The European Food Safety Authority asked for novel approaches for identifying mechanically separated meat (MSM) in meat products, due to food safety concern. In this study, a novel approach based on multivariate analysis of 43 trace elements in meat products is described. Overall, 27 trace elements and 16 rare earth elements were determined by using ICP-MS after sample mineralization of 100 meat samples, composed of different percentages of MSM, obtained at low and high pressure, and without MSM. After development and optimization, the multivariate approach was validated by analyzing and then classifying 10 “blind” meat samples, obtaining method accuracy equal to 90%. Thus, the applicability of this new analytical approach was demonstrated. The method represents a significant improvement for this type of determination, especially when MSM is obtained at low pressure, since this product is characterized by chemical characteristics very similar to fresh meat.
Miedico, O., Nardelli, V., D'Amore, T., Casale, M., Oliveri, P., Malegori, C., et al. (2022). Identification of mechanically separated meat using multivariate analysis of 43 trace elements detected by inductively coupled mass spectrometry: A validated approach. FOOD CHEMISTRY, 397(15 December 2022) [10.1016/j.foodchem.2022.133842].
Identification of mechanically separated meat using multivariate analysis of 43 trace elements detected by inductively coupled mass spectrometry: A validated approach
Paglia, Giuseppe;
2022
Abstract
The European Food Safety Authority asked for novel approaches for identifying mechanically separated meat (MSM) in meat products, due to food safety concern. In this study, a novel approach based on multivariate analysis of 43 trace elements in meat products is described. Overall, 27 trace elements and 16 rare earth elements were determined by using ICP-MS after sample mineralization of 100 meat samples, composed of different percentages of MSM, obtained at low and high pressure, and without MSM. After development and optimization, the multivariate approach was validated by analyzing and then classifying 10 “blind” meat samples, obtaining method accuracy equal to 90%. Thus, the applicability of this new analytical approach was demonstrated. The method represents a significant improvement for this type of determination, especially when MSM is obtained at low pressure, since this product is characterized by chemical characteristics very similar to fresh meat.
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