3 tips on how your business avoid becoming a victim of food fraud

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The illustration is made by Sørensen et al.

By Klavs Martin Sørensen, postdoc at the Department of Food Science at the University of Copenhagen –  researching the use of food analysis using rapid methods including the use of near-infrared spectroscopy (NIRS).

Your business can avoid food fraud by implementing Process Analytical Technology (PAT), including so-called “rapid methods” for quality control. The NIRS method of analysing or fingerprinting ingredients or raw materials using near-infrared spectroscopy is currently our best bet for detecting food fraud. Three tips for how to avoid ending up as a victim of food fraud could therefore be:

1) Establish procedures for entry control of all raw materials into the company. Here is a consideration of how to take a representative sample of your raw materials. If it is a homogeneous mass, you might just open a valve on a tanker and take a sample. But companies also have goods delivered in the form of dry goods in large bags, where what is at the bottom of the bag may be different than what is at the top and you may have to take samples from several locations.

2) Use analytical methods to get immediate answers – at the Department of Food Science, our most obvious answer is to use near-infrared spectroscopy if you want to measure all raw materials as they come into production.

3) Use the same equipment to test your company’s finished product. This is not about food fraud, but many companies have embraced near-infrared spectroscopic analytical methods, because this type of analysis can ensure that you deliver what you have promised to customers. A consistently high quality.

More and more companies we meet with make use of near-infrared spectroscopy when they have to examine their raw materials and end products and the method has made life much easier for them. Near-infrared spectroscopy, as noted, provides immediate answers and it does not destroy the raw material. In the past, you had to take samples that were then sent to a chemical laboratory, resulting in long response times.

Both small and large companies can benefit from the method, and it has been difficult for us to find an industry where you would not be able to further quality assurance with NIRS. At the Department of Food Science at the University of Copenhagen, we research the use of, among other things, NIRS and the use of the data that is produced. We look for new algorithms that can be used to monitor productions and new methods that can detect food fraud with an even greater level of detail than we can today.

From Food Authenticity to Food Fraud

In the article in Current Opinion in Food Science, the researchers defined the following 3 degrees of undesired modifications of food:

Food Fraud

Intentional misrepresentation of foods, food raw materials and ingredients, typically with the aim of artificially augmenting a quality parameter of the food item. This includes the use of prohibited substances, contamination of the product and other non-compliances to product descriptions. Food fraud can in many cases be detected by NIR spectroscopy.

Food Adulteration

Undeclared introduction of an additional cheaper substance to foods, food raw materials and ingredients with the aim of artificially augmenting the quantity of the authentic food item. Adulteration testing is both qualitative and quantitative. Food adulteration can in many cases be detected by NIR spectroscopy.

Food Authenticity

Refers to the truthfulness of the quality of foods, food raw materials and ingredients including the origin, variety, original production recipes, producers, applied methods, geographical location and time. Authenticity testing is not quantitative and could be detected by NIR spectroscopy to a limited extent.

NIR spectroscopy
Near-infrared spectroscopy can provide a physicochemical fingerprint of a biological sample (e.g. a foodstuff). This is done by sending near-infrared light into the foodstuff and then measuring the light that is sent back (not absorbed). The fingerprint will often contain 1000+ spectral variables that each relate to the physicochemical composition of the foodstuff in their own unique way. You can hold this fingerprint (called a spectrum) against a validated fingerprint of the same sample material by using multivariate data analysis (chemometrics). The measurement will detect fluctuations in many different ingredients at once, which is why it is a called a holistic and “non-targeted” method of analysis.

 

*Klavs Martin Sørensen is co-author of the article “The use of rapid spectroscopic screening methods to detect adulteration of food raw materials and ingredients”. The article has been published as an expert opinion in the scientific journal Current Opinion in Food Science. Read the article here. Other authors are postdoc Bekzod Khakimov and Professor Søren Balling Engelsen – also from the Department of Food Science (FOOD) at the University of Copenhagen.