Evaluation and validation of an accurate mass screening method for the analysis of pesticides in fruits and vegetables using liquid chromatography-quadrupole-time of flight-mass spectrometry with automated detection.

This study reports the development and validation of a screening method for the detection of pesticides in 11 different fruit and vegetable commodities. The method was based on ultra performance liquid chromatography-quadrupole-time of flight-mass spectrometry (UPLC-QTOF-MS). The objective was to validate the method in accordance with the SANCO guidance document (12571/2013) on analytical quality control and validation procedures for pesticide residues analysis in food and feed. Samples were spiked with 199 pesticides, each at two different concentrations (0.01 and 0.05 mg kg(-1)) and extracted using the QuEChERS approach. Extracts were analysed by UPLC-QTOF-MS using generic acquisition parameters. Automated detection and data filtering were performed using the UNIFI™ software and the peaks detected evaluated against a proprietary scientific library containing information for 504 pesticides. The results obtained using different data processing parameters were evaluated for 4378 pesticide/commodities combinations at 0.01 and 0.05 mg kg(-1). Using mass accuracy (± 5 ppm) with retention time (± 0.2 min) and a low response threshold (100 counts) the validated Screening Detection Limits (SDLs) were 0.01 mg kg(-1) and 0.05 mg kg(-1) for 57% and 79% of the compounds tested, respectively, with an average of 10 false detects per sample analysis. Excluding the most complex matrices (onion and leek) the detection rates increased to 69% and 87%, respectively. The use of additional parameters such as isotopic pattern and fragmentation information further reduced the number of false detects but compromised the detection rates, particularly at lower residue concentrations. The challenges associated with the validation and subsequent implementation of a pesticide multi-residue screening method are also discussed. Crown