Rezumat articol ediţie STUDIA UNIVERSITATIS BABEŞ-BOLYAI

În partea de jos este prezentat rezumatul articolului selectat. Pentru revenire la cuprinsul ediţiei din care face parte acest articol, se accesează linkul din titlu. Pentru vizualizarea tuturor articolelor din arhivă la care este autor/coautor unul din autorii de mai jos, se accesează linkul din numele autorului.

 
       
         
    STUDIA CHEMIA - Ediţia nr.4 din 2019  
         
  Articol:   ULTRAVIOLET-VISIBLE (UV-VIS) SPECTROSCOPY AND CLUSTER ANALYSIS AS A RAPID TOOL FOR CLASSIFICATION OF MEDICINAL PLANTS .

Autori:  SIMONA CODRUȚA AURORA COBZAC, DORINA CASONI, MIHAELA BADEA, BILJANA BALABANOVA, NATALIJA MARKOVA RUZDIK.
 
       
         
  Rezumat:  
DOI: 10.24193/subbchem.2019.4.14

Published Online: 2019-12-20
Published Print: 2019-12-30
pp. 191-203
VIEW PDF: PDF

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.

Keywords: : medicinal plants, classification/identification, UV-Vis spectroscopy, cluster analysis
 
         
     
         
         
      Revenire la pagina precedentă