Wide-scope screening of pesticides in fruits and vegetables using information-dependent acquisition employing UHPLC-QTOF-MS and automated MS/MS library searching

This paper presents an application of ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) for simultaneous screening and identification of 427 pesticides in fresh fruit and vegetable samples. Both full MS scan mode for quantification, and an artificial-intelligence-based product ion scan mode information-dependent acquisition (IDA) providing automatic MS to MS/MS switching of product ion spectra for identification, were conducted by one injection. A home-in collision-induced-dissociation all product ions accurate mass spectra library containing more than 1700 spectra was developed prior to actual application. Both qualitative and quantitative validations of the method were carried out. The result showed that 97.4 % of the pesticides had the screening detection limit (SDL) less than 50 mu g kg(-1) and more than 86.7 % could be confirmed by accurate MS/MS spectra embodied in the home-made library. Meanwhile, calibration curves covering two orders of magnitude were performed, and they were linear over the concentration range studied for the selected matrices (from 5 to 500 mu g kg(-1) for most of the pesticides). Recoveries between 80 and 110 % in four matrices (apple, orange, tomato, and spinach) at two spiked levels, 10 and 100 mu g kg(-1), was 88.7 or 86.8 %. Furthermore, the overall relative standard deviation (RSD, n = 12) for 94.3 % of the pesticides in 10 mu g kg(-1) and 98.1 % of the pesticides in 100 mu g kg(-1) spiked levels was less than 20 %. In order to validate the suitability for routine analysis, the method was applied to 448 fruit and vegetable samples purchased in different local markets. The results show 83.3 % of the analyzed samples have positive findings (higher than the limits of identification and quantification), and 412 commodity-pesticide combinations are identified in our scope. The approach proved to be a cost-effective, time-saving and powerful strategy for routine large-scope screening of pesticides.