Analysis of pesticide residues in strawberries and soils by GC-MS/MS, LC-MS/MS and two-dimensional GC-time-of-flight MS comparing organic and integrated pest management farming.

This study analysed 22 strawberry and soil samples after their collection over the course of 2 years to compare the residue profiles from organic farming with integrated pest management practices in Portugal. For sample preparation, we used the citrate-buffered version of the quick, easy, cheap, effective, rugged, and safe (QuEChERS) method. We applied three different methods for analysis: (1) 27 pesticides were targeted using LC-MS/MS; (2) 143 were targeted using low pressure GC-tandem mass spectrometry (LP-GC-MS/MS); and (3) more than 600 pesticides were screened in a targeted and untargeted approach using comprehensive, two-dimensional gas chromatography time-of-flight mass spectrometry (GC × GC-TOF-MS). Comparison was made of the analyses using the different methods for the shared samples. The results were similar, thereby providing satisfactory confirmation of both similarly positive and negative findings. No pesticides were found in the organic-farmed samples. In samples from integrated pest management practices, nine pesticides were determined and confirmed to be present, ranging from 2 µg kg(-1) for fluazifop-p-butyl to 50 µg kg(-1) for fenpropathrin. Concentrations of residues in strawberries were less than European maximum residue limits.

metAlignID: a high-throughput software tool set for automated detection of trace level contaminants in comprehensive LECO two-dimensional gas chromatography time-of-flight mass spectrometry data.

A new alternative data processing tool set, metAlignID, is developed for automated pre-processing and library-based identification and concentration estimation of target compounds after analysis by comprehensive two-dimensional gas chromatography with mass spectrometric detection. The tool set has been developed for and tested on LECO data. The software is developed to run multi-threaded (one thread per processor core) on a standard PC (personal computer) under different operating systems and is as such capable of processing multiple data sets simultaneously. Raw data files are converted into netCDF (network Common Data Form) format using a fast conversion tool. They are then preprocessed using previously developed algorithms originating from metAlign software. Next, the resulting reduced data files are searched against a user-composed library (derived from user or commercial NIST-compatible libraries) (NIST=National Institute of Standards and Technology) and the identified compounds, including an indicative concentration, are reported in Excel format. Data can be processed batch wise. The overall time needed for conversion together with processing and searching of 30 raw data sets for 560 compounds is routinely within an hour. The screening performance is evaluated for detection of pesticides and contaminants in raw data obtained after analysis of soil and plant samples. Results are compared to the existing data-handling routine based on proprietary software (LECO, ChromaTOF). The developed software tool set, which is freely downloadable at www.metalign.nl, greatly accelerates data-analysis and offers more options for fine-tuning automated identification toward specific application needs. The quality of the results obtained is slightly better than the standard processing and also adds a quantitative estimate. The software tool set in combination with two-dimensional gas chromatography coupled to time-of-flight mass spectrometry shows great potential as a highly-automated and fast multi-residue instrumental screening method.

Qualitative aspects in the analysis of pesticide residues in fruits and vegetables using fast, low-pressure gas chromatography-time-of-flight mass spectrometry.

Quantitative method validation is a well-established process to demonstrate trueness and precision of the results with a given method. However, an assessment of qualitative results is also an important need to estimate selectivity and devise criteria for chemical identification when using the method, particularly for mass spectrometric analysis. For multianalyte analysis, automatic instrument software is commonly used to make initial qualitative identifications of the target analytes by comparison of their mass spectra against a database library. Especially at low residue levels in complex matrices, manual checking of results is typically needed to correct the peak assignments and integration errors, which is very time-consuming. Low-pressure gas chromatography-mass spectrometry (LP-GC-MS) has been demonstrated to increase the speed of analysis for GC-amenable residues in various foods and provide more advantages over the traditional GC-MS approach. LP-GC-MS on a time-of-flight (ToF) instrument was used, which provided high sample throughput with <10 min analysis time. The method had already been validated to be acceptable quantitatively for nearly 150 pesticides, and in this study of qualitative performance, 90 samples in total of strawberry, tomato, potato, orange, and lettuce extracts from the QuEChERS sample preparation approach were analyzed. The extracts were randomly spiked with different pesticides at different levels, both unknown to the analyst, in the different matrices. Automated software evaluation was compared with human assessments in terms of false-positive and -negative results. Among the 13590 possible permutations with 696 blind additions made, the automated software approach yielded 1.2% false presumptive positives with 23% false negatives, whereas the analyst achieved 0.8% false presumptive positives and 17% false negatives for the same analytical data files. False negatives frequently occurred due to challenges at the lowest concentrations, but 70% of them involved certain pesticides that degraded (e.g., captafol, folpet) or otherwise could not be detected. The false-negative rate was reduced to 5-10% if the problematic analytes were excluded. Despite its somewhat better performance in this study, the analyst approach was extremely time-consuming and would not be practical in high sample throughput applications for so many analytes in complicated matrices.

Validation of automated library-based qualitative screening of pesticides by comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry.

A method for automated detection and reporting of pesticides in plant materials based on comprehensive two-dimensional GC/time-of-flight MS with library-based detection by software has been developed and validated. Optimum settings for detection parameters such as spectral match threshold and first and second dimension retention time tolerances were assessed with respect to occurrence of false detects and false negatives. Next the method was validated following European Union guidelines established for qualitative screening of pesticides. The validation was largely done in retrospect by using data obtained for spiked samples (235 pesticides, various crops, 0.01-0.2 mg/kg) that had been analyzed previously with routine samples over a period of 18 months. At 0.01 mg/kg, the required 95% confidence level (<5% false negatives) was met for 83 compounds. This increased to 185 compounds at the 0.2 mg/kg level. For a number of pesticides, especially at low levels, it had to be concluded that at this stage the method was not fit-for-purpose to reliably demonstrate the absence of pesticides in samples to be analyzed. On the other hand, the fact that the overall detection rate at 0.01 mg/kg was 71% clearly showed that the method does provide added value for the numerous pesticides that are not covered by quantitative methods because the infrequent occurrence does not justify inclusion in such methods.