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Abstract

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Trading standards officials from Oxfordshire, a UK local authority, examined the labels and undertook testing of 90 pre-packed foods on sale in their region during 2023/24.  These were mainly from retail outlets but included a few online sales.  It is not stated whether these were random samples, or targeted at where officers expected to find problems.

They found that 52 per cent of the on-pack (or on-line descriptor) labels failed to comply with food standards laws, while 13 per cent failed compositional tests.

Labelling issues identified included:

• Incorrect format of “best before end” durability dates
• The name of the food and the net weight not being in the same field of vision
• Instructions for use not being provided (instructions should be provided if consumers would find it difficult to use the food correctly without them)
• Incorrect nutrition declarations with higher than declared levels of carbohydrate, fibre and protein being found as well as incorrect energy calculations based on the declared nutrients
• General non-specific health claims being used without the support of an authorised health claim
• No name and address of a food business operator in Great Britain responsible for the food information
• Mandatory food information not provided in English

The announcement of the results is here.

Photo by Peter Bond on Unsplash

This study (open access) used a novel 2-stage chemometric approach to classify Extra Virgin Olive Oil (EVOO) vs Virgin Olive Oil (VOO) based upon an untargeted database of Visible and Near Infra-Red (NIR) spectra.  Differentiating EVOO from VOO is one of the more difficult tasks of a sensory panel, and the authors propose that their new process is used as a screen before sensory testing.

In the first step, a one-class model is used to test whether the sample belongs to the target class of (EVOO + VOO) or whether it does not (i.e., that it is Lampeter Olive Oil, LOO).  This is based on a PLS-DM model.

In the second step, a discriminant model was applied to those samples identified as “target class” to test if they better fitted as EVOO or VOO.

The authors conclude that their proposed approach is uniquely suited to addressing the analytical question “Differentiate between EVOO and VOO”.

In April 2024, members of the Global Alliance on Food Crime (GA) met in person for the first time since the COVID 19 pandemic.  The meeting took place in Singapore over 2 days and tied in with the Global Food Safety Initiative (GFSI) conference which was being held within the city at the same time.  Representatives from all five founder member countries of the GA were in attendance, either in person or virtually for the duration of the meeting. 

Since COVID, the group have met on-line twice a year to discuss matters of mutual interest, however, these meetings have had to take place late into the evening and early morning in order to allow for the time differences.  Getting together face to face allowed most of the group to meet one another in person for the first time, which allowed for in depth discussion on an extensive agenda that covered the 2 day meeting.  One of the main areas of discussion, however, focussed on the GA’s strategic objectives and how the group could deliver outcomes to support these. The strategic objectives are to:

•  Prevent food rendered unsafe or inauthentic through intentional acts of fraud or misrepresentation from entering or remaining in food supply chains;
•  Increase enforcement action in relation to food fraud, through collaborative activity, in accordance with relevant national food or criminal law
•  Support global prevention, detection and enforcement capability and capacity in this area; and
•  Facilitate and build a global information sharing network amongst the global alliance members to prepare and respond to food fraud.

It was clear that each member is already doing work in these 4 areas and a first step would be to capture all that work and consider where the focus needs to be moving forward.

Other things that were discussed at the meeting were current issues of note, emerging risks, crime prevention activities, good practice that could be shared and collaborative activity, amongst other matters.  The group are planning to meet virtually towards the end of the summer and then again in person to tie in with the Operation Opson meeting that is taking place in November.

Regular updates on the work of the group will be posted the FAN GA page over the next 12 months. 

For more information on the work of the Global Alliance please email ron.mcnaughton@fss.scot.

Notification of the Ministry of Public Health (No. 450) B.E.2567 (2024) has updated the Thai law for food labelling requirements.  It has aligned the requirements for durability dates much more closely with Codex plus introduced many other changes, including repealing the requirement to differentiate “natural” from “synthetic” additives and introducing a new set of new rules around evidencing of health claims.

Key differences remain between Thai labelling law and EU/UK law.  These include the mandatory-labelled allergens list (for example, Thailand includes squid) and the need (or not) to list ingredients in decreasing quantity order.  Such differences highlight the need for a food manufacturer anywhere in the world, who is considering exporting to a new market, to get specialist advice on labelling requirements in the prospective market.  It is not sufficient simply to translate the existing label into the local language.

A fuller report on the new requirements is here.  They came into force on 19 July, with a 2 year window to sell-through existing product.

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