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

• Published in: Journal of chromatography. B, Analytical technologies in the biomedical and life sciences Vol. 1170; p. 122590
• Main Authors: Simion, Ileana Maria, Casoni, Dorina, Sârbu, Costel
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 30-04-2021
• Subjects: Chemometric methods; Chromatography; Color scale image processing; Image analysis; Medicinal plant extracts classification; Chemometric methods; Image analysis; Color scale image processing; Medicinal plant extracts classification; Chromatography
• ISSN: 1570-0232; 1873-376X
• DOI: 10.1016/j.jchromb.2021.122590

•Color scale image procesing approach is proposed in HPTLC fingerprinting analysis.•Contribution of each color scale fingerprint was revealed by chemometric approach.•Medicinal plant extracts were classified by phylum using PCA-LDA approach.
A chemometric evaluation of the information provided by different color scale fingerprints in thin layer chromatographic analysis of complex samples is proposed for the correct classification of a set of medicinal plant extracts. The fingerprints of the samples were acquired on HPTLC Silica gel 60 F254 and HPTLC Silica gel 60 plates using multiple levels of visualization under UV light. Images processing on red (R), green (G), blue (B) and respectively grey (K) color scale selection was used in order to evaluate the complete chromatographic profile of the extracts. Combination of Principal Component Analysis (PCA) and Factor Analysis (FA) method was applied in order to reveal the individual contribution of each color scales in the analysis of chromatographic fingerprints. The suggested technique provides an applicable strategy to screen for efficacy-associated color scale for grouping/classification of the extracts exploiting the information provided by HPTLC fingerprints. The principal component analysis and linear discriminant analysis (PCA-LDA) method was applied for the evaluation of numerical data provided by color scale fingerprints digitization and for samples classification. A correct classification of the analyzed extracts according to the plants phylum was revealed by color scale fingerprints analysis. The proposed methodology could be considered as a promising tool with future applications in plant material investigations even from the taxonomic perspective classification.