Variability of selected trace elements of different meat cuts determined by ICP-MS and DRC-ICPMS
The aim of this study was to determine the levels of cadmium, lead, iron, zinc, selenium, manganese, copper and molybdenum in different cuts of beef, pork, lamb, chicken and foal collected from supermarkets and butcheries in Switzerland. The concentrations of manganese, copper, molybdenum, zinc, iro...
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Veröffentlicht in: | Animal (Cambridge, England) England), 2009-01, Vol.3 (1), p.166-172 |
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Sprache: | eng |
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Zusammenfassung: | The aim of this study was to determine the levels of cadmium, lead, iron, zinc, selenium, manganese, copper and molybdenum in different cuts of beef, pork, lamb, chicken and foal collected from supermarkets and butcheries in Switzerland. The concentrations of manganese, copper, molybdenum, zinc, iron, selenium, cadmium and lead were determined by inductively coupled plasma mass spectrometry (ICP-MS) after microwave digestion. Mean values and their respective coefficients of variation were calculated from the measured concentrations. The concentrations found for cadmium and lead ranged from 0.6 to 3.9 μg/100 g and 1.0 to 2.1 μg/100 g, respectively. Concentrations ranged between 0.5 and 3.3 mg/100 g for iron, 0.7 and 5.1 mg/100 g for zinc, 9 and 44 μg/100 g for selenium, 3.1 and 16.7 μg/100 g for manganese, 0.3 and 132 μg/100 g for copper and 0.9 and 3.2 μg/100 g for molybdenum. Differences found for the concentrations in meat from different species as well as between the individual meat cuts were notable for iron, zinc, selenium and copper. Manganese concentrations were found to vary unsystematically within muscles and species. Molybdenum concentrations were higher in chicken meat in comparison with the mammalian meats. The highest coefficients of variation were found for manganese (13% to 142%) and copper (13% to 224%), while the lowest was found for zinc (4% to 45%). In conclusion, in order to provide an accurate overview and to be able to calculate reliable dietary intakes, it is important to include the variability in food composition data. |
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ISSN: | 1751-7311 1751-732X |
DOI: | 10.1017/S1751731108003212 |