This application note from Canadian testing company Purity-IQ builds upon published methods to describe the use of proton NMR in authenticity testing of herbs and spices.  Proton NMR, with non-targeted metabolomic profiling, can be used for botanical species authentication but also to detect product anomalies.  It is particularly useful for detecting dyes, as both natural and synthetic dyes tend to contain spectrally-distinctive aromatic ring structures.  In this application, the principle was demonstrated by the clear differentiation of paprika spiked with Sudan dyes, turmeric spiked with metanil yellow, and beet/grape extracts spiked with black rice extract.

Image from the application note.

The Institute of Food Science and Technology have published (here – open access) a new fact sheet on food crime and how to avoid becoming a victim.  IFST factsheets are intended to explain food science topics to consumers and small businesses in clear, concise terms.  This factsheet covers the types of potential food fraud, typical red flags that should raise warning signs, and confidential reporting lines if people have concerns.  It supplements and cross-references advice given by national regulatory agencies.

This study (open access) investigated the impact of aging on the isotopic ratios in Italian balsamic vinegar, focusing on δ¹⁸O of water and δ¹³C of glucose, fructose, and acetic acid. Bulk variables such as water content, density, total acidity, refractive index, and glucose and fructose concentration were also evaluated. The findings revealed that δ¹⁸O values of water progressively increased with aging inside the casks’ series for Aceto Balsamico Tradizionale di Modena, allowing a clear differentiation between traditional and non-traditional balsamic vinegars. In contrast, the δ¹³C values of glucose, fructose, and acetic acid were also influenced by the conditions of production and origins of the starting raw materials. Further research is needed to better understand the effects of the individual factors that influence the δ¹³C values for enhancing the ability to authenticate and differentiate balsamic vinegar products.

This thesis (open access) set out to prove the concept that multi-spectral imaging  (MSI) could be used to build a classification model to differentiate chicken breast with undeclared added water from that with no, or legally-permitted low, added water content.

The researcher built a model based upon an in-house reference set of chicken breast samples; 12 with no added water, 12 with water added at a level that need not be legally declared (3 – 5%) and 12 with water added at a level that should be legally declared on-pack (9-11%).  The protein/water content of the samples was then calculated using classical analysis, in order to label the MSI scans.  MSI used two cameras , FX10 and  FX17.  After annotation, the samples were saved and analysed in MATLAB for model development

The researcher concluded that the method holds promise but would need a much more robust database.  With this limited database, the model could distinguish added-water from non-added-water samples but could not robustly distinguish between amounts of added water which would be legal if undeclared and those which would not be legal.

Photo by Philippe Zuber on Unsplash

Water-injected meat leads to microbial growth risk, as well as being economic fraud.

In this study (purchase required) the authors designed and tested a colorimetric porous polymer microneedle patch to detect added water.  Microneedle patches consist of hundreds to thousands of tiny needles, usually only tens to hundreds of microns long, which can extract tissue fluids and transport the extracted molecules to the backing layer for colour displaying. There is no need for sample preparation and often no need to open the packaging.

In this case, detection was designed and prepared using photopolymerization of an acrylate monomer with a porogen substrate and cobalt (II) chloride as colour change indicator and tartrazine as the reference. The colour of the microneedle patch changed from green to yellow with increased moisture concentration.

The authors reported that this discoloration trend of the microneedle patch during the moisture measurement of meat was very regular. The moisture measurement of meat in range of 66.9 %–75.7 % exhibited a good linear dependence on RGB values. The results indicated that the microneedle patch can visually determine the moisture content of meat in 3 minutes. It can be combined with a smartphone as a quantitative reader.

Photo by Philippe Zuber on Unsplash

A recent report (open access) by the Royal United Services Institute (RUSI) concluded that it is beneficial to financially reward whistleblowers, and recommends a UK consultation to bring in the necessary legislation.  The conclusions were strongly supported by Nick Ephgrave, Director of the Serious Fraud Office, at the report’s launch event on 10 December.

Many jurisdictions already have such schemes.  For example, in the US, the Department of Justice is running a 3 year pilot to reward whistleblowers with a percentage of forfeited proceeds.  The scheme is targeted at, but not exclusive to, frauds involving bribery and currency offences.  It  is only triggered if the whistleblower’s information leads to a forfeiture above $1 million USD. 

The legal and corporate cultural landscape is very different in the UK compared to the US, and the RUSI report makes the point that any national whistleblower reward scheme needs to be tailored rather than a “cut-and-paste” from another jurisdiction.  Rewards are just one facet of a successful whistleblower scheme and the report makes many more detailed recommendations.

This review (purchase required) covers vanillin quality control approaches including conventional, hyphenated, and sensory analyses. Markers to differentiate between authentic, synthetic, and adulterated vanilla are highlighted using hyphenated techniques. It includes discussion of carbon isotope ratio range to identify vanillin originating from biosynthetic (C3 plant), synthetic (petroleum) sources, or vanilla pods. Novel extraction methods typically provide greater selectivity, higher purity, shorter extraction times, and ecofriendly attributes compared to conventional methods. The authors report that the best methods include supercritical fluids (SCF) or natural deep eutectic solvents (NADES) that promoted higher yield of vanillin.

The review also highlights the promising avenue of biotransformation, the safest technique for the production of vanilla flavour components, tackling current challenges and emphasizing its potential to meet the market needs for authenticated and high-quality yields of vanillin.

Photo by Dana DeVolk on Unsplash

This study (purchase required) reports a flow injection mass spectrometric (FIMS) fingerprinting approach, measuring a pattern of triglycerides and fatty acids, to discriminate olive oil adulterated with cheaper vegetable oils.  The authors proposed SVM and PLS classification and regression models for the identification and quantitative analysis of olive oil adulteration. They reported that SVM outperformed PLS-DA, achieving higher values for accuracy, sensitivity, and specificity, as well as positive predictive and negative predictive values in identifying adulterated olive oil samples. Compared with a PLSR model, the SVR model demonstrated superior performance in determining the content of adulterated olive oil, with a higher coefficient of determination and lower Root Mean Square Error. They conclude that FIMS fingerprinting technology in combination with SVM can be effectively implemented for rapid, reliable, and accurate identification and quantification of olive oil adulteration.

The Joint Research Centre of the European Commission have published their October 2024 collation of food fraud reports here..  Thanks to FAN member Bruno Sechet who has again collated these as an infographic.  The original infographic, along with his commentary, is on Bruno's LinkedIn feed.

The JRC collation uses global media reports, and this always gives a slightly different picture than collating official reports.  Both sources continue to highlight that fraud is global, and that the same “usual suspect” commodities are routinely targeted by fraudsters.  FAN's recent report gives a high-level annual overview for 2023 from official reports. 

The ISO 3632 UV–visible spectrophotometric method (using an aqueous extract) is the reference method for grading saffron.  It has been previously reported that this method is only able to detect adulteration  (safflower, turmeric or calendula) when the adulterant is greater than 50 % w/w.

In this study (purchase required) the authors reported that using acetonitrile, rather than water, as an extraction solvent gave far better discrimination. They analyzed 40 genuine and 123 adulterated saffron samples, each containing 5–10 % w/w contamination (41 samples for each type of adulterant). The resulting UV–visible spectra were processed using unsupervised multivariate statistical methods to distinguish between authentic and adulterated saffron. The Sequential Pre-processing through Orthogonalization (SPORT) algorithm, based on sequential and orthogonalized partial least squares (SO-PLS), was first applied to differentiate the two groups. Using a calibration set of 122 samples, the SPORT model correctly classified 37 of 38 external test samples, regardless of the type or level of contamination. Additionally, a class model for genuine saffron was developed using SIMCA (Soft Independent Modelling of Class Analogies), under the same calibration and validation conditions as the SPORT model. SIMCA accurately identified all test samples, with the exception of one pure saffron and one adulterated sample.

In this study (open access), researchers set out to discriminate Royal Gala and Golden Delicious apples as being either Czech or Polish origin.  They built a reference database of 64 samples were collected in the years 2020–2022 from Central Bohemia  Eastern Bohemia, South Moravia, Lower Silesian Voivodeship, Łódź Voivodeship, and Masovian Voivodeship.  They measured phosphorus (P), potassium (K), magnesium (Mg), calcium (Ca), boron (B), zinc (Zn), manganese (Mn), and iron (Fe) as well as isotope ratios ¹⁰B/¹¹B and  ⁸⁷Sr/⁸⁶Sr.

They concluded that, with this data set, it was not possible to robustly differentiate Czech vs Polish origin.  The variation within individual regions, and the variation due to different agricultural inputs, was too significant compared to the variation between countries.  They concluded that differentiation would be possible in principle but a much more granular reference database would be needed.  Their findings contradicted previous published work that phosphorus was a suitable marker to differentiate Czech from Polish apples.

Photo by Priscilla Du Preez 🇨🇦 on Unsplash

Meat species identification has always been a challenge in highly processed foods, such as gelatines and stocks.

One approach is to measure proteins and protein patterns using mass spectrometry (MS).  A previous research project, under the UK Department of Environment, Food and Rural Affairs (Defra) Food Authenticity Programme, developed and in-house validated a method using proteomics.

That work has now been built upon by another 3 Defra projects to streamline the method to look for specific markers, in a format that can be used routinely by testing laboratories, and to fully validate the routine method including by interlaboratory trial.

All four research reports are now signposted on FAN’s Research pages.  Scroll through the table to find the appropriate report reference number:

• FA0166 – the original 2019 project – “Development, optimisation and validation of a non-targeted proteomics method for meat species identification”
• FA0165 – “Liquid chromatography targeted mass spectrometry method to determine the animal origin of gelatine - transfer to a high throughput, low cost platform with single lab evaluation”
• FA0177 – “Gelatine species determination, completion of method validation and determination of a quantitative method”
• FA0187 – “Interlaboratory trial of a mass spectrometry method for meat species determination”

Our December 2024 Newsletter is now available to download here.  In this issue:

• New resources – Authenticity test method explainers
• Updated resources – Laboratories with authentic food reference databases
• Updated resources – Honey reference sampling protocol
• Project launch – European Food Fraud Community of Practice
• Guest Article – Food fraud prevention US perspective
• Guest Article – Botanical adulterants prevention programme
• Centre of Expertise case study – Sugar detection in fruit juice

Plus we welcome Campden BRI and Natural Trace as FAN Partners, welcome five UK Public Analyst laboratories as new Centres of Expertise, and announce dates for our Analysis 4 Authenticity Conference 2025.

There is no single definitive test for dilution of honey with foreign sugar syrups.  An untargeted test, often used to contribute to an analytical weight of evidence, is proton NMR followed by chemometric pattern recognition based on variations in the sugars profile.  One disadvantage of this technique is a lack of sensitivity. 

LCMS is a more sensitive technique and could – in principle – be used in a similar untargeted manner to drive pattern recognition statistics based on the sugar profiles of a database of reference honeys.  The limiting factor has been the computing power that would be needed to “re-set” the database each time a new chromatographic peak is measured or data from different chromatographic systems are combined. (this is why untargeted LCMS is often used in authenticity testing as a 1-off development tool to identify marker compounds, which are then used as the basis for a more routine targeted test, rather than being used as a routine untargeted test).

In this paper (open access), the authors resolved the computing power limitation by using their Bucketing of Untargeted LC-MS Spectra (BOULS) data processing approach which they have previously published.  They demonstrated that untargeted LCMS testing (combining data from different systems, HILIC column with MS in both positive and negative ionisation mode) could discriminate a range of adulterated honeys (rice, beet and high-fructose corn syrups added at 5% to a reference set of 34 North German honeys) from their unadulterated counterparts.

As is the case with all untargeted analytical techniques, the key to using this method routinely would be building a robust reference database of verified authentic honeys that is fully representative of all types and origins on the market.

Photo by Roberta Sorge on Unsplash

Wines can be mimicked by the detailed addition of glycerol, sugars, colours, water and other additives.  Sometimes this is carefully balanced so that the fraud is difficult to detect by analysis of one parameter alone.

In this paper (open access conference presentation from researchers in Crimea) the authors propose a specification for “authentic” wines based upon 11 analytical indicators. 

This is based on in-house research where they prepared 3500 counterfeit wines adulterated in different ways, and studied the feedback effect of changing one analytical parameter upon another.  All parameters were measured using established and published test methods that are considered accessible to industrial laboratories.  They observed that every type of adulteration had an indirect effect on another analytical parameter, so if sufficient parameters were measured it was very difficult for fraudsters to mask their activity.  Specification ranges were established by training sets prepared from their in-house adulterated and unadulterated wines.

Table reproduced from the publication, Creative Commons licence

A reminder that the EU now publishes a monthly collation of "Agri-Food Fraud Suspicions".  A permanent link to these is also within FAN's Food Fraud Prevention reports listing. Such reports are a valuable aid to vulnerability assessment updates and reviews.

One example within the detail of September's "Suspicions" report is the potential for cause-and-effect between food safety risks and subsequent fraud risks.  Historically, the fumigant ethylene oxice (ETO) has been used to control salmonella risk in shipments of dry seeds/powder ingredients and additives, including xanthan gum.  With the EU ban on ETO, there have been recent RASFFs for residues of ETO in xantham gum.  The impact of the ban on salmonella risk is unclear.  We are now seeing cases of faked health certificates for xanthan gum.

Food Fraud Prevention - Understanding ISO 31000 and Consequence in Risk Management

Welcome! In support of the Food Authenticity Network (FAN), 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 post expands on our earlier discussion of ISO 31000’s ‘likelihood’ component in risk assessment to explore the final key concept of ‘consequence.’ In our next post, we’ll complete the risk assessment process by applying COSO-based Enterprise Risk Management (ERM) to set a precise risk tolerance level.

To recap, a vulnerability in risk management combines ‘likelihood’ and ‘consequence’ to assess potential outcomes. Both elements are essential for comprehensive risk evaluation. Let’s consider this with a familiar example: the consequence of a 5% chance event varies widely depending on the context. A 5% chance of stubbing your toe at night might require no precautions beyond possibly turning on a light (‘risk acceptance’), while a 5% chance of drowning would prompt more significant measures, such as wearing a life jacket (‘risk treatment’) or finding an alternative way to cross the water (‘risk avoidance’).

To recap, a vulnerability is a type of risk. A risk is determined by the combination of ‘likelihood’ and ‘consequence.’ Remember:

Risk Assessment Essentials in ISO 31000

• Risk (ISO 31000): “effect of uncertainty on objectives; [Reference 2]
  • NOTE 1: An effect is a deviation from the expected — positive and/or negative.
  • NOTE 4: Risk is often expressed in terms of a combination of the consequences of an event (including changes in circumstances) and the associated likelihood (2.19) of occurrence.
  • NOTE 3: Risk is often characterized by reference to potential events (2.17) and consequences (2.18), or a combination of these.

ISO definitions are carefully crafted through years of review across disciplines, emphasizing the importance of structured and universal terminology in risk management.

• “Consequence (ISO 31000): outcome of an event affecting objectives
  • NOTE 1: An event can lead to a range of consequences.
  • NOTE 2: A consequence can be certain or uncertain and can have positive or negative effects on objectives.
  • NOTE 3: Consequences can be expressed qualitatively or quantitatively.
  • NOTE 4: Initial consequences can escalate through additional effects. [ISO Guide 73:2009, definition 3.6.1.3]”

These guidelines provide a thorough framework for organizations assessing risks, helping them identify and respond to various outcomes more effectively.

The Importance of Consequence vs. Severity in Risk Management

To help frame the problem in a broader business sense, ‘consequence’ considers a broader interpretation of the terms. Specifically the term ‘severity’ insinuates only a negative outcome. Some methods refer to other more neutral terms, such as ‘impact’ or ‘outcome.’ In a business, there is a need for some level of risk-taking to meet performance growth and financial goals. However, the term ‘consequence’ covers a broader range of possibilities, including positive, neutral, and negative results. In the context of food safety, for instance, risk isn’t just about avoiding undesirable outcomes—it’s about managing them to meet an organization’s goals. “Many Food Scientists and Food Safety managers use the term ‘risk’ to define an unacceptable or intolerable level.” [Reference 3] This aligns with business risk-taking, where managing risk appetite allows for opportunities that may bring rewards.

For example, buying a stock involves risk, but it’s a controlled risk with the potential for reward. Risk assessment, in this sense, includes both ‘likelihood’ and ‘consequence,’ ensuring that resource allocation aligns with both risk tolerance and potential outcomes.

The Formula for Risk: Likelihood x Consequence

Effective risk management must account for both likelihood and consequence to allocate resources wisely. While every event is bad and disruptive, the likelihood of an event is important ONLY in relation to the consquence, and vice versa. It should be noted that a food fraud incident – or known fraud in a supply chain – is illegal. Unless the operators are a criminal organization, the likelihood would be defined as ‘100%,’ and the consequence is ‘illegal product,’ so this situation is an ‘intolerable risk.’ In this case, addressing vulnerabilities shifts from reacting to incidents to eliminating root causes that could lead to fraud.

Adjusting terminology to align with ISO 31000 can simplify this process, but defining your organization’s risk tolerance threshold is crucial—and often complex.

Coming Next: Determining Your Risk Tolerance and Risk Appetite

Our next post will cover determining your organization’s risk tolerance, examining both likelihood and consequence. Traditional risk assessment frameworks often assign this threshold to an undefined “someone” within the organization. However, this step is both critical and complex in the risk assessment process and requires careful consideration.

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

References

1. (R1) Spink, John W (2019). Food Fraud Prevention – Introduction, Implementation, and Management, Food Microbiology and Food Safety series, Springer Publishing, New York, URL: https://www.springer.com/gp/book/9781493996193
2. (R2) – ISO 31000 Risk Management, International Standards Organization (ISO), Updated 2023, https://www.iso.org/iso-31000-risk-management.html

3. Applying Enterprise Risk Management to Food Fraud Prevention (ERM2), 2017, Food Fraud Prevention Academy, https://foodfraudpreventionthinktank.com/wp-content/uploads/2021/05/BKGFF17-FFI-Backgrounder-2016-ERM-ERM2-v46-2.pdf

There is a price premium for tomato sauce labelled as “natural” or “no artificial additives”.  Citric acid (E330) is a common component of tomato sauces, and the cheapest form is biosynthetic (i.e. it is not “natural”).  There is therefore an incentive for deliberate misrepresentation on the label, and a consequential need for test verification methods as to whether the citric acid is “natural”.  Current reference specifications (e.g. AIJN) do not include tomato sauce.

In this conference presentation (open access) the authors report the successful use of Stable Isotope Ratio Analysis to discriminate the botanical source of the citric acid in tomato sauce  Biosynthesised citric acid is from cane or corn feedstock (C4 plants) whereas inherent tomato citric acid is C3.  The researchers established threshold values for citric acid carbon isotope ratios from authentic “natural” tomato sauces and used these to test a range of products on the market.

Photo by sentidos humanos on Unsplash

Differentiating gelatin species is an analytical challenge because of a lack of intact DNA.  Most speciation methods therefore target the profile of proteins.  Proteins are difficult to analyse - they are too large to measure directly by techniques such as LC-MS, without  prior breaking down, and their folded structure is also an important diagnostic parameter.  This structure is disrupted by many of the sampling and extraction procedures used in analytical method. Analysis of mixed gelatins is particularly difficult.

This method (open access) used a new approach based on the interaction of ethanol with amino acids inside a protein. Ethanol can denature globular proteins by disrupting intraprotein hydrogen bonds due to hydrophobic interactions. However, when added to solutions having proteins with considerable number of α-helices, ethanol can stabilize the protein structure and prevent aggregation. The specific effects of ethanol on protein structure and function can vary depending on the protein's composition and environment.

Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectroscopy was used to leverage ethanol's differential effects on gelatin's amide bands for quantifying pork gelatin contamination in bovine gelatin.

The authors report that the method showed a strong linear correlation between contamination levels and amide band transmission, with detection and quantification limits of 0.85 and 2.85 mg/100 mg (pork in bovine), respectively. It effectively identified pork gelatin in halal candy, with recovery rates from 50.05 % to 103.69 %.

The Food Safety Authority of Ireland (FSAI) 2023 Annual report, published last month, includes a summary of food fraud investigations and outcomes (see p61 onwards).

The FSAI Audits, Incidents and Investigations team conducted 57 investigations and 21 online investigations.  These ranged from warranted searches of premises to the monitoring of social media pages in cases where the online operation of unauthorised food businesses was suspected.  Outcomes included three Closure Orders, two Prohibition Orders and four Compliance Notices. Food safety concerns identified during these investigations necessitated the removal and disposal of more than 141,806 kg of products of animal origin.  The FSAI engaged with online platforms (such as Facebook and Instagram) where illegal food businesses were selling products online. This engagement resulted in two unregistered food businesses’ pages being taken down by the social media sites.

In overview, the report highlights a rise in “complex” food incidents.