Beefing up BSE detection

Researchers at the University of Arkansas have developed a fast and easy method for detecting potential BSE contamination in minced beef as it travels along a factory production line.

The system will allow manufacturers to check all products thoroughly rather than relying on random sampling, making it very unlikely that contaminated meat would accidentally reach shoppers.

The scanning device, fitted above a conveyor belt, uses a light system called attenuated total reflectance Fourier transform infrared spectroscopy (ATF-FTIR) to check if ground beef has been tainted with nerve, brain and spinal material.

Contamination occurs if meat containing prion proteins is taken from too near the spinal cord during butchering. Prions can cause the fatal human variant of BSE, Creutzfeldt-Jakob brain disease (vCJD).

The ATF-FTIR system can detect contamination down to 0.0016 per cent, compared to existing testing systems that have a sensitivity of 0.1 per cent.

As the meat passes under the scanner it moves through infrared light. Many materials are partially transparent to infrared, meaning different wavelengths of infrared radiation are absorbed at different rates. By measuring the absorption of infrared radiation at different wavelengths researchers can identify the materials present.

The Arkansas team discovered a relationship between the presence of certain phosphate groups bound to organic molecules and bovine spinal cord tissue, as bovine nerves are covered in a phosphate-rich material.

At present small samples from production lines are taken and checked using an expensive, time- consuming process known as Enzyme Linked Immunosorbent Assay (ELISA). This involves preparing antibodies to a specific protein. An enzyme is also added to the sample and the reaction is monitored to determine the presence of the BSE protein.

The FTIR system would check all meat passing through it, with results in around two minutes. ‘Near-infrared light is already used in the meat industry for determining the amount of protein and fat in products,’ said Prof Andrew Proctor of the Department of Food Science at the university.

‘We now need to study a wide range of meat samples involving different types and with a varying fat content to get a large data set to develop a model for use with all meat samples.’