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Towards the use of ion mobility mass spectrometry derived collision cross section as a screening approach for unambiguous identification of targeted pesticides in food

McCullagh, Michael
Far, Johann
De Pauw, Edwin
Eppe, Gauthier
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Abstract

Rationale

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Mass spectrometry (MS) is the reference method for the screening of ultra‐trace residues of pesticides in food because MS offers the required selectivity/sensitivity to gather information and enable the analyst to make informed decisions during the identification process. Here we present and discuss the use of collision cross section (CCS) values in addition to mass accuracy and retention times in a pesticide screening method that integrates all the features offered by coupling ultra‐performance liquid chromatography (UPLC) with ion mobility mass spectrometry (IMSMS).

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Methods

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All experiments were carried out using UHPLC coupled to a travelling wave ion mobility mass spectrometer equipped with an electrospray ionization (ESI) source working in positive mode. An in‐house library containing 200 pesticides was built using standard solutions and used as reference for a TWCCS calibration study. Matrix extracts were analyzed to evaluate the performance of different screening workflows based on TWCCS, mass accuracy and retention times.

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Results

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The results proved that TWCCS values are very consistent, as the measured values do not differ more than 1% from the in‐house reference data library and emphasized the importance of the first low m/z mobility calibration point to guarantee full independence from instrument parameters and calibrant. The screening procedure was simplified to a single step by fully exploiting the content of ion mobility without generating any false detections, either positive or negative, from spiked samples and a previous proficiency test.

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Conclusions

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The screening approach proposed in this study is unconventional and based on large mass accuracy (20 ppm) and retention time windows (0.5 min) to capture, in a first step, a maximum of detected compounds. Compounds of interest are then identified by comparing measured collision cross sections with the measured reference library collision cross sections (with relative error tolerance lower than 2%).

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2019-01-24
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Peer reviewed scientific article
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