Secrets of science magazine 02/2024

Significance of the topic

The contamination of water by a wide array of pesticides poses a critical threat to public health and the environment. Monitoring these substances accurately and efficiently is essential for safeguarding human and animal populations, ensuring regulatory compliance, and supporting sustainable water management.

Objectives and overview

This study evaluates a next-generation GC-MS platform equipped with AI-powered peak integration to perform rapid, simultaneous multi-pesticide analysis in water. The aim is to demonstrate enhanced sensitivity, reproducibility, and processing speed while minimizing operator bias and calibration errors.

Methodology and instrumentation

• Instrumentation:
  • Shimadzu GCMS-QP2050 entry model
  • AOC-30i autosampler
  • LabSolutions Insight GC-MS software with Peakintelligence™ algorithm
• Sample preparation:
  • Mixed aqueous standards of 140 pesticides (0.003–0.5 mg/L)
  • Internal standards: anthracene-d10, 9-bromoanthracene, chrysene-d12
  • Repeated precision tests at 0.005 mg/L
• Analytical conditions:
  • Splitless injection (2 µL), helium carrier gas
  • Column: SH-I-5Sil MS (30 m × 0.25 mm × 0.25 µm)
  • Temperature program: 80 °C (2 min) → 20 °C/min → 180 °C → 5 °C/min → 300 °C (3 min)
  • MS in SIM mode, ion source 230 °C, interface 250 °C
• Data processing:
  • Peakintelligence™ AI algorithm requiring no manual peak-integration parameters

Main results and discussion

• High sensitivity and linearity down to 0.005 mg/L with R² > 0.999 for representative compounds
• AI-based peak integration corrected baseline and peak overlap errors common in conventional methods
• Continuous calibration verification indicated stable results within 70–130% recovery across multiple runs
• Automatic AI processing reduced manual re-integration time and eliminated individual operator variability

Benefits and practical applications

• Reliable multi-pesticide quantitation at trace levels supports regulatory compliance for drinking and environmental water
• Automated AI integration streamlines data processing, decreases training requirements, and increases throughput
• High-performance GC-MS with AI enables laboratories to handle large sample loads with consistent objectivity

Future trends and potential applications

• Adoption of hydrogen carrier gas with turbomolecular pumps for further sensitivity gains
• Extension of AI-driven integration to additional compound classes and complex matrices
• Integration with remote or in-field GC-MS platforms for real-time water monitoring

Conclusion

The combination of the Shimadzu GCMS-QP2050 entry model with LabSolutions Insight and the Peakintelligence™ AI algorithm delivers high-sensitivity, fully automated multi-pesticide analysis. By eliminating manual integration errors and reducing processing time, this approach offers a robust and scalable solution for modern water quality laboratories.