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Multivariate color scale image analysis - Thin layer chromatography for comprehensive evaluation of complex samples

Ileana Maria Simion1, Dorina Casoni1, Costel Sârbu1

  • 1Department of Chemistry, Babeş-Bolyai University, Faculty of Chemistry and Chemical Engineering, Arany János, No. 11, Cluj-Napoca, Romania.

Journal of Chromatography. B, Analytical Technologies in the Biomedical and Life Sciences
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Summary

This study introduces a chemometric method using color scale fingerprints from thin-layer chromatography for classifying medicinal plant extracts. The technique accurately groups extracts based on plant phylum, aiding in identification and efficacy screening.

Keywords:
Chemometric methodsChromatographyColor scale image processingImage analysisMedicinal plant extracts classification

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Area of Science:

  • Analytical Chemistry
  • Chemometrics
  • Chromatography

Background:

  • High-performance thin-layer chromatography (HPTLC) is crucial for analyzing complex mixtures.
  • Color scale fingerprints offer rich data for chromatographic analysis.
  • Accurate classification of medicinal plants is vital for quality control and research.

Purpose of the Study:

  • To evaluate different color scale fingerprints for classifying medicinal plant extracts using chemometrics.
  • To determine the contribution of each color scale (R, G, B, K) in HPTLC analysis.
  • To develop a strategy for grouping extracts based on efficacy-associated color scales.

Main Methods:

  • HPTLC analysis of plant extracts using UV visualization.
  • Image processing of fingerprints across red, green, blue, and grey color scales.
  • Application of Principal Component Analysis (PCA), Factor Analysis (FA), and PCA-LDA for data evaluation and classification.

Main Results:

  • Chemometric analysis of color scale fingerprints enabled accurate classification of medicinal plant extracts.
  • PCA and FA revealed the contribution of individual color scales to the chromatographic profile.
  • PCA-LDA successfully classified extracts according to their plant phylum.

Conclusions:

  • Color scale fingerprints combined with chemometrics offer a powerful tool for HPTLC analysis of complex samples.
  • The proposed methodology facilitates the screening for efficacy-associated color scales and grouping of extracts.
  • This approach shows promise for plant material investigation, including taxonomic classification.