Food fraud: Scientists develop ‘low-cost’ country of origin detection method

Food fraud: Scientists develop ‘low-cost’ country of origin detection method

Fraud drains costs the global food industry an estimated $30 to $40 billion every year, PricewaterhouseCoopers estimates. According to the Consumer Brands Association, roughly 10% of commercially produced food and beverage products are affected by fraud.

False claims can take many forms, from tampering and adulteration to misrepresentation and substitution. Scientists at the University of Basel in in Switzerland set out to address a common problem of food fraudulently placed on the market: false country of origin claims.

Strawberries from Switzerland or olive oil from Italy can be sold at much higher prices than the same products grown or manufactured in a different country. The economic motivation for fraudsters means the authorities and food industry invest a significant amount of time and money trying to fight false declarations of origin, the researchers noted.

One method for detecting food fraud is to determine the δ18O (delta-O-18) value of a product sample, which characterizes the oxygen isotope ratio. Until now, this procedure has been highly time consuming and costly. A case of suspected fraud involved not only collecting reference data from the claimed country of origin, but also comparative data from other regions to validate or disprove the product’s origin.

Cutting costs through model calculationBasel botanist Dr. Florian Cueni has now developed a new model in collaboration with Agroisolab GmbH, a company specializing in isotope analysis. The research has been published in journal Scientific Reports.​ 

This model is intended for use in simulating the oxygen isotope ratio in plants from individual regions, eliminating the need for the time-consuming collection of reference data. It is based on temperature, precipitation and humidity data and information about the growing season of a plant, all of which are available from publicly accessible databases, the recently published study revealed.

Dr Cueni tested and validated the model on a unique δ18O reference dataset for strawberries collected across Europe over 11 years. “The case study has shown that the model can simulate the origin of the strawberries with a high degree of accuracy,”​ the researchers concluded.

A ‘wide range’ of usesThis model can be applied to much more than strawberries to determine country of origin.

“With minor adjustments to the parameters, our model can be used to determine all plant products,”​ explained Professor Ansgar Kahmen, who led the research project.

This means it is possible to simplify and speed up conventional isotope analysis by accurately simulating the regions of origin of agricultural foodstuffs, driving down cost in the process.

The model is of interest to food forensics officials or the investigating authorities and can actually be applied to applications outside the food industry, the Basel scientists noted. This could include determining the origin of confiscated drugs, for example. They also pointed to its use by private forensic institutes that inspect food or serve as expert witnesses in court. Meanwhile, NGOs such as WWF or Greenpeace are also interested – especially with regard to determining the origin of illegally logged timber. As is the food industry, which suffers reputational damage due to the sale of products that may have been falsely declared.

Source​

‘Using plant physiological stable oxygen isotope models to counter food fraud’​

Scientific Reports​

DOI: 10.1038/s41598-021-96722-9

Authors: Florian Cueni, Daniel B. Nelson, Markus Boner & Ansgar Kahmen

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