Infrared snapshot will spot contaminated meat in seconds and prevent food poisoning

14 September 2005

A new technique to spot contaminated meat in seconds instead of the hours currently needed could revolutionise the food processing industry and prevent thousands of cases of food poisoning every year, according to scientists speaking today (Wednesday, 14 September 2005) at the Society for General Microbiology's 157th Meeting at Keele University, UK.

Scientists from Manchester University have developed a new technique using infrared light which successfully spots chicken and beef contaminated with dangerous bacteria, leading to the hope that it will increase the safety of processed foods across the industry.

"Modern food processing is highly automated and efficient, but the way safety inspectors sample the products has hardly changed in half a century," says Dr David Ellis from the University of Manchester. "At present, more than 40 different methods are available to detect and measure bacteria growing in meats. However, even the most rapid of these takes several hours, so results are always retrospective, which means that infected meat could get into the food chain."

"We believe that our infrared equipment can be built into production lines, it doesn't involve injecting chemicals or touching the food itself, it's relatively cheap, results are available in seconds and can be read by a machine," says Dr Ellis. "This makes it ideal for on-line meat inspection."

The scientists have already shown that the technique works in both chicken and beef - which are reckoned to be two of the most difficult meats to check for safety. They are processed in different ways, and are typically contaminated by different types of bacteria. The method could therefore easily be applied to milk, ice-cream, cheese and other dairy produce, fruit juices and other foods.

The new technique uses infrared spectroscopy on light reflected from the surface of the food to produce biochemical 'fingerprints' of any contaminating micro-organisms, such as bacteria, and rapidly estimate their numbers.

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