Kinetics of Conversion of Dihydroxyacetone to Methylglyoxal in Honey

Abstract

Mānuka honey contains a unique non-peroxide antibacterial activity which is highly sought after due to the perceived health benefits. Methylglyoxal (MGO) is the compound predominately responsible for this non-peroxide activity (NPA). Varying levels of dihydroxyacetone (DHA) are found in mānuka nectar which converts to MGO once honey is harvested; however, this is not a 1:1 conversion. The price of mānuka honey increases as the MGO concentration increases; hence some beekeepers store their honey for extended periods of time in an attempt to increase the concentration of MGO. The level of 5-hydroxymethylfurfural (HMF, a potentially toxic compound) must stay below 40 mg/kg if the honey is to be exported. Formation of HMF is predominately dependent on time and temperature. Therefore there is a trade off between storing honey to maximise the MGO concentration and retaining a low concentration of HMF.

Currently there is not a lot of information on the conversion of DHA to MGO in a honey matrix and many beekeepers are unable to predict the maximum MGO concentration from an immature honey. The principal aim of this thesis was to learn more about the conversion of DHA to MGO in a honey matrix in order to create a tool that can predict the concentration of DHA and MGO over time when held at certain temperatures.

Four high performance liquid chromatography methods were compared to find a suitable method for the analysis of the three compounds of interest (DHA, MGO and HMF). The chosen method allowed all three compounds to be detected (using O-(2,3,4,5,6-pentafluorobenzyl) hydroxylamine, PFBHA, derivatisation) in a single 30 minute analysis.

A set of mānuka honeys were analysed for various chemical and physical properties (including moisture content, pH, acidity, amino acids, selected phenolics and trace elements) to identify potential factors that may contribute to the conversion of DHA to MGO. Amino acids and phenolic acids were identified as potential compounds that affected the conversion of DHA to MGO.

Model systems (sugar and water) were used to control the reactions occurring during storage; DHA and individual perturbants were added to the artificial honey to isolate the effect of the perturbant on the conversion. Amino acids were the main focus of these systems; alanine enhanced the conversion of DHA to MGO, whereas DHA was lost to side reactions when proline was present. Real honey samples were also analysed; correlations between the rate constant for DHA disappearance and certain compounds were observed. Temperature influenced the rates of DHA conversion to MGO and also the efficiency of the reaction.

The information from the storage trials was used as a starting point to build a predictive model. This included equations for reactions involving DHA and perturbants (either enhancement of conversion to MGO or removal to a side product) and removal of MGO. The model used the initial concentrations of DHA, MGO, amino acids and some phenolic compounds to accurately predict the change in DHA and MGO over time when stored between 20 and 37 °C.