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.

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This work provides a proposal for proper determination of matrix effects and extraction efficiencies as an integral part of full validation of liquid chromatography coupled to tandem mass spectrometry-based multiclass methods for complex feedstuff. Analytical performance data have been determined for 100 selected analytes in three compound feed matrices and twelve single feed ingredients using seven individual samples per matrix type. Apparent recoveries ranged from 60–140% for 52–89% of all compounds in single feed materials and 51–72% in complex compound feed. Regarding extraction efficiencies, 84–97% of all analytes ranged within 70–120% in all tested feed materials, implying that signal suppression due to matrix effects is the main source for the deviation from 100% of the expected target deriving from external calibration. However, the comparison between compound feed and single feed materials shows great variances regarding the apparent recoveries and matrix effects. Therefore, model compound feed formulas for cattle, pig, and chicken were prepared in-house in order to circumvent the issue of the lack of a true blank sample material and to simulate compositional uncertainties. The results of this work highlight that compound feed modeling enables a more realistic estimation of the method performance and therefore should be implemented in future validation guidelines.

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