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ARS Home » Northeast Area » Wyndmoor, Pennsylvania » Eastern Regional Research Center » Microbial and Chemical Food Safety » Research » Publications at this Location » Publication #371912

Research Project: Development, Evaluation, and Validation of Technologies for the Detection and Characterization of Chemical Contaminants in Foods

Location: Microbial and Chemical Food Safety

Title: High-throughput mega-method for analysis of pesticides, veterinary drugs, and environmental contaminants by ultra-high-performance LC-TMS and robotic mini-solid-phase extraction cleanup + low-pressure GC-TMS, Part 1: Beef

Author
item MONTEIRO, SERGIO - Biological Institute, Brazil
item Lehotay, Steven
item Sapozhnikova, Yelena
item NINGA, EDERINA - Agricultural University Of Tirana, Albania
item Lightfield, Alan

Submitted to: Journal of Agricultural and Food Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/22/2020
Publication Date: 5/22/2020
Citation: Monteiro, S.H., Lehotay, S.J., Sapozhnikova, Y.V., Ninga, E., Lightfield, A.R. 2020. High-throughput mega-method for the analysis of pesticides, veterinary drugs, and environmental contaminants by ultra-high-performance liquid chromatography-tandem mass spectrometry and robotic mini-solid-phase extraction cleanup + low-pressure gas chromatography-tandem mass spectrometry, Part 1: Beef. Journal of Agricultural and Food Chemistry. 69:1169-1174. https://doi.org/10.1021/acs.jafc.0c00710?ref=pdf
DOI: https://doi.org/10.1021/acs.jafc.0c00710?ref=pdf

Interpretive Summary: The best way to increase operating efficiency of a monitoring lab is to reduce the number of methods needed by combining different methods into the same procedure while maintaining the same (or broader) scope of contaminants monitored. In this study, two different methods of analysis for pesticides, environmental contaminants and veterinary drugs in meat were merged into a single mega-method to cover all types of chemical residues. Validation results in accordance with USDA-FSIS protocols and criteria showed that more than 200 targeted contaminants could be monitored in the same high-throughput method to save much labor, time, and cost compared to the current monitoring methods in use. This mega-method is expected to be used by many laboratories worldwide to improve accuracy of analyses while also increasing sample throughput.

Technical Abstract: Fast, efficient, and cost-effective analysis of chemical contaminants in meat is useful for international trade, domestic monitoring, risk assessment, and other purposes. The goal of this study was to develop and validate a simple high-throughput mega-method for residual analysis of 163 pesticides, 63 veterinary drugs, 24 metabolites, and 14 legacy environmental contaminants (polychlorinated biphenyls) in bovine muscle for implementation in routine laboratory analyses. The list of targeted analytes and their levels was chosen based on the Brazilian National Plan for Control of Residues in Animal Products and USDA National Residue Program. Sample preparation of 2 g test potions entailed QuEChERS-based extraction with 10 mL 4/1 (w/w) acetonitrile/water, then 204 µL was taken, diluted, and ultra-centrifuged prior to analysis of veterinary drugs and pesticides by ultrahigh-performance liquid chromatography - tandem mass spectrometry (UHPLC-MS/MS). The remaining extract was salted out with 4/1 (w/w) anh. MgSO4/NaCl and 1 mL was transferred to an autosampler vial for automated mini-cartridge solid-phase extraction (Instrument Top Sample Preparation) cleanup with immediate injection using fast low-pressure gas chromatography (LPGC)-MS/MS analysis. The automated cleanup and both instruments were all operated in parallel in 13-15 min cycle times per sample. Method validation according to USDA requirements demonstrated that 212 (80%) of the 264 analytes gave recoveries between 70–120% and RSDs =20%. Analysis of a certified reference material for veterinary drugs in freeze-dried bovine muscle was also very accurate, further demonstrating that the mega-method can be implemented to save time, labor, and resources compared to current practices to use multiple methods to cover the same analytical scope.