Handling within run retention time shifts in two-dimensional chromatography data using shift correction and modeling

Area of Science:

• Analytical Chemistry
• Chemometrics
• Chromatography

Background:

• PARAFAC (Parallel Factor Analysis) is widely used for GCxGC-TOFMS data due to its trilinear structure.
• Temperature programming in GCxGC can cause deviations from trilinearity, leading to retention time shifts.
• These shifts complicate peak modeling, especially for broadened or highly retained analytes.

Purpose of the Study:

• To evaluate PARAFAC2 for modeling GCxGC-TOFMS data with retention time shifts.
• To compare PARAFAC2 with a standard retention time correction method followed by PARAFAC.
• To assess the performance of these methods under various conditions and on real data.

Main Methods:

• Application of PARAFAC2 to handle individual peak profile variations across modulation periods.
• Implementation of retention time shift correction followed by standard PARAFAC analysis.
• Comparative analysis using simulated and real GCxGC-TOFMS data with known analytes and concentration series.

Main Results:

• PARAFAC2 successfully models shifted peak profiles by allowing generation of individual peak shapes.
• The retention time shift correction method also improved data trilinearity for subsequent PARAFAC analysis.
• Both methods showed varying performance based on shift severity, signal-to-noise ratio, and model parameters.

Conclusions:

• PARAFAC2 offers a robust approach for analyzing GCxGC-TOFMS data affected by retention time shifts.
• The choice between PARAFAC2 and shift correction depends on specific chromatographic challenges and data characteristics.
• Accurate analyte identification and quantification are achievable even with significant peak profile deviations.