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Validation of an LC-MS/MS-based dilute-and-shoot approach for the quantification of > 500 mycotoxins and other secondary metabolites in food crops: challenges and solutions
Validation of an LC-MS/MS-based dilute-and-shoot approach for the quantification of > 500 mycotoxins and other secondary metabolites in food crops: challenges and solutions
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Validation of an LC-MS/MS-based dilute-and-shoot approach for the quantification of > 500 mycotoxins and other secondary metabolites in food crops: challenges and solutions
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Validation of an LC-MS/MS-based dilute-and-shoot approach for the quantification of > 500 mycotoxins and other secondary metabolites in food crops: challenges and solutions
Validation of an LC-MS/MS-based dilute-and-shoot approach for the quantification of > 500 mycotoxins and other secondary metabolites in food crops: challenges and solutions

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Validation of an LC-MS/MS-based dilute-and-shoot approach for the quantification of > 500 mycotoxins and other secondary metabolites in food crops: challenges and solutions
Validation of an LC-MS/MS-based dilute-and-shoot approach for the quantification of > 500 mycotoxins and other secondary metabolites in food crops: challenges and solutions
Journal Article

Validation of an LC-MS/MS-based dilute-and-shoot approach for the quantification of > 500 mycotoxins and other secondary metabolites in food crops: challenges and solutions

2020
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Overview
This paper describes the validation of an LC-MS/MS-based method for the quantification of > 500 secondary microbial metabolites. Analytical performance parameters have been determined for seven food matrices using seven individual samples per matrix for spiking. Apparent recoveries ranged from 70 to 120% for 53–83% of all investigated analytes (depending on the matrix). This number increased to 84–94% if the recovery of extraction was considered. The comparison of the fraction of analytes for which the precision criterion of RSD ≤ 20% under repeatability conditions (for 7 replicates derived from different individual samples) and intermediate precision conditions (for 7 technical replicates from one sample), respectively, was met (85–97% vs. 93–94%) highlights the contribution of relative matrix effects to the method uncertainty. Statistical testing of apparent recoveries between pairs of matrices exhibited a significant difference for more than half of the analytes, while recoveries of the extraction showed a much better agreement. Apparent recoveries and matrix effects were found to be constant over 2–3 orders of magnitude of analyte concentrations in figs and maize, whereas the LOQs differed less than by a factor of 2 for 90% of the investigated compounds. Based on these findings, this paper discusses the applicability and practicability of current guidelines for multi-analyte method validation. Investigation of (apparent) recoveries near the LOQ seems to be insufficiently relevant to justify the enormous time-effort for manual inspection of the peaks of hundreds of analytes. Instead, more emphasis should be put on the investigation of relative matrix effects in the validation procedure.