Application of principal components analysis to 1H-NMR data obtained from propolis samples of different geographical origin

D. G. Watson, E. Peyfoon, L. Zheng, D. Lu, V. Seidel, B. Johnston, J. A. Parkinson, J. Fearnley

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33 Citations (Scopus)


Propolis is a widely used natural remedy and a range of biological activities have been attributed to it. The chemical composition of propolis is highly variable and its quality is often controlled on the basis of one or two marker compounds. In order to progress towards a method for the quality control of this complex material, HPLC and 1H-NMR approaches as methods of quality control have been compared. HPLC analyses of 43 samples of propolis were carried out and six marker compounds were quantified in each sample. The same samples were analysed using 1H-NMR and the spectra were then converted into their first derivative forms and digitised using the software application MestRe-C. The digitised data were subjected to principal component analysis using the software application Simca-P. It was found that the chemical composition of propolis mapped well according to the geographical origins of the samples studied when the first three principal components were used to display them. In addition, each sample was assessed for anti-oxidant activity, and the results were then overlaid onto the sample groupings according to 1H-NMR data. It was observed that anti-oxidant properties also mapped quite well according to geographical origin.
Original languageEnglish
Pages (from-to)323-331
Number of pages9
JournalPhytochemical Analysis
Issue number5
Early online date18 Jul 2006
Publication statusPublished - Sep 2006


  • propolis
  • anti-oxidant properties
  • HPLC
  • nuclear magnetic resonance spectroscopy
  • Machine Learning

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