Ultraviolet-visible (UV-VIS) spectroscopy and cluster analysis as a rapid tool for classification of medicinal plants

The ultraviolet-visible (UV-Vis) spectroscopy coupled with cluster analysis (CA) was evaluated for the classification of some medicinal plants of different geographical growing area. To have a deeper view, the experiment was carried out on herbs belonging to different families. The UV-Vis spectra of hydroalcoholic extracts were acquired in the range of 200-800 nm. The hierarchical clustering analysis (HCA) was applied to the data matrix provided by unprocessed, normalized and standardized spectra respectively. Different types of distance measuring of (dis)similarity between the samples as well as different kinds of linkage or amalgamation rule were taken into account. The best results for the classification of the selected medicinal plants were obtained using Ward’s method as the amalgamation rule combined with 1-Pearson r clustering distance measurement. The obtained results reveal the ability of HCA with Ward and 1-Pearson r algorithm to identify plant species even when the raw material has different provenience areas and different pedoclimatic growing conditions. In addition, this methodology revealed a direct link between herbs from different families

Application of HPTLC Multiwavelength Imaging and Color Scale Fingerprinting Approach Combined with Multivariate Chemometric Methods for Medicinal Plant Clustering According to Their Species

In the current study, multiwavelength detection combined with color scales HPTLC fingerprinting procedure and chemometric approach were applied for direct clustering of a set of medicinal plants with different geographical growing areas. The fingerprints profiles of the hydroalcoholic extracts obtained after single and double development and detection under 254 nm and 365 nm, before and after selective spraying with specific derivatization reagents were evaluated by chemometric approaches. Principal component analysis (PCA) with factor analysis (FA) methods were used to reveal the contribution of red (R), green (G), blue (B) and, respectively, gray (K) color scale fingerprints to HPTLC classification of the analyzed samples. Hierarchical cluster analysis (HCA) was used to classify the medicinal plants based on measure of similarity of color scale fingerprint patterns. The 1-Pearson distance measurement with Ward’s amalgamation procedure proved to be the most convenient approach for the correct clustering of samples. Data from color scale fingerprints obtained for double development procedure and multiple visualization modes combined with appropriate chemometric methods proved to detect the similar medicinal plant extracts even though they are from different geographical regions, have different storage conditions and no specific markers are individually extracted. This approach could be proposed as a promising tool for authentication and identification studies of plant materials based on HPTLC fingerprinting analysis

Regional pattern and characteristics of essential elements in several medicinal plants using spectrometric methods combined with multivariate statistical approaches

The aim of this study was to provide a regional pattern and characteristics of essential elements in several medicinal plants from North Macedonia and Romania. The content of Ca, Mg, Al, Fe, Cu, Ba and Zn was determined by ICP-OES while Na and K by FAES in some medicinal plants belonging to sixteen families. Similar profiles of elements with a high content of Ca, Mg and K were observed. Peppermint and blackberry from both countries showed extreme content in Al and Fe. A symmetric distribution for K, Ca and Zn and an asymmetric one for Na, Al, Fe and Ba were found in medicinal plants from both countries. Potassium, Ca, Mg, Al and Fe could be considered as markers for growing area. Principal Component Analysis highlighted that the variability of elements content was described by four factors (83.4%) in North Macedonia and three factors (70.0%) in Romania. The first factor could explain the influence of soil nature upon variability of elemental composition, calcareous in North Macedonia (Mg and Ca - 29.4% variance) and a rich one in hydroxides in Romania (Al and Fe - 33.1 % variance). Keywords: essential element, medicinal plant, inductively coupled plasma optical emission spectrometry, flame atomic emission spectrometry, Principal Component Analysis, two-way joining Cluster Analysi

Values of the equivalent circuit parameters for electrodes with plant extracts.

<p>Values of the equivalent circuit parameters for electrodes with plant extracts.</p

Average values of the equivalent circuit parameters for various OTA concentrations.

<p>Average values of the equivalent circuit parameters for various OTA concentrations.</p

Sensors used for ochratoxin A detection.

<p>Sensors used for ochratoxin A detection.</p

<i>Ochratoxin A</i> Detection on Antibody- Immobilized on BSA-Functionalized Gold Electrodes - Fig 4

<p>Nyquist plots at 10 mV sinusoidal ac potential perturbation, ferricyanide/ferrocyanide redox couple, for response of sensor with an antibody specific for OTA (A) or of sensor without antibody (B).</p

Schematic outline of the electrochemical immunosensor for OTA determination.

<p>Schematic outline of the electrochemical immunosensor for OTA determination.</p

Averages values of the equivalent circuit parameters for various steps of the immunosensor.

<p>Averages values of the equivalent circuit parameters for various steps of the immunosensor.</p

OTA concentration in spiked plant extracts.

<p>OTA concentration in spiked plant extracts.</p