Abstract

In this work we have evaluated the performance of two sample preparation methodologies for the large-scale multiresidue analysis of pesticides in olives using liquid chromatography–electrospray tandem mass spectrometry (LC–MS/MS). The tested sample treatment methodologies were: (1) liquid–liquid partitioning with acetonitrile followed by dispersive solid-phase extraction clean-up using GCB, PSA and C 18 sorbents (QuEChERS method – modified for fatty vegetables) and (2) matrix solid-phase dispersion (MSPD) using aminopropyl as sorbent material and a final clean-up performed in the elution step using Florisil. An LC–MS/MS method covering 104 multiclass pesticides was developed to examine the performance of these two protocols. The separation of the compounds from the olive extracts was achieved using a short C 18 column (50 mm × 4.6 mm i.d.) with 1.8 μm particle size. The identification and confirmation of the compounds was based on retention time matching along with the presence (and ratio) of two typical MRM transitions. Limits of detection obtained were lower than 10 μg kg −1 for 89% analytes using both sample treatment protocols. Recoveries studies performed on olives samples spiked at two concentration levels (10 and 100 μg kg −1) yielded average recoveries in the range 70–120% for most analytes when QuEChERS procedure is employed. When MSPD was the choice for sample extraction, recoveries obtained were in the range 50–70% for most of target compounds. The proposed methods were successfully applied to the analysis of real olives samples, revealing the presence of some of the target species in the μg kg −1 range. Besides the evaluation of the sample preparation approaches, we also discuss the use of advanced software features associated to MRM method development that overcome several limitations and drawbacks associated to MS/MS methods (time segments boundaries, tedious method development/manual scheduling and acquisition limitations). This software feature recently offered by different vendors is based on an algorithm that associates retention time data for each individual MS/MS transition, so that the number of simultaneously traced transitions throughout the entire chromatographic run (dwell times and sensitivity) is maximized.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.