Credit: Food Chemistry (2025). DOI: 10.1016/j.foodchem.2025.144231
A “robust, reliable and highly sensitive” tool that quickly and reliably identifies rogue ingredients, even in processed and cooked foods, has been developed by University of Aberdeen scientists. The work is published in the journal Food Chemistry.
The MEAT-iCode system combines proteomic testing with an advanced database to simultaneously identify multiple meat species in a single processed food sample.
In initia…
Credit: Food Chemistry (2025). DOI: 10.1016/j.foodchem.2025.144231
A “robust, reliable and highly sensitive” tool that quickly and reliably identifies rogue ingredients, even in processed and cooked foods, has been developed by University of Aberdeen scientists. The work is published in the journal Food Chemistry.
The MEAT-iCode system combines proteomic testing with an advanced database to simultaneously identify multiple meat species in a single processed food sample.
In initial lab tests of 19 shop-bought products, a team from the Rowett Institute found that most (17) contained the ingredients listed on the label.
In two cases, however, there were discrepancies. The results from one kebab showed none of the 14% lamb advertised—and another which was said to be 60% lamb and 20% chicken was recorded as containing twice as much chicken as lamb.
Food fraud is estimated to cost the UK £2 billion a year and undermines consumer confidence, a particular concern for the meat industry.
MEATiCode identifies peptides in food samples using liquid chromatography-mass spectrometry (LCMS) then matches them to a bespoke database, providing a clear picture of the origin and quantity of each meat it contains.
It can be deployed in any proteomics lab and is faster than DNA-based and other techniques, able to pinpoint ingredients that make up as little as 0.5% of a sample. It has also been shown to be able to drill down far enough to identify particular breeds, such as Aberdeen Angus.
The Rowett team is also excited by the prospect of adapting the technique to detect allergens such as nuts, fish and dairy products, extending its role in food safety—as well as expanding the database beyond meat to protect other sectors from damaging fraud.
Credit: University of Aberdeen
Dr. Renata Garbellini Duft, who led the project in Rowett Director Professor Jules Griffin’s lab, said, “Food fraud in the meat industry is a growing concern. Cases of mislabeled or adulterated meat have made consumers question what they’re eating and whether it’s safe.
“MEATiCode represents a big step forward in the fight against food fraud. It provides a highly accurate and reliable way to confirm what’s really in meat products.
“With this method, we can protect consumers, support honest suppliers, and improve food safety. As testing methods evolve, we hope to see more widespread adoption of MEATiCode in quality control and regulatory frameworks worldwide.
“Ensuring that meat products are genuine is not just about avoiding allergens or harmful additives—it also protects the value of high-quality meats, and the cultural traditions associated with them.”
Professor Griffin said, “Food fraud is a major challenge to both the consumer and the food industry and it is only getting more complicated in an ever more connected world.
“It’s important we protect both the food we produce and monitor the food we import to make sure we are eating what we think we are eating.
“MEATiCode is one tool in the armory that we now have to protect our food supply chain from illegal or accidental adulteration.”
The research team have liaised closely with Food Standards Scotland and others during the development process to understand how the system can be added to the armory available to bodies tasked with fighting food fraud from an economic and health perspective.
Food Standards Scotland Senior Scientific Advisor Kasia Kazimierczak said, “Food fraud may harm consumers and can put reputable food producers at risk.
“MEATiCode can be used as one of the methods to help safeguard product integrity, acting as a tool that allows verification of authenticity with precision.
“By identifying the presence of undeclared ingredients, it can strengthen consumers’ confidence and supports the credibility of the entire supply chain.”
More information: Renata G. Duft et al, MEATiCode: A comprehensive proteomic LC-MS/MS method for simultaneous species identification in meat authentication, Food Chemistry (2025). DOI: 10.1016/j.foodchem.2025.144231
Citation: Food-fraud breakthrough: New system speedily pinpoints rogue ingredients in popular dishes (2025, November 4) retrieved 4 November 2025 from https://phys.org/news/2025-11-food-fraud-breakthrough-speedily-rogue.html
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