Copyright is owned by the Author of the thesis.  Permission is given for 
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Influential Factors in Nectar Composition 

and Yield 

in 

Leptospermum scoparium 

 

 

A thesis presented in partial fulfilment of the  

requirements for the degree of 

Doctor of Philosophy in Plant Science 

 

 

 

Institute of Agriculture and the Environment 

College of Sciences, Massey University 

Palmerston North, New Zealand 

 

 

Elizabeth Mary Nickless 

2015 



 

 



i 

ABSTRACT 

Leptospermum scoparium (Mānuka) is the plant nectar source for medically bioactive 

honey, commercially marketed in New Zealand as Unique Mānuka Factor honey (UMF-

honey). Methylglyoxal (MGO) is the unique bioactive component of UMF honey with 

Mānuka nectar containing significant amounts of the carbohydrate dihydroxyacetone 

(DHA), the chemical precursor for MGO. Anecdotal evidence and recently published 

data from nectar samples collected from various cultivars in natural sites or botanical 

gardens has indicated that the DHA and overall composition of L. scoparium nectar 

varies according to cultivar. The source of this variation is not clearly understood and 

although there is considerable literature on climatic and genetic influences on nectar 

composition and yield within various other plant species, there is little published work 

available on the influence of genetic and environmental factors on the composition and 

yield of nectar in L. scoparium. 

Of value to the commercial UMF honey industry in New Zealand is the ability to assess 

cultivars from breeding programs for the best potential to increase overall UMF honey 

yield. Predictive modelling of yields is invaluable to the developing honey industry to 

allow assessment of environmental influences that may affect overall yield along with 

seasonal influences on nectar production in Mānuka. The research in this thesis 

establishes the effect of various parameters on overall DHA yield from Mānuka and the 

beginnings of modelling influencing environmental factors. 

 To determine influences on dihydroxyacetone (DHA) concentration and yield in the 

nectar of L. scoparium a number of studies were carried out. Methodologies for the 

collection and analysis of nectar were established. Ten different cultivars of L. scoparium 



ii 

with a range of genetic parentage were studied in controlled glasshouse conditions to 

assess phenotypic variability in terms of nectar composition and yield as well as plant 

growth and flowering amongst these cultivars. Significant differences in plant growth 

and flowering habits were observed amongst the ten cultivars, significant differences in 

nectar yield and nectar composition with regard to DHA yield were also observed. DHA 

yields ranged from 2714-7459 mg of DHA/kilogram normalised to 80 oBRIX, with total 

nectar sugar yields ranging between 0.7 and 4.8 mg amongst the ten cultivars studied. 

Preliminary research into the effect of temperature, radiation and humidity on nectar 

composition and yield were also undertaken. 

Effects of soil composition on these same parameters were researched with a subset of 

three of the ten cultivars grown on ten different soil types. Plant relative growth rates, 

dry weights and total plant height were measured throughout a 15 month glasshouse 

trial. Plant growth, flowering phenology, floral density, nectar yield and DHA 

composition data was gathered. Soils were analysed for various macronutrient and 

micronutrient levels and these parameters were modelled against plant data to 

determine which soil components were influencing plant parameters of interest. Soil 

type was shown to have no significant effect on DHA concentrations in nectar but 

results did show that soil type had a significant effect on flowering density amongst the 

three L. scoparium cultivars studied in the trial. Results from regression analysis of soil 

chemistry against measured plant parameters indicate that a fertiliser regime has the 

potential to increase nectar yields due to increased flower numbers. Multivariate 

analysis using partial least squares regression of soil composition data against plant 

parameters of value showed that soil components; phosphorus, sulphate, ferric and 

chloride were commonly shown to influence plant parameters measured.  



iii 

Analytical spectroscopy was investigated as a method to chemotype L. scoparium 

cultivars and also as a method for quantifying nectar components sucrose, glucose, 

fructose and DHA.  

Nectar composition was analysed using high pressure liquid chromatography (HPLC) and 

compared with fourier transform Raman spectroscopy (FT-Raman) and attenuated total 

reflectance infrared spectroscopy (ATR-FTIR) analytical spectroscopy methods.  

FT-Raman spectroscopy was shown to be useful in chemotyping cultivars and in addition 

proved to be a useful analytical method to predict DHA yield using leaf material from L. 

scoparium plants from the ten cultivars.  FT-Raman and ATR-FTIR proved to be relatively 

accurate techniques to quantify L. scoparium nectar components DHA, fructose, glucose 

and sucrose, compared with HPLC methods which use extensive preparation techniques.  

R-squared values were very good for all nectar components measured excepting the 

sucrose model at R2 = 0.77. The R2 for the FT-Raman predictions of DHA against HPLC 

data are very good at 0.85.  FTIR prediction data against HPLC data was also good at 0.86 

R2. Overall an accurate model is possible for quantifying DHA concentrations in nectar 

using both FTIR-ATR and FT-Raman spectroscopy. 

Overall results show that various factors need to be considered when assessing plants 

for commercial use in the (UMF) Mānuka honey industry within New Zealand. Due to 

their large impact on overall nectar yield; floral density and plant growth rate 

parameters are the two key factors of value for commercial assessment of Mānuka 

cultivars. This research also highlights the importance of assessing not just DHA 

concentration in deducing cultivar value, but overall nectar yield. These key features 



iv 

must be explored when assessing L. scoparium plants within breeding programs, prior to 

selection for large-scale field production of high UMF Mānuka honey.  

  



v 

Acknowledgements 

This work was supported by Primary Growth Partnership (PGP) funding (Ministry of 

Primary Industries, New Zealand) awarded to Mānuka Research Partnership (NZ) Limited 

(MRPL), and a scholarship from Callaghan Innovation (NZ) to L.M.N. [Contract: 

MARP1001]. 

Supervision and staff support from the Institute of Agriculture & Environment, Massey 

University; Palmerston North, New Zealand. 

The Primary Growth Partnership (PGP) scheme brings the resources of many people 

together into one research program. And I feel privileged to have worked on my thesis 

under this collaborative scheme. The PGP scheme brings an extra focus to the work and 

the connection and interaction with the commercial partners (MRPL) in the scheme has 

been an invaluable and enjoyable experience.  

There are many people, Dr Steve Holroyd, Professor Keith Gordon, Dr Chris Anderson, 

Dr Jason Wargent, Dr Jonathan Stephens, Professor Michael McManus, Dr James Milner 

and Associate Professor Alastair Robertson, who my sincere thanks go to for their 

scientific input and support for the research in this thesis. My special thanks and 

appreciation go to Georgie Hamilton for the technical support she has given me, along 

with our many enjoyable discussions on various other topics of interest while we 

worked on the Mānuka program. Additional thanks and much appreciation go to my 

supervisor Dr Steve Holroyd whose unfailing support encouraged me to attempt this 

thesis. 

There are many others who I owe a debt of gratitude for the help and support with the 

experimental work in this thesis in particular the staff at the plant growth unit at Massey 



vi 

University, Lindsey, Leslie and Steve and in addition Chris Rawlingson for his help with 

the analytical work on the HPLC and Geoff Smith at Otago University for his help with 

using the Raman equipment. And my employer: Fonterra Research and Development 

Centre (FRDC) Palmerston North who have allowed me the time from work to work on 

my thesis, and especially the support from FRDC statisticians Barbara Kuhn-Sherlock and 

Maree Luckman. 

Last thanks go to my family and the support of my partner Daryl and son Henry who 

have suffered my lack of attention when my evenings were spent focussed on writing 

and my thoughts often elsewhere focussed on data analysis. Special thanks to my son 

Henry who helped me measure plants, collect leaves and chop up plants when I needed 

his help and entertained me with his wonderful wit, humour and patience along the 

way. 

For myself, I have greatly enjoyed working on this thesis, it has been a very enjoyable 

experience and I have learnt an immense amount along the way and have really enjoyed 

getting to know all those involved and have greatly appreciated the input and 

knowledge and experience shared with me. 

 

Thank you!! 

 

 

 

  



vii 

Table of Contents 

Contents 
Title: Influential Factors in Nectar Composition and Yield in Leptospermum 
scoparium  

ABSTRACT .........................................................................................................................i 

Acknowledgements ......................................................................................................... v 

Table of Contents .......................................................................................................... vii 

Contents ........................................................................................................................ vii 

List of Tables .................................................................................................................. xii 

List of Figures ................................................................................................................ xiv 

List of Abbreviations and Symbols ............................................................................... xix 

Chapter 1: Introduction ................................................................................................. 1 

1.1 Project Overview ....................................................................................................... 1 

1.2 Ministry of Primary Industries Primary Growth Partnership .................................... 3 

1.3 Research Objectives .................................................................................................. 5 

1.4 Thesis Outline ............................................................................................................ 5 

1.5 References ................................................................................................................. 8 

Chapter 2: Literature Review ........................................................................................ 9 

2.1 Overview of Leptospermum scoparium .................................................................... 9 

2.2 Overview of Conditions Affecting Vegetative Growth ............................................ 10 

2.3 Overview of Commercial Uses of Mānuka .............................................................. 13 

2.4 Bioactive Constituents of Mānuka Honey............................................................... 15 

2.4.1 Methylglyoxal and Dihydroxyacetone ............................................................. 15 

2.5 Nectar Chemistry .................................................................................................... 18 

2.5.1 Nectar Composition ......................................................................................... 19 

2.6 Review of Secondary Metabolism and Metabolites in Plants ................................ 20 

2.6.1 Metabolomics .................................................................................................. 21 

2.7 Overview of Raman and FTIR Spectroscopic Applications ...................................... 23 

2.7.1 FTIR Spectroscopy ............................................................................................ 24 

2.7.2 Raman Spectroscopy ........................................................................................ 26 

2.7.3 Application of FTIR and Raman in Analysing Carbohydrates in Plants ............ 28 

2.8 Specific Research Objectives ................................................................................... 29 

2.9 References ............................................................................................................... 31 

  



viii 

Chapter 3: Glasshouse experimental methods ........................................................... 39 

3.1 Overview .................................................................................................................. 39 

3.2 Introduction ............................................................................................................. 39 

3.2.1 Genotypes ........................................................................................................ 39 

3.2.2 Soil Composition ............................................................................................... 40 

3.2.3 Experimental Design ......................................................................................... 41 

3.3 Plant Breeding History ............................................................................................. 42 

3.4 Glasshouse Plant Conditions Experiment 1: Genotype Comparisons ..................... 49 

3.5 Glasshouse Experimental Design ............................................................................ 52 

3.6 Glasshouse Experiment 2: Soils ............................................................................... 54 

3.6.1 Soil Analysis ...................................................................................................... 58 

3.6.2 Soil Chemistry ................................................................................................... 59 

3.7 References ............................................................................................................... 62 

Chapter 4: Chemometrics: An outline of the development of the 
chemometric workflow applied in the analysis of Mānuka plant material .............. 63 

4.1 Overview .................................................................................................................. 63 

4.2 Introduction ............................................................................................................. 63 

4.3 Workflow and Methods .......................................................................................... 65 

4.3.1 Preprocessing Spectral Data ............................................................................. 65 

4.3.2 Baseline Adjustments ....................................................................................... 69 

4.3.3 Scatter Correction ............................................................................................ 71 

4.3.4 Standard Normal Variate (SNV) ........................................................................ 71 

4.3.5 Detection of Outliers in Spectral Data ............................................................. 73 

4.3.6 Use of Derivative Spectra ................................................................................. 74 

4.4 Multivariate Data Analysis as a Tool to Explore Data ............................................. 75 

4.4.1 Principal Component Analysis (PCA) ................................................................ 75 

4.4.2 Analysing Loading Results ................................................................................ 81 

4.4.3 Explained Variance ........................................................................................... 84 

4.4.4 Prediction Modelling Using Partial Least Squares (PLS) ................................... 85 

4.5 Summary .................................................................................................................. 91 

4.6 References ............................................................................................................... 92 

Chapter 5: Genetic and environmental influences on nectar composition and 
yield in Leptospermum scoparium (Mānuka .............................................................. 95 

5.1 Abstract ................................................................................................................... 96 

5.2 Introduction ............................................................................................................. 97 

5.3 Materials and Methods ........................................................................................... 99 



ix 

5.3.1 Plant Material and Growth Conditions. ........................................................... 99 

5.3.2 Nectar Collection. ........................................................................................... 100 

5.3.3 High Pressure Liquid Chromoatography (HPLC) Conditions for DHA 
Analysis. ................................................................................................................... 101 

5.3.4 Environmental Data. ...................................................................................... 103 

5.4 Results and Discussion .......................................................................................... 104 

5.4.1 Floral Density as a Component of DHA Yield. ................................................ 109 

5.4.2 Variability in Plant Growth. ............................................................................ 112 

5.4.3 Environmental Influences on Nectar Production. ......................................... 115 

5.5 Acknowledgements ............................................................................................... 120 

5.6 References ............................................................................................................. 121 

Chapter 6: Soil type influences floral density and growth in Mānuka 
(Leptospermum  scoparium) ...................................................................................... 125 

6.1 Abstract ................................................................................................................. 126 

6.2 Introduction .......................................................................................................... 127 

6.3 Materials and Methods ......................................................................................... 129 

6.3.1 Soil collection and experimental design ........................................................ 129 

6.3.2 Nectar Collection. ........................................................................................... 132 

6.3.3 Analysis of Dihydroxyacetone. ....................................................................... 133 

6.3.4 HPLC Conditions. ............................................................................................ 133 

6.3.5 Soil Analysis. ................................................................................................... 134 

6.3.6 Plant Growth Measurement Methods. .......................................................... 135 

6.3.7 Soil Composition ............................................................................................ 135 

6.3.8 Plant data. ...................................................................................................... 136 

6.4 Results and discussion........................................................................................... 137 

6.4.1 Soil Chemistry ................................................................................................. 137 

6.4.2 Plant Response to Soil Chemistry .................................................................. 140 

6.5 Discussion .............................................................................................................. 155 

6.6 Acknowledgements ............................................................................................... 157 

6.7 References ............................................................................................................. 158 

Chapter 7: Analytical FT-Raman spectroscopy to chemotype Leptospermum 
scoparium and generate predictive models for screening for 
dihydroxyacetone levels in floral nectar .................................................................. 163 

7.1 Acknowledgements ............................................................................................... 164 

7.2 Abstract ................................................................................................................. 164 

7.3 Introduction .......................................................................................................... 165 



x 

7.4 Methods ................................................................................................................ 167 

7.4.1 Experimental Design. ...................................................................................... 167 

7.4.2 Multivariate Analysis of the Spectral Data. .................................................... 171 

7.5 Results and discussion ........................................................................................... 171 

7.5.1 Multivariate Analysis of Spectral Data from L. scoparium Genotypes. ......... 171 

7.5.2 Multivariate Partial Least Squares (PLS) Regression. ..................................... 178 

7.6 Conclusion ............................................................................................................. 180 

7.7 References ............................................................................................................. 181 

Chapter 8: Analytical method development using FTIR-ATR and FT-Raman 
spectroscopy to assay the carbohydrates; fructose, sucrose, glucose and 
dihydroxyacetone, in Leptospermum scoparium nectar .......................................... 187 

8.1 Abstract ................................................................................................................. 188 

8.2 Introduction ........................................................................................................... 189 

8.3 Experimental Methods .......................................................................................... 191 

8.3.1. HPLC conditions for DHA analysis. ................................................................ 192 

8.4. Spectroscopic methods ........................................................................................ 196 

8.5 Results and Discussion .......................................................................................... 199 

8.5.1 Regression Analysis. ....................................................................................... 200 

8.6 Conclusion ............................................................................................................. 203 

8.7 Acknowledgements ............................................................................................... 203 

8.8 References ............................................................................................................. 204 

Chapter 9: Discussion and Future Work .................................................................... 209 

9.1 Introduction ........................................................................................................... 209 

9.2 Research Objectives .............................................................................................. 210 

9.3 Discussion .............................................................................................................. 211 

9.3.1. Research of available literature to establish standard methodologies 
for nectar collection and decide on best practises for experimental design 
for assessing nectar composition, plant growth, flowering and overall nectar 
yield in L. scoparium (Chapters 3 and 5). ................................................................ 211 

9.3.2 Identification of the variance of specific nectar and growth parameters 
within several cultivars of L. scoparium to establish the potential of breeding 
programmes for increasing UMF honey yield from L. scoparium. Model the 
effects of a range of climatic conditions on nectar composition and yield in 
several cultivars of L. scoparium to allow identification of localities where 
climatic factors may be beneficial or detrimental to overall UMF honey yield 
(Chapter 5 and 6). .................................................................................................... 212 

9.3.3 Identification the effect of the influence of the environment in terms 
of soil composition on nectar, plant growth and flowering parameters to 



xi 

allow decisions to be made regarding best soil sites to establish L. scoparium 
plantations. (Chapters 5 and 6) ............................................................................... 213 

9.3.4 Research into the analytical development of FT-Raman spectroscopy 
to chemotype cultivars of L. scoparium and investigate the potential for 
linking metabolites from chemotype profiles produced by FT-Raman data to 
UMF potential in L. scoparium and test the capability of FT-Raman and ATR-
FTIR spectroscopy along with chemometric modelling techniques to 
quantify nectar components of L. scoparium (Chapters 4, 7 and 8). ..................... 216 

9.4 Recommendations for Future Work ..................................................................... 218 

Appendix A ................................................................................................................. 220 

 
  



xii 

List of Tables 
 

Table 2.1. This table shows the classification of plant metabolites into primary 
and secondary groups .............................................................................................. 21 

 
Table 3.1. Leptospermum scoparium cultivar parentage information ............................. 43 
 
Table 3.2. Chemical composition of Long-Term Fertiliser ................................................ 49 
 
Table 3.3. Chemical composition of Short-Term Fertiliser ............................................... 50 
 
Table 3.4. Ingredients of Dolomite ................................................................................... 50 
 
Table 3.5. Peters Liquid feed formulations ....................................................................... 52 
 
Table 3.6. Soil Collection Sites with information on soil types with rationale for 

choosing soils ........................................................................................................... 60 
 
Table 3.7. Soil composition data from site collected soils ................................................ 61  
 
Table 4.1. Example of a data matrix X. Individual objects or samples denoted by n 

rows and the variables denoted by X columns ........................................................ 76 
 
Table 5.1. Data ranges of environmental parameters logged at the time of nectar 

collection.  .............................................................................................................. 107 
 
Table 5.2. Table of means of the main sugars; sucrose, glucose and fructose and 

DHA in L. scoparium nectar normalised to 80oBRIX.  ............................................ 110  
 
Table 5.3. Potential DHA yield for each cultivar calculated as the product of μg of 

DHA per flower....................................................................................................... 111 
 
Table 5.4. Growth data parameters measured over 15 months for each cultivar in 

the glasshouse experiment.  .................................................................................. 113 
 
Table 5.5. Comparison of the final biomass data between the 10 cultivars .................. 114 
 
Table 5.6. Proposed estimate of potential nectar yield and growth i.e. overall 

cultivar rating ......................................................................................................... 115  
 
Table 5.7. Data ranges of environmental parameters logged at the time of nectar 

collection ................................................................................................................ 116 
 
Table 5.8. Partial Least Squares Regression (PLS) analysis of climatic influences on 

nectar production and composition.  .................................................................... 119 
 



xiii 

Table 6.1.  Description of soil type with codes Soil 1 (S1) to Soil 10 (S10) used 
for the experimental analysis.  .............................................................................. 131 

 
Table 6.2.  Average macronutrient and micronutrient concentration in the ten 

soils used for the glasshouse trial .......................................................................... 139 
 
Table 6.3. Averaged data is displayed for plant response parameters for 

Cultivar R.  .............................................................................................................. 144  
 
Table 6.4. Averaged data is displayed for plant response parameters for 

Cultivar G.  ............................................................................................................. 145 
 
Table 6.5. Averaged data is displayed for plant response parameters for 

Cultivar Y ................................................................................................................ 146 
 
Table 6.6. PLS regression results from plant growth and nectar parameter data 

of cultivars R, G and Y ............................................................................................ 152 
 
Table 6.7. Summary of analysis of Variance (ANOVA) to assess the differences 

between the cultivars in terms of response to measured parameters.  ............... 153 
 
Table 6.8. Interaction results for the parameters that showed a significant 

interaction between the cultivar (CV) and the soil type ....................................... 154 
 
Table 6.9. Calculated nectar potential (NP) and MSI value for cultivars R and G.  ........ 155 
 
Table 8.1. HPLC data showing DHA and sugar component values for the 

cultivars normalised to 80 °BRIX.  .......................................................................... 193 
 
Table 8.2. PLS models and Regression analysis results for nectar sugars in L. 

scoparium using ATR-FTIR and FT-Raman ............................................................. 197 
 
 



 

xiv 

List of Figures 
 
 
Figure 2.1. Leptospermum scoparium (site=Mt Holdsworth Road, Wairarapa, 

New Zealand) A = photo showing flowers, B = seed capsules photo showing 
mature habit of L. scoparium C=ecological habit growing alongside a steam, 
D = Mānuka plant in peak flowering ..................................................................... 10 

 
Figure 2.2. Molecular structure of methylglyoxal .......................................................... 16 
 
Figure 2.3. Concentrations of MGO ( ) and sum of methoxylated phenolic 

components ( ) in Mānuka honeys.  ................................................................... 17 
 
Figure 2.4. Proposed metabolic pathways for sugar metabolism in floral nectaries ..... 19 
 
Figure 2.5. Example of FTIR spectra of three carbohydrate components of the 

nectar of L. scoparium;  ......................................................................................... 25 
 
Figure 2.6. Example of FT-Raman spectra of various carbohydrates in solution.  ......... 27  
 
Figure 3.1. Floral Density habits of 10 cultivars BS, B, LG, MG, O, P, PU, R, Y and G ..... 43 
 
Figures 3.2-3.11. Photographs of cultivars used in the investigations in this 

thesis.  ............................................................................................................... 44-48 
 
Figure 3.12. Picture showing in-line irrigation system to each individual pot ............... 51 
 
Figure 3.13. Glasshouse plant layout for experiment 1 ................................................. 51 
 
Figure 3.14. Latin Square Design used in experiment 1 with two blocks of a 5 X 5 

grid ......................................................................................................................... 53 
 
Figure 3.15. In-line watering system for soil experiment and later photos showing 

plants and flowering in progress ........................................................................... 56 
 
Figure 3.16. Experiment 2 mid experiment showing plants growing on the ten 

different soils ......................................................................................................... 56 
 
Figure 3.17. Experiment 2 mid experiment showing plants in flower during the 

soils experiment .................................................................................................... 56 
 
Figure 3.18. Glasshouse layout to investigate the influence of soil type on growth 

and flowering of Leptospermum scoparium.......................................................... 57 
 
Figure 4.1.  Cosmic spikes are visible as very narrow, high relative intensity peaks 

in spectral data .....................................................................................................  67 
 



 

xv 

Figure 4.2. Illustration of high frequency noise in spectral data .................................... 67 
 
Figure 4.3. Example of spectral data of an organic sample set showing some 

spectra with fluorescent signal overlaying in the background resulting in a 
broad band of increased height through the middle region of the spectrum 
with the FT-Raman peaks still showing above the background band ................... 68 

 
Figure 4.3a. Full FT-Raman spectral data set plot from a large range of samples. 

Note two obvious artefact outliers in the sample set ........................................... 69 
 
Figure 4.4a. Un-processed FT-Raman spectral data showing vertical shift in the 

spectral dataset ..................................................................................................... 70 
 
Figure 4.4b. FT-Raman spectral data set after linear baseline processing. Note 

alignment of most spectral data to the zero baseline .......................................... 70 
 
Figure 4.5. Camo software data analysis showing MSC scatter effects in spectral 

data, note the classic fan shape in the descriptive data.  This would indicate 
that application of the MSC transformation may be more useful than SNV ........ 72 

 
Figure 4.6. Camo software data analysis showing data scatter after MSC 

transformation has been applied. Note that the data is now aligned .................. 72 
 
Figure 4.7. Line plot of spectral data after smoothing and alignment using SNV 

processing .............................................................................................................. 73 
 
Figure 4.8.  Hotelling with a T² statistical analysis, outliers are displayed above 

the percentile line (Red line in graph) and can be marked as above for 
removal from the dataset before recalculating the PCA ....................................... 74 

 
Figure 4.9.  Examples of the effect of 1st and 2nd derivatives on FTIR-ATR spectral 

data. A un-derivatised data, B 1st derivation, C 2nd derivation.............................. 75 
 
Figure 4.10. Representation of data points in the variable space. The red line 

passes through the centre and direction of the largest variance and is PC1 
(an eigenvector). T = the t-score value of each object point ................................ 78 

 
Figure 4.11. Representation of data points in the variable space. The red line 

passes through the centre and direction of the largest variance and is PC1 ........ 79 
 
Figure 4.12. Example of PCA on spectral data. Figure taken from G.P.S. Smith et. 

al. 2015 “Raman imaging of drug delivery systems” ............................................  80 
 
Figure 4.13.  Loadings plot of PC3 for the sub-region spectrum (1650−1150 cm−¹). 

The arrows show the wavenumbers with the most influence = the largest 
coefficient values (-ve or +ve) on PC3 ................................................................... 82 

 



 

xvi 

Figure 4.14  Loadings plot of PC4 for the sub-region spectrum (1650−1150 cm−¹). 
Regions with the large magnitude coefficients (-ve or +ve) are shown in 
boxes ...................................................................................................................... 83 

 
Figure 4.15. Correlation loadings plot. Wavenumbers in the outer ellipse have a 

higher influence on the corresponding model than wavenumbers in the 
inner ellipse. Outermost wavenumbers have the highest influence and the 
relative position in the X and Y axis indicate whether the correlation is 
positive or negative ............................................................................................... 84 

 
Figure 4.16.  Explained variance PC plot showing how much each PC contributes 

to the variation in the data set .............................................................................. 85 
 
Figure 4.17.  HPLC data showing DHA values for the cultivars normalised to 

80°BRIX. It should be noted that only five out of the seven initial cultivars 
were used in this model because only five cultivars from which nectar was 
collected flowered during this experiment ........................................................... 87  

 
Figure 4.18.   Explained variance plot for the PLS model ............................................... 88 
 
Figure 4.19.  PLS component plot of factor 3 versus factor 1 separates the P and Y 

cultivars .................................................................................................................. 89 
 
Figure 4.20.  Regression graph of PLS model, note the R² value of 0.78 and the 

inclusion of the first three factors for this model ................................................. 90 
 
Figure 5.1.  A: Ternary diagram of the dominant sugars in L. scoparium nectar of 

ten different cultivars. B: PCA score plot of main sugar composition data 
from the same ten cultivars, separate colours represent different cultivars.  ... 105 

 
Figure 5.2. Regression analysis of nectar constituents: fructose versus glucose 

illustrating the negative correlation between fructose and glucose in L. 
scoparium nectar ................................................................................................. 108 

 
Figure 5.3.  Flowering period in potted plants a) the start of flowering in days 

numbered from the 1st of January in the main experimental year, b) the 
average total flowering period for each cultivar ................................................. 112 

 
Figure 6.1. PCA plots and related loading plots of the soil chemistry data for all 

ten soils. Individual soils are labelled and coloured separately to show soil 
groupings ............................................................................................................. 138 

 
Figure 6.2. Relative start day of flowering, total days flowering, DHA 

concentration normalised to 80 oBRIX, numbers of seed capsules, basal 
stem diameter, plant height, nectar yield and relative growth rates for each 
cultivar R, G and Y ................................................................................................ 140 

 



 

xvii 

Figure 7.1. L. scoparium genotypes used in the experiments. Genotypes are 
identified by unique codes ............................................................................................ 168 
   
Figure 7.2.  LCMS data showing DHA values for the cultivars normalised to 

80°BRIX Y=Yellow; P=Pink; O=Orange; MG=Mint Green; B=Blue ....................... 170 
 
Figure 7.3. The sub-region 1650−1150cm¯¹ of Raman spectra of leaf samples of L. 

scoparium after linear baseline correction.  Y=Yellow; LG=Lime Green; 
P=Pink; O=Orange; BS=Blue Stripe; MG=Mint Green; B=Blue ............................ 173 

 
Figure 7.4.  Scores plot (PC3 and PC4) obtained using the sub-region spectrum 

(1650−1150cm−¹), plots shows the initial separation between leaf spectra of 
the seven cultivars ............................................................................................... 173 

 
Figure 7.5.  Scores plot (PC2 and PC3) obtained using the same spectral region. 

Note the further separation of B from BS and MG from Y.  ................................ 174 
 
Figure 7.6. Loadings plots for PCs 2, 3 and 4. The main peak wavenumbers from 

these plots are used to indicate what compounds, based on their molecular 
structure or reference spectra, could be responsible for differentiating the 
cultivars ................................................................................................................ 177 

 
Figure 7.7.  Regression graph of the PLS model, note the R² value of 0.75 and the 

inclusion of the first three factors for this model ............................................... 179 
 
Figure 7.8. Graph of score plot from the PLS regression of FT-RAMAN spectra of 

leaves against DHA levels in the nectar of the flowers from these five 
cultivars ................................................................................................................ 179 

 
Figure 8.1. PCA of the main sugar composition (fructose, glucose and sucrose) of 

the nectar of the ten cultivars; B, BS, G, LG, O, P, PU, R and Y. Graph A= PCA 
score plot B = Loadings plot ................................................................................. 194 

 
Figure 8.2. Comparison of FTIR (A) and FT-RAMAN (B) spectra of 8% DHA, L. 

scoparium nectar and a composition of mock nectar made from the 
saccharide solutions fructose and glucose (ratio 2:1) ........................................  195 

 
Figure 8.3. DHA regression model plots from FTIR-ATR (A) and FT-Raman (B) 

spectral data.  Also regression plots of predicted data against HPLC data for 
FTIR-ATR (C) and FT-Raman (D) ..........................................................................  196 

 
Figure 8.4. Prediction data plot from the FT-Raman regression model. Note 

samples with a larger standard deviation represented by the box around 
the mean are considered outliers in the prediction i.e. MG-4, O-6, MG-5 
and P-5 ................................................................................................................. 198 

 



 

xviii 

Figure 9.1. Illustration representing the interplay of influences on plant response 
factors relevant to the UMF honey yield  ............................................................ 209 

 
Figure A.1. Illustrating the five stages of flower development in Leptospermum 

scoparium, nectar was collected at stage IV ....................................................... 219 
 
Figure A.2. Photograph of a cross section through the middle of a Leptospermum 

scoparium flower. Dark red pigmented area is the hypanthium surface 
containing the nectaries. The moisture visible on the hypanthium surface is 
nectar ................................................................................................................... 219 

  



 

xix 

List of Abbreviations and Symbols 

AAS 

ACN 

atomic absorption spectrophotometry  

Acetonitrile  

ANOVA Analysis of Variance  

ATR Attenuated Total Reflectance  

ATR-FTIR 

(Attenuated Total Reflectance Fourier Transform  

(Infrared Spectroscopy 

B Boron 

BS Basal Stem 

Ca Calcium 

CCD Charged Couple Device 

CCE             Calcium Carbonate Equivalent  

CEC Cation Exchange Capacity 

Cl Chloride 

cm¯¹  Spectral Wavenumbers 

Co Cobalt 

Cu Copper 

CV Cultivar 

DHA Dihydroxyacetone 

EDTA Ethylene-diamine-tetra-acetic acid 

Fe Ferric/Iron 

FP Flowering Period 

F Fructose 

FTIR Fourier Transform Infrared Spectroscopy 

FT-Raman Fourier Transform Raman Spectroscopy 

g Grams 

GC Gas Chromatography 

GC-FID  Gas Chromatography with Flame Ionization Detector  

GLM General Linear Model 



 

xx 

G Glucose  

HA Hydroxyacetone  

HPLC High Pressure Liquid Chromatography 

HT Plant Height 

ICP-OES Inductively Coupled Plasma Optical Emission Spectrometry 

IR Infrared 

K Potassium 

kg Kilograms 

l Litre 

L. scoparium Leptospermum scoparium 

LCMS Liquid Chromatography Mass Spectrometry 

me milli-equivalents of exchangeable base cation 

Mg Magnesium 

mg Milligrams 

MGO Methylglyoxal 

Mj/m2 Micro-Joules of light energy per meter squared 

ml Milli-litre 

mM Milli-Molar concentration 

Mn Manganese 

MRPL Mānuka Research Partnership Limited 

MS Mass Spectrometry  

MSC Multiplicative Scatter Correction 

MSI Mānuka Soil Index  

mW Milli-Watts 

N Nitrogen 

Na Sodium 

NA Not Applicable 

NaOH Sodium Hydroxide  

NIPALS Non-Linear Iterative Partial Least Squares 



 

xxi 

NIR Near Infrared 

NMR Nuclear Magnetic Resonance  

NP Nectar Potential  

NPA Non-Peroxide Antibacterial Activity 

P Phosphate 

PC Principal Component 

PCA Principal Component Analysis 

PFBHA O-(2, 3, 4, 5, 6-pentafluorobenzyl) hydroxylamine  

PGP Primary Growth Partnership  

pH Acidity/Alkalinity level 

PLS Partial Least Squares 

PLSR Partial Least Squares Regression 

R Correlation Value 

RGR Relative Growth Rate  

RI Refractive Index  

RMSE Root Mean Square Error 

RMSEC Root Mean Square Error of Calibration  

RMSECP  Root Mean Square Error of the Prediction model. 

RMSECV  Root Mean Square Error of the Cross Validated model. 

S Sulphur/Sucrose 

SC  Seed Capsule numbers  

SD Start Days = Start of Flowering Period in Days 

SNV Standard Normal Variate 

SO4 Sulphate 

μg Micro-grams 

μL Micro-litres 

UMF Unique Mānuka Factor 

UV/VIS Ultra Violet/Visual Absorbance Spectra)  

UV Ultra Violet  



 

xxii 

Y, MG, G, B, BS, P, O, LG, PU and R Cultivar Codes 

Yd Yield 

Zn Zinc