A simple approach to reduce dimensionality from comprehensive two-dimensional liquid chromatography coupled with a...

Area of Science:

• Analytical Chemistry
• Chromatography
• Spectroscopy

Background:

• Comprehensive two-dimensional liquid chromatography (LC×LC) is crucial for complex sample analysis.
• LC×LC coupled with diode array detection (DAD) is valuable for non-target analysis and pattern identification.
• Large data volumes from LC×LC-DAD hinder wider application due to challenges in information extraction.

Purpose of the Study:

• To develop a simple and fast data treatment method for LC×LC-DAD systems.
• To address the challenge of extracting useful information from large multi-dimensional datasets.
• To enable pattern identification for characterizing complex samples.

Main Methods:

• Identification of three-dimensional (3D) regional maxima for each chromatographic peak.
• Utilizing retention times (1st and 2nd dimensions) and maximum UV absorption wavelength.
• Building a 3D fingerprint dataset for each sample.

Main Results:

• A novel, rapid method for processing large LC×LC-DAD data was developed.
• 3D fingerprints were generated, capturing key peak characteristics.
• The method successfully facilitated pattern identification in complex samples.

Conclusions:

• The developed 3D fingerprinting method simplifies and accelerates the analysis of LC×LC-DAD data.
• This approach aids in identifying patterns and characterizing samples based on their unique fingerprints.
• The methodology shows promise for non-target analysis, as demonstrated with Portuguese red wine samples.