Spotting contaminated chickens

Researchers at the University of Wales, Aberystwyth (UWA) have developed a rapid procedure which will enable food producers to detect the bacterial contamination of their meat products.

Their findings, published this week in Applied and Environmental Microbiology demonstrate a novel analytical approach that can enhance and accelerate the detection of microbial spoilage, providing rapid, accurate and quantitative results in real time so that appropriate corrective action can be taken as soon as possible.

Dr Roy Goodacre and Mr David Ellis in the Institute of Biological Sciences at UWA have used Fourier transform infrared (FT-IR) spectroscopy to produce a 'fingerprint' of the biochemical changes that occur on the surface of chicken breast meat as a result of the growth of microorganisms.

These metabolic changes result in a number of organoleptic features that make the meat unacceptable to the consumer, including changes in appearance (discoloration), the development of off-odours, slime formation, or changes in taste.

'Whilst the activity of enzymes present in muscle tissue post-mortem can contribute to a number of changes during storage, it is generally accepted that detectable organoleptic spoilage is a result of decomposition and the formation of various metabolites caused by the growth of microorganisms', says Dr Goodacre.

'We have used spectroscopic analysis to exploit this information so that, rather than measuring exclusively the presence of bacteria per se on the meat surface, infrared can be used to measure the biochemical changes within the meat substrate, enhancing and accelerating the detection of microbial spoilage. We have developed horizontal attenuated total reflectance (HATR) FT-IR spectroscopy with the most appropriate machine learning algorithms for estimating the bacterial total viable count directly off the surface of muscle foods. The effectiveness of this technology has been established through a detailed investigation of the natural spoilage process on chicken breast muscle. In addition, this technique is also very rapid (taking a few seconds) compared to hours to days by conventional means.'

The last decade has seen an exponential increase in the consumer demand for poultry and poultry products, fuelled in part by dietary health considerations and the recent BSE and foot and mouth crises. Fears over microbiological food safety issues, especially the incidence of Salmonella spp. and Campylobacter spp., in conjunction with consumer demand for a product of consistently high quality, have focused attention on a particular area of the food production industry, namely the requirement for a rapid (less than a few minutes) and accurate detection system for microbiologically spoiled or contaminated meat.

At present no such technology exists in the food industry within the Hazard Analysis Critical Control Point (HACCP) system for the routine microbiological safety and quality of meat and poultry products.

'To date, more than 40 methods have been proposed to measure and to detect bacterial spoilage in meats. The major drawback with these is that they are time consuming, labour intensive and give information about contamination retrospectively, i.e. some considerable time after it has happened, and often when it is too late to take corrective action', adds Dr Goodacre.

'Since the ideal method for the on-line microbiological analysis of meat would be rapid, non-invasive, reagentless and relatively inexpensive, we feel that these requirements can all met by the application of this spectroscopic approach. Now that we have established this methodology, our next goal is to test how our approach may aid both food safety regulatory bodies and the HACCP system,' he concludes.

This three year project 'Rapid detection of food spoilage using vibrational spectroscopic imaging and machine learning' is being funded by Agri-Food committee of the UK BBSRC.