Introduction

In the global consumer trade of honey, batches of honey are tested to ensure quality (age and storage condition) and authenticity (adulteration from other sugar sources). Quality testing identifies excessive heat treatment or aging by analysing diastase activity or the presence of 5-hydroxymethylfurfural (HMF). Diastase is the common name given to α- and β-amylases but is used interchangeably for α-amylase in honey as no β-amylase is present. Diastase is of bee origin which is added during honey ripening. The enzyme activity is used as a proxy for honey quality since heat denatures the enzyme [1, 2]. The CODEX recommends that the diastase number (DN) must be above 8, with the exception of low enzyme honeys (such as citrus) that have a lowered threshold of > 3 DN [3]. The EU directive also states that low enzyme honeys must not exceed 15 mg/kg HMF [4].

Mānuka honey is produced from the nectar of the Leptospermum scoparium (mānuka) tree and is highly sought globally due to the unique non-peroxide anti-bacterial activity [5]. This unique antibacterial activity is attributed to the presence of methylglyoxal (MGO), forming from the conversion of dihydroxyacetone (DHA) [6]. Mānuka honey is stored at moderate temperature over extended time before export for this conversion to take place to increase the antibacterial rating of the honey.

While diastase activity is a general indicator of honey age and excessive storage conditions, various factors complicate interpretation of the metric. Diastase activity levels are susceptible to multiple factors including bee age due to the expression of α-amylase changing over time [1, 2], microbial contributions of the enzyme [7], reactive species in the honey [8, 9], and a mismatch in optimal pH of the enzyme compared to the pH of honey [10, 11]. Additionally, diastase declines naturally over time without excessive heat treatment. Previous research reports that diastase activity decreases faster in mānuka honey compared to other floral honeys stored under the same conditions. DHA, MGO and 3-phenyllactic acid (3PLA) have been identified as compounds contributing to this increased decline in diastase activity [12].

The most common methods for determining diastase activity in honey include the Schade, Phadebas, Association of Official Analytical Collaboration (AOAC) 958.09 and more recently the p-nitrophenol method [13, 14]. These stopped assays measure the assay end point via colourmetric detection between 600 and 660 nm. Diastase activity is expressed as diastase number (DN) and is defined as the quantity of enzyme that converts 0.01 g of starch to the prescribed end-point at 40 °C in 1 h under the test conditions [15, 16]. Stopped-assay methods measure activity after terminating the reaction and are ideal for high-throughput screening and a single activity point which suits the needs of the honey industry. These methods, however, utilise a single substrate concentration and hence do not account for the complexity of substrate-enzyme binding interactions which can greatly affect enzyme rates [17, 18]. This is a disadvantage for mānuka honey because it overlooks any effects on diastase activity other than denaturation which could occur from the presence of unique compounds interacting with the enzyme.

Mānuka honey is a complex matrix, containing many compounds, often unique or in high abundance compared to other floral honeys [19]. Compounds within the honey matrix may bind to amino acids on the protein which can impact the structure, leading to alteration of enzyme activity [20]. Many MGO-specific protein alterations are reported in the literature, including reactions with cysteine, lysine, histidine and arginine (see Online Resource 1). MGO-induced modifications include carboxyethyl-cysteine (CEC), carboxyethyl-lysine (CEL) and a variety on arginine residues include argpyrimidine, carboxyethyl arginine (CEA). Examples of surface modifications with more than one amino acid involved in the modification include MGO-di-Cys [8], MGO-tri-Cys [8], putative crosslinking [21], Cys-MGO-Arg (MICA) [22,23,24], MGO-lysine dimer (MOLD) [8, 25,26,27], MGO-lysine-arginine dimer (MODIC) [8, 25] and adduct [28]. DHA undergoes Maillard reactions with amino groups of free amino acids [29, 30].

Given the complexity of mānuka honey, the unique presence of DHA and MGO and high concentration of phenolic compounds, enzyme activity and stability is vastly complicated in this matrix. No study thus far, has investigated the enzyme kinetics of individual compounds present in high concentration in mānuka honey or potential synergistic effects on altering diastase enzyme activity over time. Overall, this research investigated the effects of mānuka honey specific compounds (DHA, MGO and 3PLA) on diastase activity when honey is stored to provide new information on the causes of activity loss.

Methods

Samples

Two mānuka honey samples, extracted in summer 2024, were supplied by Prolife Foods, Hamilton, New Zealand, a commercial honey packer. Both honeys were classified as monofloral mānuka honey according to the New Zealand Ministry for Primary Industries (MPI) mānuka honey science definition. The starting concentrations of these compounds, along with DHA, MGO and HMF are reported in Online Resource 2. Clover honey from the same company was purchased from a commercial outlet, several jars with the same batch number were combined and homogenized to form one clover honey batch. This honey was sub-portioned for the storage trial. All honeys were stored in the freezer (− 23 °C) when not used for analysis. A separate clover and mānuka honey were used as quality control (QC) honeys for the enzyme kinetics analysis.

Chemicals

Methylglyoxal solution (MGO, ~ 40%) was obtained from Fluka. 5-hydroxymethyl-2-furfuraldehyde (HMF, 99%), 1,3-dihydroxyacetone dimer (DHA, 97%), hydroxyacetone (HA, 90%), ᴅ-(+)-glucose (≥ 99.5%), sucrose (ACS grade) and ᴅ-(-)-fructose (≥ 99%) were purchased from Sigma. O-(2,3,4,5,6-pentaflurobenzyl)hydroxylamine hydrochloride (PFBHA, 99+%) was purchased from Alfar Aesar and citric acid (> 99%) was purchased from Ajax FineChem.

Potassium iodide (PI, > 99%) and starch soluble iodometric indicator (> 99%) were purchased from Ajax Chemicals. Iodine resublimed (99.5%) was from BDH and sodium chloride (≥ 99.5%), sodium acetate (≥ 99%) and glacial acetic acid (100%) were purchased from Sigma. Tris(hydroxymethyl)aminomethane (ACS reagent, Ph Eur), calcium chloride (ACS reagent, Ph Eur), sodium chloride (≥ 99.5%), ammonium sulfate (ACS, ISO reagent, Ph Eur), ammonium persulfate (APS, ≥ 98%), ortho-phosphoric acid (85%), methanol (≥ 99.9%), glycine and N, N,N’N’-tetramethylethylenediamine (TEMED, 99%) was purchased from Sigma. Sodium dodecyl sulphate (SDS, ≥ 99%) and 30% Acrylamide/Bis 37.5:1 purchased from BIO-RAD. Coomassie blue G-250 was purchased from BDH.

Analysis of methylglyoxal, dihydroxyacetone and 5-hydroxymethyl-2-furfuraldehyde

Samples were analysed according to the method used by Grainger et al. [31] In brief, honey (1.0 ± 0.1 g) was dissolved in type 1 water (4.4 mL) and homogenized. Sample solution (150 µL) and HA: ACN (0.7 mL, 1:19) were mixed followed by addition and mixing of PFBHA solution (0.1 mL). Samples were incubated (50 °C, 60 ± 10 min) before analysis by high-performance liquid chromatography (HPLC). Separation was performed on a Kinetex® C18 150 × 4.6 mm, 5 μm column. Mobile phases were A: 30% ACN in type 1 water (v/v) and B: 100% ACN using the following gradient 0 min (10% B), 2.5 (85), 5.5 (85), 7.00 (10), 10.50 (10). The flow rate was 0.8 mL/min, injection volume was 10 µL and column oven and sample chamber temperatures were 30 °C and 8 °C respectively. The individual 2D detection channels were set at 260 nm (DHA, HA and PFBHA), 273 nm (HMF) and 244 nm (MGO). Retention times for quantification for DHA, HA, PFBHA, HMF and MGO isomers 1 and 2 were 4.09, 4.80, 4.45, 4.97, 7.5 and 7.98 min respectively.

Diastase activity

Analysis was carried out by an International Accreditation New Zealand (IANZ) accredited laboratory using the Phadebas method [32]. Disatase activity is expressed as diastase number (DN).

Mānuka marker analysis

The mānuka marker analysis for the quantification of 3PLA, 2- methyoxyacetophenone (2MAP), 2-methoxybenzoic acid (2MBA) and 4- hydroxyphenyllactic acid (4HPLA) was carried out by an IANZ accredited laboratory using the MPI mānuka marker LC-MS/MS analysis method [33].

Enzyme kinetics analysis

This method was developed from the official IHC Schade method and adapted for an enzyme kinetic experiment [32]. Sodium chloride solution (100 mL, 0.029 g/mL) was prepared. Iodine stock solution was made by dissolving iodine resublimed (11.0 g) and potassium iodide (22.0 g) in 30–40 mL of type 1 water and then making it up to 500 mL with type 1 water. Acetate buffer solution (pH 5.3) was made by dissolving sodium acetate (43.5 g) in ~ 200 mL type 1 water, adjusted the pH to 5.3 with glacial acetic acid (~ 5 mL) and made to 250 mL with type 1 water. The iodine stock solution was stored in the dark and all other solutions were stored at room temperature.

On the day of analysis, fresh starch stock solution (0.02 g/mL) and dilute iodine solution were prepared. Honey (1.000 ± 0.001 g) was dissolved in type 1 water (1.5 mL) and acetate buffer solution (0.5 mL). To the homogenized mixture, sodium chloride solution (0.3 mL) and type 1 water (2 mL) were added to get a final volume of 5 mL and was tested within 3 h.

The spectrophotometric measurements for the final λ660 readings were carried out in 200 µL volumes in 96 well plates. The reaction of samples was carried out by adding honey solution (0.4 mL) with starch substrate solutions of various concentrations (0.2 mL). Samples were homogenized and at 5 min intervals; 3 µL of each reaction mix was added to 157 µL type 1 water and 3 µL dilute iodine solution, homogenized and instantly measured at λ660. Assays were carried out in duplicate.

Data of starch concentration versus enzyme activity were fitted with the Michaelis Menten (reaction rate = Vmax [S] / KM + [S], where [S] is the concentration of starch substrate) in GraphPad Prism (version 6) software using least squares regression analysis. Fitting statistics were calculated in the software and are reported in Online Resource 3. Reported errors for the Vmax and KM are for the best fit values across two replicates. Statistical significance of changes over time was assessed for each time course via an extra sum of squares F test (GraphPad Prism version 6), assessing if a different fitted curve is justified for each time point (alternative hypothesis), or if one curve for all/both curves was sufficient (null hypothesis) with a P value cut of = 0.05. Time courses were analysed across all four time points as one, and also if later time points were significantly different to the previously measured time point. Full fitting and statistical analysis are available in Online Resource 4.

Storage trial

The time trial honeys (mānuka and clover) were incubated at 27 °C for approximately 6 months (203 days). Sub-samples were periodically taken and stored at − 18 °C until analysis.

Results and discussion

This research investigated the influence of compounds present in mānuka honey on the loss of diastase activity and isolated the cause for this loss using enzyme kinetics (Vmax and KM). Two mānuka honey samples, with different starting DHA, MGO and 3PLA concentrations, were stored for 200 days (6 months) at 27 °C to determine the loss of diastase activity and the change in enzyme kinetics (Vmax and KM). To isolate the effects of these compounds, clover honey (which does not naturally contain these compounds) were added in known concentrations to a clover honey. Clover honey is a suitable matrix because it contains native diastase and does not contain many compounds from the plant source; this approach has previously been used in the literature [12, 34]. MGO and 3PLA were investigated because previous research has reported elevated concentrations of these compounds increased the loss of diastase activity in mānuka honey [12]. DHA was included to simulate the natural conversion to MGO overtime and elucidate if it also played a role in reducing diastase activity.

Incubation was carried out at 27 °C to compare changes across samples. This temperature has been used in previous honey ageing studies [12, 31] and is within the temperature range used within the mānuka honey industry to facilitate the conversion of dihydroxyacetone (DHA) to methylglyoxal (MGO) while avoiding the use of higher temperatures that may introduce additional degradation pathways not representative of typical storage conditions. Storage of 203 days at 27 °C allowed measurable changes to occur and allow conclusions to be drawn.

The initial and final values for each analysed parameter (DHA, MGO, 3PLA, DN, Vmax and KM) are summarised in Table 1. 3PLA is one of the four chemical compounds used to define mānuka honey due to its stability [33]. The small change in the concentration of 3PLA from the initial to final days in the clover spiked samples may be due to insufficient mixing at the start of the time trial. All samples showed a decrease in diastase activity over the 200 days, albeit to various extents (Table 1). Figure 1 shows the diastase activity normalised to day 0 activity for each sample so that changes over time can be directly compared between samples.

Table 1 DHA, MGO, 3PLA, diastase activity (DN) and kinetics values (Vmax and KM) for initial and end time points*
Full size table

†3PLA is one of the four compounds analysed for the mānuka marker definition due to its stability. The change in concentration between initial and final days for the spiked samples is likely due to insufficient mixing during preparation of the dosed samples.

Fig. 1
Normalised diastase activity decreases over time in all samples, with the largest declines in mānuka 2 and mānuka 1. By about 200 days, they reach approximately minus 15.5 and minus 11.5, respectively. Clover samples decline less, ending between approximately minus 3.5 and minus 6. Clover with MGO initially rises before declining.
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Normalised diastase activity in mānuka honeys 1 and 2 and clover honey (control and spiked) samples stored at 27 °C, over ~ 200 days. Analysis was carried out in an IANZ accredited laboratory; the uncertainty of measurement is reported as ± 20%. Raw values are given in Online Resource 5

The decrease in diastase activity in the two mānuka honeys was larger than for the clover spiked samples which can be attributed to the more complex matrix. Diastase activity decreased 11.5 and > 15.5 DN for mānuka 1 and 2 respectively, compared to clover which only lost 1.5 DN in the same conditions. Huang et al. reported a faster decrease in enzyme activity in acacia and longan honey compared to linen when heated at temperatures of 40, 60 and 80 °C [35], however, these elevated temperatures are above the optimal temperature of 55 °C for A. mellifera diastase and would result in denaturation of the enzyme [11]. Flavonoid compounds have been reported to inhibit enzymes; of note, catechin and epigallocatechin gallate are reported to inhibit amylase activity [36, 37]. Mānuka honey is rich in polyphenolic compounds, which could be adding to the inhibition of amylase compared to other floral honeys that do not contain high levels of these compounds.

The addition of DHA or MGO into the clover honey accelerated the loss of diastase activity, with a decrease of 4.5 and 3.8 DN respectively. Changes in the DN, Vmax and KM values were observed for both mānuka honeys. Mānuka 2 had larger changes in DN, Vmax and KM compared to mānuka 1. For mānuka 2, DN decreased by > 8.8 fold, Vmax decreased by 5.2-fold and KM decreased by 1.5-fold (> 15.5 DN, 5.4 and 1.62 respectively), while for mānuka 1 DN decreased by 2.4-fold, Vmax decreased by 1.2-fold and KM decreased by 1.2-fold (11.5, 0.67 and 0.53 respectively). The variation can be attributed to differences in the chemical composition; DHA, MGO and 3PLA were 2.2, 1.4 and 3.4 times in higher concentration in mānuka 2 respectively. The accelerated loss due to presence of these compounds is consistent with previous research on mānuka honey [12]; to the knowledge of the authors, no literature has been published on the effect of specific compounds in any other floral honeys.

Changes in diastase activity in the mānuka matrix were further investigated by characterising rates with variable substrate concentrations, allowing Michaelis-Menten fitting to access Vmax and KM parameters (Online Resource 3). Vmax determines the maximum enzyme rate when all available active sites are occupied. Therefore, it is influenced by the concentration of active enzyme and catalytic efficiency (Vmax = Kcat × [enzyme], where Kcat is the rate per catalytic unit) [38]. The decrease in Vmax over 200 days for the mānuka honeys indicates that the diastase enzyme is either denaturing or surface level modifications are decreasing the catalytic capacity of the enzyme but cannot differentiate between the two effects. This is consistent with the measured decrease in diastase activity over time and also with a previous study [12]. The potential sites where modifications may occur are depicted in Fig. 2.

KM is the dissociation constant which determines the concentration of substrate required to occupy half of the available enzyme active sites under steady-state conditions. The KM is a particularly useful metric here as the value is independent of enzyme concentration, isolating modification effects from denaturation [39, 40]. KM also decreased over the 200 days for both mānuka samples.

To elucidate the effect of MGO, DHA and 3PLA on enzyme activity, these compounds were added individually and together to a clover matrix. All clover honeys with an individual compound added had a larger decline in activity compared to the control clover (1.3-fold decrease in activity compared to 1.1-fold for the control), indicating that each compound contributes to lowering activity. When 3PLA was added along with MGO, a larger decrease in activity was observed (1.5-fold decrease). This is consistent with a purported role of 3PLA acting as a proton donor for the MGO-induced modification reaction. A similar effect occurred when 3PLA and DHA were added together (1.4-fold decrease). In addition to facilitating the modification, 3PLA has been suggested to contribute a proton to convert the DHA dimer to two DHA monomers to speed up the conversion to MGO [34].

Fig. 2
A honeybee diastase structure marks potential modification sites across the protein surface. Arginine, lysine, histidine, and cysteine side chains are distinguished from active-site residues, which cluster near the center of the structure.
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Cartoon representation of A. mellifera diastase with side chains of interest shown as sticks. Active site residues (red), histidine (yellow), cysteine (orange), lysine (green) and arginine (cyan) residues. These highlighted surface residues present potential modification sites. The structure was generated in AlphaFold [41]

Clover honey spiked with MGO had an initial increase in Vmax up to day 43 (P = 0.0208 in an extra sum of squares F test to assess differences in model fitting) and then a steady decline following day 43 compared to clover honey spiked with 3PLA + DHA which showed an initial increase in Vmax up to day 112 and then a decrease following day 112 (P values ≤ 0.0059 after day 43; Fig. 3). This phenomenon is addressed in the final paragraph of the discussion.

Studies on α-amylase in honey are scarce in the literature, but modification of salivary α-amylase has been widely studied due to its role in diabetes. Muraoka et al. [42] reported that changes in the enzyme when incubated with MGO for 21 days. The protein profile in SDS-PAGE results suggest modifications to the enzyme in the presence of MGO; additionally, a loss of activity was also reported. Other studies report MGO can create advanced glycation end products (AGEs) which can inactivate the enzyme [43]. Irreversible changes have been reported by glycation of MGO on arginine residues as well as lysine and amino-terminal groups [44]. While a general correlation between Vmax and DN is expected, DN values may be convoluted by the substrate concentration utilised in the assay condition, where lower substrate concentrations lead to a partially saturated enzyme pool. This effect is further deconvoluted in this full kinetic characterisation by extracting the steady state constant (KM), defining the substrate concentration at which the enzyme catalysed rate proceeds at half the Vmax, giving a measure of the saturation level of the enzyme pool with increasing substrate concentration. This convolution for DN values is further exacerbated in the honey matrix since the surface level enzyme modifications have the potential to alter the KM value [39, 40].

Vmax and DN can decrease by denaturation and/or modifications to the enzyme structure reducing catalytic capacity, hence, Vmax is not a practical parameter for deconvoluting these two effects. By comparison, KM is independent of enzyme concentration and can be used to infer possible surface level modifications. Therefore, any measured changes in KM indicate changes in enzyme-substrate interaction from the interference of surface level enzyme modifications. These modifications can also affect rates; hence if KM changes are detected it is an indication that Vmax decreases are not exclusively a denaturation effect.

Fig. 3
Across eight honey treatments, normalised V max and K M change differently over 200 days. V max falls most in Mānuka 2, reaching about minus 5.5, while clover plus 3PLA plus DHA peaks near 3.5 at day 112 before returning close to zero. K M peaks near 5 for clover plus 3PLA plus DHA at day 112; both Mānuka treatments fall below zero. Asterisks mark statistically significant changes from the preceding time point.
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Normalised changes in Vmax (a) and KM (b) of diastase over time stored at 27 °C. Raw values are given in Online Resources 6 and 7. Fitted curves which are statistically different to the previous time point of the treatment course (extra sum of squares F test, P value cut off = 0.05; GraphPad Prism version 6) are indicated with an asterisk

The mānuka honeys and clover honeys spiked with MGO and 3PLA + DHA had the largest changes to KM value (all having P values ≤ 0.0208 in an extra sum squares F test indicating different curve fitting from one measured time point to the subsequent measure (Online Resource 4). The changes in KM indicate that at least some of the changes in diastase activity are due to changes in enzyme substrate binding effects from matrix-protein interactions, independent of denaturation effects. The greater observed effects in the mānuka samples indicate a greater potential activity interference in diastase activity testing of mānuka honey, consistent with the more complex matrix of mānuka honeys.

The observed changes in Vmax,KM, and diastase activity for clover honey spiked with 3PLA + DHA and MGO were similar to the mānuka honey samples which indicates that these compounds are significant contributors to the activity loss in diastase, with the changes in KM indicating protein modifications are occurring and have an effect on the catalytic function of diastase. Larger changes were observed for the 3PLA + DHA spiked clover than the 3PLA + MGO spike clover (no differences at P = 0.5 in an extra sum squares F test across the 200-day time course) which suggests that DHA modifications also contribute to loss in diastase activity. Furthermore, changes in Vmax and KM for the 3PLA + DHA spiked clover were larger than DHA spiked clover honey, suggesting that 3PLA has a proton donation role in the DHA and MGO modification reactions.

Clover honey spiked with 3PLA + DHA shows a delay in the decline in Vmax and KM (no significant difference in fitting values from day 7 to 43, P = 0.5399) consistent with the time required for DHA to convert to MGO. Past day 112 rates decline (P = 0.0059 and 0.0002 between day 43–112 and 112–203 respectively, Online Resource 4). The smaller changes to Vmax, KM and DN in the DHA only spiked clover honey compared to 3PLA + DHA spiked indicate a proton donation role of the 3PLA in DHA/MGO protein modifications. Modifications to the enzyme require a proton donor which could be supplied from phenolic acids such as 3PLA, the most abundant phenolic acid in mānuka honey. The larger changes in the mānuka matrix suggests a contribution from the total number of phenolic acids in the matrix.

Changes in Vmax and KM for the 3PLA + MGO spiked clover honey are not as large which supports the idea that DHA also binds to diastase (P > 0.05 across the time course in an extra sum squares F test; Online Resource 4). DHA reacts with amino acids such as lysine, arginine, histidine and cysteine [8, 23, 25, 27]. Binding of DHA to amino acid residues on diastase likely cause conformational or substrate binding affinity changes decreasing diastase activity and affecting Vmax and KM. Decreases in diastase activity, Vmax and KM were larger for the 3PLA + DHA sample compared to DHA only sample, consistent with the observed 3PLA-MGO synergistic effects.

Across all honey samples characterised, a positive correlation between Vmax and KM was observed (Fig. 4). A decrease in Vmax was correlated with stronger substrate affinity. This correlation is consistent with the hypothesis that compounds in mānuka honey cause surface modifications to the protein which effect both substrate binding and potential enzymatic rates. If denaturation were the only effect lowering enzyme activity across these honey samples, KM would be independent of Vmax values.

The direction of the correlation between KM and Vmax within these data could potentially be explained by a catalytic trap at the substrate-enzyme complex of the reaction pathway (Fig. 4B). If this is the case, the substrate bound state forms a stabilised ‘dead end complex’ of reduced free energy, increasing the energetic barrier (ΔG‡) to the reaction transition state [45, 46]. As such, modified enzyme variants in these data that reduce KM are correlated with decreased Vmax as these modified enzymes are trapped further in this stabilised substrate energetic minima, impeding transit through further steps of the catalytic pathway. This intertwined relationship could also explain the increase in Vmax for samples containing MGO, DHA and DHA+3PLA. The initial surface modification patterns increase the KM, reducing the energetic barrier to the transition state, thus increasing activity. This possibility is an area warranting future investigation.

As previously mentioned, the industry requirement for honey export is for diastase activity to be higher than DN 8. The findings of this study suggest that the diastase activity test may not be suitable for mānuka honey as compounds present in the honey may contribute to an accelerated loss above and beyond natural enzymatic activity decline or due to elevated heat treatment. Further work should be carried out to strength these observations; a large range of mānuka honey samples should be analysed to verify that these findings are representative of mānuka honey produced across New Zealand. Citrus honey is classified as a low enzyme honey under CODEX regulations and previous literature reports acacia honey also has low diastase [3, 47]. With the evidence found in the present work, it is suggested that further research be carried out to determine if mānuka honey can also be classified as a low enzyme honey and fall under the altered regulations (DN > ), which has a threshold of 3 DN.

Fig. 4
K M generally increases with maximum reaction rate across the honey samples. The fitted line is K M equals 1.13 times V max minus 2.26, with R squared equal to 0.6331.The energy diagram compares two enzyme-substrate complexes. The more stable complex has lower free energy and a larger energy barrier to the transition state. The diagram associates this with decreased K M and reaction rate.
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(a) Correlation between the KM and Vmax of honeys (mānuka honeys 1 and 2, clover control and spiked honeys) at 27 °C across the time trial. (b) Free energy diagram of an enzymatic reaction illustrating the catalytic trap created when substrates bind with great stability to the enzyme active site. E = enzyme, S = substrate, TS = transition state, P = product

Conclusion

Changes in KM were observed for mānuka honeys and a clover honey spiked with DHA, MGO or 3PLA and in combination. Since KM is independent of active enzyme concentration, changes to this indicate there are effects other than denaturation affecting diastase activity in honey over time and this may be confounding the measurement of enzyme rates too. Since only two mānuka honey samples were examined, the findings should not be considered representative of all mānuka honeys, but rather demonstrate the effects observed in the samples studied and provide evidence supporting a role for DHA and MGO in altered diastase activity. Further work should be done to elucidate the potential modifications that are occurring.

The standardised diastase activity testing method used in the honey industry only considers the reduced diastase activity as a denaturation effect from exposure of honey to high temperature and long storage conditions. Convolution of measured enzymatic rates from substrate binding affects means that measuring diastase activity rates in honey without considering substrate binding effects, misses relevant information and hence reduced enzyme activity from modifications is mistakenly attributed to enzyme denaturation. These modification effects are enhanced for mānuka honeys as seen by the large changes in KM for the stored mānuka honeys and clover honey spiked with 3PLA + DHA enhancing the confounding effects in mānuka testing for export quality. This research also suggests that further research is warranted to determine if mānuka honey could be classified as a low enzyme honey.