Tag Archives: food fraud

AOAC International

AOAC Sinks Teeth into Cannabis Testing, Launches Food Fraud Program

By Food Safety Tech Staff
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AOAC International

Last week Cannabis Industry Journal, a sister publication of Food Safety Tech, published its interview with AOAC International officials about the organization’s commitment to cannabis lab testing, where it sees this area headed in the future and the launch of its food authenticity and fraud program. AOAC first entered the realm of cannabis testing a few years ago and is making strides to get further involved with “methods regarding chemical contaminants in cannabis, cannabinoids in various foods and consumables, as well as microbial organisms in cannabis,” according to the article. AOAS also recently launched a food authenticity and fraud program to develop standards and methods geared toward economically adulterated foods. Read more about AOAC’s latest development on the food front as well as its push in cannabis lab testing in the article, “Spotlight on AOAC: New Leadership, New Initiatives in Cannabis and Food”.

Susanne Kuehne, Decernis
Food Fraud Quick Bites

In Wine, There Is Not Always Truth

By Susanne Kuehne
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Susanne Kuehne, Decernis
Wine
Records involving wine fraud can be found in the Food Fraud Database. Image credit: Susanne Kuehne

Three arrests were made and at least 11,000 bottles of red wine labeled high-quality IGT Toscana wines have been seized in Italy for containing lower quality wines and fraudulent labeling, misrepresenting the wine’s geographic origin. The investigation was taken to the Europol level in conjunction with German and Italian law enforcement authorities.

Resource

Authorities shutdown international wine fraud operation; three in Italy arrested. Food Safety News. Accessed February 19, 2019.

Susanne Kuehne, Decernis
Food Fraud Quick Bites

Bee Careful What You Eat

By Susanne Kuehne
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Susanne Kuehne, Decernis
Food Fraud, honey
These types of records can be found in the Food Fraud Database
Image credit: Susanne Kuehne

One of China’s most famous health brands has been banned from making honey and issued a steep fine in China after selling expired honey. For a long time, the brand’s “Premium” honey was a supposedly safe alternative in China compared to “fake” honey, mixed with sugar syrup.

Resource

Executives of TCM company in trouble over honey
Wen, X. (February 13, 2019). Executives of TCM company in trouble over honey. Accessed February 13, 2019. Retrieved from http://www.chinadaily.com.cn/a/201902/13/WS5c635b26a3106c65c34e8fba.html

Karen Everstine, Decernis
Food Fraud Quick Bites

How Food Fraud Happens

By Karen Everstine, Ph.D.
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Karen Everstine, Decernis

The food industry has been hard at work over the past few years implementing food fraud mitigation plans in response to Global Food Safety Initiative (GFSI) certification program requirements. GFSI defines food fraud as:

“A collective term encompassing the deliberate and intentional substitution, addition, tampering or misrepresentation of food, food ingredients or food packaging, labelling, product information or false or misleading statements made about a product for economic gain that could impact consumer health.” (GFSI Benchmarking Requirements, 2017)

GFSI then further defines the terminology of food fraud by citing seven categories (shown in the following diagram).

GFSI, Food Fraud
Used with permission from GFSI

In the Food Fraud Database, we categorize food fraud records using the following terminology (with examples):

  • Dilution/substitution
    • Substitution of an entire fish fillet or partial dilution of olive oil with another oil
  • Artificial enhancement
    • Addition of melamine to artificially increase the apparent protein content of milk or the addition of coloring agents to spices
  • Use of undeclared, unapproved, or banned biocides
    • The use of chloramphenicol in honeybee populations (where not permitted) or the addition of hydrogen peroxide to milk
  • Removal of authentic constituents
    • The sale of “spent” spice powder (used in the production of an oleoresin) as a whole spice powder
  • Misrepresentation of nutritional value
    • Infant formula that does not contain the required nutritional content
  • Fraudulent labeling claims
    • Misrepresentation of label attributes related to production method (organic, kosher, halal, etc.)
  • Formulation of an entirely fraudulent product (using multiple adulterants and methods)
    • The sale of “100% apple juice” that consists of sugar, water, malic acid, flavor, and color
  • Other
    • This includes counterfeits, theft, overruns, etc.

Harmonization of food fraud terminology is frequently discussed, so I thought it might be useful to provide information on how our definitions relate to the GFSI terminology:

GFSI category “Dilution”: This category maps directly to our category dilution/substitution. The reason we combine these into one category is that the intent is the same: To replace the weight or volume of a product. This can occur either through partial or full substitution of a liquid product, a granulated product, or swapping an entire intact product such as a fish filet. One of the GFSI examples for substitution is “sunflower oil partially substituted with mineral oil”, which could just as accurately be described as dilution.

GFSI category “Substitution”: As noted above, this category maps directly to our category dilution/substitution. However, we would not consider the use of hydrolyzed leather protein in milk (one of the cited examples) to be dilution/substitution because it is not used to replace weight or volume. We would view that as artificial enhancement of the protein content of milk.

GFSI category “Concealment”: We do not include a category focused on concealment because all food fraud involves concealing some aspect of the true contents of the food. One of the examples cited in this category is “poultry injected with hormones to conceal disease.” The use of antibiotics, anti-fungal agents or other substances to reduce bacterial load or mask deterioration would be classified, in our system, as the use of undeclared, unapproved or banned biocides. The use of coloring agents on fruit to improve appearance would also be classified as artificial enhancement.

GFSI category “Mislabeling”: Since all food fraud is, to some extent, mislabeling, we reserve the use of the term fraudulent labeling claims to those label attributes that describe production processes (organic, kosher, etc.). With the exception of falsification of expiration dates, the other examples cited would not be classified by us as mislabeling. The sale of Japanese star anise, which is potentially toxic, as Chinese star anise (a different species) is dilution/substitution and a health risk to consumers. The sale of cooking oil that has been recovered from waste streams and illegally produced is also a form of substitution that poses a potential health risk to consumers.

GFSI category “Unapproved enhancements”: This GFSI category aligns nicely with our category artificial enhancement, and both examples cited are nicely illustrative of the concept, which involves the fraudulent addition of a substance specifically for its function (not as a replacement for weight or volume).

GFSI Category “Gray market production/theft/diversion”: The production and sale of food products through unregulated channels would all be classified in our category called other. Because these forms of food fraud involve the sale of food outside of regulatory control, prevention measures will generally be substantially different from the prevention of fraud within legitimate supply chains.

GFSI Category Counterfeiting: This GFSI category is similar to the gray market production/theft/diversion category in that it involves intellectual property infringement and production outside of regulatory control. It would similarly be classified in our other category.

Karen Everstine, Decernis
Food Fraud Quick Bites

Media Sources for Food Fraud Intelligence

By Karen Everstine, Ph.D.
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Karen Everstine, Decernis

A recently published paper advocates the inclusion of media reports as a source of information for assessing food fraud vulnerability.1 Those of us who maintain the Food Fraud Database could not agree more. We have been monitoring media reports for years and they are an important source of information in the database (accounting for 45% of all primary source references).

As I mentioned in last month’s post, there are challenges with using media reports to inform food fraud vulnerability. Many media reports are general discussions of the issue of food fraud and are not necessarily reporting new information. It may be difficult to filter out these types of reports without manual review. There may also be concerns about the validity of media reports on food fraud. This is the reason we implemented a classification for “weight of evidence” for incident records in the database. Overall, approximately 30% of the incident records in our database are classified as a “low” weight of evidence due to unverifiable data or a lack of corroborating reports. Some of our users choose to filter these out of their searches.

We have received requests for information about how the data in the Food Fraud Database compares with numbers reported in the paper. Table 11 in the paper described the top product categories, countries and type of fraud as reported in four food safety tracking systems.1 We have adapted that table below to data from the Food Fraud Database.

Product Category % Country of Origin % Type %
Meat/Poultry 18 India 26 Dilution/substitution (misrepresentation of animal origin) 26
Seafood 16 China 9 Dilution/substitution (“other”) 19
Dairy Products 14 United States 9 Dilution/substitution with a non-food substance 14
Alcoholic Beverages 6 Columbia 6 Dilution/substitution (misrepresentation of botanical origin) 12
The most common food fraud records (“cases”) in the Food Fraud Database (2014-2015)

As shown in Table 11 in the paper, the top four products by number of articles in the media monitoring system (in 2014-2015) were meat, seafood, milk and alcohol. As shown above, when looking at data in the Food Fraud Database from 2014 and 2015, the top ingredient categories are very similar: Meat/Poultry, Seafood, Dairy Products, and Alcoholic Beverages. However, there was little agreement in the country of origin of the reported cases among any of the systems. For the Food Fraud Database (shown above), the top countries of origin in 2014–2015 were India, China, the United States and Colombia. According to the paper, the top countries of origin reported by the food fraud media monitoring system were Egypt, the United States, the U.K. and Saudi Arabia. The top country of origin reported by RASFF was China and by HorizonScan was the Czech Republic.

Table 4 reported the “types” of food fraud (which correspond to what we call “reasons for adulteration”) and the corresponding number of articles collected, which we have also adapted to the data in the Food Fraud Database below.

Types of Food Fraud in Records in the Food Fraud Database (2014–2015)
Type of Food Fraud Number of Records %
Dilution/substitution – misrepresentation of animal origin 212 26
Dilution/substitution (other) 159 19
Dilution/substitution with a substance not approved for use in foods 118 14
Dilution/substitution – misrepresentation of botanical origin 101 12
Unknown 87 11
Fraudulent labeling 64 8
Artificial enhancement of apparent protein content 58 7
Artificial enhancement with color additives 57 7
Other 41 5
Dilution/substitution – misrepresentation of geographic origin 40 5
Dilution/substitution – misrepresentation of varietal origin 28 3
Use of unapproved biocides (antibiotics, anti-fungal agents, preservatives, etc.) 21 3
Artificial enhancement (other) 7 1
Formulation of an entirely fraudulent product using multiple techniques and adulterants 2 0
TOTAL 828 *
* Greater than 100% because one record can have multiple types of associated fraud

It is not possible to make meaningful comparisons among the reported fraud “types” without harmonized definitions and standardization of data collection processes, as noted in the paper. A glance at Table 1 from the paper illustrates the variety of food fraud categorizations in use among the various systems.1 Generally, it is a challenge to directly compare any of the information coming from various sources such as RASFF, HorizonScan, the Food Fraud Database and others, due to the differences in the way data is collected, standardized and reported.

In contrast with foodborne illnesses, which are generally required to be reported to public health agencies, food fraud typically does not result in acute illness and is difficult to track. The nature of food fraud combined with differences in data tracking systems make it almost impossible to reconcile the data among the various systems. Regardless of which system is reporting, the reports are likely just a fraction of the true occurrence of food fraud; however, each can provide valuable perspective on risks to food safety (including those from food fraud). A holistic assessment of food fraud vulnerability should take into account a wide variety of information sources, including media reports.

Reference

  1. Bouzembrak, Y., et al. (November 2018). Development of food fraud media monitoring system based on text mining. Food Control. Vol. 93. Retrieved from https://doi.org/10.1016/j.foodcont.2018.06.003
magnifying glass

Food Safety Tech’s Best of 2018

By Food Safety Tech Staff
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magnifying glass

The end of the year is always a time of reflection. At Food Safety Tech, it is also a time when we like to share with you, our readers, the most popular articles over the last 12 months. Enjoy, and thank you to our loyal and new readers, as well as our contributors!

10. Three Practices for Supply Chain Management in the Food Industry

By Kevin Hill, Quality Scales Unlimited

9. Food Investigations: Microanalytical Methods Find Foreign Matter in Granular Food Products

By Mary Stellmack, McCrone Associates, Inc,

8. Stephen Ostroff to Retire from FDA, Walmart’s Frank Yiannas to Take the Reins

By Food Safety Tech Staff

7. FDA Inspections: Top Five Violations for FY2017

By Food Safety Tech Staff

6. Is There Any End in Sight for the E.Coli Outbreak in Romaine Lettuce?

By Food Safety Tech Staff

5. CDC Alert: Do Not Eat Romaine Lettuce, Throw It Out

By Food Safety Tech Staff

4. Five Tips to Add Food Fraud Prevention To Your Food Defense Program

By Melody Ge, Kestrel Management

3. 5 Problems Facing the Global Supply Chain

By Sean Crossey, arc-net

2. FDA: 172 Ill, 1 Death, Romaine Lettuce E. Coli Outbreak Likely Over

By Food Safety Tech Staff

1. Romaine Lettuce Outbreak: We Knew It Would Get Bad Quickly

By Maria Fontanazza, Food Safety Tech

Karen Everstine, Decernis
Food Fraud Quick Bites

Recent Notable Incidents

By Karen Everstine, Ph.D.
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Karen Everstine, Decernis

We developed a system that tracks food fraud records using four categories: Incidents, inference records, surveillance records and method records. Food fraud incidents are documented occurrences of fraud that include contextual information about location, perpetrators, timeframe, geographic location and other characteristics. In many ways, incidents are the gold standard of food fraud records. However, there have been unsubstantiated reports of food fraud that were subsequently discredited (such as the “plastic rice” scandal of a few years ago). For this reason, for every incident we capture, we assign a “weight of evidence” classification to provide our assessment of the strength of the evidence. For example, incidents reported directly by regulatory agencies with supporting documentation will generally be assigned a “high” weight of evidence classification.

We also work diligently to avoid “double counting” food fraud incidents, although at times this can be challenging. Incidents may be reported in multiple media outlets and, at times, the reports may not include enough information to determine if it is a new report or related to an issue already reported. We cross-reference the dates and locations of reports, along with information about the ingredients and adulterants, to help ensure that isolated food fraud cases are reported as one incident.

Food fraud, Decernia
Food fraud incidents since 1980. (Source: Decernis Food Fraud Database)

Incidents we have captured in the past two months include $14 million of counterfeit wine discovered in China, which was reportedly based on a tip off. The Carabinieri and ICQRF in Italy discovered wines with added flavorings and other additives. The Guardia di Finanza in Italy also seized adulterated extra virgin olive oil. Counterfeit liquor was discovered in Russia and bootleg liquor containing methanol caused deaths in Malaysia.

Expired (possibly rotting) eggs intended to be powdered and used in food production were discarded by regulatory authorities in India. A customer in China reported that expired carrots were being re-labeled with new dates. Adulterated milk was discovered in Pakistan. In Kenya, reports surfaced of sodium metabisulfite being used on meat to enhance its appearance. Finally, in the United States, two companies were indicted for importing giant squid and selling it domestically as octopus (which usually has a higher retail price) over a period of three years. A review of these reports illustrates how challenging it can be to collect and standardize food fraud information, especially when it is reported in media sources.

Karen Everstine, Decernis
Food Fraud Quick Bites

“Natural Flavor” Claims

By Karen Everstine, Ph.D.
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Karen Everstine, Decernis

The company that produces the very popular flavored sparkling water brand LaCroix is facing a class action lawsuit that alleges false claims of the product being “all natural.” The suit alleges that certain flavor chemicals used in the beverage are, in fact, artificial ingredients. These flavor chemicals include limonene, linalyl propionate (linalool propionate), linalool and ethyl butyrate (ethyl butanoate). While these flavor chemicals can be synthesized, they are naturally occurring chemical constituents and can therefore be derived from natural sources.

The safety of the beverages is not at issue; this is a labeling question. The suit states that linalool is “used in cockroach insecticide,” which is inflammatory and misleading. Chemical compounds, including those used as food ingredients, naturally have multiple applications and this does not have any bearing on the question of whether they are safe to use in foods.

Presumably, the labeling issue of whether these flavor chemicals were naturally or synthetically derived will be addressed as the suit progresses. This suit does, however, highlight some of the challenges we have in tracking food fraud information related to flavors.

Flavors are big business. Appealing flavors enabled LaCroix to make unsweetened sparkling water explode in popularity. If you have been on the Institute of Food Technologists Annual Meeting expo floor, you have seen the prominent displays and creative food samples offered up by the big flavor houses. It is a competitive business and very proprietary. The FDA labeling requirements for flavors allow them to be listed generally as “spice,” “natural flavor,” or “artificial flavor” (or a combination of those). This makes tracking and standardizing public records of food fraud related to flavors challenging.

Our data includes more than 60 of food fraud related to flavors represented as “natural.” Most of these records are linked to vanilla extract or various essential oils. However, we have also captured a handful of records that address misrepresentation of synthetic flavor chemicals as naturally-derived. This includes records for linalool and ethyl butyrate, among others such as vanillin and linalyl acetate. However, none of these records describe publicly reported incidents of fraud for naturally-derived flavor chemicals. The records are based on peer-reviewed publications aimed at method development for authentication of natural flavors.

Added value claims such as “natural” tend to increase food fraud risk because the costs of production can be so much higher. While an ingredient like vanilla extract is certainly one example of this, we do not tend to see the same level of evidence of food fraud potential for naturally-derived flavor chemicals in public records. When our users need to conduct a food fraud vulnerability assessment for a natural flavor that is a proprietary blend of flavor chemicals, we suggest that they incorporate information from the entire natural flavors group into their assessment. Given the proprietary nature of flavor blends and FDA labeling requirements, it is not feasible for us to track every individual flavor blend in our database.

Fortunately, given the importance of flavors to the food industry, flavor companies have a vested interest in preserving their client relationships and public reputation by ensuring flavors labeled as “natural” qualify for that label claim.

Resources

  1. The Decernis Food Fraud Database is a continuously updated collection of food fraud records curated specifically to support vulnerability assessments. Information is gathered from the scientific literature, regulatory reports, media publications, judicial records, and trade associations from around the world and is searchable by ingredient, adulterant, country, and hazard classification.

—Update— February 19, 2020: National Beverage Corp.announced dismissal of “all of the allegations contained in a prior lawsuit which challenged LaCroix’s natural ingredient labeling.” –END Update–

Karen Everstine, Decernis
Food Fraud Quick Bites

A Look at Fraudulent Labeling Practices

By Karen Everstine, Ph.D.
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Karen Everstine, Decernis

Food fraud happens in many ways, and it can be challenging to categorize the various methods of fraud. Dilution and/or substitution involves the intentional addition of an alternate product with the intent to replace weight or volume (olive oil, juices and fish are prone to this type of fraud). Artificial enhancement is the addition of a substance that is not intended to replace weight or volume, but to have a functional effect (such as the use of industrial dyes in spices). Certain forms of food fraud, such as theft/resale, counterfeit packaging, or overruns may not involve the addition of alternate ingredients. However, as customers and consumers, we would be taking a risk to trust the safety of any foods that are intentionally misrepresented.

Food Fraud
Categories of methods by which food fraud happens (as defined in the Food Fraud Database1). Graphic courtesy of Decernis

While all forms of fraud can be considered “mislabeling” in one way or another, we consider fraudulent labeling claims to be defined as misrepresentation of a label attribute that implies a particular production technique. Examples include representing non-organic products as organically produced, the sale of foods as halal that do not meet the appropriate standards, changing poultry expiration dates, and labeling products such as eggs and Iberian ham as “free range.” In 2017, a company in Canada was fined for selling falsely labeled kosher cheese. More recently, in Malaysia, millions of products were seized based on the use of fraudulent halal labels.

We have compiled more than 300 records of food fraud involving the use of fraudulent labeling claims. The most common fraudulent claims identified in our records are shown in the chart below.

Fraudulent labeling claims
Fraudulent labeling claims based on records reported in the Food Fraud Database.1

Consumer interest in organic foods is increasing and NSF cites “added value claims” such as organic and free range as one of the important factors driving food fraud risk.2 There continues to be a need for robust analytical tools for the authentication of organic foods. However, recent research has indicated it may be unlikely that authentication of these food products can be can be achieved by a single analytical method or the measurement of a single marker.3,4 Given the technical complexity and cost of ensuring the authenticity of organic label claims through analytical testing, preventing this type of food fraud also requires strong supply chain management and trustworthy supplier relationships along with effective auditing programs.

References

  1. The Decernis Food Fraud Database is a continuously updated collection of food fraud records curated specifically to support vulnerability assessments. Information is gathered from the scientific literature, regulatory reports, media publications, judicial records, and trade associations from around the world and is searchable by ingredient, adulterant, country, and hazard classification.
  2. NSF, “Risk Modelling Of Food Fraud Motivation – ‘NSF Fraud Protection Model’ Intelligent Risk Model Scoping Project FS 246004.” (2014). Retrieved from https://www.food.gov.uk/sites/default/files/media/document/NSF%20Final%20report.pdf.
  3. Inacio, CT and Chalk, PM. (January 2017) Principles and limitations of stable isotopes in differentiating organic and conventional foodstuffs: 2. Animal products. Crit Rev Food Sci Nutr.. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/25849871
  4. Capuano, E., et al. (September 11, 2012). Analytical authentication of organic products: an overview of markers. Journal of the Science of Food and Agriculture. (Vol. 93) No. 1. https://doi.org/10.1002/jsfa.5914
Food Fraud

Food Fraud: How Chemical Fingerprinting Adds Science to the Supply Chain

By Sam Lind, Ph.D.
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Food Fraud

You would be forgiven for thinking that food fraud is a sporadic issue but, with an estimated annual industry cost of $50 billion dollars, it is one currently plaguing the food and drink sector. In the UK alone, the food and drink industry could be losing up to £12 billion annually to fraud.

As the scale of food fraud becomes more and more apparent, a heightened sensitivity and awareness of the problem is leading to an increasing number of cases being uncovered.

Recently: Nine people contracted dangerous Vibrio infections in Maryland due to mislabeled crabmeat from Venezuela; food fraud raids have been conducted in Spain over fears of expired jamon re-entering the market; and authorities seize 1 ton of adulterated tea dust in India.

Spurred by the complexity of today’s global supply chains, food fraud continues to flourish; attractive commercial incentives, ineffective regulation and comparatively small penal repercussions all positively skew the risk-reward ratio in favor of those looking to make an extra dollar or two.

The 2013 horsemeat scandal in Europe was one such example, garnering significant media attention and public scrutiny. And, with consumers growing more astute, there is now more onus on brands to verify the origin of their products and ensure the integrity of their supply chains.

Forensic science is a key tool in this quest for certainty, with tests on the product itself proving the only truly reliable way of confirming its origin and rooting out malpractice.

Current traceability measures—additives, packaging, certification, user input—can fall short of this: Trace elements and isotopes are naturally occurring within the product and offer a reliable alternative.

Chemical Fingerprinting for Food Provenance

Like measuring the attributes of ridgelines on the skin of our fingertips as a unique personal identifier, chemical fingerprinting relies on differences in the geochemistry of the environment to determine the geographic origin of a product—most commonly measured in light-stable isotopes (carbon, nitrogen, sulphur, oxygen, hydrogen) and trace elements.

Which parameters to use (either isotopes, TEs or both) depends very much on the product and the resolution of provenance required (i.e. country, farm, factory): Isotope values vary more so across larger geographies (i.e., between continents), compared to smaller scales with TEs, and are less susceptible to change from processing further down the supply chain (i.e., minced beef).

The degree of uptake of both TEs and light isotopes in a particular produce depends on the environment, but to differing extents:

TEs are related to the underlying geochemistry of the local soil and water sources. The exact biological update of particular elements differs between agricultural commodities; some are present with a lot of elements that are quantifiable (“data rich” products) while others do not. We measure the presence and ratio of these elements with Inductively Coupled Plasma—Mass Spectrometry (ICP-MS) instrumentation.

Light Isotopes are measured as an abundance ratio between two different isotopes of the same element—again, impacted by environmental conditions.

Carbon (C) and nitrogen (N) elements are generally related to the inputs to a given product. For example, grass-fed versus grain-fed beef will have a differing C ratio based on the sugar input from either grass or grain, whereas conventionally farmed horticulture products will have an N ratio related to the synthetic fertilisers used compared to organically grown produce.

Oxygen (O) and hydrogen (H) are strongly tied to climatic conditions and follow patterns relating to prevailing weather systems and latitude. For ocean evaporation to form clouds, the O/H isotopes in water are partitioned so that droplets are “lighter” than the parent water source (the ocean). As this partitioning occurs, some droplets are invariably “lighter” than others. Then, when rainfall occurs, the “heavier” water will condense and fall to the ground first and so, as a weather front moves across a landmass, the rainfall coming from it will be progressively “lighter”. The O/H ratio is then reflected in rainfall-grown horticultural products and tap water, etc. Irrigated crops (particularly those fed from irrigation storage ponds) display different results due to the evaporation, which may occur over a water storage period.

Sulphur (S) has several sources (including anthropogenic) but is often related to distance from the sea (“the sea spray effect”).

Analysis of light isotopes is undertaken with specialist equipment (Isotope Ratio Mass Spectrometry, IRMS), with a variety of methods, depending on product and fraction of complex mixtures.

Regardless of the chemical parameter used, a fingerprinting test-and-audit approach requires a suitable reference database and a set of decision limits in order to determine the provenance of a product. The generation of sample libraries large enough to reference against is generally considered too cost prohibitive and so climatic models have been developed to establish a correlation between observed weather and predicted O/H values. However, this approach has two major limitations:

  1. The chemical parameters related to climate are restricted (to O and H) limiting resolving power
  2. Any model correlation brings error into further testing, as there is almost never 100% correlation between measured and observed values.
    As such, there is often still a heavy reliance on building suitable physical libraries to create a database that is statistically robust and comprehensive in available data.

To be able to read this data and establish decision limits that relate to origin (i.e., is this sample a pass or fail?), the parameters that are most heavily linked to origin need to be interpreted, using the statistics that provide the highest level of certainty.

One set of QC/diagnostic algorithms that use a number of statistical models have been developed to check and evaluate data. A tested sample will have its chemical fingerprint checked against the specific origin it is claimed to be (e.g, a country, region or farm), with a result provided as either “consistent” or “inconsistent” with this claim.

Auditing with Chemical Fingerprints

Chemical fingerprinting methods do not replace traditional traceability systems, which track a product’s journey throughout the supply chain: They are used alongside them to confirm the authenticity of products and ensure the product has not been adulterated, substituted or blended during that journey.

A product can be taken at any point in the supply chain or in-market and compared, using chemical fingerprinting, to the reference database. This enables brands to check the integrity of their supply chain, reducing the risk of counterfeit and fraud, and, in turn, reducing the chance of brand damage and forced product recalls.

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