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Development of a Methodology for the Simultaneous Analysis of Multiclass Contaminants in Milk

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Abstract

A simple methodology for the simultaneous determination of 67 pesticides, 25 veterinary drugs, and aflatoxin M1 in raw milk was developed and validated. After evaluating different combinations of sample preparation protocols, an extraction with acetonitrile:water (2:1) with QuEChERS citrate buffer salts and a combination of RP-C18 and anhydrous magnesium sulfate for the dispersive clean-up, using gas and liquid chromatography couples to mass spectrometry for determination, was selected. Recovery percentages were between 70 and 120%, with relative standard deviations below 20% at 5, 20, and 50 μg kg−1. Aflatoxin M1 was recovered in the range 66 to 88% at 0.05, 0.1, and 0.5 μg kg−1 with relative standard deviation between 8 and 11%. The quantification limits for all the analytes with the exception of diclofenac were below their respective maximum residue limits. The method was applied for the analysis of 20 commercial samples, some of which showed at least one contaminant below their maximum residue limits.

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Acknowledgments

The authors acknowledge Dra. Florencia Puigvert for language help.

Funding

This study was funded by PEDECIBA Química (Programa de Desarrollo de las Ciencias Básicas, Uruguay), CSIC-INI (Programa de Iniciación a la Investigación, Comisión Sectorial de Investigación Científica, Universidad de la República), and RALACA/FAO/International Atomic Energy Agency.

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Correspondence to Lucia Pareja.

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Rodrigo Souza declares that he has no conflict of interest. Paula Fernández declares that she has no conflict of interest. Agustina Muela declares that she has no conflict of interest. Lucia Pareja declares that she has no conflict of interest. Veronica Cesio declares that she has no conflict of interest. Horacio Heinzen declares that he has no conflict of interest.

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Souza, R., Fernández, P., Muela, A. et al. Development of a Methodology for the Simultaneous Analysis of Multiclass Contaminants in Milk. Food Anal. Methods 14, 1075–1086 (2021). https://doi.org/10.1007/s12161-020-01953-7

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