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SBSE-GCxGC-TOFMS Trace Level Organochlorine and Organophosphorous Pesticides Analysis in Brewed Green Tea

Applications | 2008 | LECOInstrumentation
GCxGC, GC/MSD, Thermal desorption, GC/TOF
Industries
Food & Agriculture
Manufacturer
Agilent Technologies, GERSTEL, LECO

Summary

Importance of the Topic


The presence of organochlorine and organophosphorous pesticide residues in brewed green tea presents both a public health and regulatory concern. Stricter international limits have driven the development of sensitive, high-resolution analytical techniques capable of detecting ultra-trace levels of multiple pesticide classes within complex matrices such as tea infusion. This study illustrates how coupling stir-bar sorptive extraction with two-dimensional gas chromatography and time-of-flight mass spectrometry addresses these challenges.

Objectives and Study Overview


The primary goal was to evaluate trace-level quantitation of 22 organochlorine and organophosphorous pesticides in a specific green tea brand. A calibration range from 10 to 500 parts-per-trillion was established to determine detectability, chromatographic resolution, and quantitative linearity. The study also compared the enhanced peak capacity of GC×GC-TOFMS against traditional one-dimensional separations in the context of pesticide analysis.

Methodology and Instrumentation


Stir-bar sorptive extraction (SBSE) was performed on 2 mL aliquots of brewed tea using a PDMS Twister bar at 1000 rpm for 60 min.
  • Thermal desorption of the stir bar was automated using a multipurpose sampler with a thermal desorption unit and cryogenic inlet.
  • Comprehensive two-dimensional gas chromatography employed a 10 m Rtx-5 MACH/LTM primary column and a 1 m Rtx-17 secondary column with a thermal modulator cycling every 4 s.
  • Time-of-flight mass spectrometry (45–550 amu) acquired data at 150 spectra/s, enabling full spectral capture for each modulation slice.
  • Data processing, deconvolution, peak identification, and quantification were managed via ChromaTOF software.

Main Results and Discussion


GC×GC-TOFMS generated contour plots exceeding 1200 peaks at a signal-to-noise ratio of 100, highlighting significant separation improvements over one-dimensional GC. Key coelutions in the first dimension, such as Sulfotepp and Lindane, were fully resolved in the second dimension with sub-200 ms separation. Calibration curves from 10 to 500 ppt yielded correlation coefficients above 0.990 for all 22 pesticides. Analysis of the tea sample revealed no detectable residues above the quantitation limits.

Benefits and Practical Applications


This integrated SBSE-GC×GC-TOFMS method delivers:
  • High sensitivity down to single-digit ppt levels without extensive sample cleanup.
  • Enhanced chromatographic peak capacity and resolution for complex mixtures.
  • Comprehensive mass spectral data for reliable compound identification.
  • Robust quantitative performance across a broad dynamic range.

Future Trends and Potential Applications


Emerging directions include coupling SBSE-GC×GC with high-resolution mass analyzers for even greater selectivity, miniaturizing extraction devices for field screening, and applying similar workflows to other food, environmental, and biological matrices. Advances in data processing and machine learning are expected to streamline deconvolution and improve automated peak annotation in complex chromatograms.

Conclusion


The described SBSE-GC×GC-TOFMS approach offers a rapid, sensitive, and reliable platform for trace-level pesticide residue analysis in brewed green tea. It meets stringent regulatory requirements, provides superior separation of isomeric and coeluting compounds, and supports accurate quantitation across ultra-low concentration ranges. This methodology can be adapted broadly for quality control and safety monitoring within the food industry.

Reference


  • Libardoni M., Heim J., Ochiai N., Sasamato K. SBSE-GC×GC-TOFMS Trace Level Organochlorine and Organophosphorous Pesticides Analysis in Brewed Green Tea. LECO Corporation & GERSTEL K.K., 2008.

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