Pattern recognition methods and multivariate image analysis in HPTLC fingerprinting of propolis extracts

Abstract

High‐performance thin‐layer chromatography (HPTLC) combined with image analysis and pattern recognition methods were used for fingerprinting and classification of 52 propolis samples collected from Serbia and one sample from Croatia. Modern thin‐layer chromatography equipment in combination with software for image processing and warping was applied for fingerprinting and data acquisition. The three mostly used chemometric techniques for classification, principal component analysis, cluster analysis and partial least square‐discriminant analysis, in combination with simple and fast HPTLC method for fingerprint analysis of propolis, were performed in order to favor and encourage their use in planar chromatography. HPTLC fingerprint analysis of propolis was for the first time performed on amino silica plates. All studied propolis samples have been classified in two major types, orange and blue, supporting the idea of existence of two types of European propolis. Signals at specific RF values responsible for classification of studied extracts have also been isolated and underlying compounds targeted for further investigation. Copyright © 2014 John Wiley & Sons, Ltd.

Rapid discrimination of different Apiaceae species based on HPTLC fingerprints and targeted flavonoids determination using multivariate image analysis

“…Based on the similarity/dissimilarity analysis or correlation matrix, a number of unsupervised and supervised chemometric methods can be performed with the data, such as principal component analysis (PCA), hierarchical cluster analysis (HCA), linear discriminant analysis (LDA), partial least square discriminant analysis (PLS‐DA), k‐nearest neighbours (KNN), artificial neural networks (ANN), and partial least square (PLS) regression . This approach provides a systemic and objective way of analysing the HPTLC plate . One of the major advantages of adopting multivariate analysis for chromatographic fingerprints is that it scrutinises the subtle differences within the chromatogram.…”

“…It does not rely on the comparison to a reference sample or compound, or quantifying a particular chemical compound(s), which can be difficult to discern for an unknown . Despite several cases, there is still a need for more comprehensive TLC fingerprinting approaches based on the full chemometric processing of the collected data.…”

Elemental composition as a tool for the assessment of type, seasonal variability, and geographical origin of wine and its contribution to daily elemental intake

“…The PCA was carried out at the exploratory level to provide insight into the structure of data and reveal some logical pattern in the data. 24 In addition, PLS-DA was used as a multivariate classication model method aimed to nd mathematical models that can assign each sample to an appropriate class of wine type.…”

Comprehensive Study of Mediterranean (Croatian) Propolis Peculiarity: Headspace, Volatiles, Anti‐Varroa‐Treatment Residue, Phenolics, and Antioxidant Properties

“…-P ropolis is ac omplex phytochemical mixture and has been analyzed (after dissolvinga nd/or preparative steps)b yv arious methodologies, e.g., HPLC with different detectors [1 -3], GC/MS with or without derivatization procedure [4] [5],H P-TLC [6], micellar electrokinetic capillary chromatography [7], or NMR [8]. In addition, UV/VIS assays have been applied, e.g., to monitor the formation of AlCl 3 complexes for the quantitative determination of flavones and flavonols [9], the 2,4-dinitrophenylhydrazinem ethodf or flavanones [9], or the FolinÀCiocalteu method for the quantification of the total phenol (TP) content [10].…”