Clean-up Strategy for Dithiocarbamate Fungicide Determination in Soybean by GC-ITD-MS and GC-PFPD: Method Development and Validation.

Food matrices consist of many components with different physical and chemical properties that may influence instrumental robustness. The soybean contains fatty coextractives which may have a deleterious effect on the gas chromatography (GC) system. In this study, the efficiencies of PSA, C18OH, C18, silica, aluminum oxide, and Florisil, as dSPE clean-up sorbents, were evaluated by the high-performance liquid chromatography (HPLC) diode-array detector and evaporative light-scattering detector analysis. The dithiocarbamates in soybean samples are determined as CS2 using acidic hydrolysis and isooctane partitioning, followed by GC-PFPD and GC-ITD-MS analyses. The linearity of the analytical curves, the instrument limit of detection matrix effects, the trueness and precision, and the method limit of quantification (LOQ) were assessed in the validation study. Milled soybean was spiked with thiram solution at three concentration levels (corresponding to 0.05, 0.1, and 0.5 mg CS2 kg-1) for recovery determination. Silica appeared to be an effective and cheap sorbent to remove coextracted matrix components without causing any CS2 losses. Recoveries were in the range of 68-91%, with relative standard deviations ≤ 8.7%. The method LOQ was 0.05 mg CS2 kg-1, and both GC-ITD-MS and GC-PFPD systems appeared to be appropriate and complementary to determine dithiocarbamate residues in soybean extracts.

A multi-residue method for pesticides analysis in green coffee beans using gas chromatography-negative chemical ionization mass spectrometry in selective ion monitoring mode.

In this study, a new gas chromatography-mass spectrometry (GC-MS) method, using the very selective negative chemical ionization (NCI) mode, was developed and applied in combination with a modified acetonitrile-based extraction method (QuEChERS) for the analysis of a large number of pesticide residues (51 pesticides, including isomers and degradation products) in green coffee beans. A previously developed integrated sample homogenization and extraction method for both pesticides and mycotoxins analysis was used. An homogeneous slurry of green milled coffee beans and water (ratio 1:4, w/w) was prepared and extracted with acetonitrile/acetic acid (1%), followed by magnesium sulfate addition for phase separation. Aliquots from this extract could be used directly for LC-MS/MS analysis of mycotoxins and LC-amenable pesticides. For GC-MS analysis, a further clean-up was necessary. C18- and PSA-bonded silica were tested as dispersive solid-phase extraction (d-SPE) sorbents, separate and as a mixture, and the best results were obtained using C18-bonded silica. For the optimal sensitivity and selectivity, GC-MS detection in the NCI-selected ion monitoring (SIM) mode had to be used to allow the fast analysis of the difficult coffee bean matrix. The validation was performed by analyzing recovery samples at three different spike concentrations, 10, 20 and 50 µg kg(-1), with 6 replicates (n=6) at each concentration. Linearity (r(2)) of calibration curves, estimated instrument and method limits of detection and limits of quantification (LOD(i), LOD(m), LOQ(i) and LOQ(m), respectively), accuracy (as recovery %), precision (as RSD%) and matrix effects (%) were determined for each individual pesticide. From the 51 analytes (42 parent pesticides, 4 isomers and 5 degradation products) determined by GC-MS (NCI-SIM), approximately 76% showed average recoveries between 70-120% and 75% and RSD ≤ 20% at the lowest spike concentration of 10 µg kg(-1), the target method LOQ. For the spike concentrations of 20 and 50 µg kg(-1), the recoveries and RSDs were even better. The validated LOQ(m) was 10, 20 and 50 µg kg(-1) for respectively 33, 3 and 6 of the analytes studied. For five compounds, the European Union method performance requirements for the validation of a quantitative method (average recoveries between 70-120% and repeatability RSD ≤ 20%) were not achieved and 4 problematic pesticides (captan, captafol, folpet and dicofol) could not be detected as their parent compound, but only via their degradation products. Although the matrix effect (matrix-enhanced detector response) was high for all pesticides studied, the matrix interference was minimal, due to the high selectivity obtained with the GC-NCI-MS detection. Matrix-matched calibration for applying the method in routine analysis is recommended for reliable quantitative results.