Food Fraud and Authenticity Testing

Introduction

Food fraud frequently refers to a variety of intentional frauds. The deliberate adulteration of food for financial gain is one sort of food fraud. This is the purposeful substitution, diluting, or adding of food products, as well as the removal or replacement of genuine ingredients without the customer's awareness, all for the seller's financial gain. Olive oil, fish and seafood goods, honey, maple syrup, some fruit juices, animal products, spices, coffee, tea, and organic items are the food categories most impacted.⁽¹⁾

1. Why it is important to prevent Food fraud

Although food fraud is not intended to cause harm, it can cause serious illness or even death. When melamine was used as a nitrogen source to fraudulently increase the measured protein content of milk in 2008, it resulted in more than 50000 children being hospitalized and six deaths ⁽³⁾

Fraud Prevention process

A management system for food fraud is an ongoing procedure. It begins with a stage of evaluation to identify the weaknesses in food fraud, then moves on to the design, review, and implementation of mitigation...⁽⁴⁾

These activities aided in raising awareness of the issue of food theft among government and industry organizations. The Global Food Safety Initiative (GFSI) has already included strategies to mitigate these hazards in the sets of schemes it has acknowledged. Since January 2015, these ideas have been incorporated into the British Retail Consortium's (BRC) standard. Additionally, this topic is covered in the most recent iterations of the Safe Quality Food (SQF) and Food Safety System ⁽⁵⁾

Vulnerability assessment

The following 3 aspects must be evaluated in order to determine an ingredient's susceptibility to food fraud

• Vulnerability caused by the ingredient's properties

The steps taken by the buyer to reduce the risk of fraud have nothing to do with factors such as ingredient market price, history, composition, physical state, or level of processing. This is known as an ingredient's inherent susceptibility. Some ingredients are more prone to adulteration by nature (e.g., Apple chunks are less vulnerable than apple liquids or purees.) ⁽⁶⁾

• Vulnerability caused by external factors affecting the business

The level of demand (quantity) for an ingredient, its range of application (it is used in a variety of goods and businesses), or market price fluctuations can all increase a product's vulnerability to fraud. ⁽¹⁾

• Vulnerability caused by factors under the buyer's control

This indicates the effectiveness or ineffectiveness of a company's mitigation strategy (full traceability, adequate purchasing specifications, availability of analytical methods, and robustness of surveillance programmers). ⁽¹⁾

It is critical to remember that vulnerability assessment is a continuous process that must be kept up to date in light of new information and external pressures.

2. Regulations

The mitigation of food fraud and adulteration is a key component of food safety management systems, according to new benchmarking guidelines published by the Global Food Safety Initiative (GFSI). Food fraud vulnerability assessments and mitigation plans have been or are currently being incorporated by all GFSI benchmarked Certified Program Owners into their certification requirements. The requirement for the food business to prevent food fraud is reinforced by the FDA Food Safety Modernization Act in the U.S. and rules that are being reviewed in Europe.⁽⁶⁾

The methods required by non-GFSI standards for a food industry to combat food fraud differ. Some specify or recommend a VACCP programme, which is focused on activities for assessing the risk of food fraud. Others, like AIB, demand that risks of food fraud be taken into account throughout the supplier approval procedures. The Food Safety Modernization Act (FSMA) laws mandate that food companies identify risks from economically driven food fraud, such as adulteration, and put preventative controls in place to reduce the risks.

There are several noticeable variances amongst the most well-known standards. For example, while the BRC Food Safety Standard simply calls for businesses to examine the risks from adulteration or substitution activities, the SQF Food Safety Code mandates that food businesses assess and manage the risks from food fraud of the counterfeit type. While the SQF and IFS standards specifically address food fraud training, BRC mandates horizon scanning operations.

The current requirements of each of the main food safety standards are compared in the table below. ⁽⁷⁾

The full names of the standards are: AIB International Consolidated Standards for Inspection of Prerequisite and Food Safety Programs, 2023 BRCGS Global Standard Food Safety, Issue 9 FSSC 22000, Version 5.1 Global G.A.P. Integrated Farm Assurance (IFA), Version 5.4-1 IFS Food, Version 7 SQF Food Safety Code, Edition 9⁽⁷⁾

3. Testing Methods:

Testing for food frauds can be done in one of two ways, depending on the degree of vulnerability and type of fraud committed.

• Targeted analysis
• Non-Targeted analysis

When the adulterants are known or the suspect food contains naturally occurring markers—physical, biological, or chemical—that can expose its identity or purity, targeted analysis is used.

A non-targeted strategy is taken into consideration if the adulterating elements are new or have not been previously detected because a targeted approach will not be able to trace them using standard analytical procedures.

Physical Methods

Physical approaches that are frequently employed for the detection of food adulteration include microscopic and macroscopic visual structure examination as well as physical parameter analysis (e.g., morphology, texture, solubility, bulk density, etc.).

Chemical Methods

The most used chemical testing technique at the moment is liquid or gas chromatography in combination with mass spectrometry since it makes it easier to detect analytes at low concentrations, even in extremely complex food matrices.

Nuclear magnetic resonance (NMR) spectroscopy is a fingerprinting technology that can identify the physical and chemical characteristics of the atoms within a molecule and provide useful structural information. Solids, liquids, and complicated mixes are just a few of the sample types that can be studied with NMR spectroscopy. ⁽⁷⁾

Biological methods

The detection of adulterants, which are biological molecules, is best accomplished with DNA-based molecular methods. For the purpose of identifying adulterants in food items, three main techniques are used: approaches based on PCR, sequencing, and hybridization

4. Eurofins Services:

• Eurofins offers NMR based (high-resolution Nuclear Magnetic Resonance) profiling for evaluating all types of honey. This cutting-edge high-throughput method gives a variety of information that is both targeted (quantification of specific chemicals) and non-targeted (identifying deviations from reference spectra).
• Animal products must be genuine and authentic to meet the demands of the market today. An important factor in determining a product's authenticity and marketability is its species. Eurofins provide a variety of techniques and standard operating procedures for identifying animal species, including ELISA, qualitative real-time PCR, quantitative real-time PCR, and mitochondrial DNA sequencing.
• Eurofins is also an expert in authenticity analyzes in the herbs and spices segment. The "NGS" (Next Generation Sequencing) and the "NMR profiling" are two newly developed techniques that can be used to analyses herbs and spices in addition to the traditional techniques. Both of these supposedly "non-targeted" analyses are distinctive in that they can respond to a range of adult queries. By employing these processes, among other things, we Eurofins can raise the level of authenticity of herbs and spices. Our NMR profiling method in particular allows us to reveal what is "hidden" beneath the iceberg's tip. Additionally, we provide the option to locate the source of raw materials using our patented SNIF-NMR technology.
• When it comes to PDO (Protected Denomination of Origin) certification, Eurofins additionally provides the option of setting up a targeted analytical strategy and particular data banks to aid in protecting producers from fraudulent imitations of their products or false declarations of geographic origin.

Our particular expertise:

Fruit juice and derived products, Honey, Maple Syrup: detection of addition of sugar, water, colorings, aromas or other undeclared additives, determination of fruit content

Wines, Ciders: detection of chaptalization, sugaring, dilution or addition of glycerol, checking the process used in sparkling products, conformity to the isotopic profile

Spirits, Beers: control of the botanical origin of the alcohol, detection of addition of water, sugars or flavors (according to current regulations and/or product specifications)

Flavors: checking whether a flavor is natural (vanilla, aniseed, bitter almond, cinnamon, linalool, etc.)

Caffeine: checking for natural or synthetic sources in tea, coffee or guarana-containing drinks

Meat products: confirmation of animal species

Fish: confirmation of species and of origin (wild farmed)

Dairy products: confirmation of the main feed used (grass or maize silage), detection of the addition of lipids, lactose or casein, check flavorings (e.g., fruit, vanilla)

Cereals: confirmation of variety

Basmati rice: quantification of the amount of basmati present in rice

References:

1. https://www.linkedin.com/pulse/food-fraud-prevention-foodsafety-standard
2. https://www.isothai.com/forums/index.php?app=core&module=attach§ion=attach&attach_id=10672
3. https://www.scribd.com/document/323796374/Food-Fraud-Prevention
4. https://www.eurofins.com/assurance/food/services/consulting-labelling/food-fraud-management/
5. https://books.google.com/books?id=SCxeDgAAQBAJ
6. https://mygfsi.com/wp-content/uploads/2019/09/Food-Fraud-GFSI-Technical-Document.pdf
7. https://foodfraudadvisors.com/facts-stories-news-advice/
8. https://www.lifeasible.com/custom-solutions/food-and-feed/food-testing/authenticity-testing/

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