based approaches represent an emerging analytical technology that is growing within the food sector, providing  the potential to not only screen and test input materials, but also the production process and end products. 

Photo by Braňo on Unsplash

This questionnaire is part of a UK Department for Environment, Food and Rural Affairs (Defra) funded project tasked with reviewing the application of NGS technology to food authenticity testing and supporting harmonisation and the development of standards for NGS approaches applicable to the verification of food authenticity. The questionnaire is targeted at individuals involved in the food and associated diagnostics sectors, including technology developers, suppliers and official controls.

Your participation in this questionnaire will directly help inform the direction of the project and contribute to guidance within the sector.

Please do not provide any information that could be used to identify you. Thank you for participating in our questionnaire which should only take around 15 minutes to complete. Your feedback is important.

Access questionnaire.

UK National Measurement Laboratory at LGC

Thanks again to FAN member Bruno Sechet for formatting the JRC monthly report of food fraud media stories as an infographic.  You can register to receive JRC's report directly by e-mail here.  It is usually published in the 2nd week of the following month.

Aptamers are short, single stranded sections of DNA or RNA that can selectively bind to a protein or similar biochemical molecule.  They are, theoretically, an ideal basis for species tests; unlike PCR, they could underpin a test for highly processed products that was also faster, cheaper, and more suited for point-of-use kits.

To date, there is no published porcine-specific aptamer that is specifically bound to a heat-stable protein. This study (purchase required) has taken some important steps along the way, but also highlights the challenges.  The authors screened, characterised and validated aptamers bound to any pork protein through the SELEX process, combined with Next Generation Sequencing (NGS) and Liquid Chromatography Mass Spectrometry (LC-MS) analysis. The putative porcine-specific aptamers were selected after fourteen rounds of selection using centrifugal-ultrafiltration separation technique against five negative controls. The best candidate had a binding affinity with a dissociation constant of 27.61 ± 1.92 nM.  However, the selected porcine-bound aptamers were not specific and could also bind to multiple proteins from negative samples. LC-MS analysis showed that the aptamers bound to troponin and tropomyosin subunits, and these proteins have potential as target markers for future authentication studies. The authors conclude that future research could develop aptamers with higher specificity towards porcine protein which could be used as a practical tool for food authentication in real meat-based food samples.

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Basmati rice is a defined term in the UK with a strict technical specification and legally-established trading goodwill. In 2017 an EU trademark application was made to use “Basmati” on a rice variety that does not meet this specification.  The application was supported by the EU Intellectual Property Office.  The application was opposed by a UK rice importer acting as a proxy for the Indian government export agency (because the Indian government has no direct recourse to the EU courts).  The case is still ongoing and is now complicated by the fact that – since EU exit – it could also be argued that the UK proxy has no recourse to the EU courts.

The EU Advocate General has just ruled that the objectors have a valid case and that they still have recourse to the EU courts.  The case can proceed to the Courts of Justice.

Read the analysis by the legal team acting for the Indian government’s representative here. 

This review article assesses meat authentication techniques based on DNA, protein, and metabolite fingerprints of animal meat species for their applicability to cultured meat.  Theu authors discuss areas in the cultured meat industry that are vulnerable to food fraud. They consider that none of the traditional techniques adequately addresses all of the authentication questions likely to be asked.

The authors recommend the identification of markers (both physical and biochemical) to differentiate conventional meat from cultured meat in order to ensure overall product traceability.  Technique-based categorization of cultured meat products could ease the identification of appropriate authentication methods.

The authors conclude that novel technologies for novel foods, such as cultured meat, need a different approach in terms of authentication methods. The increasing production efficiencies of cultured meat companies should be coupled with increasing regulatory support to protect them from the threat of sham products undermining their market. Cultured meat authentication is essential and must be considered because, in the future, these gaps may be bridged by technological advancements, increasing the similarities between conventional and cultured meats

A standards-based approach for cultured meat authentication would create a safer future for all stakeholders and help prevent food fraud. This could also lead to the increased acceptability of cultured meat and meat products by validating claims and labels.

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The United Kingdom Food Security Report (UKFSR) sets out an analysis of statistical data relating to food security by examining past, current, and predicted relevant trends to present the best available understanding of food security.

The UK Department for Environment Food & Rural Affairs (Defra) published the first UKFSR on 16 December 2021 and is now planning the production of the next UKFSR, which will be published in the second half of 2024.

Defra is currently seeking users' views on the content of the 2024 UKFSR.

As with the 2021 report, the next report will cover 5 themes:

• Theme 1: Global availability
• Theme 2: UK food supply sources
• Theme 3: Supply chain resilience
• Theme 4: Food security at household level
• Theme 5: Food safety and consumer confidence.

Please help Defra to improve the next report by answering a few short questions on these themes, and the report as a whole, by 15 December 2023: Access Defra questionnaire.

Thank you!

This review article covers the use of low-cost point-of-use molecular biology methods for meat speciation testing;  methods such as loop-mediated isothermal amplification (LAMP) or gold nanoparticles linked with oligonucleotides. Such methods are currently more widely used in clinical applications than in authenticity testing but there have been recent publications showing use for meat speciation. The authors conclude that the introduction of these new DNA technologies has facilitated the ease and accuracy of fraud detection. These closed-tube methods (“molecular probes”) are robust and highly sensitive for the specific amplification of target DNA and are also rapid, low-cost and available on site.

This review provides an overview of the molecular methods developed that can be applied for investigating ground meat adulteration and focuses on the advantages of the rapid closed tube methods that can yield colour results interpreted with the naked eye. The application of such time- and cost-effective molecular tools in the food market is proposed to provide a first-level filter for meat adulterated products, serving as a complementary tool to the more in-depth -omics approach.

This paper explores the potential of blockchain technology in promoting sustainable food production and consumption (SFPC) from a consumer perspective in India.  Consumer confidence has been shaken by food safety concerns alongside unexpected events like COVID-19 and geopolitical conflicts. In recent times, consumer focus has shifted a lot towards food safety and security. The study adopted exploratory factor analysis (EFA) to identify the factors strengthening consumer trust through blockchain technology. The EFA helped classify the items into five factors, i.e., reliability, sustainability, impact on health, trust, and switching intentions. The results reveal that these factors are the most significant reasons consumers are willing to accept a blockchain-enabled food system over a traditional system. The study findings will benefit organisations willing to introduce blockchain within their operations to improve the consumer base. It will also prove to be helpful for researchers and academicians to understand consumer perspectives towards blockchain for SFPC.

This feasibility study (purchase required) showed that lipid profiling can discriminate lamb breed and also (unlike stable isotope or elemental profile) the cut of meat.  The authors used Ninxia Tan sheep, a premium breed in China, as proof of concept.  They measured a large panel of lipids in reference populations of authentic and inauthentic breeds and cuts.  They then assessed different Machine Learning protocols for feature selection. 

1230 molecules across 29 lipid classes were identified in longissimus dorsi and knuckle meat of both Tan sheep and Bahan crossbreed sheep. Applying multivariate statistical methods, 12 lipid molecules were identified as potential markers for breed and and 7 as potential markers for the cut of meat. Stepwise linear discriminant analysis was applied to select 3 and 4 lipid molecules, respectively, for discriminating lamb breed and cut, achieving correct rates of discrimination of 100 % and 95 %.

They conclude that back-propagation neural network was superior to other machine learning approaches for this application. Integrating lipidomics with back-propagation neural network approach can provide an effective strategy to trace and certify lamb products, ensuring their quality and protecting consumer rights.

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In this article the authors analysed the last decade of RASFF alerts relating to adulterated and unauthorised supplements and discussed the potential health impacts.  They conclude that health concerns rise in parallel with the rise in the popularity and market availability of these products.  

The most frequent pharmaceuticals for the adulteration of food supplements were phosphodiesterase-5 inhibitors (235 records); anorexics and laxatives (76), including sibutramine and its active metabolite N-didesmethyl sibutramine, phenolphthalein and 2,4-dinitrophenol.  There were also stimulants, among which 1,3-dimethylamine (97), and synephrine (53) were the most numerous.  Also included were nootropic drugs (24); anabolics and prohormones (16); and cannabinoid cannabidiol (14) (pending authorization as a novel food ingredient).

Over 65% of these notifications were classified as serious risks, and over 80% of these were alert or border rejection notifications, mainly generated as a result of official control on the market.

The authors recommend that a harmonized nutrivigilance system should be considered as a tool to detect and scrutinize the adverse health effects of food supplements, along with measures to improve their safety, quality, and testing.

Photo by Myriam Zilles on Unsplash

The last decade has witnessed significant advances in analytical technologies with the capabilities to support food integrity and authenticity testing within the rapidly evolving food industry. Devices that allow diagnostic tests to be performed at or near the point of need, often termed Point-of-contact (POC), represent a growing area within the food sector with the potential to provide real-time monitoring of input materials and production process. POC devices can range from handheld spectroscopic devices such as Raman and FT-IR instruments to desktop portable systems inclusive of compact mass spectrometry, NMR and next generation sequencing (NGS) systems.

UK National Measurement Laboratory at LGC

In this study (open access) the authors developed a chemometric model to discriminate adulterated maple syrup.  Spectral measurement was by Attenuated Total Reflectance FTIR with data then processed using Principle Component Analysis.  The authors built their reference library from 69 authentic samples obtained directly from producers and further verified by an expert sensory panel.  They prepared in-house adulterated samples by mixing in sugars from three of 15 cheaper sources at proportions from 5% to 25% giving a total library of 667 adulterated and non-adulterated reference samples. Spectra from these samples were used to build six libraries and three models. They developed a method to perform a qualitative library search using a similarity search, based on the first derivative correlation search algorithm.

 Of the four Canadian classes of Grade A maple syrup, the model could discriminate with high confidence adulteration in “golden” and “amber” syrups but was less specific for  “dark” or “very dark” classes.

 Photo by Nadine Primeau on Unsplash

This Commission overview report describes how Competent Authorities in Member States deliver their obligations to combat food fraud under Article 9(2) of the Official Control Regulations (2017/625).

It outlines how Member States fight fraud along the agri-food chain. Fraud in the agri-food chain affects industry and consumers economically, undermines consumer trust and may lead to serious health issues. The EU has recognised the importance of tackling fraudulent and deceptive practices in the agri-food chain and since 2019 Member States are required to carry out risk-based controls to detect fraudulent and deceptive practices. The Commission carried out a project between 2020 and 2022 to collect information on the new arrangements put in place by Member States to fight fraud in the agri-food chain. Based on this project, the Commission has published an overview report which focuses on eight Member States and how their competent authorities developed control arrangements and strategies to combat fraudulent practices. It presents the challenges, opportunities, and several good practice examples in relation to fraud related controls in the Member States.

This report follows a Technical Guidance Document published in March 2023, to support Member States in their efforts to combat fraud within the agri-food supply chain. This guidance document clearly outlines how to uniformly interpret and apply the respective EU laws in the context of fighting food fraud. It was highlighted in a previous FAN blog in April and has been published on the following website: https://publications.jrc.ec.europa.eu/repository/handle/JRC131525