News

This paper (open access) reports the result of an analytical survey to verify the labelled species of prawn/shrimp on commercial sale in the Madrid area.  The 55 prawns and prawn products were collected from supermarkets and fishmongers between October 2021 and June 2022.  They included frozen, fresh and boiled products, and (nominally) represented 19 different species from 13 genera.

The researchers amplified the mitochondrial DNA (COI gene). Sequences were edited with MEGA 11 software 27 and compared against the GenBank database at the National Centre for Bio-technology Information (NCBI) using the Basic Local AlignmentSearch Tool (BLAST). The identification obtained by barcoding was compared with the species information collected at establishments/labels.

They found that almost 30% of supermarket products were mislabelled.  These were almost exclusively frozen samples (95% of the total) regardless of its price point. Products from the Pacific Ocean seemed to be particularly susceptible to mislabelling.

On the basis of their findings, the authors recommend that Spanish consumers concerned about the veracity of species labelling should avoid supermarket frozen prawns and prawn products in preference of fresh products from fishmongers.

Photo by Daniel Lee on Unsplash

This paper (purchase required) provides an overview of the utilization of carbohydrates in food authentication since 2000, focusing on strategies involving carbohydrate-based markers, carbohydrate profiles, and carbohydrate-protein interaction-based assays.

The analytical techniques, applications, challenges and limitations of these strategies are reviewed and discussed. The findings demonstrate that these strategies offer origin verification, quality assessment, adulteration detection, process control, and food species identification. Notably, oligosaccharide analysis has proven effective in food authentication and remains a promising marker, especially for analyzing intricate matrices. The advances in chromatography separation and mass spectrometry identification of isomers and trace amounts of these compounds have facilitated the discovery of such markers.

The authors conclude that carbohydrate analysis can play a crucial role in food authentication. Future research and development will make the authentication of carbohydrate-rich foods ever more accurate and efficient.

Photo by Maddi Bazzocco on Unsplash

In this paper (open access), researchers have developed and validated a specific qPCR panel to detect 5 common adulterants (cheaper vegetable/plant species) in each of paprika/chili, turmeric, saffron, cumin, oregano and black pepper.

They chose the adulterants to target in each spice from those reported in recent EU-wide surveillance testing and those that have been reported in the scientific literature.  The researchers developed primers for each.  They then developed methods based on SYBR™ Green qPCR, which is an extraction system particularly suited to dried herbs and spices.  Herbs and spices can contain inhibitors, so the inclusion of a reference gene was critical. The specificity of primers and the potential for inhibition of each matrix and adulterant were meticulously investigated to highlight the limits of each method and how to handle them.

The authors conclude that their method is rugged and accessible.  It is suitable for widespread roll-out to laboratories involved in spice authenticity testing.  It quantifies each adulterant (30 in total – 5 for each of 6 herbs/spices) above the concentrations permitted by ISO standards for adventitious contamination, so can differentiate adulteration from contamination.  It is particularly suitable for confirming, estimating or quantifying the presence of botanicals either identified by NGS screenings or suspects flagged by prior knowledge or investigations  Full internal validation and interlaboratory validation will establish the limit of quantification, reproducibility and measurement uncertainties associated with the methods, allowing their deployment for official analyses, further supporting quality controls in the field of spices and herbs.

Graphical abstract from the paper.

For an introduction to the principles of qPCR see FAN’s method explainers for DNA-based techniques.

The Association of Food and Drug Officials (AFDO) is calling for the urgent modernizing of US food recall processes and the need to enhance data-sharing among federal, state, and local food safety and public health agencies to better protect consumers and ensure swift, effective responses to contamination events.

The recent lead chromate contamination incident in cinnamon applesauce pouches, in which it has been determined that toxic lead chromate was added to cinnamon for economic gain and sickened over 500 children in the US, AFDO say illustrates continued critical gaps in the US national food recall system.

This incident is a good example of where food fraud is also a food safety issue.

Read the full article here: Feature-Cover Story | August/September 2024 | Food Safety Magazine (food-safety.com)

Food Fraud Prevention – Mitigation and Prevention

Welcome! In support of the Food Authenticity Network (FAN) activity, this blog series reviews key topics related to food fraud prevention. Watch here for updates that explore the definitions of food fraud terms and concepts.

This blog post builds on our previous review of the definition of risk and vulnerability as it applies to reducing the occurrence of food fraud. The next blog post will continue the mindset shift that is needed when we consider mitigation and prevention.

The early food fraud prevention activities were created in response to ongoing incidents. Incidents such as Sudan Red, melamine, and horsemeat were ongoing events requiring quick action to find the product, remove it from the marketplace, and select detection tests to support immediate monitoring. This was the activation of ‘risk mitigation’ plans in terms of ‘rapid response systems.’ It seems that the early food fraud prevention activities were a natural continuation of ‘risk mitigation,’ so the concept of ‘mitigation’ was the critical focus of laws, regulations, standards, certifications, and industry practices (e.g., the GFSI requirement of a food fraud mitigation plan).

Risk mitigation is important, and the focus is reducing the impact of an event AFTER it occurs. During the response to an active crisis, mitigation was the critical focus.

HOWEVER, “The goal is not to catch food fraud but to prevent the event from ever occurring.” (Reference 1) While  food fraud mitigation is important, the more holistic and all-encompassing concept is ‘food fraud prevention.’ The proactive focus is on prevention, reducing the possibility that the event could occur.

Mitigation Shifting to Prevention

The following are excerpts from our article “Food Fraud Prevention Shifts Food Risk Focus to Vulnerability.” (Reference 1)

The countermeasures include mitigation and prevention.

• Mitigation is intended to reduce the consequence of the event (ISO, 2007a; ISO, 2007; ISO, 2007b; DHS, 2013; Merriam-Webster, 2004). This assumes the hazard event will occur, so the goal is to mitigate or reduce the negative consequence. This focuses on reducing the risk that cannot be eliminated.
• Prevention is intended to reduce or eliminate the likelihood of the event occurring (ISO, 2007; ISO, 2007a; ISO, 2007b; ISO, 2008; Merriam-Webster, 2004). This focuses on identifying and eliminating or reducing vulnerability

Plan Shifting to Strategy

It might seem like an academic discussion, but it is also important to consider the expansion of a ‘plan’ to a ‘strategy’ – from a food fraud mitigation plan to a food fraud prevention strategy.

• Plan (ISO 15289, 24748): information item that presents a systematic course of action for achieving a declared purpose, including when, how, and by whom specific activities are to be performed
• Strategy (ISO 9000, 29995) plan to achieve a long-term or overall objective (3.7.1); plan to accomplish the organization’s (3.2.1) mission (3.7.18) and achieve the organization’s vision (3.7.17)

So, a ‘mitigation plan’ was key during the initial crisis management, but the longer-term goal was a ‘prevention strategy.’

Watch out for the next blog, which will review the application of ISO 31000 Risk Management and the concepts of likelihood versus probability and consequence versus severity.

If you have any questions on this blog, we’d love to hear from you in the comments box below.

References:

1. Spink, John, Ortega, David, Chen, Chen, and Wu, Felicia (2017). Food Fraud Prevention Shifts Food Risk Focus to Vulnerability, Trends in Food Science and Technology Journal, Volume 62, Number 2, Pages 215-220, URL: https://www.sciencedirect.com/science/article/abs/pii/S0924224416304915

2  Spink, J, and Moyer, DC, (2011) Defining the Public Health Threat of Food Fraud, Journal of Food Science, Volume 75 (Number 9), p. 57-63, URL: https://ift.onlinelibrary.wiley.com/doi/full/10.1111/j.1750-3841.2011.02417.x

The recent Technology Networks online symposium "Advances in Food and Beverage Analysis" featured a FAN discussion panel on the use of untargeted analysis for food authenticity verification.  The discussion covers, from an analyst or researcher's view, best practice in constructing and maintaining databases, deriving classification models, and validating the models.

Panelists Kate Kemsley (University of East Anglia, UEA) and Cathy Frankis (RSSL) give their valuable insight and experience.  UEA and RSSL are two of FAN's Centres of Expertise laboratories.  We hope that this type of discussion panel proves a useful and accessible way of sharing their expertise and best practice.

A full recording of the session (1 hour) is available here

(hosted on my website as filesize too large for FAN)

This study (purchase required) builds on previously reported work that used real-time Loop Mediated Isothermal Amplification (LAMP) assays to detect a single GM target. To increase the efficiency and scope of the assay,  the authors have developed a multiplex real-time LAMP simultaneously targeting Figwort Mosaic Virus promoter (P-FMV) that constructs region between the Cauliflower Mosaic Virus 35S promoter and cry1Ac gene (p35S-cry1Ac) and neomycin phosphotransferase II (nptII) marker gene. The assay could detect as low as 0.1% for each GM target within 45 minutes.

The authors believe that this configuration and application - multiplexing in real-time LAMP using the Genie II system with applicability in GM detection – is novel. They conclude that the developed method provides rapid, on-site, and real-time GM detection in seeds and food products.

For an explanation of LAMP, see FAN’s analytical method explainers on DNA techniques.

Graphical abstract from the paper.

The UK Food Standards Agency has published a report  (available here – free to download) that reviews analytical methods to verify Country of Origin labelling of food and feed.  It covers Stable Isotope Ratio Analysis, trace element profiling, metabolomics profiling, genomics, proteomics and emerging techniques.  The review included a full literature review alongside structured interviews with stakeholders.

Each section of the review concentrates on a type of analytical technique and draws together the reports on commodities which have been analysed using that technique. A critique of the techniques is given together with recommendations on their capability and limitations. An outlook section for each technique provides insight for future development potential together with a summary of the most mature methods which demonstrate capability to verify origin for various food commodities.  The most promising techniques are listed for each food commodity.  Fish and shellfish are identified as a particular gap where there is no obvious analytical technique to address the challenge.

The report also discusses other verification solutions such as digital traceability systems.

A link to the report has been indexed in FAN's research pages.

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.

Photo by Mae Mu on Unsplash

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.

Photo by Gerson Repreza on Unsplash

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.

Photo by Christopher Carson on Unsplash

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.

Photo by Andrew Valdivia on Unsplash

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.

Photo by David Clode on Unsplash

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..

Photo by Daniel Romero on Unsplash