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Mechanically separated meat (MSM) is defined as “product obtained by removing meat from flesh-bearing bones after deboning or from poultry carcasses, using mechanical means resulting in the loss or modification of the muscle fibre structure”. These alterations in muscle fibre structure mean that MSM does not possess the typical texture of meat and MSM is therefore often used in meat products where the texture of the meat is not a necessary quality in the finished product. MSM is excluded from the legal definition of meat for labelling purposes and cannot be counted towards the meat content declaration required for meat products. In addition, MSM must be separately labelled in the ingredients. To enforce these legal requirements and to protect consumers from misdescribed products, a method to distinguish MSM from meat in meat products is needed. Previous studies have been unable to find a marker to reliably distinguish MSM from meat in a meat product, and currently MSM can only be identified at the raw ingredient stage. <P>
The aim of this project was to use advanced laboratory techniques and predictive models to identify potential markers for MSM and to develop a test to identify MSM, even when mixed with other ingredients.
Research Approach:<BR> This project applied a metabolomic approach to detect low molecular weight markers in MSM that were not present in hand-deboned meat (HDM) and desinewed meat. Following the systematic optimisation of the conditions to extract metabolites, chicken and pork MSM, HDM and desinewed meat samples were analysed using gas chromatography coupled to mass spectrometry (GC-MS) to generate metabolic profiles for each type of sample. Different statistical methods were used to create chemometric models to differentiate MSM from HDM and desinewed meat, and to detect potential MSM biomarkers. In addition to the untargeted metabolomics approach, a method to detect bone-derived compounds was optimised, to investigate whether these could be used to identify MSM. The ability of the methods developed to predict the sample type (MSM, HDM or desinewed) of unknown samples was also tested.
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Results and findings:<BR>
GC-MS analysis showed that there were significantly different amounts of certain metabolites in MSM, HDM and desinewed meat. Selected biomarker concentrations, when used in combination, were indicative of the different sample types, but confirmation using other statistical approaches would be required. However, by performing statistical analysis using all of the metabolomic data, it was possible to create chemometric models to differentiate between MSM, HDM and desinewed meat. These models can also detect MSM when mixed with other meat ingredients, down to levels of 10% MSM. Very few bone-derived compounds were detected that could be used as potential biomarkers of MSM although, as for the untargeted metabolomic approach, it was possible to differentiate between MSM and HDM samples using chemometric models created using all the data. This project has therefore demonstrated that it is possible to differentiate MSM from other meat ingredients using metabolite profiling. However, at present this requires advanced statistical analysis, and further investigation to establish the predictive ability of the models would be necessary.
<p>Find more about this project and other FSA food safety-related projects at the <a href="http://www.food.gov.uk/science/research/" target="_blank">Food Standards Agency Research webpage</a>.