Analytical considerations on the use of a fruit-specific and representative matrix in pesticide residue analysis by LC-ESI-MS/MS |
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| Authors: | Anna Stachniuk Emilia Fornal |
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| Institution: | 1247. Chemistry Department, The John Paul II Catholic University of Lublin, 20-718, Lublin, Poland
2247. Laboratory of Separation and Spectroscopic Method Applications, Centre for Interdisciplinary Research, The John Paul II Catholic University of Lublin, 20-718, Lublin, Poland
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| Abstract: | One of the quantification methods frequently applied to pesticide residue analysis in food by liquid chromatography — mass spectrometry (LC-MS) involves matrix-matched calibrations with a representative matrix used for all commodities belonging to one group. This approach, although very practical, is deemed to generate analytical errors. The effect of the application of a representative-matrix calibration curve on the pesticide quantification result was examined. Extractions of 56 pesticides from five soft fruits (strawberries, blackberries, raspberries, black currant and red currant) were carried out using QuEChERS method. Pesticide determinations were performed by LC-MS/MS in multiple reaction monitoring mode. Quantification difference functions and parameters were proposed and calculated. At the concentration of 0.05 mg kg?1 for ca. 90% of examined pesticides the quantification difference arising from the use of a representative matrix calibration curve (raspberries) instead of a specific fruit matrix calibration curve was below 20% for black and red currents, and below 30% and 35% in the case of strawberries and blackberries, respectively. The 25% difference limit was not exceeded for 51 pesticides in black and red currents, 46 pesticides in blackberries and 45 pesticides in strawberries. Quantification difference functions and parameters such as relative standard deviation of corrected process efficiencies were found to be helpful in data-driven decision-making on the applicability of a representative matrix; the former may be also used as a tool for data correction to ensure the reliability and accuracy of analyses.  | |
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