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Qualitative Pesticide Screening of a Dried Cherry Sample Using HRMS

Applications | 2015 | WatersInstrumentation
Ion Mobility, LC/TOF, LC/HRMS, LC/MS, LC/MS/MS
Industries
Food & Agriculture
Manufacturer
Waters

Summary

Significance of the topic


High‐resolution mass spectrometry (HRMS) offers powerful non‐targeted screening capabilities for detecting pesticide residues in complex food matrices. By combining unbiased data acquisition with advanced data review workflows, HRMS addresses regulatory requirements for sensitivity, specificity, and rapid reporting while also enabling discovery of unexpected or unknown contaminants.

Objectives and Study Overview


This study evaluates the qualitative pesticide screening performance of the Waters Pesticide Screening Application Solution (PSAS) coupled with the UNIFI Scientific Information System. A dried cherry extract, previously characterized by LC–MS/MS, was re‐analyzed using a data‐independent MS acquisition. Key performance metrics included false positive/negative rates, ease and speed of data review, and the ability to identify both known and previously undetected pesticides.

Methodology and Instrumentation


Sample Preparation:
  • QuEChERS extraction of dried cherry (2.5 g/mL in ACN), dried and reconstituted to 1 g/mL in 75:25 water/ACN.
  • 10 µL injections for LC–HRMS analysis.

Chromatography and MS Conditions:
  • System: ACQUITY UPLC I-Class with BEH C18 column (1.7 µm, 2.1 × 100 mm) at 45 °C.
  • Mobile phases: 10 mM ammonium acetate (pH 5) in water (A) and methanol (B); gradient from 98:2 to 1:99 over 13 min, flow 0.45 mL/min.
  • Mass spectrometer: Xevo G2-XS QTof, ESI positive/negative, MS with low CE 4 eV and high CE ramp 10–45 eV; acquisition 50–1200 m/z at 4 spectra/s.

Used Instrumentation


  • ACQUITY UPLC I-Class System
  • ACQUITY UPLC BEH C18 Column (1.7 µm, 2.1 × 100 mm)
  • Xevo G2-XS QTof Mass Spectrometer
  • UNIFI Scientific Information System

Key Results and Discussion


All eight pesticides previously reported by LC–MS/MS were confidently detected with HRMS, and an additional seven compounds were identified, for a total of 15 residues. The combination of accurate‐mass precursor and fragment ion matching, tight retention‐time alignment (<±0.5 min), and isotope pattern scoring within UNIFI workflows delivered high specificity and low false‐positive rates. Componentization of data allowed extraction of clean spectra and chromatograms at peak apexes, enabling rapid visual confirmation of compound identity.

Benefits and Practical Applications


  • True non‐targeted screening for unlimited analytes in a single injection.
  • Simultaneous collection of qualitative and quantitative data for targeted and untargeted compounds.
  • Automated workflows and filters in UNIFI streamline data review, reducing analysis time and operator variability.
  • Fragment ion confirmation and isotope scoring greatly enhance confidence in residue identification.

Future Trends and Opportunities


As monitoring lists expand, HRMS screening will become increasingly central to routine food and environmental analysis. Integration of collision cross‐section (CCS) values, advanced statistical filtering, and machine‐learning algorithms will further improve unknown identification. Retrospective data mining and structural elucidation of novel metabolites will drive new insights in food safety and regulatory science.

Conclusion


The Waters PSAS with UNIFI and MS demonstrates robust qualitative screening of pesticides in complex matrices. High resolution, unrestricted acquisition, and an integrated review environment enable rapid, reliable identification of known and unexpected residues, supporting regulatory compliance and laboratory efficiency.

Reference


  1. Waters Corporation. An Overview of the Principles of MS: The Engine that Drives MS Performance. White Paper No. 720004036, October 2011.
  2. Cleland G., Graham K., Rosnack K., Burgess J. Simple HRMS Data Review Using Workflows, Views and Filters Within a Novel Integrated Scientific Information System. Technical Note No. 720005436en, June 2015.
  3. Waters Corporation. Waters UNIFI Scientific Information System Componentization. White Paper No. 720004587en, April 2013.

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