Scientists at the University of Aberdeen’s Rowett Institute have developed a groundbreaking tool that can accurately identify the type and breed of meat used in ready-made or shop-bought meals — a step they say will help curb food fraud and protect consumers.
The new system, named MEATiCode, is designed to determine a product’s authenticity, detect cross-contamination, and identify “rogue ingredients” in processed foods. It can analyse multiple types of meat within a single product — a first of its kind, researchers said.
Food fraud — the deliberate misrepresentation or mislabelling of food products — costs the UK an estimated £2 billion annually.
During trials, scientists tested beef, pork, chicken, and lamb samples from various commercial meals. They discovered two cases where the meat content did not match the label: one kebab contained none of the 14% lamb advertised, while another meal labeled as 60% lamb and 20% chicken was found to contain twice as much chicken as lamb. In 17 other samples, the contents matched the claims.
Incorrect labelling poses serious risks for consumers with allergies or those who avoid certain meats for religious reasons, the researchers said.
Project lead Dr. Renata Garbellini Duft explained, “When you buy a burger in the supermarket, you have to trust the label. But using this method, we know exactly what’s inside. In one single experiment, we can detect many different species.”
The MEATiCode process involves analysing meat samples against a database of eight species by identifying unique peptides — short chains of amino acids — that provide a clear biological fingerprint. The technology is so precise it can even detect specific breeds such as Aberdeen Angus.
Garbellini Duft said food misrepresentation is “a growing concern” and expressed hope that the innovation will promote more testing, reduce losses from fraud, and support local meat producers known for their high-quality products.
Following its success in meat identification, the research team plans to extend the technology to detect fraud in honey — described as “one of the most commonly adulterated products” — and later adapt it for whisky authentication and allergen detection in nuts, fish, and dairy products.
Source: BBC