Food scientists at the Institute of Food Research on the Norwich Research Park have teamed up with Oxford Instruments to develop what they claim is a fast alternative to DNA analysis.
Because horses and cattle have different digestive systems, the fat components of the two meats have different fatty acid compositions, the team claims.
The new method looks at differences in the chemical composition of the fat in the meats, using similar technology to a hospital magnetic resonance imaging (MRI) scanner, used for example to scan brains.
A technician could determine whether a piece of raw meat originated from a horse or a beef herd.
The method, developed with funding from Innovate UK and the Biotechnology and Biological Sciences Research Council (BBSRC) had recently been trialled in an industrial setting by a leading meat processor, said the IFR.
It is currently being extended by the team of scientists to test for other meat species, including pork and lamb.
Last year’s horsemeat scandal exposed the potential vulnerability of the meat supply chain to fraud and even to threats to public health, and highlighted gaps in testing.
The currently favoured method of meat species testing relies on DNA, which can tell one meat from another based on the genetic makeup of the source animals. But it was relatively slow and expensive and prone to contamination if not used carefully, said IFR.
In response to this, a new method using a totally different approach has been developed by Oxford Instruments and IFR.
The key technology is the ‘Pulsar’, a high resolution, small bench-top nuclear magnetic resonance spectrometer developed by Oxford Instruments. Software to carry out mathematical analysis of the spectral data has also been developed at IFR.
“It’s a stroke of luck really that some of the most important meats turn out to have fat signatures that we can tell apart so easily with this method,” said Dr Kate Kemsley, lead IFR researcher working on the project.
“It’s been very satisfying to see results from a real industrial setting sit right on top of those we generated in our two labs. We think this testing method should work well at key points in the supply chain, say at meat wholesalers and processors.”