High chromatography reproducibility enables large panel MRM assays for pesticides in fruit and vegetables

Methods

Material and solutions: All experiments were performed utilizing the iDQuant standards kit for pesticide analysis (SCIEX P/N 4465661) of certified reference material (ISP Guide 34, IOS/IEC 17025 and ISO 9001:2008) which includes 206 pesticides. The kit contains 10 mixes of about 20 pesticides each at initial concentrations of 100 µg/mL in 100% acetonitrile.

The kit was first used to optimize MRM conditions and adjust the retention times of existing methods to update the Scheduled MRM Pro algorithm for best performance.

Fruit and vegetable samples were extracted using an roQ QuEChERS extraction kit procedure [EN 15562 Kit, Phenomenex (P/N KS0-8909).

Sample preparation: Mix J of the SCIEX iDQuant kit for pesticide analysis, containing 20 compounds, was spiked into arugula sample and Mix C into red grape and used to verify method performance for identification and confirmation. Matrix calibrators of concentrations 1000, 500, 200, 100, 50 and 20 ng/mL were prepared.

Arugula and red grapes were frozen at -20°C, then thawed to room temperature prior to weighing and extraction. The following steps were performed, in the order listed:

• Preparation of 10 g of homogenized sample
• Addition of 10 mL acetonitrile and extraction by vigorous shaking for 1 min
• Addition of Phenomenex roQ QuEChERS kit buffer-salt mix (KS0-8909) and immediate vigorous shaking for 1 min using a vortex mixer
• Centrifugation for 10 min at 9000 rpm
• Transfer of a 1 mL aliquot of the sample extract into a tube containing Phenomenex roQ dSPE kit (KS0-8916, 8913, 8914 or 8915 depending on sample type)
• Cleanup by vigorous shaking for 30 sec and centrifugation at 9000 rpm
• Transfer of 500 µL of the cleaned sample extract into an autosampler vial
• 2x dilution with water prior to filtering through VWR 0.45 µm polypropylene filter and transfer to autosampler vial for LC-MS/MS analysis

Chromatography: LC separation was achieved using the SCIEX ExionLC 2.0 system and a Phenomenex Synergi 2.5 µm, 2.0 x 50 mm Fusion-RP column (P/N 00B-4423-B0). A 20 minute gradient of water and methanol with ammonium formate buffer was used, with a flow rate of 0.4 mL/min and column temperature of 40 ̊C. The SCIEX ExionLC 2.0 system autosampler was used with a configuration consisting of a 250 µL syringe, 250 µL buffer tubing, 100 µL sample loop and 15 µL needle tubing. In order to optimize sample consumption and minimize the injection cycle time, the injection mode used was the µL pick-up plus mode, and the injection volume was set to 2.0 μL. The syringe speed was set to low and speed factor to 1. Advanced rinse mode was used with 1000 µL acetonitrile/methanol/isopropanol (2:2:1 v/v/v) with 0.1% formic acid wash solvent and 1500 µL water/methanol (9:1 v/v) containing 5mM ammonium formate transport solvent.

Mass spectrometry conditions: The SCIEX Triple Quad 3500 system was operated with the Turbo V ion source using an electrospray ionization (ESI) probe. 428 MRM transitions were monitored (194 compounds in positive mode (388 transitions) and 20 compounds in negative mode (40 transitions) using the Scheduled MRM Pro algorithm with a detection window of 40 sec and with polarity switching to allow analysis of all compounds in a single method.

Data acquisition was performed using Analyst software 1.7.2 with Components for the ExionLC 2.0 system. It is worth noting that the ExionLC 2.0 system is also fully supported for instruments in which data acquisition is performed using SCIEX OS software 2.1.5 and later.

Data processing: Data processing of mass spectrometry acquired data was performed using SCIEX OS software 2.1.5 in which calibration curves, precision and accuracy statistics were generated.

High quality chromatography

428 MRM transitions were monitored using the Scheduled MRM Pro algorithm which allowed the quantification and identification of 200 pesticides in a single LC-MS/MS run. An example chromatogram of a matrix-matched standard at 20 ng/mL is shown in Figure 2. Very good separation was achieved, with narrow peak widths and very good peak symmetry, which is important when performing quantification. Peak symmetry was measured using the asymmetry factor—the distance from the center line of the peak to the back slope, divided by the distance from the center of the peak to the front slope, at 10% of the maximum peak—which is typically around 1.0. The example chromatograms shown in Figure 3 further highlight the narrow and symmetrical peak widths achieved with the LC system and selected chromatographic phase. For the data shown in Figure 3, the average asymmetry factor across the concentration range was 1.1 for emamectin, 1.1 for metaflumizone, 0.9 for acetamiprid and 0.9 for Fenuron.

Retention time reproducibility

Very good retention time stability is critical when using narrow retention time windows to ensure the peaks remain within the detection windows. Stability of the LC pump over time is critical to ensure consistent retention times are delivered across large sample batches. This reduces the time spent readjusting methods to accommodate retention time drifts and minimizes any lost data due to peaks shifting out of target windows. Figure 1 highlights the excellent LC pump stability with overlaid chromatograms from 25 consecutive injections. 

As shown in Figure 3, the retention time precision of each of the analytes across a range of retention times for these injections is less than 0.1% CV, with a mean of 0.066 % CV for the 150 compounds. For most compounds tested, the maximum retention time difference over 50 injections was <1.5 seconds.

Narrow retention time windows of 40 seconds were used in order to time-schedule such a large number of compounds in a single 20 minute acquisition method. Figure 4 illustrates the retention window width as centered around the detected peak.

When retention time stability is very good, more MRM transitions can be scheduled per run. In this method, two MRM transitions per compound were monitored in order to enable ion ratios to be computed between the quantifier and qualifier transitions. This is also highlighted in Figure 4, showing the ion ratio acceptance criteria lines that are automatically computed and plotted in Analytics in SCIEX OS software. 

Quantification performance

Solvent standards were injected at a concentration ranging from 20 to 1000 ng/mL. Example calibration lines are shown in Figure 5. Linear regression with 1/x weighting was used. The linear coefficient of determination (r²) was typically higher than 0.99.

The area reproducibility was also computed from 25 replicate injections of 1 µL, then 25 replicate injections of 10 µL, using the 100 ppb standard. Typical variance results are shown using selected compounds, without the use of internal standard, in Figure 6.

Compound identification

Compound identification is typically performed by retention time matching and calculating the ratio between quantifier and qualifier MRM transitions. The ion ratio of a detected pesticide in unknown samples is compared to the ratio observed in standard samples and tolerance levels are applied to affirm the positive detection of that target pesticide. These tolerance levels are defined by several guidelines and can be user-defined in the SCIEX OS software.

MRM ratios were automatically calculated in SCIEX OS software. The ratio of quantifier and qualifier peak areas in the unknown samples is automatically compared to the average ratio of all included standard samples for compound identification. Tolerance levels are displayed in the peak review window in Analytics. Here, a generic tolerance of 30% was used, following SANCO/12682/2019 guidelines.¹

Verification of qualitative performance

Mix J of the SCIEX iDQuant kit for pesticide analysis containing 20 compounds was spiked into the arugula sample and Mix C was spiked into the red grape sample at 10 µg/kg.

As well as MRM ratio comparisons, compounds are also identified based on retention time matching. That also makes it critical to have good retention time stability, which is achieved through a combination of good sample clean up, chromatographic conditions and gradient pump stability. The results of identification based on retention time matching and MRM ratio comparison are summarized in Table 1. All 20 pesticides were confidently identified in all spiked samples. The average retention time error ranged from 0.017 to 0.355% and the average MRM ratio error from -1.50 to 10.42%.

Conclusions

The SCIEX ExionLC 2.0 system has been successfully used in an LC-MS/MS method for the analysis of over 200 pesticides in food samples, after a QuEChERS based sample clean-up.

The key performance attributes of the SCIEX ExionLC 2.0 system, namely the flow rate precision and resulting retention time reproducibility, has enabled the use of the Scheduled MRM Pro algorithm workflows in the simultaneous identification and quantification of a large panel of pesticide residues. This has been achieved without any compromise in data quality by allowing both the cycle time and dwell time to remain optimal.

The method provided sufficient speed and sensitivity to quantify all of the pesticides (~200) with good linearity from 20 to 1000 ng/mL, with linear coefficient of determination (r²) performance typically above 0.99 and coefficient of variation typically well below 10%.

Qualitative method performance was verified by 20 compounds, into 2 different matrices at a concentration of 10 µg/kg. All compounds were confidently identified in all samples. This was, in part, due to the excellent pump stability afforded by the ExionLC 2.0 system, which was demonstrated by the retention time precision of each of the analytes across a range of retention times being less than 0.1% CV. Retention time errors observed were well below the ±0.1 min tolerance.

References

1. SANCO/12682/2019 guidelines. Analytical quality control and method validation procedures for pesticide residues analysis in food and feed.