%0 Generic %D 2013 %T Revealing the identification power of CCS: A novel approach applied to pesticide analysis in food %A Séverine Goscinny %A M. McCullagh %A V. Hanot %A G. Eppe %K acquisition %K analysi %K analysis %K approach %K approaches %K AS %K Attention %K Benefit %K Case %K data %K detection %K factors %K food %K identification %K INFORMATION %K Ion %K Ion Mobility %K IS %K Laboratories %K Mass %K method %K methods %K mobility %K Multidimentional analysis,LC-IMS-HRMS,identity confirmation, %K ON %K performance %K pesticide %K Pesticides %K Residue %K result %K results %K Sample %K Samples %K SCREENING %K Screening method %K separation %K series %K Solutions %K Strategies %K Strategy %K System %K Test %K time %K use %K values %X

Performing pesticide analysis in food requires coping with multi-class compounds, different matrices and responding rapidly. Screening methods are very useful as they can discriminate samples without any pesticides from those with detectable residues. The laboratory can then focus their efforts on quantitative methods for a smaller number of samples. Different strategies can be applied for screening purposes. Full scan acquisition has however driven most of the attention because of its inherent benefit of theoretical detection of unlimited number of compounds. In spite of this analytical potential, it is well characterized that many factors can influence mass spectra for LC-based methods and given the complexity of the samples analysed, reliable identification can be unreachable in some cases. Ion mobility is known to be a powerful analytical tool for the separation of complex samples and collision cross sections of compounds derived from drift time has been extensively used for characterization purposes. We will present a novel way to use these special mobility features in screening methods from acquisition to data processing. For the assay, UPLC-HDMSE experiments were performed on a Synapt G2-S using a series of standard solutions, spiked matrices and a previous proficiency test. CCS values were generated from the standard solutions and inserted into a scientific library within a new scientific information system. Then, the screening method performances were tested with samples (blank matrices, spiked samples and proficiency test). Based on these results, we will show how we can reliably reduce the number of false positive and more importantly avoid false negative identifications.

%B RAFA 2013 %I NA %C NA %8 0/0/2013 %G eng %N RAFA 2013 %1 2211 %2 5-8 novembre 2013