Multivariate image analysis-thin layer chromatography (MIA-TLC) for simultaneous determination of co-eluting...

Area of Science:

• Analytical Chemistry
• Chromatography Science

Background:

• Peak overlapping is a significant challenge in Thin-Layer Chromatography (TLC).
• Accurate simultaneous determination of co-eluting compounds is crucial for various analytical applications.

Purpose of the Study:

• To apply multivariate image analysis (MIA) for the first time to Thin-Layer Chromatography (TLC).
• To develop a method for the simultaneous determination of species with overlapping chromatograms.

Main Methods:

• An imaging system with a digital camera and MIA software was used to record TLC plate images.
• Multivariate calibration using partial least squares (PLS) was applied to 2D and 3D chromatograms.
• Principal component analysis and variable selection were employed to optimize models.

Main Results:

• The MIA-TLC method successfully determined co-eluting components in synthetic and real mixtures.
• Accurate quantification was achieved with relative errors below 10%, often below 5%.
• Validated for ternary mixtures of indicators and nifedipine with its degradation product.

Conclusions:

• MIA offers a powerful solution for resolving peak overlapping in TLC.
• The developed MIA-TLC method enables accurate simultaneous analysis of complex mixtures.
• This approach advances quantitative analysis in TLC for overlapping components.