Development of a fully automated analytical platform based on static headspace‐gas chromatography‐tandem mass spectrometry for the analysis of five N‐nitrosamines in dried aquatic products of animal origin
BACKGROUND The development of rapid and sensitive monitoring methods for trace N‐nitrosamines (NAs) in foodstuffs is essential for mitigating the potential health risks to consumers. In the present study, an analytical platform based on one step fully automated static headspace sampling and gas chro...
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Veröffentlicht in: | Journal of the science of food and agriculture 2022-12, Vol.102 (15), p.7107-7114 |
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Sprache: | eng |
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Zusammenfassung: | BACKGROUND
The development of rapid and sensitive monitoring methods for trace N‐nitrosamines (NAs) in foodstuffs is essential for mitigating the potential health risks to consumers. In the present study, an analytical platform based on one step fully automated static headspace sampling and gas chromatography‐tandem mass spectrometry (GC‐MS/MS) was developed and validated for the analysis of N‐nitrosamines in dried aquatic products of animal origin. The samples and sodium chloride solution mixture were incubated in a heated headspace vial for analyte evaporation, coupled to automatic sampling and online GC‐MS/MS analysis. The proposed method requires minimal sample preparation and organic solvent consumption. Five N‐nitrosamines including N‐nitroso dimethylamine, N‐nitroso methyl ethylamine, N‐nitroso pyrolidine, N‐nitroso piperidine and N‐nitroso diphenylamine were selected as model compounds to optimize the significant factors by a using Box–Behnken design.
RESULTS
The optimum conditions achieved limits of detections in the range 0.08–0.29 μg kg−1, with correlation coefficient over 0.998. Relative recoveries in dried aquatic product sample were in the range 76.9–92.4%, with relative SDs of 1.9–7.2%.
CONCLUSION
These results confirm the reliability of the developed method for further application in trace level monitoring of the target analytes in foodstuffs. © 2022 Society of Chemical Industry. |
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ISSN: | 0022-5142 1097-0010 |
DOI: | 10.1002/jsfa.12072 |