Multivariate optimisation of a green UHPLC approach for fingerprinting Brazilian green propolis — ASN Events

Multivariate optimisation of a green UHPLC approach for fingerprinting Brazilian green propolis (#136)

Cristiano Funari 1 2 , Mari Egeness 1 , Renato Carneiro 3 , Alberto Cavalheiro 2 , Hernan J Cortes 1 4 , Emily F Hilder 1 , Robert A Shellie 1
  1. Australian Centre for Research on Separation Science , University of Tasmania, Hobart, Australia
  2. Chemistry Institute, São Paulo State University, Araraquara, BR
  3. Department of Chemistry, Federal University of São Carlos, Sao Carlos, BR
  4. HJ Cortes Consulting LLC, Midland, MI, USA

Acetonitrile and methanol are the most used organic solvents in liquid chromatography (LC) analysis in general and this pattern is also observed in analysis of propolis. Although these solvents present favourable properties for separation and detection in LC, they are potentially toxic 1, 2. Ethanol is a green alternative for replacing methanol in reversed phase LC, since both are from the same class of solvent selectivity3. Ethanol is a biodegradable, less toxic solvent that can be produced by fermentation of renewable resources4-6. While the high viscosity of ethanol/water mixtures is a drawback, the advantageous properties such as low volatility, miscibility with water, and UV cut-off at 210 nm, promote the use of ethanol as a mobile phase4-6. Propolis is a bee product used by bees to seal the beehive and keep it antiseptic.7 Propolis’ biological activities and chemistry are dependent to the flora from which the bees prepare propolis.7 For this reason a chromatographic fingerprinting approach to identify specific propolis types could be very useful. In this work, Experimental design was adopted to optimise an ultra-high performance liquid chromatography (UHPLC) method for fingerprinting Brazilian green propolis (produced mainly from Baccharis dracunculifolia). Five variables were investigated in a screening step by means of fractional factorial design.6 Then, the most relevant variables were employed in a Doehlert design. The mathematical model generated from this design predicted optimal conditions to maximise sample peak capacity. The optimised conditions led to a sample peak capacity of 562 ± 3 % (n = 7). The UHPLC approach to fingerprint green propolis was statistically optimised, which is in line with environmental legislation and analytical trends.

Acknowledgements: Grant #012/15877-7, São Paulo Research Foundation (FAPESP) and Australian Research Council (ARC)

  1. J. D. Pritchard, Health Potection Agency Compendium of Chemical Hazards: Methanol, Public Health England, 2011.
  2. R. Fritz, W. Ruth and U. Kragl, Rapid Commun. Mass Spectrom., 2009, 23, 2139-2145
  3. M. Vitha and P. W. Carr, J. Chromatogr. A, 2006, 1126, 143-194
  4. C. J. Welch, N. Wu, M. Biba, R. Hartman, T. Brkovic, X. Gong, R. Helmy, W. Schafer, J. Cuff, Z. Pirzada and L. Zhou, Trends Anal. Chem., 2010, 29, 667-680
  5. P. Sandra, G. Vanhoenacker, F. David, K. Sandra and A. S. Pereira, LC-GC Europe, 2010, 23, 242-259
  6. C. S. Funari, R. L. Carneiro, A. M. Andrade, E. F. Hilder and A. J. Cavalheiro, J. Sep. Sci., 2013, in press
  7. C. S. de Funari, V. de Oliveira Ferro and M. B. Mathor, J. Ethnopharm., 2007, 111, 206-212