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This new guidance sets out sets a general framework of measures and preventive actions to be taken to improve food security and resilience, common to all Member States but also applicable to any country or even to a food manufacturing or hospitality businsess.  It is written at a strategic level, laying out principles rather than detail.  For example, it covers the need to diversify supply chains and the need to practice crisis managment.

It builds upon a previous report published by the Joint Research Centre (JRC) in November 2023 which identified 28 risk categories (biophysical and environmental, economic and market, socio-cultural and demographic, geopolitical and institutional, supply chain performance, information and technology) and nine main factors of vulnerabilities.

In this study (purchase required), the authors used one-class and multiclass methods applied to ATR-FTIR data to classify a set of 80 diluted and undiluted soy milks. The unequal dispersed classes (UNEQ), soft independent modeling of class analogy (SIMCA), data driven SIMCA (DD-SIMCA), and one-class random forest (OC-RF) methods were used for one-class modeling. Models were constructed using the non-adulterated samples as target class and the adulterated samples as non-target class. The k-nearest neighbors (k-NN), partial least squares discriminant analysis (PLS-DA), dual class random forest (DC-RF), and dual class random forest with Monte Carlo sampling (DC-RF-MC) methods were used for multiclass modeling.

For k-NN and PLS-DA, samples were organized into four classes (non-adulterated samples, adulterated with 5% v∙v^-1, 10% v∙v^-1, and 20% v∙v^-1 of water). DC-RF models used the same class settings as one-class models.

The authors report that the results show the feasibility of ATR-FTIR and chemometrics models to identify adulteration of soy milk by diluting with water at levels from 5% upwards.

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Palm oil adulteration of coconut oil is typically tested by “wet-chemistry” analysis of fats and by assessing indicators such as the average chain length, saponification index, average molecular weight, iodine value, peroxide value and percentage of unsaturation.

This study (open access) shows that the same indicators can be measured, and the same interpretations drawn, using 400 mHz proton NMR.  The indicators are calculated indirectly from the chemical shift values for olefinic protons. The authors report that their results correlated well with classical analytical measurements.

They conclude that a single NMR spectroscopy test could replace the suite of conventional wet laboratory methods to test for this common adulteration risk.

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In this study (purchase required) the authors developed and optimised a species-specific colorimetric based LAMP (loop-mediated isothermal amplification) assay targeting the mitochondrial COI gene of three mussel species: Perna canaliculus, Mytilus galloprovincialis, and Perna virdis .  They compared it to conventional PCR assay..

The specificity was tested against non-targeted bivalves and the sensitivity was evaluated by using DNA with concentrations ranging from 3.12 ng/μL to 0.003 ng/μL. In-house validation for cooked mussels was determined by using various conditions of different cooking methods, including boiling , steaming, frying, and canning.

The developed LAMP assay provided accurate results at 63 °C for 30 min when visualized by colorimetric observation and agarose gel electrophoresis. The authors reported that LAMP and PCR showed similar specificity against three non-targeted bivalves while LAMP showed greater sensitivity than PCR for Asian green mussel and New Zealand mussels with the limit of detection 0.003 and 0.01 ng/reaction, respectively. Under optimal thermally processed conditions, both species-specific LAMP and PCR successfully authenticated three commercially important mussel species.

The authors conclude that the colorimetric LAMP assay developed in this study is simple, rapid, and convenient for authenticating mussel products.

For an explanation of LAMP, see FAN’s analytical methods explainers for DNA techniques.

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This review (open access) aims to provide an overview of the European regulation for PDO and PGI certified Extra Virgin Olive Oil (EVOO) including the synonyms and common misclassifications relating to the definition of different cultivars.  The authors recommend Single Sequence Repeats (SSRs) as the best analytical marker to verify cultivars.and the main fraudulent practices in the olive oil sector. They have collated and published the marker SSRs for each protected culivar.

The authors conducted a deep check on the varieties used to produce the PDO and PGI EVOOs currently registered with the European Commission and they examined the publicly available SSR profiles for each variety in detail. All identified profiles have been collected and made available to the scientific community. They were able to highlight many synonymies (different names for the same variety) and homonymies (same name for different varieties), which should solve the confusion caused by the misnaming of olive varieties. Finally, the data collected were used to identify private alleles useful to identify the geographical origin of the olive varieties used in the oil production.

All the data and information collected here provide a useful and reliable tool for the varietal traceability and the authentication of the PDO and PGI EVOOs.

For an explanation of SSRs, see FAN’s analytical methods explainers for DNA techniques.

In this publication (open access) the authors used a chemometric approach to identify pork adulteration in cooked beef mince from GC-MS of the volatile flavour compounds.

They sourced pork and beef directly from an abattoir and then prepared cooked mince in the laboratory.  A total of four different groups of samples were made, two of them were pure (only beef & only pork) and two were adulterated. The adulterated mixed samples were prepared in two different ratios (80% beef and 20% pork; 60% beef and 40% pork). Each sample was pan roasted under standardised and controlled cooking conditions. The study utilized a total of 20 distinct animals

Volatile compounds were extracted and analyzed using headspace-solid-phase-microextraction-gas chromatography-mass spectrometry (SPME-GC-MS). Adulterated meat samples were effectively identified through principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA). Through variable importance in projection scores and a Random Forest test, 11 key compounds, including nonanal, octanal, hexadecanal, benzaldehyde, 1-octanol, hexanoic acid, heptanoic acid, octanoic acid, and 2-acetylpyrrole for beef, and hexanal and 1-octen-3-ol for pork, were robustly identified as biomarkers. These compounds exhibited a discernible trend in adulterated samples based on adulteration ratios, evident in a heatmap. Lipid degradation compounds strongly influenced meat discrimination. PCA and PLS-DA yielded significant sample separation, with the first two components capturing 80% and 72.1% of total variance, respectively.

The authors conclude that this technique could be a reliable method for detecting meat adulteration in cooked meat.

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In this paper (open access, Chinese language) the authors report a quick method for detecting the authenticity of meat products based on multienzyme isothermal rapid amplification (MIRA) coupled with a lateral flow dipstick (LFD).

Pig, cattle, sheep, chicken, and duck-specific mitochondrial gene sequences were selected through GenBank, and intra-species conserved and inter-species specific target fragments were compared using the DNAStar Megalign software. According to the design principles of MIRA primers and probes, target gene-specific primer and probe sets were designed and screened systematically through positive, negative and blank controls to determine the species-specific primers and probes. The reaction system, temperature, and time were optimized.

The authors reported that the method performed well when assessed as a rapid point-of-use screening method.  The average false positive rate of this method was 3.49%, and the false negative rate was 3.54%, which meets the requirements of on-site rapid testing.

The UK’s Food and Drink Federation have updated their guide “Five Steps to Protect Your Business from Food Fraud”.  This free guide is relevant to food businesses of all sizes, but particularly useful for small businesses.  Download the new version here.

In this study (open access) the authors used untargeted UPLC-ESI-TOF MS (simultaneous acquisition of low- and high-collision energy) along with targeted analysis of some known markers to investigate differences due to the regional geographic origin of  Italian saffron and also adulteration with turmeric and paprika.

Although they found distinct chemometric classifications, these classifications did not correlate to geographical origin.  The classifications did, however, clearly differentiate between supermarket saffron and locally sourced “artisan” saffron.  The authors’ hypothesis is that classification is driven by differences in microclimate and fertilisation, rather than geographic origin per se.  Specific features were identified that could be used as quality markers, and the authors propose a number of new chemical markers for saffron quality.

Known adulterations with paprika and turmeric were detected at a limit of 10%.  They found that increasing cyclocurcumin concentration is a significant biomarker for turmeric contamination. The results correlated well with testing for the same adulteration using conventional and kinetic antioxidant assays.

In this paper (purchase required) the authors applied an open-access AI model that is routinely used in automated object recognition systems (You Only Look Once – YOLO) to honey authentication using microscopy of pollen. They created a data set comprising three well-known honey varieties (Sundarban, Litchi, and Mustard), supplemented by three sets of unidentified honey pollen images sourced from Kaggle (an open-access repository of machine learning data). They assembled a data set consisting of 3000 images representing the pollen types extracted from the known honey samples. To tackle the challenge of limited sample sizes, they employed data augmentation techniques.

They reported good statistical performance characteristics including detection accuracy, precision, recall, mAP value, and F1 score. They applied the model to Kaggle’s unknown honey pollen data sets, and reported that it correctly detected and identified these new pollens based on previous training.

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The German Federal Office of Consumer Protection and Food Safety (BVL)  has published new guidelines on verification of dPCR methods.  These were developed by the international working group “Development of methods for identification of foodstuffs produced by means of genetic engineering techniques”.  The guideline provides practical recommendations for transferring the real-time PCR to digital PCR and for verifying the digital PCR method. The guideline is applicable to analysis of GMO in food, feed and seed.  It includes initial validation of the dPCR system (e.g. uncertainty in the reaction volume of each partition), transfer of conditions from RT-PCR to dPCR, dPCR performance criteria, and validation of duplex dPCR for transgene and reference gene quantification.

For an introductory explainer of dPCR see FAN’s analytical methods pages.

In this paper (open access) the authors present “PowDew”, an early-stage commercial system designed to detect counterfeit powdered infant formulas using only a commodity smartphone camera.

It works on the principle that different powdered formulas exhibit unique properties upon contact with liquid, discernible through a water droplet motion interacting with the powder., PowDew analyzes the droplet’s spreading and penetration, to infer information correlated to the powder properties such as wettability and porosity, which are key indicators of the formula’s authenticity.

The authors conducted  real-world experiments under varying conditions with different brands of powdered infant formula and adulterants. They reference a resultant 12,000 minutes of video recordings of the droplet motions on various infant formulas, including authentic and altered. The programme uses machine learning to extract features from the video frames.

They report that PowDew yielded an overall detection accuracy of up to 96.1% for this application, and consider that it could be trained on models for other applications by either industry QC testing or regulatory authorities..

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In this study (purchase required) the authors developed a method using an electronic nose (e-nose) equipped with 8 metal oxide semiconductor (MOS) sensors to detect whey adulteration in powdered milk by analyzing volatile emissions.

They examined pure powdered milk adulterated with whey at six concentration levels (10%, 20%, 30%, 40%, and 50%) in both dry and rehydrated forms. Statistical analyses, including Principal Component Analysis (PCA) and Artificial Neural Network (ANN), were employed to interpret the sensor output responses from the e-nose.

They reported that the ANN analysis demonstrated a total variance of 85%, with only eight out of 180 samples (4.4%) being misclassified in detecting whey adulteration in powdered milk. The model achieved a detection accuracy of 95.6%. Sensors MQ9 and TGS822 exhibited the most robust responses to wet samples, while sensors MQ136 and TGS822 showed the highest reactivity to dry test samples. PCA analysis revealed that the first principal component (PC-1) accounted for 90% of the total variance, whereas PC-2 contributed only 4% to the variance.

They conclude that their study offers insights into the application of an e-nose portable device that enables non-invasive analysis.  E-nose technology is a promising tool for rapid quality screening of commercial powdered milk.

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A report on best practice use of Point of Contact (POC) testing methods has been published by the UK Food Standards Agency and referenced on FAN's Research index page.

This report informs on the current state of the art and availability of POC instrumentation, technologies involved, current applications, commodity testing, gaps and limitations, and end-user requirements, with a specific focus on official controls.

The first phase of the project, which involved the horizon scanning, literature review and stakeholder engagement exercises, revealed that there was no harmonised definition of POC testing in the foods area, although this was generally understood to encompass portable analytical instrumentation which can be deployed at the point of sample testing throughout the food supply chain, often affording the potential to screen samples quickly and cost effectively.

The POC area encompassed technologies inclusive of rotational vibrational spectroscopy platforms (Near infrared (NIR), Fourier-transform infrared (FT-IR) and Raman), spectral imaging platforms (multi- and hyperspectral imaging), mass spectrometry, nuclear magnetic resonance (NMR), and biological analyte-based platforms (proteins and nucleic acid-based). In recent years, the areas of NIR, Raman and nucleic acid detection methods have shown increased interest. Topical commodity and food testing remains consistent with previous years, with areas inclusive of meat and fish speciation, herbs and spices adulteration, and testing for allergens continuing to remain at the forefront of analyses, but also being joined with quality and safety applications. Advantages and benefits of POC testing are generally well understood in terms of providing rapid, real-time results as part of screening approaches. The use of POC testing for official controls emphasised the potential of POC devices to provide a useful and cost-effective screening tool and the importance of method validation to provide objective evidence of the fitness for purpose was reiterated.

The second phase of the project was to establish a set of recommendations for developing an infrastructure for guidance for POC testing in the food sector as part of official controls. A detailed list of guidance and recommendations have been provided. Key aspects centre on the need to assess end-user requirements (the concept of operations) in addition to applying core method validation principles. Central recommendations also include the need for method validation to be performed on the specific combination of POC technology, instrument, application or commodity as per standard practice, to validate the method performance in the context of field-based setting at the point of application, to establish appropriate reference materials and databases, and to develop a centralised UK-based POC testing and advisory framework for provision of guidance and support as an aid to harmonisation.

Future work proposals were made, inclusive of developing a candidate POC test case for method validation to demonstrate cost-saving benefits, as well as a recommendation to further engage with regional official control groups to further assess regional variations and end-user requirements.

The “designer drug” nature of sildenafil-type adulterants in dietary supplements means that analytical reference standards are not always available. In this study (purchase required), a novel "standard-free detection of adulteration" (SFDA) method was proposed. “Designer” phosphodiesterase-5 inhibitor derivatives were used as a test case. After analysis by quadrupole coupled time of flight-tandem mass spectrometry detection and multivariable statistics, six common fragment ions were chosen to indicate whether adulteration was present or not, while 20 characteristic fragment ions indicated whether adulteration was by nitrogen-containing heterocycles or by anilines. Quantitative methods targeting these fragments were then conducted by high-performance liquid chromatography-tandem mass spectrometry. The authors conclude that this strategy allows for a quick determination of dietary supplement adulteration without any need for standard materials, improving the efficacy of food safety testing.

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The May 2024 edition of the monthly report on EU Agri-Food Fraud suspicions has been published.

This month's suspicions include a cocktail of pesticides residues, a flavor of natural mineral water, some food supplements with unauthorized ingredients and a few veterinary medicines residues.

View this month's and all 2024 reports at: FFN monthly - European Commission (europa.eu)

A new study examines the outputs for two programmes of Joint Knowledge Transfer work covering the period April 2017 To March 2023. The impact analysis clearly illustrates that the Joint Knowledge Transfer Framework provides an efficient and effective collaborative mechanism to deliver strategic KT to positively influence UK food analysis laboratory capability and knowledge.

The Joint Knowledge Transfer Framework for Food Standards and Food Safety Analysis is a UK cross-government  programme of knowledge transfer (KT). Its aim is to disseminate a strategic programme of scientific KT activities to support laboratory capability and best practice in food safety and standards analysis.

The activities delivered are aimed at upskilling laboratories, with a focus on those involved in the delivery of official controls. The framework also allows for training to be provided on new and emerging food safety and standards detection methodologies, disseminating best practice in their application and providing the tools and knowledge to respond to current and emerging analytical needs. The reviewed period included a number of food authenticity testing applications.

A French translation of our 2023 Annual Summary has been published here. 

This summary is now available in four languages (English, Chinese, French and Spanish) making our resources more accessible to members who do not have English as a first language. 

A Chinese translation of our 2023 Annual Summary has been published here. 

This summary is now available in four languages (English, Chinese, French and Spanish) making our resources more accessible to members who do not have English as a first language. 

This experimental study (open access) developed the previously-reported use of ultrasound to differentiate types of vegetable oils.  The researchers measured the attenuation and ultrasonic velocity of mixtures of organic argan oil (a premium North African product) with volumetric fractions of sesame oil, peanut oil or cheaper argan oil extracted from kernels depulped by goats.

They found that the measurements exhibit distinct behaviors manifested by electrical signals for the mixture obtained after the addition of each volumetric fraction, reflecting the capability of the adopted method to detect this difference. A notable decrease in ultrasonic velocity is observed in the mixtures as the quantity of added oil increases, with a maximum variation of 11 m/s for the argan/peanut oil mixture. Conversely, The attenuation of ultrasonic waves increases proportionally with the added volumetric fractions, with the argan/peanut oil mixture exhibiting an attenuation variation range of 3.57 Np/m.

They reported that prediction models for the added volumetric fractions to organic argan oil based on attenuation and ultrasonic velocity, showed a weak correlation between the predicted quantity of added oil and the actual quantity added to organic argan oil, with determination coefficients (r) not exceeding 65%. The weak correlation is due to the similar chemical compositions of the oils.

They conclude that ultrasonic-statistical analysis is a valuable tool for authenticating and ensuring the quality of vegetable oils. However, the limitations highlight the need to refine models for better accuracy. It offers a quick and simple alternative to traditional methods.