Evaluation of two sample treatment methodologies for large-scale pesticide residue analysis in olive oil by fast liquid chromatography-electrospray mass spectrometry

In this study, a comprehensive evaluation of two simple sample treatment methodologies has been carried out for the development of large-scale multi-residue methods for pesticide testing in olive oil. The proposed methodologies are based on (a) liquid-liquid partitioning with acetonitrile followed by dispersive solid-phase extraction clean-up using graphitized carbon black, primary-secondary amine and C-18 sorbents; (b) liquid partitioning with acetonitrile saturated with petroleum ether followed by matrix solid-phase dispersion (MSPD) using aminopropyl as sorbent material and a Florisil cartridge for final clean-up in the elution step. To evaluate the proposed sample treatment methodologies, 105 representative multi-class pesticides were studied using fast liquid chromatography-electrospray time-of-flight mass spectrometry (LC-TOFMS). For validation purposes, recoveries studies were carried out at 10 and 100 mu g kg(-1) levels, yielding recovery rates in the range 70-130% for 72% of analytes using liquid-liquid procedure and for 57% analytes using MSPD procedure. The LC-MS method provided good linearity, precision and accuracy. The limits of detection obtained were lower than 10 mu g kg(-1) for more than 85% analytes using both sample treatment methodologies. In addition, minor matrix effects (i.e. signal suppression or enhancement <= 20%) were observed in ca. 70% of the studied compounds. Data obtained shows that both sample treatment methodologies proposed can be successfully applied for large-scale pesticide testing in olive oil samples, showing the ability to quickly detect trace amount of over one hundred target species with different physicochemical properties, without requiring expensive instrumentation for sample treatment step and involving relatively low amounts of solvent consumption and waste generation. (C) 2010 Published by Elsevier B.V.