Food fraud detection: a low-cost approach

Food fraud can cause billions of dollars in economic damage every year. Now botanists at the University of Basel have developed a model that can be used to determine the origin of food in a low-cost manner. The new method has been tested and validated on strawberries.

The most common type of food fraud is false labelling concerning the country of origin in order to maximise profits. For example, strawberries from Switzerland or olive oil from Italy can be sold at much higher prices than the same products from other countries. Food authorities and the food industry spend a great deal of time fighting false declarations of geographical origin, which is estimated to cost up to $50 billion each year.

One method for detecting food fraud is to determine the δ18O (delta-O-18) value of a product sample, which characterises the oxygen isotope ratio. Until now, this procedure has been time-consuming and costly as 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.

Basel botanist Dr Florian Cueni has now developed a model in collaboration with Agroisolab, a company specialising in isotope analysis. This model is intended for use in simulating the oxygen isotope ratio in plants from individual regions, thereby eliminating the need for the time-consuming collection of reference data. The model 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.

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.

“With minor adjustments to the parameters, our model can be used to determine all plant products,” said Professor Ansgar Kahmen, who led the research project. This makes it possible to simplify and speed up conventional isotope analysis by simulating the regions of origin of agricultural foodstuffs.

In addition to food industry applications, the model is of interest to food forensics officials, drug-investigating authorities, and even NGOs such as WWF or Greenpeace with regard to determining the origin of illegally logged timber.

The research study was published in the journal Scientific Reports.

Image credit: ©stock.adobe.com/au/Kheng Guan Toh