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In a recent webinar, which is now available on-demand, Holly Lee powerful strategies to tackle complex residue testing. From boosting throughput to fine-tuning method sensitivity, Holly shared key ways to maximize performance across large pesticide panels.

Catch the top audience questions—and the expert answers that followed—below.

Does SCIEX provide a consolidated list of MRLs ( Maximum Residue Limits) established by regulatory bodies world wide? The Food and Agricultural Organization (FAO) of the United Nations maintains a Pesticide Registration Toolkit, which lists multiple sources of both international and national/regional MRLs.

The New Zealand Ministry of Primary Industries maintains a database of global MRLs and provides links to the specific MRL legislations and regulatory bodies of different countries.

The FOODCHAIN ID Regulatory Limits also maintains an international database of MRLs, although only the US MRLs are available for free upon registration, while access to the global MRLs covering >130 countries requires a subscription.

What internal standards are commonly used for pesticide analysis?

Internal standards were not used in the pesticide assays, which necessitated the use of matrix-matched standards to correct for matrix effects, as demonstrated in the technical note. Procuring isotopically-labeled internal standards for each analyte would have been very challenging given the large target panel, but careful selection of a few surrogate internal standards to represent the diverse chemistry across the analytes may improve recoveries.

What is the typical percentage of uncertainty associated with the standard  methods compated to   your methods? I’m particularly interested in how deviations from ISO procedures might impact result variability.

The small number of batches tested here would not provide a good comparison of the uncertainty percentage against other methods. The ideal comparison would require different labs implementing this method for routine analysis, followed by periodic assessment of the uncertainty from multiple batches ran overtime.

How many MRM transitions can be monitored with polarity switching enabled on your system?

In the pesticides in tea project, 422 MRM transitions were monitored, with 412 transitions in the positive mode and 10 transitions in the negative mode.

What criteria are used to exclude former candidate ions from analysis?The “Exclude former candidate ions” parameter allows the user to pause triggering EPI scans of previously selected precursor ions based on a user-specified frequency. This prevents redundant fragmentation and helps optimize cycle times for better data acquisition efficiency. In the pesticides in juice project, this parameter was set to pause triggering for 4 seconds after 2 repeated occurrences of a candidate precursor ion.

From matrix matching, were the samples spiked before the QuECHERs extraction, or was spiking performed afterward?Apparent and absolute recoveries were evaluated by spiking before and after the QuEChERS extraction.

For determining the apparent recoveries, the spiking occurred directly into a composite tea matrix, followed by the extraction. The concentrations in these pre-spiked samples were quantified against the matrix-matched calibration curves and compared against the nominally spiked levels to calculate the apparent recoveries.

For determining the absolute recoveries and matrix effects, the unspiked tea matrix first underwent extraction, followed by spiking in the final extract. The areas in these post-spiked samples were compared against those in the pre-spiked samples and the aqueous calibration standard at the same concentration to calculate the absolute recoveries and matrix effects, respectively.

For the pesticides that showed poor recovery in tea matrices, are there alternative strategies to improve the results?

The addition of isotopically-labeled and/or surrogate internal standards before extraction and before injection would help correct for extraction losses, matrix effects and instrumental variations. Given that only a small subset of the panel exhibited poorer recoveries and matrix effects, the use of internal standards to target these specific compounds would be more economically feasible than for the entire list. However, compromises to certain method optimizations, such as the source parameters and sample preparation, were inevitable due to the diverse physicochemical properties in the large pesticides panel. For example, some macrocyclic lactones, such as avermectin, are susceptible to thermal degradation in the ion source and may require lower source temperatures. For these analytes, a separate method may be required to optimize the quantitative performance.

When using the QTRAP 6500+ for multi-residue pesticide method, I notice poor peak shapes and reduced sensitivity when enabling DBS or EPI/IDA modes. Could this be due to cycle time, dwell time, or other settings specific to these modes? What can I do to improve peak shape and maintain quantification performance?

Triangular or trapezoid-like peak shapes typically indicate that insufficient data points were collected across each LC peak. A target number of 10–12 data points (ideally >15) should generate a well-sampled peak for reproducible integration. Peak sampling efficiency highly depends on the cycle time, which in turn is influenced by MRM concurrency and dwell time. If too many analytes elute at the same time, the concurrency would increase the cycle time to a value higher than the desired value, resulting in poorly sampled peaks.

A few tips and tricks:

1. For the analytes with poor peak shapes, check the MRM concurrency in that region. If too many other analytes are eluting at the same time, the gradient may need to be optimized to improve peak resolution. A quick calculation based on the LC peak width and the desired number of data points across each peak can help optimize for the appropriate cycle time. In addition, the scheduled MRM algorithm (sMRM) will significantly improve cycle times by selectively acquiring data only within the retention time (RT) windows of each transition.
2. Optimize the dwell time based on the strength of the MRM transition – lower dwell times for more sensitive transitions, higher dwell times for less sensitive transitions. While a higher dwell time can help improve signal-to-noise ratio, the extra time spent on that transition will add to the overall cycle time. The Method Editor in SCIEX OS software automatically calculates the dwell times for each transition based on the concurrency and the user-defined cycle time.
3. The EPI scan also adds extra scan time to the overall cycle time; therefore, it is important to optimize the DDA criteria to avoid redundant triggering. For example, setting the intensity threshold too low would cause over-triggering. If your LC peaks are relatively Gaussian-shaped, I recommend turning on DBS so that the EPI triggering is based on the change in the peak intensity, instead of the absolute value. This usually means EPI triggering would occur as the peak starts eluting, during which the intensity would sharply increase. The Exclusion List would also be useful for avoiding triggering undesired analytes, such as known contaminants or internal standards. Dynamic exclusion, as indicated by the “Exclude former candidate ions”, is another parameter that allows the user to decide on the cadence of EPI triggering.

What chromotpgraphic column, injection volume and mobile phase are typically used for large-panel pesticide assays?

For the pesticides in tea project, we used a Phenomenex Kinetex Biphenyl column (2.6 μm, 100 mm x 3 mm, P/N 00D-4622-Y0). The injection volume was 10 μL. The mobile phases consisted of 90:10 (v/v) water/methanol and 90:10 (v/v) methanol/water for A and B, respectively, both with 5mM ammonium formate.

Does the QTRAP system offer screening capabilities similar to those of a QTOF?

QTRAP can generate full-scan MS/MS spectra like QTOF, but the selectivity of the two instrument types is significantly different due to the wide discrepancy in resolution. Nominal mass systems like the QTRAP have unit resolution (~0.7 Da FWHM), while accurate mass systems like the QTOF have much higher resolution (SCIEX QTOF system, ≥42,000 (FWHM)). The increased selectivity from the higher resolution enables the QTOF to better differentiate isomers or isobars through narrow mass filtering, which may otherwise be indistinguishable at unit resolution on a QTRAP system. However, if other identification criteria are met (i.e. RT, ion ratios, alternative fragment ion), the MS/MS spectra generated by either systems can provide another line of confidence through library searching or comparison against published MS/MS databases.

Is it possible to analyze pyrrolizidine alkaloids using SCIEX ATRAP systems? Yes, the SCIEX QTRAP systems have been used for developing methods for the detection and quantitation of pyrrolizidine alkaloids (PA). I recommend the following technical note and publications featuring the SCIEX QTRAP systems.

Technical note:

Highly selective analysis of pyrrolizidine alkaloids in herbal extracts

Publications:

Lin, R. et al. Foods. 2025, 14, 1147.

Chung, S.W.C. et al. J. Agric. Food Chem. 2018, 66, 3009-3018.

Sixto, A. et al. ACS Omega. 2019, 27, 22632-22637.