Dehydrated vegetables are popular in instant foods, but few reports have focused on their pesticide residues. This research developed and validated a modified QuEChERS method combined with ultra-performance liquid chromatography–tandem mass spectrometry to determine 19 kinds of neonicotinoid and carbamate pesticides in freeze-dried cabbage. Herein, acetonitrile/water (v/v = 2:1) was selected in the extraction step. Meanwhile, 4 g anhydrous magnesium sulfate and 1 g sodium chloride were applied to the partitioning step. Dispersive solid-phase extraction sorbents were selected, and liquid chromatography conditions were further optimized for dealing with the matrix effect. The limits of quantification ranged from 1.0 to 10.0 μg/kg. The validation results were acceptable, with average recoveries of 78.7–114.0% and relative standard deviations below 14.2%. The method recoveries were closely related to the volume proportion of water in the extractant. Finally, the developed method was applied to real freeze-dried cabbages and four pesticides (propamocarb, imidacloprid, acetamiprid, and thiacloprid) were detected in six samples.

A simple, fast and reliable analytical method was developed for 20 free amino acids (FAAs) determination in honey samples through a dilute-and-shoot strategy and hydrophilic interaction liquid chromatography tandem mass spectrometry. Compared with previous reports, direct dilution by water has significantly reduced the matrix effect and facilitated full extraction of FAAs. Further, a 5 min determination method was established with an acetonitrile–water mobile phase system with 0.1% formic acid addition. The established method was validated and demonstrated several advantages including short detection time, wide linear range over 3–4 orders of magnitude, high sensitivity down to 0.1 ng/mL and negligible matrix effect. Twenty FAAs were determined in 10 honey samples from different botanical origins by this method, and 19 FAAs were found. This general applicable method was also promising for fast determination of FAAs in other practical samples.

Dinotefuran (DNT) is a neonicotinoid insecticide widely used in pest control. Identification of structurally related impurities is indispensable during material purification and pesticide registration and certified reference material development, and therefore needs to be carefully characterized. In this study, a combined strategy with liquid chromatography high-resolution mass spectrometry and SIRIUS has been developed to elucidate impurities from DNT material. MS and MS/MS spectra were used to score the impurity candidates by isotope score and fragment tree in the computer assisted tool, SIRIUS. DNT, the main component, worked as an anchor for formula identification and impurity structure elucidation. With this strategy, two by-product impurities and one stereoisomer were identified. Their fragmentation pathways were concluded, and the mechanism for impurity formation was also proposed. This result showed a successful application for combined human intelligence and machine learning, in the identification of pesticide impurities.