Multivariate look at the TLC retention: A concise review

ABSTRACT

The multivariate analysis of retention data in thin-layer chromatography (TLC) allows the chromatographer to visualize the multidimensional retention data and explore hidden properties and dependences. The most often used techniques are hierarchical cluster analysis and principal component analysis; however, some other techniques are also reported. This review presents an introduction and focuses on the application of multivariate TLC retention data in retention modeling, lipophilicity determination, QSAR/QSRR (as supporting tool), solvent selection, and comparison of TLC with other separation methods. It seems that multivariate analysis of chromatographic data can bring significant improvement to discussion of any chromatographic study.

KEYWORDS:

• Cluster analysis
• multivariate analysis
• PARAFAC
• principal component analysis
• thin layer chromatography