extraction and variation of the essential oil from western
TRANSCRIPT
Extraction and Variation of the Essential Oil from Western
Australian Sandalwood (Santalum spicatum)
Paul Moretta, B.Sc. (Hons)
This thesis is presented for the degree of
Doctor of Philosophy
The University of Western Australia
Department of Chemistry
2001
This thesis is presented for the degree of Doctor of Philosophy to The University of
Western Australia.
The work described in this thesis was carried out by the author in the Departments at
The University of Western Australia under the supervision of Dr Robert. D. Trengove
and Associate Professor Emilio. L. Ghisalberti. Unless duly referenced, the work
described is original.
Paul Moretta
June 2001
ii
Acknowledgements
This study could not have been performed without the help of many people, all whom I
owe a great deal of thanks.
I would firstly like to thank my supervisors Robert Trengove and Emilio Ghisalberti for
the opportunity to undertake a PhD, and their never-ending enthusiasm, support and
advice over the duration.
I could not go without thanking my fellow lab members, Brendan, Courtney, Anthony
and Gavin, along with numerous honours students, who have constantly helped with
numerous problems and provided me with a wealth of knowledge, along with numerous
years of entertainment. I must especially thank Brendan who always took time out of his
'busy' schedule for advice on writing and countless computer solutions.
The Department of Conservation and Land Management (CALM) now Forest Products,
need to be thanked for their support of the project, in particular Syd Shea, Don Keene,
and Peter Jones. Special thanks must be directed towards Dave Evans, Ben Sawyer, Jon
Brand and Kim Phillips from CALM, and Anthony who helped in the collection of
samples. I must also thank Westcorp for providing bulk samples of sandalwood for large
scale extraction.
To George, Nigel, Darko, and Bruce from the workshop who were always available to
manufacture anything on demand, no matter how obscure the design, and provide
numerous tools to process the wood, many thanks.
iii
Mike Whitby, Brendan Grierson, Rod Minnet and Dennis Gere from Agilent
Technologies must also be thanked for their assistance and generosity in relation to the
equipment and consumables used for the project.
Finally I would like to thank my parents for the oppurtunities they have given
throughout my life, and Simonne for her understanding and support. -
iv
Abstract
Western Australian sandalwood (Santalum spicatum) is a small tree that contains
fragrant oil within the heartwood. Even though sandalwood was one of WA's first
industries, and has continued to supply the world with wood for over 150 years, little
focus has been placed into research and development of the industry, compared to East
Indian sandalwood (Santalum album), particularly in the field of chemistry. S. album
contains an oil content of over 6% and santalol content of over 90%. Much conjecture
exists in the literature as to the amount and chemical composition of sandalwood oil
found in Santalum spicatum.
The essential oil from Western Australian sandalwood was extracted by supercritical
carbon dioxide. Solid bed trapping conditions were optimised by using a standard
mixture of compounds representative of the components of sandalwood oil. It was found
that the type of trapping material, trap temperature, flow rate and rinse solvent all had an
effect on the recoveries. Quantitative recoveries of the standards were obtained when
Isolute diol was used as the trapping material at 20°C, using polar rinse solvents such as
ethanol, ethyl acetate or methyl-tert-butyl ether.
The effects of the extraction parameters including density, time and particle size on the
extraction of real sandalwood samples were examined. An extraction density of 0.75
g/mL for 30 minutes was sufficient to completely remove the volatile components of the
sandalwood oil from the wood, leaving behind the larger molecular weight compounds
not responsible for the odour of the oil. The SFE extraction method was up-scaled from
7mL to 300 mL with no effect on oil yield. The oil extracted using these optimal
V
trapping and extraction conditions was found to differ in both yield and composition to
the oil extracted using hydrodistillation and solvent extraction (hexane and ethanol).
Variations in the yield and composition of extracted sandalwood oil were found to exist
for different sections of the tree. More oil and higher santalol contents were found in the
roots of sandalwood trees, and these values decreased moving further up the tree. The
oil content was also found to vary across the diameter of the tree. More oil was found in
the centre of the wood (heartwood) compared to the outer sapwood.
To aid in the knowledge of sandalwood, a study was conducted to examine whether
differences existed in oil yield and composition due to geographic location. A total of 87
trees from 12 geographic locations were sampled. Average oil yields were found to
differ significantly between geographic locations, ranging between 2.0 and 4.6%. The
oil composition was also found to vary between geographic locations, with the average
santalol content varying between 3.3 and 66.6%. An investigation was also conducted to
see if differences in oil arose due to seasonal variation. No significant variation was
found to exist in oil yield and composition from trees samples during summer, autumn,
winter or spring.
vi
Table of Contents
1. Introduction 1
1.1. Essential Oils 1
1.2. Sandalwood 2
1.2.1. Sandalwood Species 2
1.2.2. S. spicatum 4
1.2.3. Uses ~ 12
1.2.4. Sandalwood Oil 14
1.2.5. Factors affecting Sandalwood Oil Quantity and Quality 17
1.3. Supercritical Fluid Extraction 24
1.3.1. What is a Supercritical Fluid? 24
1.3.2. Supercritical Fluid Extraction 27
1.4. Optimisation of SFE 32
1.4.1. Extraction Conditions 33
1.4.2. Collection Conditions 39
1.4.3. Adsorption 42
1.4.4. Desorption 43
1.5. Extraction of Essential Oils 46
1.5.1. Steam and Hydrodistillation of Essential Oils 46
1.5.2. Solvent Extraction of Essential Oils 50
1.5.3. Other Extraction Techniques 51
1.5.4. SFE for the Extraction of Essential Oils 51
1.6. Analysis of Essential Oils 54
1.6.1. Gas Chromatography 54
1.6.2. Liquid Chromatography 55
1.6.3. Supercritical Fluid Chromatography 55
1.7. Aims of Project 57
2. Experimental 58
2.1. Equipment 58
2.2. Optimisation of Trapping Conditions 59
2.2.1. Materials 59
2.2.2. Time Course Extraction of Standard Mixture 60
2.2.3. Trapping Conditions 62
2.2.4. Hydrodistillation of Standard 65
2.3. Optimisation of Sandalwood Extraction 66
2.3.1. Materials 66
2.3.2. Calculations of Percentage Yield, Volatiles and Composition 67
2.3.3. Exhaustive Extraction 68
2.3.4. Effect of Density on Percentage Yield, Percentage Volatiles, and Composition 69
vii
2.3.5. Particle Size 70
2.4. Large Scale Extraction 73
2.4.1. Materials 73
2.4.2. Instrument Modification 74
2.5. Comparison of Extraction Techniques 76
2.5.1. Materials 76
2.5.2. Methods 77
2.6. Sandalwood Survey 78
2.6.1. Geographic - 78
2.6.2. Seasonal Variation 85
2.6.3. Sectional Examination 86
3. Results and Discussion 88
3.1. Optimisation of Trapping Conditions 88
3.1.1. Extraction Time Course of Components of Standard Mixture 88
3.1.2. Trapping 91
3.1.3. Inert Trapping Material 93
3.1.4. Non-polar traps 97
3.1.5. Polar Trapping Material 101
3.2. Desorption 105
3.2.1. Inert Trapping Material 106
3.2.2. Non-Polar Trapping Material 106
3.2.3. Polar Trapping Material 110
3.2.4. Rinse Temperatures 114
3.3. Hydrodistillation of Standard Mixture 114
3.4. SFE Extraction Conditions for Sandalwood Samples 116
3.4.1. Extraction Time 117
3.4.2. Density 120
3.4.3. Particle Size 123
3.5. G C - M S Identification of Components in Volatile Sandalwood Oil 128
3.6. Comparison of Extraction Techniques 129
3.7. Scale up of Extraction 133
3.8. Section of Tree 135
3.9. Geographic Variation 150
3.10. Seasonal Variation in Oil Yield and Volatile Composition 162
4. Conclusion Error! Bookmark not defined.
5. References 170
6. Appendix 183
Vlll
Table of Figures
1.1. Santalum spicatum 4
1.2. Distribution of S. spicatum in Western Australia 6
1.3. Distribution of sandalwood species in Australia 8
1.4. Major components of sandalwood oil 16
1.5. Phase (pressure-temperature) diagram of a pure substance 25
1.6. Variation of the reduced density of a pure component in the vicinity of its critical point 27
1.7. Schematic diagram of basic SFE apparatus ._ 31
1.8. Liquid solvent SFE trapping device 40
1.9. Solid bed trapping device 41
1.10. Conversion of sabinene in acidic conditions 49
2.1. Structure of compounds used in the standard mixture 60
2.2. Modification of the SFE apparatus to allow scale-up of the extraction vessel to 300 m L 75
2.3. Large-scale trapping device 75
2.4. Coring of sandalwood trees 79
2.5. Drillhole filled with Sellys polyfiller post core sampling 80
2.6. Sampling locations throughout Western Australia 85
2.7. Exposed roots of a sandalwood tree 87
3.1. Cumulative percentage of individual components of the standard mixture extracted over 80
minutes at a C 0 2 density of 0.90 g/mL 90
3.2. Cumulative percentage of individual components of the standard mixture extracted over 80
minutes a t a C 0 2 density of 0.65 g/mL 90
3.3. Cumulative percentage of individual components of the standard mixture extracted over 80
minutes at a C 0 2 density of 0.30 g/mL 91
3.4. Phases bonded to solid silica supports used in the study
93
3.5. Recoveries of the components of the standard mixture using stainless steel beads at various trap
temperatures 95
3.6. Recoveries of the components of the standard mixture using stainless steel beads at various flow
rates 97
3.7. Recoveries of the components of the standard mixture using Hypersil O D S at various trap
temperatures 98
3.8. Recoveries of the components of the standard mixture using Isolute CI 8 at various trap
temperatures 99
3.9. Recoveries of the components of the standard mixture using Hypersil O D S at various flow rates 100
3.10. Recoveries of the components of the standard mixture using Isolute C18 at various flow
rates 101
3.11. Recoveries of the components of the standard mixture using Isolute silica at various trap
temperatures 103
3.12. Recoveries of the components of the standard mixture using Isolute cyano at various trap
ix
temperatures 103
3.13. Recoveries of the components of the standard mixture using Isolute diol at various trap
temperatures 104
3.14.Rinsing efficiency ofhexane using Hypersil O D S 108
3.15. Rinsing efficiency of iso-octane using Hypersil O D S 108
3.16. Rinsing efficiency ofhexane using Isolute CI 8 109
3.17. Rinsing efficiency of iso-octane using Isolute C18 109
3.18. Rinsing efficiency ofhexane using Isolute silica 110
3.19. Rinsing efficiency of iso-octane using Isolute silica - Ill
3.20.Rinsing efficiency of hexane using Isolute cyano Ill
3.21. Rinsing efficiency of iso-ocatne using Isolute cyano 112
3.22. Rinsing efficiency of hexane using Isolute diol 112
3.23. Rinsing efficiency of iso-ocatne using Isolute diol 113
3.24. Effect of hydrodistillation on m e recovery of m e standard mixture 115
3.25. Time course of the extraction of total oil from sandalwood at various densities 118
3.26. Time course of the extraction of volatile oil from sandalwood at various densities 118
3.27. Theoretical extraction profile of an analyte from a solid matrix 119
3.28. Yield and composition of volatiles extracted from sandalwood at various densities 121
3.29. Compositional variation in components of sandalwood oil extracted at various densities 122
3.30. Yield and volatile composition of oil extracted from sandalwood of various particle sizes by
SFE (Study 1) 125
3.31. Yield and volatile composition of oil extracted from sandalwood of various particle sizes by
SFE (Study 2) 127
3.32. Yield and composition of volatiles extracted by different various techniques 131
3.33. Compositional variation in sandalwood oil extracted by various extraction techniques 132
3.34. Chemical conversion of lanceol to nuciferol 132
3.35. Time course of the extraction of total oil from sandalwood using a 300 m L extraction vessel... 133
3.36. Comparison of oil yield from 7 m L and 300 m L extraction vessel 135
3.37. Oil yield and percentage volatiles of sandalwood oil along Tree 1 137
3.38. Oil yield and percentage volatiles of sandalwood oil along Tree 2 137
3.39. Oil yield and percentage volatiles of sandalwood oil along Tree 3 138
3.40. Major compositional changes along Tree 1 140
3.41. Major compositional changes along Tree 2 141
3.42. Major compositional changes along Tree 3 141
3.43. Hypothetical derivation of acyclic and monocyclic sesquiterpenes in sandalwood 144
3.44. Hypothetical derivation of bicyclic and tricyclic sesquiterpenes from the bisabolonium cation in
sandalwood 145
3.45. Variation in oil yield and percentage volatiles across the diameter of Tree 1 147
3.46. Variation in oil yield and percentage volatiles across the diameter of Tree 2 147
3.47. Variation in oil yield and percentage volatiles across the diameter of Tree 3 148
3.48. Sampling positions across the diameter of the three trees 148
x
3.49. Major compositional changes across the diameter of Tree 1 149
3.50. Major compositional changes across the diameter of Tree 2 150
3.51. Major compositional changes across the diameter of Tree 3 150
3.52. Variation in the oil content of sandalwood trees from various geographical locations 153
3.53. Variation in the percentage volatiles of sandalwood trees from various geographical locations... 153
3.54.Fisher's pairwise comparison for statistical differences in oil yields between locations 154
3.55. Fisher's pairwise comparison for statistical differences in percentage volatiles between location 154
3.56. Average rainfalls and temperatures for sandalwood sampling locations 156
3.57. Variation in the average percentage santalol from sandalwood trees from various geographical
locations 158
3.58. Variation in the average percentage a- bisabolol from sandalwood trees from various
geographical locations 158
3.59. Variation in the average percentage t,t- farnesol from sandalwood trees from various
geographical locations 159
3.60. Variation in the average percentage nuciferol from sandalwood trees from various geographical
locations 159
3.61. Fisher's pairwise comparison for statistical differences in a- santalol between locations
160
3.62.Fisher's pairwise comparison for statistical differences in P- santalol between locations 160
3.63. Fisher's pairwise comparison for statistical differences in t,t- farnesol between locations 161
3.64. Fisher's pairwise comparison for statistical differences in nuciferol between locations 161
3.65. Variation in oil yield from 5 locations sampled during 4 different seasons 163
3.66. Variation in percentage volatiles from 5 locations sampled during 4 different seasons 163
XI
Table of Tables
1.1. Species and world-wide distribution of commercially exploited sandalwood 2
1.2. Host species of S. spicatum 5
1.3. Oil yield and Santalol content of commercially exploited sandalwood 14
1.4. Variation in the composition of S. spicatum oil from various sections of the tree 20
1.5. Orders of magnitude of physical data of gas, supercritical fluid and liquid 25
1.6. Critical conditions for pure components 29
1.7. Relative solubility in C 0 2 of classes of compounds typically found in plant material 52
2.1. H P L C grade solvents used as rinse solvents for SFE 59
2.2. Compounds used in the standard mixture 59
2.3. Extraction and trapping conditions for exhaustive extraction of the standard mixture 61
2.4. G C conditions for the analysis of the standard mixture 62
2.5. Specifications of trapping materials 62
2.6. Extraction and trapping conditions used to examine the effect of the trapping material 64
2.7. G C conditions for the analysis of sandalwood oil 68
2.8. Extraction and trapping conditions for exhaustive extraction of sandalwood oil 69
2.9. Extraction and trapping conditions used to completely extract the sandalwood oil from the
matrix at various densities 70
2.10. Range of particle sizes used in study 1 71
2.11. Extraction and trapping conditions for exhaustive extraction of sandalwood oil in the particle
size studies 72
2.12. Extraction times used to completely extract the sandalwood oil from the matrix at various
particles sizes 73
2.13. Extraction and trapping conditions for the large-scale extraction of sandalwood (300 m L ) 76
2.14. Optimised SFE conditions for the extraction of sandalwood oil 78
2.15. G C conditions for the analysis of sandalwood oil to determine variation between trees 81
2.16.GC-MS conditions for the analysis of sandalwood oil 82
2.17. Locations and dimensions of sandalwood trees in the geographical survey 83
2.18. Locations and dates of sampling of sandalwood trees in the seasonal survey 86
2.19. Locations and dimensions of the 3 trees in the sectional survey 86
3.1. Molecular weights and boiling points of the components of the standard mixture 89
3.2. Polarity indexes of solvents used for desorption of standard mixture 105
3.3. Cumulative percentage of volatile oil extracted from sandalwood of various particle sizes by
SFE (Study 1) 124
3.4. Cumulative percentage of volatile oil extracted from sandalwood of various particle sizes by
SFE (Study 2) 126
3.5. Peak number, retention time and compounds of Western Australian sandalwood oil 128
3.6. Minor compositional changes along the three trees 142
3.7. Oil yield and santalol content of trees sampled in geographical survey 152
xii
3.8. Identification number corresponding to the geographical locations used in Fisher's pairwise
comparisons 155
1
1. Introduction
1.1. Essential Oils
By definition, essential oils are highly volatile substances isolated by a physical method
or process from an odiferous plant of single botanical species \ These oils were termed
'essential' because they were thought to represent the very essence of odour and flavour.
The term 'volatile oil' is interchangeably used with essential oil since it refers to the fact
that most of the components of the oil have low boiling points and can be recovered
from the plant tissue by steam distillation. Volatile oil is often the preferred term as it
provides a complete distinction from the higher boiling point compounds of natural
products such as triglyceride oils and fats .
Essential oils consist of a complex mixture of compounds in which the final flavour and
fragrance results from an intricate combination and proportion of the constituents. The
principle components of essential oils are mono- and sesquiterpenoids, with minor
amounts of other compounds such as aromatic and heterocyclic compounds ' . Many
essential oils contain a high proportion of mono- and sesquiterpene hydrocarbons. The
odour of these compounds is low in comparison to their oxygenated derivatives, and is
often removed from the oil by processes such as distillation .
Essential oils can be extracted from the blossoms, seeds, fruits, fruit peels, leaves,
stems, bark, wood, roots or secretions from plants. The oils are usually stored in
specialised structures within the plant tissue, such as glandular hairs on the epidermis,
oil tubes in the pericarp, or isolated cells within the tissue 4. The time taken to remove
the oil from the plant material is highly dependent on the localisation of these structures.
2
For example, the extraction of oil from the leaves or blossoms of a plant would be easier
than the extraction of oil from the wood or seed matrix.
Essential oils have many uses, ranging from flavourings, fragrances and therapeutic
agents to many industrial uses. They have been isolated from more than 1500 species
belonging to over 87 plant families. Approximately 150 different types-are commonly
traded on today's world market5.
1.2. Sandalwood
1.2.1. Sandalwood Species
The essential oil extracted from sandalwood (genus Santalum) is one of the oldest
ingredients for perfumery 6. The aromatic wood consists of a light yellow sapwood
surrounding a dark brown inner heartwood which contains the oil. The value of the
wood is determined by the amount and quality of oil contained within the heartwood.
Only those species that contain the highest quality oil are commercially viable to
harvest. Of the 29 species of sandalwood world-wide, only 7 are commercially
exploited. These 7 species along with their global distribution are shown in Table 1.1.
Sandalwood Species Distribution
Santalum album India, Indonesia, Timor and Australia Santalum austrocaledonicum N e w Caledonia and Vanuatu
Santalum ellipticum Hawaiian Islands Santalum lanceolatum Australia Santalum macgregorii N e w Guinea
Santalum spicatum Australia Santalum yasi Fiji and Tonga
Table 1.1. Species and world-wide distribution of commercially exploited sandalwood
3
S. album (East Indian sandalwood) has served as the benchmark for sandalwood quality,
a factor that has placed a high demand on the species for centuries. This, coupled with
inadequate management programs, illegal smuggling, and disease, has caused natural
stands of the trees to diminish over time 7.
The reduced availability of S. album has resulted in a greater demand for, and
acceptance of, sandalwood of lower quality. This has placed enormous stress on the
populations of other sandalwood species, particularly those found on small Pacific
islands. S. yasi, S. austrocaledonicum, S. ellipticum, and S. macgregorii have been
overexploited with drastic reductions in the sizes of the species and significant declines
in the quality of trees ' . A species of sandalwood (S. fernandezianum) in the Juan
Fernandez Islands off the coast of South America was exploited to extinction in the
early 1900s 10.
The geographic isolation and late settlement (1788) of Western Australia has meant that
natural stands of S. spicatum remained virtually untouched, while stands of sandalwood
in India and the Pacific were overexploited. The early settlers first initiated trade of S.
1117
spicatum in Western Australia in 1845 ' . Due to the widespread distribution of the
tree throughout the state and the imposition of stringent management programs, export
of S. spicatum has continued to the stage that Western Australia is now the main
supplier of internationally traded sandalwood 13'14.
4
1.2.2. S. spicatum
1.2.2.1. Description
Western Australian sandalwood (Santalum spicatum (R. Br.) A. DC.) is a small tree or
shrub which may reach heights between 3 and 8 m when fully mature. The tree consists
of irregular spreading branches with green-grey narrow leaves (Figure 1.1). It is slow
growing, taking between 50 and 90 years to fully mature depending on rainfalll . The
stem diameter can range from 100 to 300 m m and the tree is considered harvestable
when the diameter is greater than 127 m m at 150 m m above ground level.
Figure 1.1. Santalum spicatum
The tree flowers from 3 years and flowering can occur at any time of the year depending
on rainfall16. Flowering is most frequent during mid-summer (February) to autumn
(May). Between October and January, the fruit usually ripens into a leathery red-brown
epicarp with a smooth round hard endocarp (nut) up to 2 cm in diameter 1415.
5
Sandalwood seeds germinate following imbibition of rain water which cracks the nut.
Only 1 to 5% of the total seeds germinate 16. This, along with sandalwoods
susceptibility to fire and grazing by domestic and feral herbivores, mainly sheep, goats
and rabbits, has resulted in low levels of regeneration outside conservation reserves.
Establishing plantations of Western Australian sandalwood has proven difficult since it
is a root hemi-parasite, as are all species of sandalwood. While these trees do produce
their own photosynthates, they also require part of their essential nutrients to come from
a host plant(s)17. The tree uses haustoria that protrude from the roots and attach
themselves to the roots of one or more host plants. There is much conjecture as to
whether sandalwoods are facultative or obligate parasites. A list of host species recorded
for S. spicatum commonly pertaining to the Acacia and Eremophila genera, is shown in
Table 1.2. During periods of drought, the parasite is able to adapt by drawing moisture
and nutrients from the root system of the host through a direct xylem-to-xylem union.
Under extreme drought, it has been observed that the host plant may die before the
parasite 15. Little is known about the role of the host, and whether the rate of growth and
the quality of sandalwood varies with different hosts .
Host Species Recorded for Santalum spicatum
Acacia acuminata Dodonaea lobulata Acacia aneura Eremophila alternifolia
Acacia collectioides Eremophila dempsteri
Acacia hemiteles Eremophila ionantha
Acacia linophylla Eremophila oldfieldii Acacia tetragonophylla Eremophila oppositifolia Cassia chatelainiana Eucalyptus loxophleba Cassia nemophila Eucalyptus wandoo
Casuarina cristata
Table 1.2. Host species of S. spicatum 15
6
1.2.2.2. Distribution
Western Australian sandalwood is distributed over an area of 161 million hectares of
southwestern Australia (Figure 1.2) 19. Prior to clearing of the land for agriculture in the
'Wheatbelt', in the southern region of Western Australia, the total area was much larger,
ranging from a latitude of 24°S to 35°S. However the total harvestable area at present is
only 82 million hectares. The remaining areas consist of reserves and national parks 15.
Stands of S. spicatum were also widely distributed in South Australia, but have largely
disappeared due to agricultural and pastoral activities20.
Figure 1.2. Distribution of& spicatum in Western Australian
7
1.2.2.3. Climate
S. spicatum is generally found in the arid and semi-arid regions of Western Australia
where rainfall is between 200 and 600 mm annually . In rainfall areas of 200 mm,
sandalwood has a tendency to be found on lower slopes and drainage lines . The
amount of rainfall has been shown to have a marked effect on the regeneration and
growth rate of the trees 15. The time required to reach a commercial size in a 500 mm
rainfall zone can be 23 years, whereas in a 300 mm rainfall zone the tree may take up to
100 years to reach full size 21.
1.2.2.4. Soils
Western Australian sandalwood is generally found growing on red soils with a pH
91
ranging from neutral to mildly acidic (pH 4.5) . The most important aspect of the soil
is that it must be free draining. Sandalwood prefers lighter type soils such as loams and
sandy loams with a granite composition. Granite soils are characteristically high in
potassium that has been shown to be important in sandalwood nutrition ' . Heavy clay
soils, waterlogged sites and saline areas are not suitable.
1.2.2.5. History of the Sandalwood Industry in Australia
Six species of Santalum grow naturally in Australia: S. acuminatum, S. album, S.
lanceolatum, S. murrayanum, S. obtusifolium and S. spicatum . Their distributions
throughout Australia are illustrated in Figure 1.3. With the exception of S. album, all are
native to Australia. Only S. album, S. lanceolatum and S. spicatum are of the necessary
quality to be commercially acceptable.
8
Figure 1.3. Distribution of sandalwood species in Australia
Statham has comprehensively examined the history of the involvement of Australia in
the sandalwood trade. She identified three distinct stages: The Offshore Industry (1805 -
1860), Australian Sandalwood (1844 -1929) and Government Control (1929 - present)
1 \ and these are summarised below.
Australia's involvement with sandalwood began in 1805, 17 years after foundation of
the colony in 1788. Whalers and sealers from Sydney, during the off-season periods in
the Pacific Islands, brought back sandalwood to trade and thus fund future expeditions.
This was essentially a small scale trade and quantities did not exceed several hundred
tonnes. By the mid 1860s, the offshore industry ceased due to diminishing commercial
stands in the Pacific region.
In 1843, a report reached Perth on the west coast of Australia of the high prices being
obtained for a wood of a tree similar to one found growing in the region. It is thought
that the early Indian and Chinese labourers were the first to recognise the commercial
potential of the wood. Up until this time, the early settlers on the west coast had used the
wood for firewood and as a building and fencing material, and large areas were burned
during clearing of the land 24.
The first shipment of Western Australian sandalwood took place in 1845, when 4 tonnes
of wood was exported to Bombay as a trial to determine if harvesting the wood would
be a commercially viable option to help overcome a balance of trade deficit. News was
received that the wood would fetch £10 per tonne in Bombay and £20 - 30 per tonne if
shipped directly to Canton. Even though the wood was inferior to the top quality S.
album and not suitable for carving, it was in high demand as the powdered form for
incense. During this period, harvesting of sandalwood rapidly increased and by 1848, it
had become the colony's primary industry.
During the late 1800s, the demand for Western Australian sandalwood increased due to
export restrictions of S. album from India. Following the gold rush in Kalgoorlie (600
km east of Perth) came the construction of railways that gave access to vast areas of
10
uncut sandalwood and lowered the cost of transportation to the coast. Consequently the
industry trebled in size during this period, with annual export quantities reaching 9000
tonnes.
In 1913, Braddock established a plant to distil sandalwood just outside Perth. The
reported claims of the healing properties of sandalwood oil, and the outbreak of World
War I, significantly increased the demand for the oil. In 1917, over 3000 lbs of
sandalwood oil were being exported to England. The industry flourished throughout the
1920s and was not affected until the 1930s by deterioration of conditions in China and
the outbreak of World War H
By the late 1920s the need of Government regulation in the industry became clear as
stockpiles began to build up on the wharves at Fremantle and the sandalwood workers
could not be paid for their harvest. The Sandalwood Control Act, introduced in 1929, set
restrictions on the amount of sandalwood harvested. Over the following years, new
plans were negotiated mainly by altering harvesting quotas, aimed at stabilising the
market and increasing the price of sandalwood. At this point Australia held 80 % of the
international market.
During the mid 1900s the export of sandalwood remained highly profitable. The
distillers of oil through this period absorbed 10- 20 % of the wood harvested, but the
price they were prepared to pay for the wood was much less than what was paid on the
overseas market. As a consequence, sandalwood oil production in Australia ceased in
1971.
11
Throughout the 1980s, the market demand for incense continued to increase due to
rising populations in Asia and exports in Australia ranged from 1600- 2000 tonnes per
year. Concern was expressed over how long sandalwood stands would be able to
support the current demand. To reduce the amount of native wood harvested and as an
opportunistic way to make money, numerous companies established sandalwood
plantations. By far the largest project to date is the plantation of S. album in Kununurra,
in the northern tropical region of Western Australia, which began in 1997. The
plantation is situated on the Ord River which provides irrigation during the dry season.
S. album was chosen over & spicatum since & album has a faster growing rate and
provides higher return.
In 1997, sandalwood oil production was commenced once again in Western Australia by
Mt Romance Pry. Ltd, situated in Albany . The company won a government tender for
the sale of sandalwood, in which they receive up to 1000 tonnes of S. spicatum per
annum. M t Romance currently produces its own range of cosmetics using the distilled
oil as a base, and is looking to sell the oil in the international market as a base for the
perfumery industry.
1.2.2.6. Conservation
Sandalwood harvesting in Western Australia is administered by the Department of
Conservation and Land Management (CALM), according to the provisions of the Forest
Products Commission Act 2000. The harvesting and marketing of the sandalwood is
managed by the Forest Products Commission (FPC). Wescorp Pty. Ltd. is the sole
processor and marketing agent for S. spicatum.
12
Harvesting of the wood is performed by licensed sandalwood pullers under contract by
the FPC. The trees are harvested by attaching a chain around a tree connected to a four-
wheel drive vehicle, and pulling the tree out of the ground. Invariably, not all the tree is
utilised as some of the roots remain in the ground.
1.2.3. Uses
Sandalwood's highly aromatic wood has been prized for centuries, and its use in
religious and cultural ceremonies can be traced back through mythology to the 7th
century BC, and through the literature to 2300 years ago26. The wood is traditionally
used by Indians and Chinese for carvings, incense and oil.
Carvings
The highest quality wood is utilised for carvings. Logs are graded for carving and many
specifications must be met. The log must be 1 m in length, free of any cracks, rot or
blemishes, have a heartwood diameter of at least 125 mm, and an oil content of at least
i o
2 % . These logs are turned into religious ornaments, boxes, beads and other
handicrafts.
Major exporters of high grade logs are Australia, Hawaii, Fiji and Indonesia. Export is
to Hong Kong and Taiwan who in turn distribute to China, Japan and Singapore. India
who produces the highest grade of logs, due to its fine grain and oil content, have a ban
on all sandalwood export due to diminishing resources. Some sandalwood is illegally
exported and sold for exorbitant prices on the black market. Harsh penalties have been
implemented in attempts to curtail this practise.
13
Incense
Incense plays an important role in Buddhist and Hindu religious ceremonies. This,
coupled with the spread of the practice in Western countries, has led to a large and
increasing market for incense.
The incense market uses logs of all quality. Australia supplies most of-the incense world
market at present. The wood is mostly ground to a powder on site in Western Australia
and exported to Singapore and Taiwan for processing. The powdered wood is attached
to bamboo slithers with wood resin or compacted into incense sticks.
Oil
Sandalwood oil is extracted from the stem and roots and is one of the most valuable
essential oils in the world. More than 90 % of the world production of sandalwood oil is
from India 13 and represents over 50% of the country's total exports 27. The essential oil
is a pale yellow viscous liquid and is described as having a sweet, warm, persistent
woody odour.
The oil has various traditional uses. It has been used as an antiseptic, antiscabietic,
diuretic, and for the treatment of dermatitis, gonorrhoea, bronchitis and bladder
infection 13'28,29. More modern applications have used the oil in treatment against the
organisms Staphylococcus aureus, Bacillus anthracis, Bacillus subtilis and the Herpes
virus30'31. The oil has also shown to have chemopreventive action on carcinogenisis in
32
mice .
By far the major modern day use of the oil is as a base fragrance in perfumery. Much of
the sandalwood oil produced in India is exported to perfumeries in France and New
14
York. The oil blends very well with almost all types of perfumes and flavours and has
become a common fixative in countless woody floral and oriental floral bases .
Sandalwood oils are also used extensively in soaps, moisturising creams and powders. It
has been shown to act as an insect repellent in some creams34.
1.2.4. Sandalwood Oil
The amount and quality of oil contained in sandalwood differs considerably between
species (Table 1.3). The santalol content, made up of the sesquiterpene alcohols a- and
(3-santalol, is responsible for the aroma and quality of the sandalwood oil. The highest
quality oils have a santalol content of over 90%. The santalol content of the 7
commercially exploited sandalwood species is shown in Table 1.3.
Species
Santalum album
Santalum austrocaledonicum Santalum ellipticum Santalum lanceolatum Santalum macgregorii Santalum spicatum Santalum yasi
Oil Yield (%)
6-7 a
3 -5 a
n/a la
4-6 a
2 - 5 a
5a
Santalol Content (%)
>90b
>90c
n/a n/a n/a
10-70d
87c
Table 1.3. Oil yield and santalol content of commercially exploited sandalwood . . . ..... 13, 35 36 . 37-41
(n/a= not available) a b e d
1.2.4.1. Composition of S. album
The composition of East Indian sandalwood oil has been examined extensively. The oil
is a complex mixture of over ninety chemical compounds, of which at least fifty have
been suitably characterised 42_44. The santalol content consists of approximately 60 % a-
santalol and 30 % P- santalol37'45-47. Brunke has shown that p- santalol is the main
contributor to the aroma of the oil, possessing a typical sandalwood odour with powerful
15
wood, milky and urinous tones 48'49. By contrast, a- santalol possesses a much weaker
woody, cedarwood-like scent.
There is much disagreement in the literature on the compounds present in the remaining
10 % of the oil. There is general agreement that the sesquiterpene hydrocarbons a- and
p- santalene, and santalyl acetate contribute between 4- 6% to the oil 43-45>46>50>51. other
sesquiterpene alcohols include (+)-(Z)-epi-P~santalol, (-)-(E)-p-santalol, (-)-Z-lanceol
and (+)-(Z)-nuciferol45,49. Numerous other acids, aldehydes, ketones and alcohols have
also been identified 48'52"58.
1.2.4.2. Composition of S. spicatum
The composition of Western Australian sandalwood has been investigated to a much
lesser extent than the East Indian variety. An examination of the literature revealed only
seven references to Western Australian sandalwood oil38"41,59"61. Since most of these
refer to work carried out without the benefit of modern analytical techniques, a number
of discrepancies in the results reported are evident, in particular the santalol content.
Early work by Penfold estimated a santalol content of 35 %39'40, while Guenther
claimed a higher value between 40 and 45 % . In a more recent study, S. spicatum
collected near Kalgoorlie, Western Australia, afforded an oil containing 10% santalols60
and30%santalols41.
Due to the lower santalol content of S. spicatum, the other components of the oil
contribute significantly to the odour. There is general agreement that one of the major
components ofS. spicatum is trans, trans- farnesol, responsible for approximately 30 %
of the oil41'59'60'62. Other compounds previously identified and significantly contributing
16
to the oil composition include the sesquiterpenes epi-a- bisabolol, Z- nuciferol,
dendrolasin and cis- lanceol. The oil also contains a hydrocarbon fraction (~6%) that is
composed of a- santalene, epr-P-santalene, p~ santalene, and a and P- curcumene. The
structures of some of the main components of sandalwood oil are shown in Figure 1.4.
a- bisabolol OH
Nuciferol a- curcumene
Dendrolasin (Z)-a-frans-berg amotol
a- santalene p- santalene
CH2OH
(Z)-cc- santalol
,CH2OH
(Z)-epi-p-santalol
CH2OH
(Z)-p- santalol
Figure 1.4. Major components of sandalwood oil
17
1.2.5. Factors affecting Sandalwood Oil Quantity and Quality
Within sandalwood species, a great deal of variation occurs in both the oil yield and
composition from stand to stand and tree to tree. As shown in Table 1.3, the reported
santalol content for S. spicatum varied widely. Although little research has been
performed to account for these differences, some generalisations can be made and are
discussed with below.
1.2.5.1. Environmental
Environmental factors such as geographic location, climate, temperature, rainfall,
altitude and soil type may lead to differences in oil quantity and composition.
Jayappa has shown that the oil extracted from East Indian sandalwood grown in
different geographical regions throughout India differs in physical characteristics 63.
Differences were found in percentage yields, refractive indices, optical rotation and
santalol content, yet no correlation was made between the environmental conditions
prevailing at each location and the differences in the oils.
It is thought that rainfall has a profound effect on the development of heartwood, which
may account for differences in oil yield. For individual trees of similar size, the trees
with a faster growth rate may well produce a lower proportion of heartwood 13. Since it
is known that trees in high rainfall areas have faster growth rates that those in arid
conditions 14'15,645 the heartwood content of a given tree would be lower in higher
rainfall areas.
18
Much of the research on the effect of soils has concentrated on the growth of
sandalwood seedlings with various nutrition supplements. Results have shown that
chelated iron increases the growth of sandalwood seedlings65, as do calcium
supplements . Although these results show added benefits at the nursery stage, the long
term effects of these nutrients on the amount and composition of the oil are not known.
1.2.5.2. Host Species
As with the research into the effect of soil on sandalwood, studies on host species have
been limited mainly to the nursery level. Consequently, limited information on the
influences of the host on heartwood oil formation is available. The results, however, do
show quite conclusively the need for a host in seedling development64,67'69. With an
adequate host, the biomass of the seedling can increase almost 9 fold. Since host quality
is considered to be one of the most important siviculture components influencing early
growth, heartwood yield may also be dependent on the host species.
1.2.5.3. Section of Tree
One of the major reasons for the variation observed in oil yields and composition is
most likely due to the differences in oil found within the different sections of the trees.
There is general agreement that the roots and buttwood contain more oil with a higher
santalol content than the stem and branches. It was also found that oil content decreased
by 45% along the length of the tree (from root to tip). Work carried out on East Indian
sandalwood showed that the roots contained 8.43 % oil, compared to 5.79% in the trunk
and 3.52% in the branches 63'70. Little difference was found in the santalol content along
the length of the tree, decreasing by only 3 %. The santalol content found in the roots,
19
trunk and branches were 91.87, 89.09 and 88.62% respectively. This slight decrease was
accompanied by a 3% increase in the sesquiterpene hydrocarbons, santalyl acetate and
santalenes. Although this increase in santalyl acetate and santalenes may seem small, it
corresponds to an overall 35 and 45% increase for each of the sesquiterpene
hydrocarbons.
Similar studies on & spicatum have shown completely different trends in the oil and
santalol content from different sections of the tree, as shown in Table 1.4. The oil
content was found to decrease moving up the length of the tree, from a maximum of
8.38% in the buttwood to a minimum of 1.78% in the high branches62. It is interesting
to note that the buttwood has a higher oil content than the roots (7.41%), in contrast to
the results seen in S. album.
The santalol content of the oil in S. spicatum was shown to be higher in the roots and
buttwood, and decline markedly moving further up the tree (Table 1.4) 41>62'71. Relative
amounts of both trans, fr-aws-farnesol and a-bisabolol can be seen to differ in the oil
extracted from various sections of the tree. The percentage of a- bisabolol ranges from
3.1% in the buttwood to 18.8% at 30 cm above the first branch. These results clearly
indicate that the section of the tree extracted will have a great influence on both the oil
content and composition.
20
Percentage
(%)
Yield
a- bisabolol
a- santalol trans,trans-farnesol
P- santalol nuciferol
Root
7.41
3.9 6.9 3.1
2.7 2.0
Butt
8.38
3.1 10.0
5.3
3.8 2.2
Mid-trunk
4.80
12.1
1.6 6.6
0.6 2.5
Top-trunk
4.58
15.9
1.1 7.9
-
1.9
Trunk
30a
4.51
18.8
0.6 8.8
-
1.5
Trunk
70b
4.08
18.0
0.6 7.5
-
1.4
High
Branch
1.78
17.2 -
8.0
-
-
Table 1.4. Variation in the composition of S. spicatum oil from various sections of the tree 4I
* Section of tree 30 c m above Top-trunk Section of tree 70 cm above Top-trunk
1.2.5.4. Cross Section
Not only has the oil content and composition been shown to vary along the length of the
tree, changes have also been shown to occur across the diameter of the tree. In a 51
album heartwood disc taken at approximately lm above ground level, there is an
average 20% decrease in the oil content from the core to periphery . There is also a 2%
decrease in the santalol level, while the content of santalyl acetate and santalenes
increase by 60 and 30% respectively.
A similar study on a wood disc from the buttwood of 5. spicatum showed no clear trend
in the amount of oil across the diameter of the disc 62. The oil was not analysed for
composition. The different results obtained in the two studies may be due to
interspecific differences, or the positions along the tree from which the disc was taken.
1.2.5.5. A g e of Tree
As expected, it was found that the oil content in young trees (0.2 - 2.0%) was markedly
lower than that of mature 5. album (2.8 - 5.6%)72. More surprising was the difference in
the oil composition between young and mature trees. The santalol content in young trees
ranged from 72 to 83%, which was considerably lower than the 86 to 91% range seen in
21
mature trees. The level of santalyl acetate/santalenes was found to be higher in young
trees, which was thought to arise from a conversion of santalyl acetate/santalenes to
santalols as the trees develop
1.2.5.6. Ageing of Sample
The age of a sandalwood oil sample may influence the composition of the oil. It has
been shown that the colour of freshly distilled oil was generally pale yellow and turned
golden yellow on standing for 4 to 6 months 72. Analysis of the oils before and after
ageing showed an increase in the santalol content and a decrease in a- and P- santalene,
and santalyl acetate.
1.2.5.7. Extraction
Different extraction procedures can afford different oils. This can be illustrated by the
extraction of 5. album and 5. spicatum by steam distillation and supercritical fluid
extraction (SFE) 41>73'74. For both species, higher oil yields were obtained by SFE
compared to steam distillation. The composition of both oils also differed depending on
extraction techniques. This was particularly evident in the 5. spicatum sample. The more
volatile components of the oil were present in higher proportions in the steam distilled
extract, whilst the less volatile components were much less abundant. Compositional
differences in the oils between the two extraction techniques was assumed to reflect the
harsh extraction conditions associated with steam distillation, namely prolonged times at
relatively high temperatures in the presence of traces of acids. Many of the trace
compounds identified may be enzymatic or oxidative degradation products of the main
22
sesquiterpenoid compounds, particularly the more volatile components. The effect of
different extraction methods is described in more detail in Section 1.5.
1.2.5.8. Adulteration
One of the more obvious reasons for differences in sandalwood oil compositions,
particularly in the East Indian variety, is due to adulteration of the oil. This is a process
in which an adulterant is added to the oil before or after extraction to increase the
amount of oil ' . The adulterant is usually polyethylene glycol, a high boiling
compound that is difficult to detect by G C 77,78. Cheaper essential oils are also used,
such as 'Morpankhi oil' which is produced from Thuja orientalis growing in north India
79
1.2.5.9. Other factors
There are a number of other factors that are capable of producing differences in the
composition of essential oils. Although these factors have not been investigated for
sandalwood oil, they have been examined for other essential oils.
Climatic conditions have been shown to have a marked affect on the composition of
Thymus vulgaris80. At low altitudes in warm, dry mediterranean environments, the
plants contained mainly phenolic compounds (thymol and carvacrol). Moving further
from the Mediterranean coast towards more humid conditions, the plants produced
fewer phenolic compounds. The main components of these plants were cyclic non-
phenolic terpenes (thujanol-4 and a- terpineol) and acyclic monoterpenes (linalool and
geraniol).
23
Closely linked to the effect of climate are those due to season. Seasonal changes were
observed in the essential oil in the leaves of Artemisia judaica. The oil content was low
during winter (1%) and peaked in late summer at 4%. The composition of the oil was
also shown to change. Although the combined amount of camphor and piperitone in the
oil was constant (64%), the proportion of the two compounds varied with the season. In
winter, the piperitone content was reduced whilst levels of camphor increased. The
reverse was the case in summer. It is important to understand how these oils change
with the seasons as it allows the optimal time for harvesting to be determined.
Although the environmental and processing factors discussed above are capable of
producing changes in the essential oil of a plant species, the genetic makeup of the plant
is the underlying factor governing the production of oil. It has been shown that genetic
variability occurs between plants of the same species. Variability in the composition of
an essential oil of the same species can be qualitative (involving the presence or absence
of a compound), or quantitative (components present at different amounts). Qualitative
characteristics are dependent on a single or few genes whereas quantitative
characteristics are determined by several genes 80. The oil content depends on the
number and quantity of precursors formed and the capacity of oil producing structures.
As environmental factors can have a substantial influence on the composition of oil,
examination of these genetic differences can only be performed in a controlled
environment. Seedling ofArtemisia judaica grown under the same conditions contained
essentially the same oil composition as the parent plants. Therefore, by genetic
selection, it may be possible to cultivate plants of high quality using the seed stock from
those plants of superior oil content and quality.
24
1.3. Supercritical Fluid Extraction
1.3.1. What is a Supercritical Fluid?
A supercritical fluid is defined as a substance that is above its critical temperature and
critical pressure. This definition can be explained through the use of a phase diagram
(Figure 1.5). A phase diagram for a pure substance shows the temperature and pressure
regions where the substance occurs as a single phase (solid, liquid, and gas) and the
phase transition lines where two of the phases can exist in equilibria. These two phase
regions between solid- gas, solid- liquid and liquid - gas involve the phase transitions of
sublimation, melting and vapourisation respectively. The three curves intersect at the
triple point, where the solid, liquid and gaseous phases coexist in equilibrium. The gas-
liquid equilibrium curve ends at the critical point. Increasing the temperature along this
curve increases the pressure at which both phases can coexist. This, in turn increases the
density of the gas phase and decreases the density of the liquid phase. At the critical
point the density of both phases are equal and the two phases are indistinguishable. At
this point, the substance is termed supercritical and consists of a single phase. If the
temperature and pressure are above the critical parameters, the substance will always be
single phase, and no further liquefication or vapourisation of the substance will occur.
25
P r e s Pc
s u r e
Tc
Temperature
Figure 1.5. Phase (pressure- temperature) diagram of a pure substance Pc= critical pressure, Tc= critical temperature, C P = critical point, T P = triple point
1.3.1.1. Properties of Supercritical Fluids
Since a supercritical fluid exists from the merging of a liquid and gas, supercritical
fluids exhibit physical properties intermediate between the two states (Table 1.5). The
relevance of these properties in relation to applications of supercritical fluids will be
discussed below.
Density (g/mL) Dynamic Diffusion Viscosity Coefficient
(g/cm-sec) (cm2/sec)
Gas 0.0006-0.002 0.0001-0.003 0.1-0.4 Supercritical Fluid 0.2-0.5 0.0001-0.0003 0.0007 Liquid 0.6-1.6 0.002-0.03 0.000002-0.00002
Table 1.5. Orders of magnitude of physical data of gas, supercritical fluid and liquid81
Viscosity/Diffusivity
Supercritical fluids exhibit significantly lower viscosities and higher diffusivities than
liquids. These properties are dependent on both pressure and temperature. The viscosity
and diffusivity of a supercritical fluid approach those of a liquid as the pressure is
increased. As pressure increases, viscosity will increase unlike a liquid, and diffusivity
26
will decrease. As the temperature is increased the viscosity will decrease unlike a gas,
and diffusivity will increase. The increase in viscosity with pressure and diffusivity with
temperature is more pronounced in the region close to the critical point.
The low viscosity and high diffusivity of supercritical fluids means that mass transfer is
higher than in liquids alone. This, combined with their very low surface tension,
means that they can more readily penetrate porous materials and are able to transport
dissolved solutes through materials very efficiently.
Density
The solvent power of a fluid is dependent on the number and strength of interactions
between the solute and solvent, and therefore is dependent on the density of the fluid. In
general, the greater the density, the greater the solvent strength of the fluid. Since
density is dependent on pressure and temperature, changes in any of these parameters
can have an effect upon the solvent power of a fluid. The relationship between density
of a supercritical fluid and pressure at various temperatures is illustrated in Figure 1.6.
The variables are all expressed as reduced variables, which is the ratio between their
actual values and critical values. Therefore, the critical point results from the triple
intersection where all the reduced values are equal to one. The change in density with
pressure at a constant temperature can be seen to be typically non-linear. In the vicinity
of the critical point small changes in pressure or temperature result in the largest
changes in density, whereas moving further away from the critical point the change in
density is less pronounced. The unique ability to control the density of a supercritical
fluid leads to the ability to control the solvent power with small changes in pressure and
temperature.
27
2.0
11 1.0
0 0.1 1.0 10.0
P*-P'PC
Figure 1.6. Variation of the reduced density of a pure component in the vicinity of its critical point82
P R = reduced density, P R = reduced pressure, T R = reduced temperature, CP= critical point
Although liquids generally have higher densities than supercritical fluids, the density of
a liquid is essentially independent of pressure. It is the ability of a supercritical fluid to
change it density, hence solvent power, combined with the low viscosity and high
diffusivity that give supercritical fluids their unique properties that can be used in a
variety of applications. These applications include supercritical fluid extraction,
supercritical fluid chromatography and supercritical fluids as reaction solvents.
1.3.2. Supercritical Fluid Extraction
Supercritical fluid extraction (SFE) is an extraction process that uses a supercritical
fluid as the extraction solvent. This extraction technique takes advantage of the high
diffusivity, low viscosivity and minimal surface tension which allows rapid penetration
into the desired matrix, often the rate limiting step in traditional extraction techniques.
The high mass transfer rates allow rapid transport of solute leading to decreased
extraction times.
28
The most advantageous property of supercritical fluid extraction is its adjustable solvent
strength through alteration of its density. If the density of the supercritical fluid is
increased, the fluid will be able to extract compounds of a higher polarity and size. This
allows selective extraction for a particular class of compound through changes in
pressure and temperature.
Since many supercritical fluids are gases at ambient conditions, the extracted analytes
can be separated from the solvent without the need for a concentration step; often a
requirement with liquid solvent extractions.
1.3.2.1. Applications of SFE
Although supercritical fluids have been known for some time, their use in extraction is
only recent . SF E gained acceptance in the 1980s mainly due to two reasons. Firstly,
the U S Environmental Protection Agency began to discourage the use of some organic
solvents commonly used in extraction because of the adverse effect of these solvents on
the environment84. SFE was seen as a 'clean' method of sample preparation and a
superior method of extraction. Secondly, the production of commercial analytical scale
S F E equipment made this technique generally available to research laboratories.
Although SFE can be used to extract liquid samples, by addition of an inert solid matrix,
its main use has been as an alternative for the extraction of solid matrices85. Areas of
applications include environmental monitoring (pesticides, PAHs, PCBs)86"88, natural
products (flavours, fragrances, pharmaceuticals) " , foods (fats, oils) ' , and polymer
i • 95-97
analysis
29
1.3.2.2. Choice of Supercritical Fluid Solvents
The fluids that have been used for SFE are listed in Table 1.6. These supercritical fluids
cover a large range in polarity. In theory, a solvent can be chosen based on the polarity
of the target compound/s. However, practical considerations, such as the temperature
and pressure required to obtain the critical parameters, often govern the selection the
solvent. Low critical parameters are favoured since the cost of equipment increases
when high pressures and temperatures are needed.
C o m p o u n d TC(°C) Pc (Bar)
Xenon 16.6 58.4 Trifluoromethane 26.2 48.6
Carbon Dioxide 31.0 73.8 Ethane 32.2 48.8 Nitrous Oxide 36.5 72.4 Sulfur Hexafluoride 45.6 37.6 Propane 96.7 42.5 Ammonia 132.4 112.8 Methanol 239.5 80.9 Water 374.2 221.2
Table 1.6. Critical conditions for pure components Tc= critical temperature, P c= critical pressure
The use of some fluids is restricted due to problems encountered at high pressures and
temperatures. Water and ammonia are both corrosive at supercritical conditions,
ammonia is toxic, ethane is highly flammable, and nitrous oxide has been reported to
explode under pressure ".
Carbon dioxide is the most commonly used supercritical fluid for extraction for the
following reasons:
i) It has a relatively low critical temperature and pressure;
ii) It is relatively inert and therefore has a low reactivity;
iii) It is classed as non-toxic, which allows it to be used in the food industry;
30
iv) O n a small scale, it is not classed as an environmental pollutant;
v) It is widely available at low cost and in high purity.
One of the major disadvantages of supercritical C02 as a solvent is its low solvent
strength. The solvating power of supercritical C 0 2 is generally equated to that ofhexane
. This limits the application of C 0 2 to the extraction of compounds of low polarity.
For the extraction of more polar compounds, rather than using a solvent of higher
polarity, this problem can be overcome through the use of a modifier. A modifier is a
polar organic solvent, such as methanol, that is added to the supercritical carbon dioxide
to increase the polarity of the solvent. The modified C 0 2 equates to having a solvent
strength equivalent to that of chloroform and more polar compounds can be extracted
100
1.3.2.3. Instrumentation
The instrumentation of SFE is very simple. Basic instrumentation must allow the
following; an extraction fluid to be pressurised and heated to supercritical conditions,
the supercritical fluid to contact the sample and dissolve the analytes of interest,
transport of the supercritical fluid with dissolved analyte from the sample, and
collection of the analytes by removal of the supercritical fluid. A typical schematic of a
basic SFE device is illustrated in Figure 1.7.
31
Pressure/Flow Controller
1 •=•—i Extraction vessel
Collection Vessel
Fluid Pre-Heat
Extraction Fluid
Figure 1.7. Schematic diagram of basic SFE apparatus
Method of Extraction
The extraction fluid is usually withdrawn from a cylinder containing a liquid-gas
mixture. The cylinder contains a dip tube, which allows the more dense liquid phase to
be withdrawn from the cylinder. The carbon dioxide is thereby supplied to the pump as
a liquid where it is pressurised to the desired value. If the extraction fluid is supplied to
the pump as a gas, the pump will have difficulty in sustaining the necessary flow.
Once the desired pressured has been reached, the fluid passes through a preheating zone.
This heats the fluid to above the critical temperature where it becomes supercritical. The
supercritical carbon dioxide then passes through the extraction cell containing the
sample. Those analytes within the sample matrix which are soluble in supercritical
carbon dioxide are dissolved and flow out of the cell with the extraction fluid. The
conditions required to remove the analytes from the matrix will be discussed in detail in
Section 1.4.1. At this point, the temperature no longer needs to be controlled. This is
because a decrease in temperate will bring about an increase in density and the analytes
will remain soluble in the liquid carbon dioxide.
Fluid Pump
/*N
32
The fluid and dissolved analytes are passed through a restrictor where the pressure is
decreased. Restrictors are usually fixed diameter tubes or electronically controlled
variable orifices which provides the back pressure in SFE. With a fixed restrictor, flow
cannot be controlled independently of the pressure. Using a variable restrictor, flow
rates can be controlled using pressure and size of the variable orifice. A s the fluid passes
out of the restrictor the pressure is lowered to atmospheric conditions over a short
distance. Associated with this rapid expansion is Joule-Thomson cooling which can
cause plugging of the restrictor, especially by ice. To help overcome this problem, the
restrictor zone is heated. Blockages tend to occur more frequently in fixed restrictors
since variable restrictors can increase the orifice diameter if pressure build up is
detected.
As the fluid depressurises, the dissolved analytes are no longer soluble in the extraction
fluid. Gaseous carbon dioxide is released leaving behind precipitated analytes. The
analytes are collected on cryogenically controlled solid bed traps or in a liquid solvent in
which the analytes are soluble. A more detailed description of the collection methods
will be described in Section 1.4.2.
1.4. Optimisation of SFE
For successful SFE, two processes must occur efficiently. Firstly, the analytes of interest
must be completely removed from the matrix, and secondly, there must be quantitative
recovery of these analytes in the collection vessel. Therefore, optimisation of S F E can
be thought of as two separate processes, extraction and collection. Each of these
processes will be discussed in detail below.
33
1.4.1. Extraction Conditions
The ability to extract target analyte/s from a matrix is determined by101:
• Analyte solubility in the supercritical extraction fluid
• Analyte-matrix interaction
• Position of the analyte within the matrix
• Porosity of the matrix
As can be seen from the above determinants, the matrix can have a major effect upon
the extractability. Even though an analyte may be soluble in a supercritical fluid it may
be incompletely extracted. The effect of the matrix is clearly evident with polyaromatic
hydrocarbons (PAHs) spiked onto various matrices. Complete recovery was achieved
from silica wool, polyurethane foam, silica gel and ODS. Alumina and diatomaceous
earth gave low recoveries of some compounds, whereas activated charcoal exhibited
strong matrix-analyte interactions which prevented recovery of any of the PAHs
There are a number of parameters in the extraction procedure that can be optimised to
achieve complete extraction. These parameters are density (pressure), temperature,
mode of extraction (static or dynamic), flow rate, extraction time and particle size.
1.4.1.1. Density
The effect of density on solvating power has been discussed in detail in Section 1.3.1.
Density governs the solubility of an analyte in a supercritical fluid. Numerous reports
have examined the solubility of a wide range of compounds in supercritical carbon
dioxide 103,104. This has allowed correlations to be made between the size and
functionality of a compound to its solubility in supercritical C02. If the sample contains
34
low molecular weight, non-polar compounds, low densities will be sufficient to
solulibise the compounds. For higher molecular weight, non polar compounds, high
densities will be required. For high molecular weight polar compounds, high densities
with polar modifiers are required.
Since at higher densities the solubility of a compound increases, density can be utilised
to decrease extraction times. This is because less volume of solvent is required to
dissolve the same amount of solute as the density is increased. Increasing the density,
combined with dynamic extraction (Section 1.4.1.3), can be extremely useful in
decreasing extraction times if selectivity in the extraction is not required.
The density parameter has very little effect on the removal of the analytes from the
matrix. It is the physical characteristics of viscosity and diffusivity that are utilised to
interact with matrix. It has been proposed, however, that for intracellular material, the
increased pressure resulting from increasing the density can break open cellular
structures to free some analytes.
1.4.1.2. Temperature
Temperature is an important but complex parameter for controlling extraction. As the
temperature increases under isobaric conditions the density decreases. Lower
temperatures are therefore used to obtain maximum densities for maximum solvating
power. Temperature can also be used to aid in the extraction of the analytes from the
matrix. Increasing the temperature can increase diffusion and disrupt matrix associations
thereby aiding the extraction process.
35
Increasing temperature will increase diffusivity of the supercritical fluid. For samples
whose matrices are difficult to penetrate, or for analyte- matrix association that is large,
higher temperatures can be used to increase mass transfer. For many environmental
samples, it is not the solubility of the analytes that is the rate-limiting step, but it is
desorption from the matrix that determines the rate of extraction. Extracting these
samples at higher temperatures will increase diffusivity and mass transfer to improve the
desorption kinetics 105.
An example of temperature disrupting matrix association is evident in the extraction of
additives from polymers 106,107. As a matrix, polymers have very little porosity at room
temperature. If the extraction temperature is increased high enough to soften the
polymer, the matrix is disrupted. The supercritical fluid is now able to interact with the
polymer additives within the polymer matrix, and extraction efficiency is also increased
due to an increase in both diffusivity and mass transfer as discussed above.
In some cases, high temperatures can cause problems. Analytes that are thermally
unstable at high temperatures can decompose thus altering the composition of the
analytes. This is particularly important in the extraction of natural products and will be
dealt with in detail in Section 1.5.
1.4.1.3. Mode of Extraction
SFE can be performed in two modes; static or dynamic extraction. The method of
• 10R
extraction depends on the sample size to extraction cell volume ratio . In static
extraction, a fixed amount of supercritical fluid interacts with the analyte matrix. The
extraction vessel is pressurised to supercritical conditions and the sample is soaked in
36
the solvent for a given period of time. This mode of extraction utilises the supercritical
fluid properties of high diffusivity and mass transfer to access the analytes within the
matrix. Following extraction, the restrictor is opened and as the fluid depressurises, the
analytes are swept out of the extraction cell to a collection device.
In dynamic extraction, fresh solvent is continuously passed through the extraction cell
containing the sample. The restrictor is constantly open, and combined with the
pressure, delivers the extraction fluid at a desired flow rate. The collection of analytes is
continuous throughout the entire extraction time.
The static mode of extraction is limited in its solubility capability. As time increases, an
equilibrium is established between the analytes in the supercritical fluid and analytes in
the matrix. If solubility is not favourable in the supercritical fluid, exhaustive extraction
may not occur. Static extraction is often followed by a short period of dynamic
extraction to help overcome this problem.
During dynamic extraction, the dissolved analytes are constantly removed from the
matrix so analyte-matrix interactions are limited. This is generally the preferred mode of
extraction and is used for 90% of all reported applications of SFE 109.
One drawback of dynamic extraction is that it uses far more extraction fluid than static
extraction. During long periods of dynamic extraction, problems maybe encountered if
the supercritical fluid is impure. The contaminants will ultimately concentrate in the
collection device and interfere in the analysis of the extracts. This poses a particular
problem in the trace analysis of environmental samples.
37
1.4.1.4. Flow Rate
As discussed above, flow rate is only applicable in the dynamic mode of extraction.
Flow rates are limited by the capability of the pump but generally fall in the range of 0.5
mL/min to 4 mL/min for analytical applications. Faster flow rates allow for more
extraction fluid to pass through the cell per unit time, and typically, results in shorter
extraction times. Higher flow rates however, make trapping more difficult for the more
volatile compounds. This is because a greater flow rate will produce a greater expansion
once depressurised, which propels the analytes from the restrictor at greater velocities.
The lighter the compound, the more difficult it is to precipitate in the collection device
since it is able to escape with the depressurised high velocity extraction fluid. This will
be discussed in Section 1.4.3.
1.4.1.5. Extraction Time
The extraction time is dependent on sample size, density and flow rate. The larger the
sample size, and the lower the density and flow rate, the longer the extraction time will
be. When optimising SFE, the time taken to completely extract the components of
sample must be determined. This enables extraction and collection parameters to be
examined.
1.4.1.6. Particle Size
Increased permeation of the extraction fluid into the matrix increases the rate of
extraction. Therefore, for a solid sample, the extraction rate increases with a higher
surface area and smaller particle size. The greater surface area allows the extraction
fluid to permeate the matrix more efficiently and the smaller particle size leads to
38
shorter internal diffusion pathlengths over which the extraction fluid must travel to
reach the solutes.
For solid samples, where analyte extraction is restricted by diffusion through the matrix,
grinding can be used to obtain smaller particle sizes. Grinding is usually performed in a
blender followed by mechanical sieving to achieve the desired particle-size or particle
size range. Due to its importance in SFE, numerous studies have reported the effect of
particle size on extraction110"113. Studies on rosemary have shown that reducing the
particle size accelerated extraction, improved extraction efficiency and shortened
extraction time 114. Extraction was complete within 20 mins with particle sizes below
500 um, whereas for unground samples extraction was incomplete after 60 min.
The heat generated by reducing the particle size can lead to loss of the more volatile
components of the sample 114"116. To overcome this problem, cryogenic grinding can be
employed. This involves grinding in the presence of dry ice or liquid nitrogen.
Cryogenic grinding can also help in sample preparation of natural products. When plant
material is ground, cellular membranes are disrupted and this may release certain
enzymes which can decompose the components of interest114. Cryogenic grinding
inactivates these enzymes and prevents enzymatic degradation.
Problems can be encountered if the particle size is too small. Particle sizes of below 50
um should be avoided because they may become compacted in the extraction vessel
which can lead to channelling of the extraction fluid 117. This is where the supercritical
fluid passes through the small channels in the matrix leading to inefficient contact
between the supercritical fluid and parts of the sample matrix.
39
1.4.2. Collection Conditions
The collection of extracted analytes in SFE must involve quantitative transfer of the
extracted analytes from the extraction vessel to a collection device, and quantitative
collection of the analytes in a collection device. In developing an SFE method,
collection conditions must be addressed before extraction conditions, otherwise poor
recoveries may be falsely attributed to extraction conditions.
As previously discussed, the effect of the matrix can have a significant effect on the
extractability of certain compounds. To optimise the collection conditions it is important
to eliminate the effect of the sample matrix. This is usually achieved by spiking a small
amount of a standard mixture into the extraction vessel on an inert matrix. Recoveries of
compounds in the standard mixture are measured to determine if 100% of the extracted
components have been collected, indicating quantitative collection. Once this has been
determined, real samples can be extracted and the effectiveness of the extraction
conditions and matrix effects evaluated.
The collection device is situated directly after the restrictor (Section 1.3.2.3). Collection
of the extracted analytes is achieved after depressurisation of the extraction fluid to
ambient conditions. A liquid C02 flow rate of 1 mL/min equates to a gaseous C02 flow
rate of approximately 500 mL/min. Trapping of the analytes from a such a high flow
rate can prove extremely difficult, particularly for volatile analytes. There are three
common collection devices used for trapping in SFE; liquid solvent traps, inert solid bed
traps, and active solid bed traps.
40
Liquid Solvent Trapping
Liquid solvent trapping 118"121 is depicted in Figure 1.8. A narrow bore tube from the
restrictor is immersed into a liquid solvent (5-20mL) within a small container. The
depressurising extraction fluid bubbles through the solvent and vents to the atmosphere
leaving behind the analyte dissolved in the liquid solvent. The liquid solvent is often
cooled to aid in the collection of the volatile analytes. The most important parameter in
this type of trapping is the choice of solvent. It must solubilise the target analytes and
should be compatible with the analysis technique.
Heated Restrictor
Pressure Release
Transfer Tube •
Collection Solvent o
o Oo
,o &
Figure 1.8. Liquid solvent SFE trapping device
Solid Bed Traps
In solid bed trapping 119'122-1245 the depressurised extraction fluid flows through a packed
trap containing a solid support onto which the analytes adsorb (Figure 1.9). The solid
support within the trap baffles the expanding flow to aid in the precipitation of solute
molecules while allowing the expanding solvent gas to escape. The trap is often
cryogenically cooled to prevent the escape of volatile components from the trap. The
solid support consists of particles ranging from 30-100 urn in diameter. There are two
41
types of solid supports used in solid bed trapping; inert and active. An inert support,
such as silanised glass or stainless steel beads, exhibits no functionality. Active supports
comprise a chromatographic stationary phase where adsorption of the analytes on the
solid support is enhanced through interactions with the stationary phase. Commonly
used active supports include silica based supports such as octadecylsilica (ODS), cyano,
diol and amino.
Heated Restrictor ^_
Solid Bed Trap^^^ L_
Frit
To waste *-
(a) (b)
Figure 1.9. (a) Solid bed trapping device (b) cross section of solid bed trap showing the solid bed packing
Once the analytes have been collected on the solid support in the trap, they are eluted
from the adsorbent with a small volume of solvent (l-3mL). A solvent that exhibits a
high solvating power for the analytes is chosen. Alternatively the trap can be heated
during the desorption process to increase the amount of solute dissolved.
For successful collection of the analytes, both the adsorption and desorption of the
collection processes should be quantitative. There are several important parameters to
consider when optimising these processes.
Solid Bed Packing
42
1.4.3. Adsorption
Trapping material functionality, trap temperature, and extraction fluid flow rate can all
influence the adsorption process. The effect of each of these parameters is discussed
below.
1.4.3.1. Trapping Material
The trapping of compounds on solid bed traps can occur through two mechanisms;
physical trapping (often called cryotrapping) and/or chemical trapping. Trapping on
inert solid bed traps can only occur through cryotrapping since the trapping material
possesses no functionality. Active solid bed traps have the advantage that one or both
mechanisms can be used in the trapping process. The differences between inert and
active sorbent trapping mechanisms are evident in P A H extraction. The recoveries of
various P A H s were determined by collecting spiked P A H s onto cryogenically cooled
stamless steel and O D S . All P A H s were trapped quantitatively on the O D S trap,
however on the stainless steel trap the more volatile bi- and tricyclic P A H s were lost.
The retentive nature of the O D S was sufficient to prevent the compounds passing
through the trap with the gaseous extraction fluid.
The effect of the polarity of active solid supports has been studied in detail
118,119,122,124,126,127 p Q r increase(j interactions between the support and compounds, the
polarity of the trapping material must match that of the target compounds. This is
particularly important if the compounds cannot be trapped cryogenically. For example,
for a mixture of hydrocarbons (CIO to C32), the recoveries on the polar traps (cyano,
silica, diol, and amino) were lower than those on non-polar traps (C8 and O D S ) . The
effect of the trapping material is clearly evident in the trapping of the lower molecular
43
weight hydrocarbons. The polar traps yielded recoveries of < 8 0 % for CIO and CI2
hydrocarbons, whereas 1 0 0 % recovery was achieved with non-polar traps.
1.4.3.2. Trap Temperature
Cryogenic trapping is extremely important in solid support trapping, in particular when
using an inert solid support. Obviously, the more volatile the compound, the lower the
trap temperature required. At a trap temperature of-25°C, hydrocarbons below CI 1 are
not trapped on glass beads. If the temperature is lowered to -65°C, 9 5 % of CI 1
hydrocarbons can be trapped 128. L o w temperatures and the appropriate choice of active
solid support can result in increased recovery.
1.4.3.3. Extraction Fluid Flow Rate
In dynamic SFE, the extraction fluid flow rate dictates the flow of expanding gas from
the restrictor. If the velocity of the expanding gas is too great, the analytes have less
time to interact with the solid support, resulting in low recoveries. Again, this is mainly
a problem with more volatile compounds. Extraction fluid flow rates can generally be
higher with active solid supports (1-4 mL/min) than with inert solid supports due to the
multiple trapping mechanisms 129.
1.4.4. Desorption
During the desorption step, the analytes collected on the trap are eluted from the trap by
a rinse solvent. Parameters such as choice of rinse solvent, solvent flow rate, and trap
temperature can influence recovery. The effect of each of these parameters is discussed
below.
44
1.4.4.1. Rinse Solvent
The choice of rinse solvent in the desorption process depends on several considerations
130.
• The solubility of the analyte(s) in the rinse solvent;
• Compatibility of the rinse solvent for subsequent analysis or processing;
• Solvent power required to desorb the analytes from the trap packing material.
During inert solid support trapping only the first two points need be considered and
quantitative recovery is dependent on choosing an appropriate solvent. The third point
must be carefully considered when using an active solid support, since the sorbent has
the ability to retain the analytes from the trap. Selection of a rinse solvent is guided by
the same considerations involved in the selection of an appropriate elution solvent in
liquid chromatography (LC). Non-polar solvents can be used to elute analytes from a
non-polar support. As the polarity of the support increases, the polarity of the rinse
solvent must also increase since the trapped compounds will have a greater affinity for
more polar solvents. By using two rinse solvents of different polarity, fractions
containing different classes of compounds may be obtained. This aspect of selective
1 90
elution has not been extensively studied
1.4.4.2. Solvent Flow Rate
The solvent flow rate generally has an influence on the volume of solvent required to
rinse the analytes from the trap. As mentioned above, the trap acts as a LC column
during desorption. The flow rate will affect the zone broadening of the analytes as they
elute from the trap. The lower the flow rate, the lower the zone broadening, hence
minimising the volume of solvent used. Lower flow rates however increase the time
45
required to elute the analytes from the trap. Selecting the appropriate solvent flow rate
requires a balance between the volume of solvent used and time.
1.4.4.3. Trap Temperature
Depending on the application, the temperature of the rinse solvent may be varied during
the desorption process. For difficult to dissolve analytes, higher temperatures may be
required for increased solubility. Conversely, for thermally labile compounds lower trap
temperatures may be desirable.
During desorption, the temperature of the restrictor and trap should be 5-10°C lower
than the boiling point of the rinse solvent, otherwise vaporisation of the solvent occurs.
Furthermore, the temperature must also be above the melting point of the rinse solvent
to prevent freezing.
Liquid Trapping vs Solid Support Trapping
Liquid and solid support traps vary considerably in their trapping mechanisms and each
possesses various advantages and disadvantages. Liquid traps do not have the ability to
baffle the expanding extraction fluid from the restrictor. Thus, high flow rates cannot be
used as excessive bubbling will occur and the more volatile analytes will be lost. Studies
have shown that higher recoveries are obtained using solid bed traps over liquid traps
124,127
Another disadvantage of liquid trapping involves the Joule-Thomson cooling associated
with the depressurising of the extraction fluid that leads to low temperatures in the
46
collection vessel. Because the restrictor is often immersed in the solvent, freezing can
occur and small pieces of ice may clog the restrictor if it is not heated.
One major advantage of solid bed trapping is its ease of automation. Samples can
continually be extracted without the need to replace the trap, providing all the analytes
had been completely removed from the trap by the previous desorption process. An
aggressive solvent is quite commonly used after collection of the sample is complete to
ensure no analytes remain on the trap.
1.5. Extraction of Essential Oils
Since many fragrance and flavour compounds are sensitive to acids, the composition
and quality of the oil is dependant on the extraction procedure. The common methods
for the extraction of essential oils are considered below.
1.5.1. Steam and Hydrodistillation of Essential Oils
Essential oils have traditionally been extracted by steam distillation. This method
consists of passing steam through the plant material held in a suitable container
equipped with a condenser. The heat of the steam causes the volatile oils to expand,
thereby bursting open the cells containing the oil. The volatile oil and the water vapour
pass into the condenser where they return to the liquid state. The oil and water have
different densities and form two distinct layers that can be separated. In general, the
essential oil fraction is less dense than water unless it contains a significant proportion
of aromatic compounds.
47
Hydrodistillation is a similar technique in which the plant material is immersed in a
suitable quantity of water and the mixture boiled.
In both of these extraction techniques, high temperatures (~100°C) are involved. These
temperatures can often result in modifications of the original constituents in the oil by
heat-induced reactions and loss of volatile compounds can occur. The odour of the
steam distilled extract can therefore vary considerably from that of the fresh plant
material. Studies have been performed comparing the composition of the headspace
over fresh herbs to that of the essential oil recovered by steam distillation 131. It was
found that the headspace sample contained numerous compounds which make a
significant contribution to the aroma of the herb that were absent from the steam
distilled oil.
A number of studies have compared the composition of essential oils recovered by
steam, hydrodistillation and SFE 90>91>132-135. The extraction temperature used in SFE is
considerably lower since the critical temperature for CO2 is 31.3 °C. Modification of
the oils during extraction is therefore much less likely, and the odour of the SFE extracts
is thought to more closely resemble that of the natural material. Moyler136 extracted the
oil from clove buds using steam distillation and liquid C02 extraction. It was shown that
prolonged distillation caused hydrolysis of eugenyl acetate to eugenol and acetic acid.
The odour of the liquid C02 extract was sweeter, less medicinal and slightly floral and
resembled more closely the aroma of the natural clove bud than the steam distilled
extract. The liquid C02 extract had a much higher level of eugenyl acetate which was
responsible for the more floral odour. The liquid C02 extract was steam distilled and the
oil collected had a lower content of eugenyl acetate than the starting material. Traces of
48
acetic acid could be detected in the water distillate serving as evidence that degradation
was occurring during steam distillation.
Similar studies on rosemary have shown that the hydrodistilled extract contained a
higher proportion of monoterpene hydrocarbons which contribute minimally to the
aroma of the oil137. In contrast, the SFE extract contained a higher percentage of
oxygenated monoterpenes that strongly contribute to the fragrance of the oil.
Organoleptic tests were performed by a standard testing panel which judged the SFE oil
to have a strong fragrance of rosemary leaves while the hydrodistilled oil possessed a
less intense aroma considered to be slightly different from the starting material.
The composition of oils extracted by steam/hydrodistillation and SFE has also been
shown to differ for reasons other than thermal degradation. Since steam and
hydrodistillation require volatilisation of the components, collection of these
compounds require condensation. If the compound is too volatile to be condensed it may
escape through the condenser and avoid collection. This results in the loss of the top
notes of the fragrance. O n the other hand, if the compound has a low vapour pressure,
volatilisation m a y not take place, and the compound will not be found in the extract.
This typically can be detected by a loss of back notes in the fragrance.
Moyler 138 has shown that a liquid C02 extract of ginger contained the volatile
component hexan-1-al in the oil, which is completely absent from the steam distilled oil
due to its volatility. It was found that an extra 3 % of these top notes where present in
the C 0 2 extract. This extract was also found to contain more of the higher molecular
weight components (eg gingerols) which have lower vapour pressures. Since these
49
compounds are less volatile, they are only marginally responsible for the odour of the
oil, however they do posses fixative properties.
Apart from temperature effects in steam- and hydrodistillation, the pH of the liquid
phase can cause acid catalysed reactions. Most plant material in the presence of water
develops a pH between 4 and 7, and for fruits the pH may be lower139, Evidence for
these acid catalysed reactions was obtained in a study involving steam distillation of
Juniperus sabina at various pH values (2.2 to 8) 140. As the pH of the distillation water
was lowered, the concentration of sabinene decreased with concomitant increases in the
levels of its decomposition products (Figure 1.10).
sabinene
H7H20
1
^y
cc-terpinene y-terpinene terpinolene terpinen-4-ol
Figure 1.10. Conversion of sabinene in acidic conditions 140
The advantages of steam/hydrodistillation are mainly apparent on a commercial scale
because of the simplicity and low cost of design compared to SFE.
50
1.5.2. Solvent Extraction of Essential Oils
Solvent extraction employs the use of an organic solvent, or a mixture of organic
solvents, to extract the oil from plant material. The solvent used depends on the
solubility of the oils in the solvent. The plant material can be soaked in the organic
solvent at ambient temperatures, or extracted by boiling solvent in a Soxhlet-type
apparatus. Solvent extraction assisted by ultrasound, also known as sonication, is
another variation on this technique.
To recover the oils, the solvent must be removed by evaporation, which is achieved by
heating, usually under high vacuum, co distillation, or nitrogen sparging. If heat and
high vacuums are used to remove the solvent, components of the oil with a boiling point
similar to the solvent may also be removed, resulting in the loss of the more volatile
compounds.
Solvent extraction involves lower temperatures than those used in steam distillation.
Removal of the solvent can be achieved at <70 °C and modification of the composition
through heat and acid catalysed reactions is minimised.
One of the shortcomings of solvent extraction is that the organic solvents have low
selectivity. Thus, apart from the desired volatile compounds, high molecular weight,
non-volatile compounds, such as fatty oils, resins, waxes and colouring matters, are co-
extracted. This m a y lead to visually unattractive oils due to their viscous nature and dark
colouring even though oil yields are higher than those obtained by other extraction
techniques. Also, the extract may require a further clean up before analysis due to these
unwanted extracted compounds.
51
Hexane extraction of grape seed oil resulted in a yield (7.5%) comparable to that
obtained by SFE (6.9%) U1. The greater yield obtained from the solvent extraction
method was shown to be due to the presence of a higher free fatty acid concentration
and an unsaponifiable fraction due to the non-selective nature of the solvent. The
reduced high molecular weight compounds in the SFE extract simplifies the analytical
process and prolongs the GC capillary column lifetime, without affecting the aroma of
the oil.
1.5.3. Other Extraction Techniques
Less traditional methods of extraction of essential oils include:
a) Accelerated solvent extraction (ASE) which is a form of high pressure solvent
extraction used to shorten the extraction time.
b) Cold pressing in which the oils are crushed from the plant material.
c) Microwave assisted processes (MAP) in which liquid- phase or gas-phase extractions
can be performed.
1.5.4. SFE for the Extraction of Essential Oils
One of the major advantages of SFE (C02) in the recovery of essential oil relates to the
selectivity of the extraction process. Low molecular weight oxygenated compounds that
are responsible for the odour of the oil are readily soluble in the extraction fluid,
whereas the high molecular weight polar compounds are practically insoluble. It is this
selectivity that makes supercritical C02 an attractive solvent for the recovery of essential
oils. The oils obtained contain more top notes resulting from the low molecular weight
compounds that are usually lost in traditional extraction techniques. The oils also
contain a small amount of high molecular weight compounds which, although not
52
making any contribution to the fragrance, are able to act as natural fixatives and help
stabilise the oil. A list of the solubilities in C02 of classes of compounds pertaining to
natural products is shown in Table 1.7.
Very Soluble
Non-polar and slightly polar organic compounds of low molecular weight < 250
Examples include mono and
sesquiterpenes
Thiols, pyrazines and thiazoles Acetic acid, benzaldehyde, hexanol, glycerol, acetates
Sparingly Soluble Almost Insoluble
Organic compounds with higher molecular weights (up to ~ 400)
Examples include substituted
terpenes and sesquiterpenes, water, oleic acid, decanol and saturated lipids up to C12
Sugars, protein
Tannins, waxes, inorganic salts Chlorophyll, carotenoids, citric and malic acids Glycine, nitrates and many components in pesticides and insecticides
Table 1.7. Relative solubility in C 0 2 of classes of compounds typically found in plant material 142
The high diffusivity of supercritical fluids is utilised in the extraction of essential oils.
Most plant material contains the oil within cellular structures. Because of the high
diffusivity, supercritical C02 as a solvent is able to penetrate the plant material and
dissolve the essential oil more readily than in traditional methods of extraction, leading
to much shorter extraction times.
The low temperatures used with SFE, discussed previously in Section 1.4.1.2, produce
an oil with an odour that more closely resembles that of the natural plant material.
SFE does not pose the many environmental and safety concerns that surround other
extraction techniques, relating to both the consumers and producers. Since the extraction
fluid is a gas, the final product contains no solvent residue. Although C02 is a major
contributor to the greenhouse effect, any increase in the amount of C02 arising from
industrial operations would be negligible 143. C02 also has much less of an effect
53
on the environment than many traditional solvents used in large quantities in solvent
extraction.
Analytical scale SFE has the potential to be completely automated. Many of the
commercial instruments are capable of extracting numerous samples per batch,
minimising time and labour. SFE can also be directly coupled to a chromatographic
system for analysis, termed on-line S F E 126>144>145. This has the advantage of eliminating
sample handling and the possibility of sample loss and contamination, and decreases the
overall analysis time.
Because of the high pressure associated with SFE, the initial cost of equipment is high.
However, it has been found that the energy associated with the normal heat requirements
for distillation and evaporation of organic solvents is greater than that associated with
the running cost of SFE 146. This decreased cost, coupled with a fully automated system,
could produce considerable savings compared to other traditional extraction techniques.
1.5.4.1. Applications of C 0 2 S F E to Natural Products
SFE has been traditionally used for the preparative-scale isolation of compounds from
plant matrices, eg. the decaffeination of coffee, and extraction of hops and tobacco
150
In more recent times the trend has been toward analytical-scale SFE and its use as a
sample preparation method prior to analysis. Numerous essential oils have been
extracted using SFE 90'104>135>138>151-155. The extracts obtained require little clean up, so
54
analysis can be performed directly after extraction. The fast sample turnaround makes
SFE an ideal technique for the screening of components in many natural products when
combined with the appropriate analytical technique.
1.6. Analysis of Essential Oils
The analysis of essential oils primarily involves the separation and identification of their
components. This requires the use of chromatographic and spectroscopic techniques.
The advent of new analytical methods combined with the development of computers has
dramatically improved the methods of analysis over the past 50 years. These methods
are discussed below.
1.6.1. Gas Chromatography
The most important development in the field of essential oils analysis came in 1952
with the introduction of gas chromatography (GC). The transition from packed column
GC to capillary GC in 1957 increased the popularity of the technique. In more recent
times, companies have manufactured specific columns for essential oil applications.
These columns contain a polar stationary phase (polyethylene glycol) which is able to
interact with the oxygenated compounds in the oil.
GC is ideally suited for the analysis of essential oils due to the volatility of their
components. Compounds are separated according to their boiling point and affinity for
the stationary phase. The separated compounds are usually detected by a flame
ionisation detector (FID). Although FID provides high sensitivity, it does not provide
structural information. If structural identification of the separated components is
55
required GC can be coupled to mass spectrometry (GC-MS) 156,157 or Fourier transform
infrared spectroscopy (GC-FT-IR)158'159.
Other techniques such as headspace analysis and solid phase micro-extraction (SPME)
can be used to analyse the aroma of essential oils. These techniques isolate the
volatile components, which can then be analysed by GC or GC-MS with no sample
preparation required.
1.6.2. Liquid Chromatography
Liquid chromatography (LC) is used as a method of analysis when the essential oil
contains compounds that are not easily volatilised. LC is often used to analyse essential
oils extracted by solvent extraction since this extraction technique removes the higher
molecular weight components of the oil such as oleoresins. LC can be coupled to a
number of spectroscopic techniques such as ultraviolet (UV), FT-IR, MS and NMR for
detection and structural identification 161,1 2.
1.6.3. Supercritical Fluid Chromatography
Supercritical fluid chromatography (SFC) is a hybrid analytical technique between GC
and LC, in which the mobile phase is a supercritical fluid. Therefore SFC offers
chromatographic parameters between both techniques such as liquid solvating power but
with much higher resolving power than HPLC. However SFC is often not favoured as a
routine method of analysis as method development often proves more difficult. SFC
instrumentation is similar to that of LC, and separation can be performed on both
capillary and packed columns. The advantage of SFC is that it can be used to analyse a
wide range of compounds due to its hybrid chromatographic parameters. Currently the
56
major application of SFC is the separation of chiral compounds. Detection and structural
identification in SFC can be achieved with both liquid and gas phase detectors 163~165.
57
1 -7. Aims of Project
The aim of the project was to conduct a field study on Western Australian sandalwood
examining variations in the quantity and quality of the oil from trees at different
geographic locations, at different seasons and from various sections of the tree. The
results provide valuable information for the management and utilisation of S. spicatum.
To this end, the development of a fast, automated SFE method for extracting the large
number of samples was required. Optimisation of the method would involve the
examination of the effect of various extraction conditions (density and particle size), and
collection conditions for solid bed trapping (trapping material, flow rate, trap
temperature, rinse solvent, rinse temperature and rinse volume).
The effectiveness of SFE as an extraction technique was also investigated by
comparison with the traditional extraction methods of hydrodistillation and solvent
extraction.
58
2. Experimental
2.1. Equipment
Supercritical Fluid Extraction
Extractions were performed using a Hewlett- Packard 7680T supercritical fluid
extraction module. The SFE module was controlled through the SFE HP Chemstation
software (REV. A.04.04). The extraction fluid used was N45 Grade C02 (Air Liquide)
and Food Grade C02 (Air Liquide) was used for cryogenic cooling.
Gas Chromatography
Analysis was performed using a Hewlett- Packard 5890 Series II Gas Chromatograph
equipped with a flame ionisation detector (FID). The GC consisted of a HP 7673
autosampler, split/splitless inlet, and electronic pressure control (EPC) of the carrier and
detector gases. The carrier gas used was UHP He (Air Liquide) and the detector gases
were HP H2, HP N2 and Medical Air (Air Liquide).
Gas Chromatography/Mass Spectrometry
Analysis was performed using a Hewlett-Packard 5890 Series II Gas Chromatograph
equipped with a Hewlett-Packard 5972 Mass Selective Detector. The GC consisted of a
HP 7673 autosampler, split/splitless inlet, and electronic pressure control (EPC) of the
carrier gas (UHP He, Air Liquide). Identification of unknown compounds were
determined by library searches using the NIST/EPA/NIH Mass Spectral Library (NIST
•98).
59
Solvents
Reagent grade ethanol was dried by refluxing the ethanol over magnesium for a
minimum of 24 hours and then distilled. All other solvents were HPLC grade (Table
2.1).
Rinse Solvent Supplier Hexane Iso-octane Methyl-tert-butyl Ether (MTBE) Ethyl Acetate
Mallinckrodt Mallinckrodt
Fluka Mallinckrodt
Table 2.1. H P L C grade solvents used as rinse solvents for SFE
2.2. Optimisation of Trapping Conditions
2.2.1. Materials
Standard Mixture
The percentage recovery was determined by using a standard mixture (Section 2.2.3.2).
The components of the mixture are listed in Table 2.2 and their structures shown in
Figure 2.1.
Compound Supplier
Limonene Cineole Citronellal Nerol (3- Ionone trans, trans- Farnesol a- and 0- Santalol Manool
Sigma-Aldrich Fluka Fluka
Sigma-Aldrich BDH
Sigma-Aldrich Dragoco B D H
Table 2.2. Compounds used in the standard mixture
60
P- ionone
CH2OH
"OH
Citronellal Nerol
a- santalol
trans, trans- farnesol
CH2OH
P- santalol Manool
Figure 2.1. Structure of compounds used in the standard mixture
Internal Standard
AR grade octan-1-ol (Sigma-Aldrich) was used as an internal standard (IS). The IS was
diluted 1:20 with ethanol for use.
2.2.2. Time Course Extraction of Standard Mixture
2.2.2.1. Preparation of Extraction Thimbles
A 80 u L aliquot of the standard mixture (Section 2.2.1) was pipetted into a 7 m L
extraction thimble containing 1 cm of filterflocs (Machery Nagel). A further 1 cm of
filterflocs was placed into the thimble and sealed with caps at both ends.
61
2.2.2.2. Exhaustive Extraction
The prepared thimbles were extracted using the conditions set out in Table 2.3. The time
taken at each density (0.25, 0.65 and 0.95 g/mL) to completely extract the spiked sample
from the thimble was determined by using stepwise extractions over a total time of 120
minutes. Samples were collected after 10, 20, 30, 50, 70, 90 and 120 minutes in 1.5 mL
vials containing 20 pL of IS. Extraction was considered complete when no response was
detected on GC analysis.
Extraction Conditions
Density (g/mL) Pressure (bar) Extraction Temperature (°C) Flow Rate (mL/min) Equilibration Time (min) Extraction Time (min) Nozzle Temperature (°C)
0.30, 0.65, & 0.90 81,104, & 281 40 1.0 0 Up to 120 45
Trap Conditions
Nozzle Temperature (°C) 45
Trap Packing ODS Trap Temperature (°C) 20 Trap Rinsing Temperature (°C) 40 Trap Rinse Solvent Ethanol Trap Rinse Volume (mL) L5
Table 23. Extraction and trapping conditions for exhaustive extraction of the standard mixture
2.2.2.3. G C Analysis
The concentrated samples were diluted with ethanol to provide an appropriate response.
1 uL of sample was injected into the GC and analysed by the method shown in Table
2.4. The amount of each compound extracted was measured as peak area and the octanol
IS used to normalise the peak areas to adjust for small discrepancies in rinse and
injection volumes.
62
Conditions
Column HP- Innowax (30m x 0.25 m m x 0.25 um)
Injection Mode Splitless Constant Flow Rate (mL/min) 1.2 Injection Temperature (°C) 250 Detector Temperature (°C) 250
Temperature Program
Initial 50°Caforl5min R a m p Rate 1 50-220 °C at 20 °C/min Final Hold 220 °C for 10 min
Table 2.4. GC conditions for the analysis of the standard mixture
Wh e n hexane and M T B E were used as solvents the initial temperature was decreased to 35°C to achieve complete separation of limonene and cineole
2.2.3. Trapping Conditions
2.2.3.1. Materials
Trap Packing
Six types of solid sorbent trapping materials with various functionalities were examined.
The specifications of each of the solid sorbents used are shown in Table 2.5.
Trapping
Material
Stainless Steel
ODS C18 Cyano Silica
Diol
Supplier
Hypersil
Isolute Isolute
Isolute Isolute
Particle Size
(p.m)
30 30 62 61 57 65
Pore Size
(A)
n/a 120 54 54 56 54
Surface Area
(m2/g)
n/a 175 561 561 n/a 561
Carbon
Loading
(%)
n/a 9-10
19.3
8.5 n/a 6.8
Table 2.5. Specifications of trapping materials (n/a= not applicable)
Packing of Traps
The traps were packed with the aid of a purposely designed funnel which was screwed
into the top of the trap. The solid sorbent was passed through the funnel into the trap.
The trap was vibrated to ensure uniform packing. Once the trap was full, the funnel was
removed and the trap vibrated further. A stainless steel frit contained within a Teflon
63
ring was placed in the top of the trap positioned by screwing in a trap plug. The trap was
then connected to the SFE module and rinsed with approximately 20 m L of solvent and
the void volume measured before use.
2.2.3.2. Effect of Collection and Extraction Conditions on Recovery
The effects of various trapping and extraction conditions on the recovery of the
components of the standard mixture were examined. The recovery of the components
was calculated using the peak areas of the components of the extracted standard mixture
compared to a control representing 1 0 0 % recovery. The control was prepared by
pippetting 80 uL of the standard mixture directly into a vial containing 20 uL of IS, to
which 1.4 m L of solvent was added. The IS was used to normalise the peak areas to
account for small discrepancies in rinse and injection volumes. All extracts were
analysed by G C using the method in Table 2.4.
Effect of Trapping Material
The extraction thimbles were prepared with the standard mixture as described in Section
2.2.2.1. Extractions of the standard mixture were performed in triplicate for each of the
six solid sorbents as trapping materials using the conditions shown in Table 2.6.
64
Extraction Conditions
Density (g/mL) Pressure (bar) Extraction Temperature (°C) Flow Rate (mL/min) Equilibration Time (min) Extraction Time (min) Nozzle Temperature (°C)
Trap Conditions
Nozzle Temperature (°C) Trap Packing
Trap Temperature (°C)
Trap Rinsing Temperature (°C) Trap Rinse Solvent Trap Rinse Volume (mL)
0.65
104 40 1.0(0.5, 1.0 & 2.0) 0 30 45
-
45 As shown in Table 2.5 20 (0,20 & 40) 40 (20,40 & 60) Ethanol
1.5
Table 2.6. Extraction and trapping conditions used to examine the effect of trapping material
Effect of Trap Temperature
Trap temperatures of 0°, 20° and 40°C for each type of trapping material were examined
using the conditions shown in Table 2.6.
Effect of C02 Flow Rate
Flow rates of 0.5, 1.0 and 2.0 mL/min for each type of trapping material were examined
using the conditions shown in Table 2.6.
Effect of Rinse Solvents
The efficiency of five different rinse solvents of various polarity to reconstitute the
adsorbed compounds from the six different types of trapping materials was examined.
The five rinse solvents used were hexane, iso-octane, methyl-tert-butyl ether (MTBE),
ethyl acetate and ethanol, as in Section 2.1 and Table 2.1.
The standard mixture was extracted using the extraction conditions described in Table
2.6. The trap conditions, however, varied slightly in that the six trapping materials used
65
were each rinsed with ethanol, hexane, iso-octane, M T B E , and ethyl acetate. To
determine whether the adsorbed components were being completely removed from the
trap by the first 1.5 m L rinse volume, a further three 1.5 m L rinses were collected in
separate vials.
Effect of Rinse Temperature
Rinse temperatures of 20°, 40° and 60°C for each type of trapping material were
examined using the conditions shown in Table 2.6.
2.2.4. Hydrodistillation of Standard
The standard mixture (250 uL) was placed into a 100 m L round bottomed flask attached
with a condenser, and hydrodistilled for 24 hours in 50 m L of distilled water. The
distillate was extracted with M T B E (3 x 50 m L ) and dried (MgS04). The solvent was
removed under a stream of nitrogen until 25 m L of solvent remained. The remaining
M T B E was left to evaporate under ambient conditions to afford the hydrodistilled
standard mixture. A volume of the standard mixture (80 uL) was transferred to a vial
containing 20 uL of IS and analysed by G C (Table 2.4). The recoveries of the
individual components of the standard mixture were calculated as described in Section
2.2.3.2.
66
2.3. Optimisation of Sandalwood Extraction
2.3.1. Materials
Sandalwood
A piece of sandalwood buttwood, approximately 1 m long, was obtained from the
Department and Conservation and Land Management (CALM). The wood was reduced
to fine wood chips using a wood carving tool fitted to an angle grinder. The chips were
reduced to a powder in a stainless steel Waring commercial blender in the presence of
dry ice. The powdered wood was dried in a dessicator for 48 hours prior to extraction.
Preparation of Extraction Thimbles
7 mL extraction thimbles with a bottom cap in place were packed with 2 cm of
filterflocs (Machery- Nagel). The weight of the empty thimble and filterflocs was
weighed on a 5 point balance (Sartorius MC 1). Approximately 1 g of powdered
sandalwood was placed into the extraction thimble and weighed to determine the exact
mass of wood to be extracted. A further 2 cm of filterflocs was positioned on top of the
wood, and the top end cap sealed in place.
For all samples of sandalwood extracted, the percentage oil yield, percentage volatiles
and composition were measured. A description of how each of these parameters were
measured is outlined below.
67
2.3.2. Calculations of Percentage Yield, Volatiles and Composition
Measurement of Percentage Yield
Each extracted sample was collected in a pre-weighed 1.5 mL amber vial. The solvent
was left to evaporate under ambient conditions and placed in a dessicator to remove any
residual water. The vial containing the oil was reweighed to determine the amount of oil
extracted. The percentage yield of oil from dry wood was calculated using the following
equation:
% Yield = weight of oil extracted / weight of dry wood x 100%
Measurement of Volatiles
The volatile component was defined as the portion of the oil that eluted from the GC
column. The non-volatile material does not elute from the column and deposits on the
inlet liner or on the analytical column. The percentage of volatiles was calculated using
the IS. To estimate the percentage volatiles a number of assumptions were made. Firstly
it was assumed that the peak area response from octanol corresponds to the mass of
octanol added prior to analysis. The second assumption was that octanol has the same
FID response as the components of the sandalwood oil. If these assumptions hold true,
the mass of sandalwood oil eluting from the column (mass volatile oil) can be calculated
using the equation below. Even if the second assumption is not true, the error would be
consistent for all samples and allow direct comparisons to be made.
Mass octanol / Peak area of octanol = Mass volatile oil / Peak area of volatile oil
68
The mass of volatiles in the extracted total oil can be calculated knowing the dilution
factor, and if required the percentage of volatiles in the oil can also be calculated using
the equation below.
% Volatiles = Mass volatile oil/Mass total oil x 1 0 0 %
G C Analysis of Sandalwood Oil
1 uL of sample was injected into the GC and analysed by the method shown in Table
2.7.
Conditions
Column
Injection M o d e Constant Flow Rate (mL/min) Injection Temperature (°C) Detector Temperature (°C)
Initial R a m p Rate 1
Final Hold
HP- Innowax (30m x 0.25 m m x 0.25 um)
Splitless
1.3 250 250
Temperature Program
50°C 50to240atl5°C/min
240°Cforl0min
Table 2.7. G C conditions for the analysis of sandalwood oil
Compounds with a peak area of greater than 1 % of the total volatile oil components
eluting from the column were used to determine the chemical composition of the oil.
2.3.3. Exhaustive Extraction
The thimbles containing the ground sandalwood were extracted using the conditions set
out in Table 2.8. The time taken at each density (0.45, 0.55, 0.65, 0.75, 0.85, and 0.95
g/mL) to completely extract the oil from the sandalwood was determined by using
69
stepwise extractions over a total extraction time of 90 minutes. Samples were collected
after 10, 20, 30, 45, 60 and 90 minutes. All extractions were performed in triplicate.
Extraction Conditions
Density (g/mL)
Pressure (bar)
Extraction Temperature (°C) Flow Rate (mL/min)
Equilibration Time (min) Extraction Time (min)
Nozzle Temperature (°C)
0.45, 0.55, 0.65, 0.75, 0.85, & 0.95 89, 93, 104, 134, 211, 281, & 383 -40 1.0 0 Up to 90 45
Trap Conditions
Nozzle Temperature (°C) Trap Packing Trap Temperature (°C)
Trap Rinsing Temperature (°C) Trap Rinse Solvent Trap Rinse Volume (mL)
45 Isolute Diol 20 40 Ethanol
1.7
Table 2.8. Extraction and trapping conditions for exhaustive extraction of sandalwood oil
2.3.4. Effect of Density on Percentage Yield, Percentage Volatiles, and
Composition
The time taken to completely remove the volatile portion of the oil for each of the six
densities was used as the extraction time. Extractions at each density were conducted
using the conditions outlined in Table 2.9. The percentage yield, percentage of volatiles
and composition of the extract for each density were measured.
70
Extraction Conditions
Density (g/mL)
Pressure (bar)
Extraction Temperature (°C) Flow Rate (mL/min) Equilibration Time (min) Extraction Time (min) Nozzle Temperature (°C)
0.45
89
40 1.0 0 90 45
0.55
93
40 1.0 0 60 45
0.65
104
40 1.0 0 45 45.
0.75, 0.85
&0.95
134, 211, & 383 40 1.0 0 30 45
Trap Conditions
Nozzle Temperature (°C) 45 45 45 45 Trap Packing Isolute Diol Isolute Diol Isolute Diol Isolute Diol Trap Temperature (°C) 20 20 20 20
Trap Rinsing Temperature (°C) 40 40 40 40 Trap Rinse Solvent Ethanol Ethanol Ethanol Ethanol Trap Rinse Volume (mL) L5 L5 L5 1.5
Table 2.9. Extraction and trapping conditions used to completely extract the sandalwood oil from the matrix at various densities
2.3.5. Particle Size
Materials
Hammer-milled sandalwood powder was obtained from Mt Romance Pty. Ltd. via
Wescorp Sandalwood Pty. Ltd. The wood was dried in a dessicator for 48 hours prior to
extraction.
Preparation of Wood
Two studies, using different particle sizes were performed. In Study 1, the wood
extracted was of a particle size range, and in Study 2, the wood extracted fell below a
single particle size. The percentage yield, percentage volatiles and composition for each
extract were measured as described in Section 2.3.2.
Study 1
12 sieves of various mesh diameters were stacked vertically. The mesh sizes of the
sieves ranged from the largest at the top (1.7 mm) to smallest at the bottom (53 um). A
quantity of hammer-milled sandalwood was placed into the top sieve and the stack
shaken manually allowing the sandalwood to fall through the sieves. The sandalwood
particles collected in the sieve where the mesh size was smaller than the particle size of
the wood. The wood collected in each sieve represented a range in particle size between
the mesh size of the two sieves in which the powdered wood fell through and collected.
The ranges of particle sizes where the powdered wood was collected is shown in Table
2.10. The samples of wood of differing particle sizes were removed from the sieves and
stored in labelled glass jars.
Range of Particle Sizes Collected
Above 1700 1700-1400-1180-1000 850-710-600-500-355-250-180
•1400 •1180 •1000 -850 •710 •600 •500 •355 •250 •180 -53
(um)
Table 2.10. Range of particle sizes used in study 1
Study 2
Particle size experiments were performed in collecting 5 samples, which fell under only
one particle size. The 5 particle sizes used were <1700, <1400, <1000, <710, and <500
um. The hammer-milled sandalwood was placed on each of the sieves and the sieves
were shaken manually. The wood passing through the sieves were collected in a plastic
bucket and transferred to labelled glass jars.
72
Exhaustive Extraction
Prepared samples were extracted using the conditions illustrated in Table 2.11. The time
to completely extract the oil from the sandalwood for each particle size range was
determined by using stepwise extractions over a total extraction time of 60 minutes.
Samples were collected after 15, 30,45, and 60 minutes. The percentage yield,
composition and percentage of volatiles were measured as outlined in Section 2.3.2.
Extraction Conditions
Density (g/mL)
Pressure (bar)
Extraction Temperature (°C) Flow Rate (mL/min) Equilibration Time (min) Extraction Time (min) Nozzle Temperature (°C)
0.75 134 40 1.0 0 U p to 60
45
Trap Conditions
Nozzle Temperature (°C) Trap Packing Trap Temperature (°C) Trap Rinsing Temperature (°C)
Trap Rinse Solvent Trap Rinse Volume (mL)
45 Isolute Diol 20 40 Ethanol
1.7
Table 2.11. Extraction and trapping conditions for exhaustive extraction of sandalwood oil in the particle size studies
Effect of Particle Size on PercentageYield, Percentage Volatiles and Composition
The time taken to completely remove the volatile portion of the oil (Section 3.4) was
used as the extraction time. Extractions were carried out using the conditions in Table
2.11 with the extraction times for both study 1 and 2 given in Table 2.12.
73
Extraction Conditions Extraction Time (min) 90 60 45 Particle Size (um) Above 1700, 1180-1000, 600-500,500-Study 1 1700- 1400, 1000 - 850, 355,355 - 250,
1400-1180 850-710,710 250-180,180--600 53
Particle Size (um) < 1700 < 1400,1000, Study 2 710, & 500
Table 2.12. Extraction times required to completely extract the sandalwood oil from the matrix at various particle sizes
2.4. Large Scale Extraction
2.4.1. Materials
Sandalwood
Powdered sandalwood was obtained from Wescorp Sandalwood Pty. Ltd. The wood was
dried in a dessicator for 48 hours prior to extraction.
Preparation of Extraction Cell
A 300 mL high pressure gas cylinder (Whitey) was packed with 2 cm of filterflocs
(Machery- Nagel). The empty cylinder and filterflocs was weighed on a 2-point balance
(Satorius Basic). Approximately 100 g of powdered sandalwood was placed into the
cylinder and reweighed to determine the exact mass of wood to be extracted. Enough
filterflocs was positioned into the cylinder on top of the wood to prevent the movement
of particles out of the cylinder. The extraction cell was positioned inline by attaching a
V? NPT - 1/16" union to the cylinder and 1/16" stainless steel tubing in the flow path as
described below.
74
2.4.2. Instrument Modification
Figure 2.2 shows the modifications made to the SFE to permit scale-up of the extraction
process. The existing stainless steel fluid line was disconnected at both the union before
the chamber preheat unit, and at the three-way union prior to the high pressure isolation
valve. Approximately 5 m of 1/16" coiled stainless steel tubing was connected to the
union before the chamber pre-heat. A 300 m L high pressure gas sampling cylinder
(Whitey) was connected to the end of this tubing, and served as the extraction chamber.
Another section of stainless steel tubing was connected from the end of the 300 m L high
pressure gas sampling cylinder to the three-way union prior to the high pressure
isolation valve. The solid bed trap was removed and replaced by a piece of 1/8" stainless
steel tubing that was connected to a custom made stainless steel trapping device (Figure
2.3), capable of collecting large amounts of extracted oil. The trapping device was
immersed in an ice bath during extraction to aid in the precipitation of the extraction
analytes. The 300 m L extraction vessel was placed in a thermostated water bath. The 5
m of tubing connected to the extraction vessel was submerged in the water bath, and
acted as a preheat for the fluid before entering the extraction chamber. A standard 7 m L
metal thimble was left in the SFE sample carousel to allow for normal instrument
operation by triggering the appropriate sensors during an extraction.
The SFE was operated through the program Mod 1, which allowed manual control over
the operations of the SFE. The time taken to reach pressure using the 300 m L extraction
vessel exceeded the instruments shut off time warning of underpressure conditions.
Using M o d i the pressurisation process could be restarted until the desired pressure was
attained. Following depressurisation, there was no rinse step as the oil could be
collected directly from the tapered bottom of the custom made trap.
75
High Pressure Disconnected SFE Isolation Valve Tubing Tubing to Large-Scale Trap
1 /16" Stainless Coiled Tubing Steel Tubing y for Pre-heat
Thermostat and Stirrer
SFE Thimble Pre-heat Fluid Pump High Pressure 300 m L Extraction Cell On/Off Valves
Figure 2.2. Modification of the S F E apparatus to allow scale-up of the extraction vessel to 300 m L
Pressure Release
Top of Trap
Body of Trap
Tapered Bottom
1/16" Stainless Steel Tubing from SFE
A
* •
Extension of 1/16" Stainless Steel Tubing
Figure 23. Large-scale trapping device
76
Time Course and Percentage Yields
The prepared extraction cells were extracted using the conditions set out in Table 2.13.
The time taken at each density (0.45, 0.55, 0.65, 0.75, 0.85 and 0.95 g/mL) to
completely extract the sandalwood oil was determined by using stepwise extractions
over a total extraction time of 800 minutes. Samples were collected after 100, 200, 300,
400, 500 and 800 minutes in a pre-weighed custom made large scale trapping device.
The percentage yield was calculated for each density using the total amount of oil
extracted over the 800 minute period.
Extraction Conditions
Density (g/mL) 0.45, 0.55, 0.65, 0.75, 0.85 & 0.95
Pressure (bar) 89, 93, 104, 134,
211, 281, & 383 Extraction Temperature (°C) 40 Flow Rate (mL/min) 2.0 Equilibration Time (min) 0 Extraction Time (min) Up to 800 min
Nozzle Temperature (°C) 45
Trap Conditions
Nozzle Temperature (°C) 45 Trap Packing Trap Temperature (°C) 0-10°C Trap Rinsing Temperature (°C)
Trap Rinse Solvent
Trap Rinse Volume -
Table 2.13. Extraction and trapping conditions for the large-scale extraction of sandalwood (300mL)
2.5. Comparison of Extraction Techniques
2.5.1. Materials
The wood used for the comparison of the extraction techniques was from the same
source that was used for the particle size study in Section 2.3.5. The percentage yield,
77
percentage volatiles and composition for each extract was measured as described in
Section 2.3.2.
2.5.2. Methods
Hydrodistillation
Approximately 50 g of powdered sandalwood was placed into a modified Dean-Stark
apparatus and hydrodistilled for 24 hours in 500 m L of distilled water. The distillate was
extracted with M T B E (3 x 50 m L ) and dried (MgS04). The solvent was removed under
a stream of nitrogen until 25 m L of solvent remained. The remaining M T B E was left to
evaporate under ambient conditions to afford a pale yellow oil.
Ethanol Extraction
Approximately 50 g of powdered sandalwood was magnetically stirred for 24 hours in
ethanol (500 m L ) . The sandalwood powder was removed by vacuum filtration and
washed with ethanol (100 mL). The ethanol was removed under a stream of nitrogen
until 25 m L of solvent remained. The remaining ethanol was left to evaporate under
ambient conditions to afford a dark red-brown viscous oil.
Hexane Extraction
Approximately 50 g of powdered sandalwood was magnetically stirred for 24 hours in
hexane (500 m L ) . The sandalwood powder was removed by vacuum filtration and
washed with hexane (100 mL). The hexane was removed under a stream of nitrogen
until 25 m L of solvent remained. The remaining hexane was left to evaporate under
ambient conditions to afford a yellow oil.
78
SFE
Approximately 1 g of sandalwood oil was placed into extraction thimbles as described
in Section 2.3.1. The sandalwood was extracted under the optimised conditions set out
in Table 2.14.
Extraction Conditions
Density (g/mL) Pressure (bar)
Extraction Temperature (°C) Flow Rate (mL/min)
Equilibration Time (min) Extraction Time (min)
Nozzle Temperature (°C)
0.75 134 40 1.0 0 30 45
Trap Conditions
Nozzle Temperature (°C) Trap Packing
Trap Temperature (°C) Trap Rinsing Temperature (°C) Trap Rinse Solvent Trap Rinse Volume (mL)
45 Isolute Diol 20 40 Ethanol
1.7
Table 2.14. Optimised SFE conditions for the extraction of sandalwood oil
2.6. Sandalwood Survey
2.6.1. Geographic
2.6.1.1. Materials
Sandalwood Samples
Core samples were taken from the buttwood of living sandalwood trees 10 cm above
ground level. The outer bark of the tree was removed and samples were taken by drilling
through the tree with a Vz inch auger drill bit attached to a Tanaka (TED-262-L) two-
stroke fence post borer (Figure 2.4). The drill bit was rotated slowly during core
sampling to limit the heat generated and minimise volatilisation of components of the
oil within the wood. The sandalwood shavings were collected by holding a plastic zip
79
lock bag directly beneath the drill bits point of entry into the tree. To prevent infection in
the tree, a small branch of dead wood was positioned inside the hole, and sealed to the
atmosphere with Selleys polyfiller (Figure 2.5).
The diameter of the trees 15 cm above ground level was measured and the approximate
height and condition of the trees noted. The GPS of the trees were recorded using a
Magellan GPS 2000XL Satellite Navigator. The trees were tagged with aluminium tags
attached to copper wire for future reference.
Figure 2.4. Coring of sandalwood trees.
The shavings were collected and the oil extracted and analysed.
80
Figure 2.5. Drill hole filled with Selly polyfiller post-core sampling
Sample Preparation
The sandalwood shavings collected from core sampling in the field were brought back to
the laboratory for preparation before extraction. Any bark in the sample was removed.
The shavings were blended in a stainless steel Waring commercial blender in the presence
of solid carbon dioxide until a powder was attained. The powder was removed from the
blender and stored in labelled glass jars. The ground samples were dried for 48 hours in a
dessicator prior to extraction.
2.6.1.2. Methods
Extraction of Sandalwood
The sandalwood samples were placed in thimbles (Section 2.3.1) and extracted using the
SFE conditions shown in Table 2.14. Percentage yield, percentage of volatiles and
81
composition of the oil was determined as previously described (Section 2.3.2). Each
sample was extracted in triplicate.
G C Analysis of Sandalwood Oil
1 uL of sample was injected into the GC and analysed by the method shown in Table
2.15.
Conditions
Column
Injection Mode
Constant Flow Rate (mL/min)
Injection Temperature (°C) Detector Temperature (°C)
HP- Innowax (30m x 0.25 m m x 0.25 um) Splitless 1.3 250 250
Temperature Program
Initial
Ramp Rate 1 Ramp Rate 2 Final Hold
60°C for 5 mins 4°C/minfol65°C 7°C/minto240°C 10 mins
Table 2.15. G C conditions for the analysis of sandalwood oil to determine variation between trees
The chemical composition of the oil was calculated based on peak area. Only
compounds with a peak area of >1% were presented in the results. This GC analysis
method differs from the method used for the sandalwood optimisation (Table 2.7) in
that the analysis times were longer. The compositional differences were not as important
in the optimisation of the SFE methods. Greater separation was required to accurately
determine differences in composition of the sandalwood oil.
G C - M S Analysis of Sandalwood Oil
1 uL of sample was injected into the GC and analysed by the method shown in Table
2.16. The linear velocity and temperature program were the same as those of the
previous GC method, thus allowing retention times to be matched. MS was performed
82
in Electron Ionisation (EI) mode (70eV). This allowed identification of unknown
compounds to be determined by GC-FID on a routine basis from retention times.
Conditions
Column
Injection Mode Constant Flow Rate (mL/min) Injection Temperature (°C) Detector Temperature (°C)
HP- Innowax (30m x 0.25 m m x 0.25 urn) Splitless 0.75 250 250
Temperature Program
Initial Ramp Rate 1
Ramp Rate 2 Final Hold
60°C for 5 mins 4°C/mintol65°C 7°C/minto240°C 10 mins
Table 2.16. GC-MS conditions for the analysis of sandalwood oil
2.6.1.3. Sandalwood Locations
The 87 sandalwood core samples were taken from 12 regions throughout Western
Australia (WA). Figure 2.6 shows the geographic location of the 12 regions in WA.
Table 2.15 lists the region where each sample was taken, the height and diameter of the
tree, and the GPS location. A number of regions were further subdivided into locations
(26 in total). Sampling of locations within a region was only performed when
sandalwood trees were found in different landtypes within the same region. Sandalwood
trees from a location were found within a 200 m radius.
Sample
Wanjarrie 1.1.1
1.1.2
1.1.3
1.1.4
1.2.1
1.2.2
1.2.3
1.3.1
1.3.2
1.3.3
Midgut
1.4.1
1.4.2
1.4.3
1.5.1
1.5.2
1.5.3
Gascoyne
1.6.1
1.6.2
1.6.3
1.6.4
1.6.5
Approx Height (m)
3.0
n/a
2.5
3.0
4.0
3.5
4.0
2.5
3.5
3.0
4.0
3.0
4.0
4.0
6.0
5.5
Junction
3.0
5.5
4.5
3.5
n/a
Diameter (mm)
129
88
111
154
155
138
151
161
170
132
167
135
139
140
150
189
166
247
146
147
83
GPS(deg, min)
27 26 S 120 34 E 27 26S 120 34 E 27 26E 120 34 E 27 26E 120 34 E 27 25S 120 35 E 27 25S 120 35 E 27 25S 120 35 E 27 20S 120 37 E 27 20S 120 37 E 27 20S 120 37 E
24 39S 11820E 24 39S 11820E 24 39S 11820E 24 52S 118 24 E 24 52S 118 24 E 24 52S 11824E
25 24S 116 06 E 25 24S 116 09 E 25 24S 116 06 E 25 24S 116 06 E 22 24S 116 06 E
Sample Approx Height (m)
Shark Bay 1.7.1 2.5
1.7.2 5.0
1.7.3 4.5
1.7.4 4.0
1.8.1 2.0
1.8.2 2.0
1.8.3 2.0
Murchison
1.9.1 2.5
1.9.2 4.0
1.9.3 3.0
1.10.1 2.0
1.10.2 2.0
1.10.3 3.0
Burnerbinmah
1.11.1 2.5
1.11.2 2.5
1.11.3 2.5
1.11.4 n/a
1.12.1 3.0
1.12.2 5.5
1.12.3 2.0
1.13.1 3.0
1.13.2 2.5
1.13.3 3.0
Diameter GPS (deg, (mm)
176
202
231
178
147
155
229
194
130
120
113
140
166
138
144
165
77
180
274
113
129
117
163
min)
25 50 S 113 40 E 25 50S 113 40 E 25 50S 113 40 E 25 50 S 113 40 E 25 51S 113 40 E 25 51S 113 40E 25 51S 113 40 E
26 52S 115 56E 26 52S 115 56E 26 52S 115 56E 27 00S 11603E 27 00S 116 03 E 27 00S 116 03 E
28 47S 11715E 28 47S 117 15E 28 47S 11715E 28 47S 117 15E 28 47S 117 17E 28 47S 117 17E 28 47S 11717E 28 44S 117 21 E 28 43S 11723E 28 43S 117 23 E
Table 2.17. Locations and dimensions of sandalwood trees in the geographic survey Diameter of tree was measured 150 m m above ground level
Sample
MtElvire 1.14.1
1.14.2
1.14.3
1.14.4
1.15.1
1.15.2
1.15.3
1.16.1
1.16.2
1.16.3
Approx Height (m)
2.0
n/a
2.5
3.5
4.0
4.5
2.5
3.0
4.0
2.5
Goongarrie
1.17.1
1.17.2
1.17.3
1.18.1
1.18.2
1.18.3
1.19.1
1.19.2
1.19.3
2.0
4.5
4.0
3.5
4.0
3.5
3.0
2.5
2.5
Bullock Holes
1.20.1
1.20.2
1.20.3
3.0
3.0
3.0
Diameter (mm)
106
89
200
137
190
187
149
159
165
135
121
174
204
140
182
171
124
130
139
143
143
151
GPS (deg, min)
29 15S
119 38 E
29 15S
119 38E
29 15S
119 38 E
29 15S
119 38E
29 19S
119 36E
29 19S
119 36E
29 19S
119 36E
29 24S
119 35 E
29 24S
119 35 E
29 24S
119 35 E
30 01S
121 02 E
30 01S
121 02 E
30 01S
121 02 E
30 01S
121 07 E
30 01S
121 07 E
30 01S
121 07 E
30 04S
121 08 E
30 01S
121 08 E
30 01S
121 08 E
30 32S
121 45 E
30 32S
121 45 E
30 32S
121 45 E
Sample Approx Height (m)
Bullock Holes
1.21.1
1.21.2
1.21.3
1.22.1
1.22.2
1.22.3
3.5
4.0
4.0
4.0
5.0
4.5
Katanning
1.23.1
1.23.2
1.23.3
1.23.4
1.23.5
1.23.6
Ninghan
1.24.1
1.24.2
1.24.3
1.24.4
1.24.5
Jaurdie
1.25.1
1.25.2
1.25.3
1.26.1
1.26.2
1.26.3
3.0
3.5
2.5
3.5
2.5
4.0
2.0
3.0
2.0
3.5
2.5
2.5
2.0
4.5
5.0
3.0
2.5
Diameter GPS (deg, (mm)
141
135
143
180
122
126
80
200
160
205
125
130
122
102
160
182
150
150
152
170
178
138
115
min)
30 32S
121 46 E
30 32S
121 46 E
30 32S
121 46 E
-30 32 S
121 45 E
30 32S
121 45 E
30 32S
121 45 E
33 26S
117 40E
33 26S
11740E
33 26S
11740E
33 26S
117 40E
33 26S
11740E
33 26S
117 40 E
29 29S
117 10E 29 29S 11710E 29 29S 117 10E 29 29S 117 10E 29 29S 11710E
3107S 120 18 E
3107S
120 18 E
3107S
120 18 E
30 51S
121 09 E
30 51S 121 09 E
30 51S
121 09 E
Table 2.17 \cont.... Locations and dimensions of sandalwood trees in the geographic survey Diameter of tree was measured 150 m m above ground level
85
Figure 2.6. Sampling locations throughout W A
2.6.2. Seasonal Variation
Sandalwood trees from Wanjarrie, M t Elvier, Goongarrie, Bullock Holes and Katanning
were sampled over an 18 month period to determine if differences existed in the oil due
to seasonal variation. Samples were collected in spring, summer, autumn and winter. The
dates each sample was taken from the regions are shown in Table 2.18.
86
Date of Core Sampling Region
Wanjarrie Mt Elvire
Goongarrie Bullock Holes Katanning
Spring
21/09/98 25/09/98 25/09/98 28/09/98 30/09/98
Summer
12/01/00 13/01/00 14/01/00 14/01/00 21/01/00
Autumn
07/03/99 08/03/99 09/03/99 09/03/99 15/03/99
Winter
04/08/99 05/08/99 06/08/99 06/08/99 23/08/99
Table 2.18. Locations and dates of sampling of sandalwood trees in the seasonal survey
2.6.3. Sectional Examination
2.6.3.1. Materials
Three sandalwood trees were harvested from Lakeside Reserve approximately 20 km
east of Kalgoorlie. The size, diameter and GPS location of the trees are given in Table
2.19.
156
159
144
30 49 85 E 121 36 72 S 30 49 96 E 121 36 69 S 30 49 94 E 12136 71 S
Sample Approximate Height Diameter (mm) GPS (m) (deg, min, sec)
Treel 2.5
Tree 2 3.0
Tree 3 3.0
Table 2.19. Locations and dimensions of the 3 trees in the sectional surveys Diameter of tree was measured 150 m m above ground level
Harvesting of Sandalwood Trees
The trees harvested were situated on the edge of washed out river beds and were chosen
for ease of removal. The roots were exposed (Figure 2.7) by washing away the soil on
the edge of the river bank with water from a fire-fighting water hose supplied by a water
tanker. The tree was loosened from the soil by a combination of digging and washing
the soil from the tree with water. The trees were removed whole with the roots intact
and cut 50 cm above ground level with a chainsaw for ease of transport.
Figure 2.7. Exposed roots of a sandalwood tree. Harvesting of the tree required the roots system to remain intact. The earth was removed by washing
away the soil with water from a fire hose.
2.6.3.2. Longitudinal Sampling
Core samples were taken along a length of each tree from the roots to the branches at
5cm intervals. The method used for sampling was a variation of that described in Section
2.6.1.1. In between taking core samples, the auger drill bit was cooled in a dry
ice/acetone mixture. Instead of using a fence post borer, the drill bit was rotated by an
electric hammer drill. The shavings collected were reduced to powdered wood as
described in Section 2.6.1.1 and dried for 48 hours in a dessicator prior to extraction. All
extractions were performed in triplicate.
2.6.3.3. Cross Sectional sampling
The trees were cut using a bandsaw at 10 and 5 cm above ground level. A section of the
buttwood 5 cm in width was obtained. Core samples were taken across the diameter of
the tree with sampling method used in Section 2.6.3.2.
88
3. Results and Discussion
3.1. Optimisation of Trapping Conditions
Optimisation of the trapping conditions was performed using a standard mixture. The
standard mixture contained compounds representative of those found in real sandalwood
oil, and other compounds of varying size, volatility, and functionality that are commonly
found in essential oils (Table 2.2, Figure 2.1). These included the major sesquiterpene
(C15) alcohols of Western Australian sandalwood (trans, trans-famesol, and a- and f3-
santalol), limonene, cineole, citronellal, nerol and P-ionone, which represented the more
volatile CIO terpenes of alkene, ether, aldehyde, alcohol and ketone functionality
respectively. Manool, a diterpene alcohol (C20) was included to examine the
effectiveness of the collection procedure on higher molecular weight alcohols. The
boiling points and molecular weight of the components are shown in Table 3.1.
3.1.1. Extraction Time Course of Components of Standard Mixture
Exhaustive extraction was performed on the standard mixture to determine the time
required to completely extract and transfer the compounds to the solid bed trap for three
C02 densities (0.30,0.65, and 0.95 g/mL). The recoveries of each of the components
were measured after 10,20, 30, 40, 60, 80 and 120 minutes of extraction at each density.
An extraction time course showing the cumulative percentage recovery of each
component of the standard mixture recovered over time at densities of 0.30, 0.65, and
0.90 g/mL is given in Figures 3.1- 3.3 (Appendix Al). The compounds along the x-axis
represent their elution order from the GC column, hence, order of decreasing volatility
and increasing size.
89
It can be seen that the rate of extraction of each compound increased as the density of
the extraction fluid also increased. This was because as the density of the extraction
fluid was increased, the solvent strength also increased, allowing more compound to be
dissolved per unit time. An exception to this occurs where the rate of extraction of
limonene and cineole at a density of 0.30 g/mL is greater than at 0.65 g/mL, which was
an unexpected result.
Compound Limonene Cineole Citronellal Nerol P- ionone t,t- farnesol a- santalol p- santalol Manool
Molecular Weight 136.2 154.3 154.3 154.3 192.3 222.4 220.4 220.4 290.5
Boiling Point (°C)
176 176 208 225 229
263, 137@ 3 m m 148@ 5mm 158@ 5mm
144-145® 0.2mm
Table 3.1. Molecular weights and boiling points of the components of the standard mixture
At a density of 0.90 g/mL, all of the compounds in the standard mixture were extracted
at similar rates, indicating that each compound had a similar solubility in the C02
solvent. This was also evident at 0.65 g/mL, although the initial rate of extraction was
slower. Extraction with C02 at a density of 0.30 g/mL showed significantly different
rates of extraction for the various classes of compounds in the standard mixture even
though the cumulative percentage of the CI 5 and C20 compounds extracted at 0.30
g/mL may be an underestimate as not all of these compounds were extracted after 120
minutes (Figure 3.3) as the recoveries of these compounds after 80,100 and 120
minutes had not begun to decrease. After 30 minutes, over 60% of the monoterpenes
(limonene, cineole, citronellal, nerol and p-ionone) were extracted, but only 3% of the
sesquiterpenes {trans, fra/w-farnesol, and a- and p-santalol) and the diterpene manool.
90
This shows the larger CI5 and C20 compounds are far less soluble in C 0 2 at this density
than the CIO compounds.
120
Limonene Cineole Citronellal Nerol P-ionone a-santalol f,f-farnesoI P-santalol Manool
Figure 3.1. Cumulative percentage of individual components of the standard mixture extracted
over 80 minutes at a C 0 2 density of 0.90 g/mL
i2o
100
2
Warn Limonene Cineole Citronellal Nerol P-ionone a-santalol f.f-farnesol P-santalol Manool
Figure 3.2. Cumulative percentage of individual components of the standard mixture extracted
over 80 minutes at a C 0 2 density of 0.65 g/mL
°80
a 60
•40
°30
•20
• 10
91
• 1 2 0
• 100
• 8 0
• 6 0
• 4 0
• 3 0
• 2 0
• 1 0
Limonene Cineole Citronellal Nerol P-ionone "-santalol r,?-farnesol P-santalol Manool
Figure 3.3. Cumulative percentage of individual components of the standard mixture extracted
over 120 minutes at a C 0 2 density of 0.30 g/mL
A density of 0.65 g/mL was chosen to examine the effect of the various trapping
conditions on recovery since the compounds were completely recovered (>95%
recovery) after 30 minute of extraction.
3.1.2. Trapping
SFE can be can be divided into two distinct steps, extraction and collection. Extraction
involves the removal and transfer of the analytes from the matrix to the collection device,
while collection involves the recovery of the extracted analytes by the collection device.
For successful SFE, both these steps must be quantitative. The development of efficient
collection methods can prove difficult, due to the high gaseous C02 flow rates at the
restrictor after depressurisation. It is therefore important to develop a quantitative
collection method before addressing the extraction step.
Collection in SFE using a solid bed trap as the collection device relies on the adsorption
of the analytes onto the solid support (trapping). This can occur through two
mechanisms; physical and chemical adsorption. In physical adsorption on both inert and
92
active solid supports, the solid surface onto which the analytes precipitate is
cryogenically cooled. For efficient trapping of volatile components, sub-ambient trap
temperatures are required (cryotrapping). In chemical adsorption on active sorbents,
trapping occurs through interactions between the analytes and the active sorbent. There
is not one universal trap that will be effective for all classes of compounds. Active solid
supports have the advantage over inert solid supports because trapping, can occur
through both physical and chemical adsorption, and the analyst can choose the sorbent
that is most compatible with the target analytes.
A number of solid supports at three trap temperatures (0, 20 and 40°C) were examined
in this study. The solid supports were chosen to cover a wide range of polarities; inert
(stainless steel beads), non-polar (Hypersil O D S , Isolute CI8) and polar (Isolute cyano,
silica, and diol). The five active solid supports are silica and silica based sorbents,
bonded to chromatographic stationary phases of CI 8 (from two manufacturers), cyano,
or diol functionality (Figure 3.4).
The effectiveness of the collection procedure was assessed from the percent recovery of
the analytes, where a recovery over 95 % indicated quantitative collection. In a real
sample, however, the recovery cannot be measured, since the initial amounts of analytes
to be extracted are not known. To calculate the percent recovery in this study, the
mixture of known standards was used (Table 2.2, Figure 2.1). A measured amount (80
uL) of the standard mixture was extracted from an inert matrix and the percent recovery
of each component was measured.
C18- Octadecyl CN- Cyanopropyl Si- Silica 20H- Diol
93
-Si-
NC
Isolute Cyano
Si
I OH
Isolute Silica
HO
-OH
Isolute Diol
Hypersil O D S Isolute C18
Figure 3.4. Phases bonded to solid silica supports used in the study
The recoveries of the components of the standard mixture on the six trapping materials
at trap temperatures of 0,20 and 40°C at a flow rate of 1.0 mL/min are graphed in the
following sections. The results show the effect of trapping material, trap temperature
and compound volatility on the recovery of the individual compounds. For simplicity,
the results from each category of trapping material (inert, non-polar, and polar) will be
discussed separately.
3.1.3. Inert Trapping Material
The recovery of the components of the standard mixture using stainless steel beads
(Figure 3.5, Appendix A2) varied considerably. Quantitative recovery was not achieved
for any of the compounds at any of the three trap temperatures. This indicated that
physical adsorption alone did not efficiently trap the compounds.
94
Due to the lack of chemical functionality associated with the stainless steel beads, the
poor recoveries were a result solely of trap temperature and compound volatility. The
influence of trap temperature on recovery was much less for the less volatile compounds
(i.e higher boiling points). The recoveries of all compounds less volatile than citronellal
differ only minimally at the trap temperatures examined. Recoveries of over 90% were
achieved at a trap temperature of 0°C for all compounds. Increasing the temperature to
20°C, resulted in a slight loss of these compounds, with recoveries between 63 and 79%
being achieved. A further increase in the trap temperature from 20 to 40°C did not lead
to further loss and recoveries ranged between 61 and 79%. These results show that
physical adsorption is less efficient at a trap temperature of 20°C compared to 0°C. At
the higher temperature more of each compound can escape from the trap with the
expanding gas.
The recoveries of the more volatile compounds (limonene, cineole, and citronellal) were
much lower. The differences in volatility of these compounds appeared to have a strong
influence on their recoveries. At a trap temperature of 0°C, the recovery of citronellal,
the least volatile of the three compounds (b.p 208°C), was 77%, while the more volatile
limonene and cineole, which have the same boiling point (176°C), were recovered at 7
and 14% respectively. These recoveries are considerably lower than the recoveries seen
for those compounds less volatile than citronellal (90.1 -92.5 %).
The loss in recovery as the trap temperature increased was more evident for these more
volatile compounds (particularly evident for citronellal) than those compounds less
volatile than citronellal. An increase in the trap temperature from 0 to 40°C resulted in a
67% decrease in recovery of citronellal, compared to only a 25% decrease in nerol.
Complete loss of limonene and cineole was observed at trap temperatures of 20 and
95
40 C. The different losses in recoveries of these compounds were again attributed to
differences in the compounds volatihty. Greater physical adsorption occured between the
nerol molecules and the stainless steel beads as the trap temperature increased compared
to more volatile compounds.
In summary, it appears that those compounds with a boiling point greater than citronellal
(>225°C) exhibit similar recoveries and similar losses as the trap temperatures were
increased. The recoveries of these compounds were on the most part influenced by trap
temperature. Compounds with a boiling point similar to or below that of citronellal
<225°C show much poorer recoveries, and were much more dependent on the volatility
of the compound. The more volatile the compound, the lower the recovery. Greater
losses in recoveries were also experienced as the trap temperatures increased.
120
Limonene Cineole Citronellal Nerol B-ionone a-santalol t.t -farnesol B-santalol Manool
Figure 3.5. Recoveries of the components of the standard mixture using stainless steel balls as the
trapping material (inert trap) at trap temperatures of 0, 20 and 40°C and flow rate of 1 mL/min.
The non-quantitative recoveries on the stainless steel bead trap were due to the escape of
the compounds with the expanding gas, by inefficient physical adsorption. Decreasing the
velocity of the expanding gas by decreasing the extraction fluid flow rate might
96
improve recoveries. Flow rates of 0.5,1.0 and 2.0mL/min were examined at a trap
temperature of 20°C (Figure 3.6, Appendix A2). As the flow rate increased, the recovery
of all compounds in the standard mixture decreased. This clearly demonstrates the
limited ability of the inert trapping material to retain the components of the standard
mixture by physical absorption processes at the higher flow rates.
The recoveries of those compounds with a volatility less than citronellal were improved
by decreasing the flow rate to 0.5 mL/min. The lower flow rate enables more efficient
physical interactions with the stainless steel beads, due to the decreased velocity of the
expanding gas through the restrictor. At a trap temperature of 20°C the recoveries of
these compounds improved approximately 35- 40% by decreasing the flow from 2.0 to
0.5 mL/min.
The effect on the recoveries of the more volatile compounds (limonene, cineole, and
cirtronellal) as the flow rate decreases was much less apparent. The recovery of
citronellal was increased 19.7% by decreasing the flow rate from 2.0 to 0.5 mL/min.
Limonene and cineole were not trapped at any flow rate. Although these compounds had
a longer time to interact with the stainless steel beads at the lower flow rates,
presumably lower trap temperatures were required to aid in precipitation due to their
high volatility.
97
• 0.5
• 1
• :
limonene Cineole Citronellal Nerol B-ionone a-santalol //-farnesol B-santalol Manool
Figure 3.6. Recoveries of the components of the standard mixture on stainless steel beads (inert
trap) at extraction fluid flow rates of 0.5,1.0 and 2.0 mL/min at a trap temperature of 20°C.
3.1.4. Non-polar traps
Chemical adsorption along with physical adsorption can occur on the CI 8 sorbents
(Hypersil O D S and Isolute CI8, Figure 3.4). This can occur by interactions between the
compounds with the CI8 phase (dispersive forces), and the compounds with residual
silanol groups on the silica sorbent (hydrogen bonding).
Figures 3.7 and 3.8 (Appendices A 3 and A4) shows the recoveries obtained using the
two CI 8 traps at 0, 20 and 40°C at an extraction fluid flow rate of 1 mL/min.
Quantitative recoveries of all compounds, except limonene and citronellal were achieved.
Limonene, containing only alkene functionality, interacts with the CI 8 phase through
dispersive forces and physical adsorption. The other compounds have functional groups
that can form strong hydrogen bonds with the residual silanol groups on the surface of
the base silica along with the dispersive forces. The weaker interactions between
limonene and the CI 8 sorbent may result in the lower recoveries with the Hypersil
ODS trap. It appears however, that these interactions can be greatly enhanced
98
from a combination of chemical and physical adsorption, as the recovery improved from
17 to 9 4 % when the temperature of the trap was decreased from 20 to 0°C.
Interestingly, Isolute CI 8 and Hypersil ODS traps differ in their interaction with
limonene. Quantitative trapping was seen at all 3 trap temperatures using the Isolute CI8
trap, but only at 0°C on the Hypersil ODS trap. These different trapping abilities can be
rationalised by consideration of the different manufacturer specifications (Table 2.5),
such as average particle size, average pore size, specific surface area, and in particular
carbon loading. Carbon loading is a measure of the percent of phase (CI 8) bonded to the
base silica. Isolute CI 8 has a higher carbon loading (19.3%) than Hypersil ODS (9-10%)
and the potential for interactions between limonene and the CI 8 bonded phase is greater
with Isolute CI 8.
10
120
140
limonene Cineole Citronellal Nerol B-ionone o-santalol //-farnesol B-santaloI Manool
Figure 3.7. Recoveries of the components of the standard mixture using Hypersil ODS as the
trapping material (non-polar trap) at trap temperatures of 0, 20 and 40°C at a flow rate of 1.0 mL/min
99
Limonene Cineole Citronellal Nerol (J-ionone a-santalol /./-farnesol P-santalol Manool
Figure 3.8. Recoveries of the components of the standard mixture using Isolute C18 as the trapping
material (non-polar trap) at trap temperatures of 0, 20 and 40°C at a flow rate of 1.0 mL/min
Quantitative trapping of citronellal was not observed on either of the non-polar traps at
any of the three trap temperatures. This result was unexpected, since citronellal is
capable of forming hydrogen bonds with the residual silanol groups on the sorbent in the
same manner as the other polar compounds. It is tempting to suggest that the aldehyde
group, at least in part, may lead to the formation of a hemiacetal, which would covalently
link the aldehyde to the silanol group, resulting in partial retention on the trapping
material. This, however, is not tenable in view of the quantitative recoveries obtained
with Isolute silica and diol sorbents described below (see Figures 3.11 and 3.13).
Although low recoveries of both limonene and citronellal were observed on the Hypersil
ODS trap, and citronellal on the Isolute CI 8 trap, the recoveries were greater than those
using the inert trap (Figure 3.5). This shows that some form of chemical adsorption is
occurring. On the inert trap, the trapping of these compounds was very much dependent
on their volatility, the more volatile compounds experiencing lower recoveries.
However on both CI8 traps, cineole, which has the same boiling point as limonene, was
trapped quantitatively at all three trap temperatures, while limonene and citronellal
(which has boiling point higher than cineole) were not, showing the importance and
selectivity of chemical adsorption in the trapping process.
The effectiveness of the non-polar sorbents in trapping the components of the standard
mixture was seen by varying the flow rate (Figures 3.9 and 3.10, Appendices A3 and
A4). For the compounds trapped quantitatively on both traps, the flow rate was shown
to have no effect on recovery, illustrating the strength of the chemical adsorption in
retaining the compounds. The strength of the hydrogen bonding was sufficient to retain
these compounds even at a higher velocity of expanding gas. Limonene was poorly
retained on Hypersil ODS but quantitatively recovered on Isolute CI8 at all three flow
rates. This can be assumed to be due to the superior carbon loading of the Isolute CI 8.
* m
D0.5
• 1
• 2
-i r
Limonene Cineole Citronellal Nerol B-ionone a-santalol f,i-farnesol P-santalol Manool
Figure 3.9 Recoveries of the components of the standard mixture using Hypersil ODS as the trapping material (non-polar trap) at extraction fluid flow rates of 0.5,1.0 and 2.0 mL/min at a
trap temperature of 20°C.
120
100
80 --
> 60 o
40 -
20
0 -
l*Pj ±ri
no.5 m • 2
Limonene Cineole Citronellal Nerol P-ionone a-santalol/,/-farnesol P-santalol Manool
Figure 3.10 Recoveries of the components of the standard mixture using Isolute C18 as the trapping material (non-polar trap) at extraction fluid flow rates of 0.5,1.0 and 2.0 mL/min at a
trap temperature of 20°C.
3.1.5. Polar Trapping Material
Chemical adsorption on the polar traps occurs mainly through interactions with the polar
groups of the bonded phases and hydrogen bonding with the residual silanol groups.
Isolute silica contains a hydroxyl group as its main functionality (Figure 3.4). It would be
expected that hydrogen bonding might be the dominant interaction. On the other hand,
Isolute cyano and diol posses a short non-polar hydrocarbon chain in their functionality
of 4 and 8 carbons respectively (Figure 3.4), that could also enable interactions with
compounds through dispersive forces together with hydrogen bonding. This has the
advantage that a wider range of compounds can be trapped.
The recoveries of the compounds at 0, 20 and 40°C on the three polar traps (Isolute
silica, cyano, and diol) are shown in Figures 3.11-3.13 (Appendices A5- A7). All
compounds, except limonene and citronellal, were quantitatively recovered on the three
polar traps, at all three trap temperatures. These were able to hydrogen bond with the
polar bonded phases and residual silanol groups. The recoveries of limonene and
citronellal on the three polar traps varied, but were above 8 5 % at all trap temperatures,
showing far superior recoveries over the non-polar traps.
The lowest recoveries of limonene and citronellal on the three polar traps were seen
with the silica sorbent, affording recoveries of 85.2 and 86.0% at 40°C respectively
(Figure 3.11). These lower recoveries were due to the inefficient ability of Isolute silica
to interact with these less polar compounds through dispersive forces. As was seen with
the non-polar traps, by decreasing the trap temperature to 0°C, both compounds were
quantitatively recovered.
Citronellal was quantitatively trapped on the cyano trap at all temperatures, but the
recovery of limonene at 40°C was slightly lower (90.5%). The non-polar portion of the
bonded phase was unable to sufficiently prevent the escape of limonene at 40°C. A
decrease in the trap temperature to 0°C was sufficient to completely retain limonene on
the trap.
Isolute diol showed quantitative recoveries of all compounds irrespective of the trap
temperature. In this case, the longer non-polar portion of the bonded phase was able to
interact more strongly with limonene and citronellal.
103
• 0
• 20
• 40
Limonene Cineole Citronellal Nerol p-ionone a-santalol/,/-farnesol B-santalol Manool
Figure 3.11. Recoveries of the components of the standard mixture using Isolute silica as the trapping material (polar trap) at trap temperatures of 0,20 and 40°C at a flow rate of 1.0 mL/min.
120
100
P 60 o o
tltir ft H~
10
120
140
Limonene Cineole Citronellal Nerol P-ionone a-santalol /./-farnesol p-santalol \fenool
Figure 3.12. Recoveries of the components of the standard mixture using Isolute cyano as the
trapping material (polar trap) at trap temperatures of 0, 20 and 40°C at a flow rate of 1.0 mL/min.
104
10
120
140
I I I I I I Limonene Cineole Citronellal Nerol P-ionone a-santalol/./-farnesol p-santalol Manool
Figure 3.13. Recoveries of the components of the standard mixture using Isolute diol as the
trapping material (polar trap) at trap temperatures of 0,20 and 40°C at a flow rate of 1.0 mL/min.
Isolute diol was chosen as the trapping material to be used for sandalwood extractions as
quantitiative recoveries were shown at all trap temperatures. The trap temperature
chosen was 20°C, since this temperature was closest to ambient. A trap temperature of
20°C was favoured over 0°C as it minimised the amount of cryogenic carbon dioxide
required to cool the trap during the extraction process, and favoured over 40°C since the
time required to heat the trap would increase pre-run time.
There was no significant difference between the recoveries of the compounds between
flow rates of 0.5 and 2.0 mL/min at a trap temperature of 20°C on the three polar traps
(Appendices A5- A7). This showed that the interactions between the compounds and
polar sorbents were much greater than those with the non-polar sorbents, which showed
a loss in recoveries of limonene and citronellal as the flow rate was increased.
105
3.2. Desorption
The recoveries of components of the standard mixture are dependent on both the
adsorption and desorption processes. Even though compounds are trapped efficiently,
inefficient desorption from the trap will result in low recoveries. It is therefore important
to optimise the desorption conditions, such as rinse solvent, rinse volume and rinse
temperature.
The most influential parameter on the desorption of compounds from the trap is the
rinse solvent. Non-polar interactions between the analyte and the sorbent are best
disrupted by non-polar solvents and polar interactions are more effectively disrupted by
polar solvents. To examine the effect of the rinse solvent on desorption of the
components of the standard mixture from each of the six solid sorbents, five organic
solvents of various polarity were chosen. The solvents were, in order of increasing
polarity, hexane, iso-octane, methyl-tert-butyl ether (MTBE), ethyl acetate and ethanol.
The polarity index for each of these solvents is shown in Table 3.2.
Solvent
Hexane Iso-octane MTBE Ethyl Acetate Ethanol
Polarity Index
0.0 0.1 2.5 4.4 5.2
Table 3.2. Polarity indexes of solvents used for desorption of standard mixture
The standard mixture was extracted using the optimal conditions established previously
(Table 2.6), and the traps were rinsed with four successive 1.5 mL rinse volumes. The
recovery of each component was measured in each of the rinse volumes to determine the
effectiveness of each solvent on the desorption of the compounds. Optimal desorption
occurred when the compounds were desorbed from the trap by the first 1.5 mL rinse
volume. The results from the recovery of the last rinse volume were not included, as
prior to the final rinse, the SFE depressurised which invariably resulted in higher
recoveries measured in the final rinse compared to the rinse previous. The results are
again discussed in relation to the categories of trapping material (inert, non-polar, and
polar).
3.2.1. Inert Trapping Material
Using the stainless steel beads as trapping material, over 99% of the total amount of
each compound recovered was rinsed from the trap by the first 1.5mL rinse volume
(Appendix A2). The recoveries of limonene and cineole could not be determined, as
they were not trapped at 20°C.
With an inert trap, the compounds do not interact with the stationary phase, and
recoveries are determined by their solubility in the rinse solvent. The results showed that
all the compounds were soluble in each of the rinse solvents.
3.2.2. Non-Polar Trapping Material
Figures 3.14 to 3.17 (Appendices A3 and A4) show the rinsing efficiency of the non-
polar solvents (hexane and iso-octane) with the non-polar traps (Hypersil ODS and
Isolute CI8). Limonene, cineole, and citronellal were most efficiently desorbed from
both non-polar traps by the non-polar rinse solvents due to their limited ability to
interact with the silanol groups. Limonene only experiences dispersive forces with the
CI8 bonded phase, while cineole and citronellal have limited H-bonding ability
compared to alcohols. These interactions can easily be disrupted by the non-polar
solvents and these compounds are more efficiently eluted from the trap. Iso-octane was
less efficient in desorbing the compounds from the trap than hexane. This can be
107
explained to be due to more inefficient disruption of the polar interaction (H-bonds)
using iso-octane compared to hexane since the same inefficient desorption was also seen
for the more polar compounds (alcohols).
The CIO alcohol (nerol), and the CI5 alcohols (t,t-farnesol, and a- and P- santalol),
were the least efficiently desorbed compounds from both non-polar traps. These
alcohols bond more strongly to the residual silanol groups on the base silica, and
consequently, the non-polar rinse solvents did not have the ability to disrupt these polar
interactions. Again, iso-octane was less efficient at eluting these compounds from the
traps compared to hexane.
The results clearly show that p-ionone and manool, which potentially can form
hydrogen bonds with the residual silanols, were desorped more efficiently from the non-
polar traps, using the non-polar solvents, than the CIO and CI5 alcohols. The
differences in rinsing efficiencies compared to the CIO and CI5 alcohols can be
explained by structural differences, p-ionone is a ketone and forms weaker hydrogen
bonds with the silanol groups than the alcohols and are more easily disrupted by the
non-polar solvents. Manool has a large non-polar portion with a strong affinity for the
non-polar solvents and can be desorped more efficiently than the smaller alcohols.
Lower recoveries were obtained for all polar compounds from the Hypersil ODS trap
compared to the Isolute CI8 trap. This was again attributed to the carbon loading
differences between the two sorbents. The higher carbon loading percentage of the
Isolute CI8 sorbent compared to the Hypersil ODS results in a lower percentage of
residual silanols that can interact with the alcohols. The non-polar solvents therefore can
more easily disrupt the polar interactions with the Isolute C18 sorbent.
108
120
100
80
60
£
Ba. - rrtfl M*i P if fti
D 1st rinse
• 2nd rinse
D 3rd rinse
Limonene Cineole Citronellal Nerol P-ionone a-santalol /,/-farnesol P-santalol Manool
Figure 3.14. Rinsing efficiency ofhexane using Hypersil ODS
120
100
80
60
40
j
Ii I
Ei
j
I - " L , ffi*i*i, -
L rfl T_
1, «*•*, , ffl1!, ffl5!, Limonene Cineole Citronellal Nerol P-ionone a-santalolf,f-fernesol P-santalol Manool
Figure 3.15. Rinsing efficiency of iso-octane using Hypersil O D S
109
120 i
100
,-, 80 -
u 60
40
20
ifi
a i
m
fL h
O 1st rinse
Q 2nd rinse
03rd rinse
Limonene Cineole Citronellal Nerol P-ionone "-santalol U-farnesol P-santalol Manool
Figure 3.16. Rinsing efficiency ofhexane using Isolute C18
120
100
80
I 6 0 | a
40 +
20 -
*
m
m *
G 1st rinse
E2nd rinse
•J 3rd rinse
Limonene Cineole Citronellal Nerol P-ionone a-santalol t,t -farnesol P-santalol Manool
Figure 3.17. Rinsing efficiency of iso-octane using Isolute C18
The polar solvents (ethyl acetate, M T B E and ethanol) were much more efficient in
rinsing the compounds from the trap than the non-polar solvents, desorbing over 9 6 % of
the compounds in the first rinse volume (Appendices A 3 and A4). These polar solvents
were capable of disrupting the polar interactions of the compounds with the residual
silanol groups.
110
3.2.3. Polar Trapping Material
A s expected, poor recoveries from the polar traps were achieved using non-polar
solvents (Figures 3.18- 3.23, Appendices A5- A7). The less polar compounds (limonene,
cineole and citronellal) were rinsed most efficiently from the traps (>90% in the first 1.5
m L rinse volume), due to their high affinity for the solvent. Much lower rinsing
efficiencies were found for the less volatile compounds, in particular the CIO and CI5
alcohols, where three 1.5 m L rinse volumes ofhexane or iso-octane were not sufficient
to completely desorb these compounds from the trap. This is due to the inability of the
non-polar solvent to disrupt the polar interactions with both the residual silanols and
polar bonded phase. As was observed for the non-polar traps, P-ionone and manool were
more effectively desorbed from the polar traps by the non-polar solvents than the CIO
and CI5 alcohols due to weaker interactions with the polar sorbents. Again, hexane was
more efficient at eluting the compounds from the trap than iso-ocatane.
120
100
80
g 60 o o P4 40
20--
(H
fl—F • r 1
.Hi , —1*1 ,
-,-
1 m
— , — n , rl 1, rfl,
D 1st rinse
D 2nd rinse
D 3rd rinse
Limonene Cineole Citronellal Nerol p-ionone a-santalol f-farnesol P-santalol Manool
Figure 3.18. Rising efficiency ofhexane using Isolute silica
11
" 1st rinse
^ 2nd rinse
^3rd rinse
Limonene Cineole Citronellal Nerol P-ionone "-santalol t,t -farnesol P-santalol Manool
Figure 3.19. Rinsing efficiency of iso-octane using Isolute silica
120
100
80
60
40 -
20 -
- ' * ~ — 1-*-
p
J* i _ r
ri u ft J — — ) — —' 1 ' *1
• 1st rinse
• 2nd rinse
• 3rd rinse
Limonene Cineole Citronellal Nerol P-ionone a-santalol t,t -farnesol P-santalol Manool
Figure 3.20. Rinsing efficiency of hexane using Isolute cyano
112
120-.
100
80 6s-
» 60 o o Pi
40
20
0- a ifl i
5
+i A g -h Tl
Limonene Cineole Citronellal Nerol p-ionone a-santalol t,t-farnesol p-santalol Manool
Figure 3.21. Rinsing efficiency of iso-octane using Isolute cyano
D 1st rinse
• 2nd nnse
• 3rd rinse
120 -m
100
£ 80
t* 60
40
20
0 4
ii A A
i
^L
fl
L -ff JL^L Limonene Cineole Citronellal Nerol P-ionone a-santalol t,t-farnesolP-santalol Manool
• 1st rinse
• 2nd rinse
• 3rd rinse
Figure 3.22. Rinsing efficiency of hexane using Isolute diol
113
D lstnase
• 2nd rinse
D 3rd rinse
Limonene Cineole Citronellal Nerol B-ionone a-santalol t.t-farnesol B-santalol Manool
Figure 3.23. Rinsing efficiency of iso-octane using Isolute diol
Similar rinsing efficiencies with the non-polar solvents were observed between Isolute
silica and diol, both of which have - O H functionalities. Isolute cyano, which has a -CN
functionality, showed better rinsing efficiencies than Isolute silica and diol for the more
polar compounds. This reflects the weaker interactions between the cyano functional
group and polar compounds that can be more easily disrupted by a non-polar solvent.
All compounds of the standard mixture were rinsed efficiently from the three polar traps
with the polar solvents (ethyl acetate, M T B E , ethanol) (Appendices A5- A7). A recovery
of over 9 7 % the total amount recovered was rinsed from the trap in the first 1.5mL rinse
volume.
Ethanol was chosen as the rinse solvent for the extraction of sandalwood samples due to
its ability to efficiently desorb all the components of the standard mixture, low cost, and
ease of purification.
114
3.2.4. Rinse Temperatures
The desorbtion of analytes from a trap may be improved by increasing the temperature
of the trap during the rinse step. This, presumably, is due to increased solubility of the
analyte and weaker H-bonding interactions. The recovery of the components of the
standard mixture, at trap rinse temperatures of 20,40 and 60°C with ethanol as the rinse
solvent were examined (Appendices A2- A7). No significant differences in the
recoveries were seen with any of the 6 traps. It would be interesting to determine
whether rinsing efficiencies could be improved by using the non-polar solvents with the
active solid bed traps by increasing the trap temperature during the rinsing process. The
conclusion could be made however, that for rinse trap temperatures between 20 and
60°C, no loss in recovery was observed during the desorption step. A trap rinse
temperature of 40°C was chosen for the sandalwood extraction since this temperature
was closest to the nozzle temperature of 45°C.
3.3. Hydrodistillation of Standard Mixture
To examine the effect of hydrodistillation on these compounds, the standard mixture
was hydrodistilled as described in Section 2.2.4. The distillate was extracted with
MTBE since this solvent was found to recover 99% of all components of the standard
mixture in the first 50 mL extraction volume. The MTBE was removed under nitrogen.
The final recovery is dependent on the efficiency of the hydrodistillation, extraction and
evaporation procedures. To determine the effect that the extraction and evaporation
steps may have on the recoveries during the hydrodistillation methodology, a control
was used, in which the mixture was extracted from water.
115
The recoveries of the components of the standard mixture in the control and
hydrodistilled extract are shown in Figure 3.24 (Appendix A8). The control showed a
recovery of 66.6 and 74.3% for limonene and cineole respectively, indicating a loss of
these compounds during the extraction or evaporation steps. The low recoveries were
mainly attributed to losses during the evaporation of the solvent, due to the high
volatility of both limonene and cineole, since it was already known the extraction step
removed 9 9 % of all compounds in the first 50 m L extraction volume. Compounds with
boiling points greater than limonene and cineole (>174°C) in the control were recovered
quantitatively in the control.
Limonene Cineole Citronellal Nerol P-ionone a-santalol t,t-farnesol P-santalol Manool
Figure 3.24. Effect of hydrodistillation on the recovery of the standard mixture
The low recoveries of limonene and cineole observed for the control were also evident in
the hydrodistilled standard. This indicates that the losses of these compounds did not
occur during the hydrodistillation process. The other compounds, with the exception
of P-ionone and manooL afforded much lower recoveries after hydrodistillation,
presumably due to thermal degradation of the compounds at the high temperatures
116
involved in hydrodistillation. It is unlikely that the low recoveries were due to
volatilisation during hydrodistillation, since the more volatile compounds (limonene and
cineole) were relatively unaffected by hydrodistillation. Unexpectably, citronellal was
not recovered in the hydrodistilled sample. This may be due to solubility effects or
oxidation of the compound to citrobellic acid that may then react further with other
alcohols. There is also a reduction in the recovery of nerol, a- and P-santalol and t,t-
farnesol.
3.4. SFE Extraction Conditions for Sandalwood Samples
The effect of extraction conditions on sandalwood samples was examined using the
optimised collection conditions determined previously (Table 2.14). The aim was to
selectively extract the volatile components of the oil from the wood, leaving behind the
non-volatile material that has little impact on the aroma of the oil. To extract the volatile
components of the oil, the compounds must be dissolved by the supercritical CO2,
removed from the matrix, and transported to the solid bed trap for collection. These
processes are affected by a number of extraction parameters; density, temperature, mode
of extraction, flow rate, extraction time and particle size.
As the method was to be used for the extraction of a large number of samples, some of
these extraction parameters were set constant during the optimisation procedure.
Dynamic extraction was used since static extraction would substantially increase the
time involved. A C02 flow rate of 1 mL/min, which had previously been shown not to
affect the recovery of the volatile analytes with Isolute diol as the trapping material
(Section 3.1.5), was selected. An extraction temperature of 40°C was used for all
117
extractions, to minimise degradation of thermally labile compounds. Therefore only
density, extraction time, density and particle size needed to be optimised for extraction.
3.4.1. Extraction Time
Exhaustive extraction was performed on sandalwood samples to determine the time
required to completely remove the volatile oil for each density examined (0.45,0.55,
0.65, 0.75, 0.85, and 0.95 g/mL). Percentage yields, percentage volatiles, and oil
composition were measured after 10,20, 30,45, 60, and 90 minutes of extraction at
each density.
The extraction time course, graphed in Figure 3.25, shows the cumulative percentage of
the total oil extracted from sandalwood at each density (Appendix A9). The rate of
extraction of the oil increases with density. This extraction profile includes many of the
non-volatile compounds that contribute minimally to the odour of the oil and are not
eluted from the GC column during analysis. Many of these non-volatile compounds
require longer extraction times because of their lower solubility in supercritical CO2.
Since the aim was to selectively extract the volatile components of the oil, a more
appropriate illustration of the extraction time course is shown in Figure 3.26 (Appendix
A9). This shows the cumulative percentage of the total volatile components of the oil
extracted from sandalwood at each density, based on the peak area of compounds
eluting from the GC (Section 2.3.2). As can be seen, the rates of extraction were greater
than for the total oil extraction (Figure 3.25), thereby resulting in shorter extraction
times.
118
S
g> 80
u
20 40 60 80
Extraction Time (min)
100 120 140
Figure 3.25. Time course of the extraction of total oil from sandalwood at various densities
20 40 60 80
Extraction Time (min)
100 120 140
Figure 3.26. Time course of the extraction of volatile oil from sandalwood at various densities
Stahl has used a theoretical model to profile the extraction of an analyte from a solid
matrix 166 (Figure 3.27). This can be used to help explain the results obtained in the
extraction of volatile oil from sandalwood (Figure 3.26). Region I shows the initial
extraction of the analytes, which is highly dependent on the solubility of the analytes in
the extraction fluid. The more soluble the analytes are in the extraction fluid, the higher
119
the initial rate of extraction. The extraction profile for sandalwood shows that the initial
rate of extraction of the volatile compounds during Region I increased with density.
After 10 min extraction at a density of 0.45 g/mL, only 22.2% of the volatile compounds
have been extracted, compared to 84.5% at a density of 0.95g/mL. The initial extraction
of the volatile compounds during Region I at the lower densities required longer times,
due to the decreased solvent power. There appears to be very little difference however,
in the rates of extraction between densities of 0.75 and 0.95 g/mL, suggesting that the
volatile components of sandalwood oil are equally soluble in supercritical CO2 at
densities in this range.
Y (amount of analyte recovered)
Y max
I I
I 'I I '" • '
Amount of Solvent ^ Amount of Time
Figure 3.27. Theoretical extraction profile of an analyte from a solid matrix166
Region II represents the transition to diffusion controlled kinetics where the analyte-
matrix interactions must be disrupted. The rate of extraction in this region is lower than
in region I since it now is dependent on diffusion rather than solubility. In the extraction
profile for sandalwood, this region is absent at the high densities. The effectiveness of
the supercritical fluid in dissolving the compounds at high densities, may cause Region I
and II to occur almost simultaneously. Region II becomes more evident at the lower
densities where the conditions for extraction are less favourable, due to lower pressures
> i
Y
and lower solubilities. The reduced rate of extraction due to the diffusivity of the
supercritical fluid can be seen between 30 and 60 minutes at densities of 0.45 and 0.55
g/mL.
Region in represents an extremely slow rate of extraction which is diffusion limited and
reflects the limited mobility of the analyte in the matrix or difficulty in-the extraction
fluid penetrating the matrix. In this region a significant amount of time is required for
little increase in the amount of analyte recovered. In many extractions, it is not feasible
to continue the extraction into Region HI due to the high energy costs involved for
minimal increase in yield. For this reason, the extraction of sandalwood was deemed to
be quantitative when >96% of the volatile portion of the oil was removed. This occurred
after 30 minutes for densities of 0.95, 0.85, and 0.75 g/mL, 45 minutes for 0.65 g/mL,
60 minutes for 0.55 g/mL and 90 minutes for 0.45 g/mL. These conditions were used to
examine the effect of density on percentage yield, mass of volatiles and composition of
the oil.
3.4.2. Density
It is well known that solubility of a compound in CO2 is closely correlated with its
vapour pressure (or volatility)167. In a complicated model, such as sandalwood, the
relative proportion of volatile and non-volatile compounds extracted would differ with
density. It was possible to determine the relative amount of the volatile and non-volatile
compounds in each extract (volatile is defined as those compounds which would elute
from the GC column during analysis, non-volatile as those that were retained on the
column). The percentage of volatiles and non-volatiles in the extracted oil was
calculated through using an internal standard previously described in Section 2.3.2.
121
Different stationary phases of the GC column can influence the elution or retention of
many compounds. Since sandalwood is a complex mixture of compounds, the results of
the percentage volatile calculation were verified using a non-polar column (HP-5MS).
The percentage of volatiles using the polar analytical column was 29.4 ±1.7%, which
agreed within experimental error to the results from the non-polar column (26.7 ±1.9%).
The percentage yield and mass of volatiles of the oil extracted from sandalwood at the
six densities is shown in Figure 3.28 (Appendix A10). The percentage yield of oil ranged
from 1.8%, extracted at a density of 0.45 g/mL, to 4.8% at a density of 0.95 g/mL and
increased almost linearly with increasing extraction densities between 0.55 and 0.95
g/mL. The amount of volatile compounds remained constant as the density was
increased, indicating that the solubility of these compounds was similar between 0.45 and
0.95 g/mL. The overall increase in yield was due to the increase in non-volatile material
extracted as the density increased the solvation power of the supercritical C02.
3 3
I mass non-volatiles
I mass volatiles
0.95 0.85 0.75 0.65 0.55 0.45
Density (g/mL)
Figure 3.28. Yield and composition of volatiles extracted from sandalwood at various densities Mass of volatiles and non-volatiles was the mass of oil extracted assuming the mass of total oil extracted
was the percentage yield (i.e. amount extracted from 100 g of dry wood)
122
Composition
The compositions of the volatile oils extracted at each density differed primarily in the
amount of the two least volatile compounds eluting from the GC (Figure 3.29, Appendix
A10). Figure 3.29 shows the 3 most common components of Western Australian
sandalwood oil and the last two compounds eluting from the GC column identified by
their retention times. The relative amounts of the compounds were similar for extraction
densities between 0.95 and 0.65 g/mL. However, at a density below 0.65 g/mL, the
solvating power of the supercritical fluid was not sufficient to completely extract the two
late eluting compounds. A decrease in the amount of these compounds from 10.5 to
4.7%, and 4.2 to 1.2% was observed as the density decreased from 0.65 to 0.45 g/mL.
To ensure that the maximum amounts of volatile compounds were extracted, a density of
0.75 g/mL was used as the optimal density for the extraction of sandalwood volatile oil
for a time of 30 minutes.
«-bisabolol a-santalol a-farnesol 26.67
Compound or Retention Time (min)
28.35
Figure 3.29 Compositional variation in components of sandalwood oil extracted at various densities
123
3.4.3. Particle Size
The size of the matrix can have a profound influence on efficiency of extraction.
Smaller particle sizes generally leads to more rapid and complete extractions by
increasing the surface area and decreasing the diffusion path length. Grinding of the
samples can be employed to decrease the particle size of solids. Sandalwood samples
were ground in a blender in the presence of solid carbon dioxide to prevent volatilisation
and degradation of compounds by the heat generated in the grinding process.
To examine the effect of the size of the matrix on extraction, two particle size studies
were conducted. The first examined the effect of various particle size ranges (Table
2.10) on percentage yield, mass of volatiles and oil composition. Although this study
provided valuable information towards the understanding of the effect of the matrix size
on extraction it would be of no commercial benefit. Obtaining the optimal particle size
range would be labour intensive and produce wastage. A second particle size study was
therefore conducted examining the effect on percentage yield, mass of volatiles and oil
composition from wood extracted below a single particle size (Section 2.3.5). This
process required the use of only one sieve rather than a series of sieves, and much less of
the wood was wasted. This study has direct commercial benefit.
3.4.3.1. Particle Size Study 1
Extraction Time
Exhaustive extraction (Table 2.11) was performed on each particle size range, to
determine the time required to completely remove the volatile oil. The cumulative
percentage of the volatile oil extracted over a 60 minute period for each particle size
range is shown in Table 3.3. It can be seen that as the particle size decreased the rate of
extraction increased. The total amount of oil extracted in the first 15 minutes ranged
from 62.1% for a particle size >1700 um to 84.7% for a particle size range of 355-250
um. The greater amount of volatile oil initially extracted from the smaller particle size
range is due to the fact that the intraparticle diffusion resistance is less for smaller
particles because of the smaller diffusion pathways.
Extraction was considered complete when >96% of the total volatile fraction was
extracted. This occurred after 60 minutes extraction for particle size ranges between
>1700 and 850-710 urn, and 45 minutes for size ranges between 600-500 and 180-53
um. These extraction times were used for extraction of the wood, to determine the effect
of the particle size ranges on percentage yield, mass of volatiles and oil composition.
Time (min)
15
30
45
60
CTJMMULATTVE PERCENTAGE OF VOLATILE OIL EXTRACTED (%)
Particle Size Ranges (um)
>1700
62.1
83.4
93.7
100.0
1700-
1400
61.8
83.7
93.9
100.0
1400-
1180
65.6
85.8
94.6
100.0
1180-
1000
66.4
86.9
95.1
100.0
1000-
850
73.2
89.7
96.4
100.0
850-
710
73.0
89.9
96.3
100.0
710-
600
76.7
91.4
97.1
100.0
600-
500
79.3
92.6
97.5
100.0
500-
355
79.1
92.0
97.2
100.0
355-
250
84.7
94.8
98.2
100.0
250-
180
83.3
93.3
98.5
100.0
180-
53
83.8
93.7
98.2
100.0
Table 3.3. Cumulative percentage of volatile oil extracted from sandalwood of various particle sizes by SFE (Study 1)
Effect of Particle Size Distribution Range on Oil Yield and Percentage Volatiles
The percentage yield and amount of volatiles extracted using the optimal extraction
conditions (Tables 2.11 and 2.12) for each of the particle size ranges are depicted in
Figure 3.30 (Appendix Al 1). The yield increased from 1.6 to 3.7%, as the particle size
range decreased from >1700 um to 250-180 um. The increase can be seen to be the
result of an increase in both the amount of volatile and non-volatile compounds (43%
125
and 57% increase respectively). Presumably, as the particle size decreased, the extraction
fluid can more efficiently extract both a higher amount of volatile and non-volatile
compounds from the matrix due to both increased surface area and smaller internal
diffusion pathlengths.
Interestingly, decreasing the particle size range to 180-53 um, yielded lower amounts of
volatiles and non-volatiles, resulting in a lower percentage yield (3.3%). This might arise
from channelling effects due to the small particle size 117. This leads to inefficient contact
between the supercritical fluid and parts of the sample matrix, thus reducing the
percentage yield.
o o r i—i
A
o o " * •
*7 o o r--*
o 00 . — i
*7 o o •* w—t
o o o *7* o 00 .—1
—*
o W~l
00 o o o .-H
o i—i
r-o «n 00
o o NO ©
r-
o o <r> O O NO
Particle Size Range (mm)
V% «0 m o o *Ti
o «rt c-< •rt «r» d
O 00
.--, o v~t CS
o *r\ o 00 ^H
Figure 3.30. Yield and volatile composition of oil extracted from sandalwood of various particle
sizes by SFE (Study 1). Mass of volatiles and non-volatiles was the mass of oil extracted assuming the mass of total oil extracted
was the percentage yield (i.e. amount extracted from 100 g of dry wood)
Composition
The percentage of each component of the oil at the particle size ranges studied is given
in Appendix Al 1. Even though the amount of volatiles extracted at the various particle
size ranges differed, the relative amounts of each compound in the extracted volatile oils
were similar.
3.4.3.2. Particle Size Study 2
Extraction Time
The cumulative percentage of the volatile oil extracted over a 60 minute period (Table
2.11) from the wood below a single particle size is shown in Table 3.4. As observed in
Study 1, the rate of extraction was higher for samples of smaller particle sizes.
Extraction was deemed complete when over 96% of the volatile oil was recovered. This
was 60 minutes for a particle size <1700 um, and 45 minutes for particle sizes <1400,
<1000, <710, and <500 um.
Time (min)
15
30
45
60
CUMMULATIVE PERCENTAGE OF VOLATILE
OIL EXTRACTED (%)
Particle Size Range (um)
<1700
67.5
88.7
96.0
100.0
<1400
78.5
92.0
97.0
100.0
<1000
80.0
91.9
97.5
100.0
<710
82.3
94.4
98.0
100.0
<500
85.0
94.9
98.0
100.0
Table 3.4. Cumulative percentage of volatile oil extracted from sandalwood of various particle sizes by SFE (Study 2)
Effect of Particle Size Distribution Range on Oil Yield and Percentage Volatiles
Each particle size range was extracted using the optimised extraction condition (Tables
2.11 and 2.12). The effect of the particle sizes below a single size on the percentage
127
yield and composition of volatiles, was less than that found in Study 1 (Figure 3.31,
Appendix A12). This was because the samples in Study 2 consisted of a much broader
range of particle sizes, with many common to each sample. The percentage yield ranged
from 2.6% for wood of particle sizes <1700pm, to a maximum of 3.9% for particles
sizes <710um (Figure 3.31). The increase in amount of oil extracted was mainly due to a
67% increase in the amount of non-volatile material. No further increase in percentage
yield was observed as the particle sizes decreased from <710 to <500um which may
again be attributed to channelling 117.
4.5
4
3.5
3
£ 2-5 2 15 ? 2
1.5
1
0.5
0
" m a s s non-volatiles
^ m a s s volatiles
T
i I •
T 1
— i — •
gta
— i — — i —
J_
— E E -
<1700 <1400 <1000 <710
Particle Size Range (Mm)
<500
Figure 3.31. Yield and volatile composition of oil extracted from sandalwood of various particle
sizes by SFE (Study 2).
Mass of volatiles and non-volatiles was the mass of oil extracted assuming the mass of total oil extracted
was the percentage yield (i.e. amount extracted from 100 g of dry wood)
Composition
The percentage of each component of the oil at the particles size ranges studied are given
in Appendix A12. The relative amounts of each compound in the extracted volatile oils
were similar.
3.5. G C - M S Identification of Components in Volatile Sandalwood Oil
Sections 3.7-3.10 required the identification of as many of the components as possible
of volatile sandalwood oil, in order to examine compositional differences. Each
compound that corresponded to >1% of the total composition of the volatile oil by GC-
FID was assigned a number. The compound giving rise to the peak was identified by
GC-MS and the corresponding retention time was used for routine identification using
GC-FID. A list of the compounds identified is shown in Table 3.5. The peak number
corresponds to the peak numbers in Appendices A13- A20.
Peak N o
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32
Retention Time (min)
20.79
22.66
23.57
27.82 30.52 33.09
33.42
35.21
39.74 40.03
40.41
40.59 40.84 41.89
42.24
42.63 43.12
43.21
43.38 43.61 43.71
44.28 44.52
44.80
47.02 49.13 50.35 51.51 53.32 54.11
57.12 58.22
Identified Compound
p-santalene
a-curcumene
P-farnesene dendrolasin
nerolidol
P-bisabolol
y-curcumene
a-bisabolol n.i a-santalol
Z-a-frans-bergomotol
trans, fr-a/w-farnesol n.i E-cis, epi-P-santalol
cw-P-santalol
n.i £ra«.s-P-santalol
n.i n.i n.i c&y-lanceol nuciferol
n. n. n. n. n. n.i n. n.i n.i
i
n.i
Table 3.5. Peak number, retention time and compounds of Western Australian sandalwood oil The peak number corresponds to the peak number found in Apendices A13-A20
The compounds identified are consistent with those previously identified m S. spicatum,
S. album and S. austrocaledonicum 36.37,3^1,43,45,47,48,50,52,53,57-60,62,70,168,169 Compound
13 is only found in small amounts in a few of the sandalwood trees sampled.
Compounds 18,22, 24, and 25 are all minor compounds of sandalwood oil and are
prevalent in many of the trees sampled. Interestingly, many of these compounds had not
been shown to exist in previous studies 36>37>57>58'60 The most likely structure of these
compounds would be isomeric forms of C15H26O. An important unidentified compound
was compound 26, which was present at up to 20% in some extracted oils. Brophy
had also found a compound that was tentatively identified as a C15H26O alcohol
composing 6.4% of Western Australian sandalwood oil eluting after *ran,s-P-santalol
and prior to cw-lanceol.
The late eluting compounds were not identified (compounds 29-40). These compounds
are not included in the published chemical composition of numerous West Australian
sandalwood oils 41,6°. This is important to note as this work has shown that compounds
35 and 36 often consist of up to 20% of the oils (Appendices A15 -A24). These late
eluting compounds may be isomeric forms of santalyl, bergamotyl, lancyl, or nuciferyl
acetates, previously noted to exist in S. album and S. austrocaledonicum ' . The
exclusion of these compounds in the volatile oil calculations will result in an
overestimate of the other components, and be a possible source for the variation
amongst previous studies.
3.6. Comparison of Extraction Techniques
Figure 3.32 (Appendix A13) shows the percentage yield and amount of oil extracted
from Western Australian sandalwood by hydrodistillation, SFE (CO2 density of 0.75
g/mL), and solvent extractions (hexane and ethanol). Extraction conditions are given in
130
Section 2.5. The variations in the percentage yield are mainly due to the different
amounts of non-volatile compounds extracted by each method. In comparison, the
different amounts of volatile compounds contributed minimally to the differences in the
percentage yields.
Ethanol was by far the most efficient solvent for extracting the oil from the wood, with a
percentage yield of 8.6%. Its high polarity and hydrogen-bonding properties facilitated
the extraction of a large amount of non-volatile compounds, which made up 79.5% of
the total amount of oil extracted. This resulted in the extract appearing as a heavily
viscous oil with an unattractive dark brown colour. In contrast, extraction of the wood
with the less polar solvent hexane afforded a more visually attractive, yellow flowing
oil, which contained a lower amount of non-volatile compounds (62.8%), at a
considerably lower yield (2.9%). SFE (CO2 density of 0.75 g/mL) produced a visually
similar oil, at lower percentage yield (2.1%), containing a slightly lower percentage of
non-volatile compounds (57%). This yield could be improved by extracting at a higher
density, thereby increasing the strength of the solvent, enabling more of the non-volatile
compounds to be extracted. Hydrodistillation extracted the least amount of oil (1.4%).
This extraction technique only provides those compounds that are steam volatile and the
extract consists predominately of a volatile fraction, with only 39.5% due to non-volatile
compounds. Consequently the oil is much less coloured than the samples obtained by
hexane extraction and SFE.
131
T3
9
8
7
6
5
4
3 +
2
I mass non-volatiles
I mass volatiles
1
Hvdrodistillation SFE Hexane Ethanol
Figure 3.32. Yield and composition of volatiles extraction by various extraction techniques Mass of volatiles and non-volatiles was the mass of oil extracted assuming the mass of total oil extracted
was the percentage yield (i.e. amount extracted from 100 g of dry wood)
3.6.1.1. Effect o n Composition
The effect of the extraction techniques on the percentage composition of the five major
components is illustrated in Figure 3.33. The complete composition of the oil extracted
by each technique is given in Appendix A13. The most noticeable feature is the
difference observed in the percentages of a-santalol and nuciferol. A lower percentage of
a-santalol (-8%) is extracted by ethanol, and a higher percentage of nuciferol (-7%) is
extracted by hydrodistillation.
The low value of a-santalol using ethanol extraction may be partially explained by the
solvent's selectivity. As has already been shown in the study with different SFE
extraction densities, higher densities will extract greater amounts of late eluting
compounds from the GC (Figure 3.29). Since ethanol extracts more non-volatile
compounds than the other extraction techniques the relative percentage of the individual
compounds, in particular the highly volatile compounds may decrease as a result. In
Figure 3.33, four of the five major compounds with the exception of t,t-farneso\ are
132
present in lower amounts compared to the other extraction techniques. The decrease in
the amount of a-santalol however is considerably larger than for the other compounds,
which suggests other process may cause the lower percentage of a-santalol.
Interestingly, the amount of nuciferol is considerably higher in the hydrodistilled oil,
compared to the other compounds. This may arise from the conversion of enols or dienes
to the aromatic nuciferol catalysed by acid and oxygen. For example, lanceol or double
bond isomers of it could be converted to nuciferol as shown in Figure 3.34.
25 #
I 20 % "3 £ 15 o u HO
1 10 o SB a,
»1 1 1 1 , 1 J 1 |_uJ 1 —1—L-^-MS
i
J—|—L^J—1—1—1—L_
' Hydrodistillation
' SFE
' Hexane
' Ethanol
a-bisabolol a- santalol /./-farnesol P-santalol nuciferol
Figure 3.33. Compositional variation in sandalwood oil extracted by various extraction techniques
Lanceol Nuciferol
Figure 3.34. Chemical conversion of lanceol to nuciferol
133
3.7. Scale up of Extraction
The extraction of sandalwood was scaled up from a 7 m L extraction vessel (~1 g) to 300
mL (~ 100 g) to achieve a larger volume of oil. The 300 mL extraction vessel was
attached externally in a water bath for temperature control, and the SFE module
modified as described in Section 2.4.
Extraction Time Course
Exhaustive extraction was conducted on sandalwood samples to determine the time
required to completely remove the oil at various densities (0.45, 0.55, 0.65, 0.75, 0.85,
and 0.95 g/mL). The extraction method was paused without depressurisation of the
system after 100, 200, 300, 400, 500, and 800 mins and the oil collected was weighed,
and the cumulative percentage yield calculated (Figure 3.35, Appendix A14).
2.5
3 1.5
1 -
0.5 *
• — t — 100
A • •
X X
X X
200 300 400 500
Time (mins)
•
X X
A
•
• 0.45
•0.55
±0.65
X0.75
*0.85
•0.95
•+•
600 700 800 900
Figure 3.35. Time course of the extraction of total oil from sandalwood using a
300 m L extraction vessel
The amount of wood extracted increased 100 fold compared to the normal mode of
operation. As expected the time required to completely extract the oil from the wood
134
also increased. The extraction was stopped after 800 minutes. In the last 300 minutes,
25.6, 21.1, 20.7, 16.4, 14.4, and 11.4% of the total amount of oil were extracted at
densities of 0.45, 0.55, 0.65, 0.75, 0.85 and 0.95 g/mL respectively. From these results it
appears that extraction is not complete, but it must be remembered that samples
collected during the first 500 minutes did not involve depressurisation, which is required
to expel the majority of the oil from the extraction vessel and tubing.
The effectiveness of the 300 mL extraction procedure in amount of oil extracted was
measured by comparing the percentage yields at each density after 800 mins extraction
to the previously optimised extraction conditions using the 7 m L extraction vessel
(Table 2.9) illustrated in Figure 3.36. Although the results were comparable, at
densities <0.75 g/mL the percentage yield is slightly greater with the larger scale
extraction, while slightly lower at densities >0.75 g/mL. This can be explained in terms
of the different trapping devices used in each method. The custom made large scale
trapping device relies on purely physical adsorption for trapping, and can not baffle the
expanding gas flow from the restrictor. Therefore, at the higher densities, the trap may
be limited in its ability to completely precipitate the extracted analytes due to the greater
volume of expanding gas.
135
J -
2.5 •
2 -
Yield (%)
i
0.5
0
• 1 • — 1 —
1 1 | 1300 mL
l7mL
0.45 0.55 0.65 0.75 0.85 0.95
Density (g/mL)
Figure 3.36. Comparison of oil yield from 7 m L and 300 m L extraction vessel
3.8. Section of Tree
It has already been shown that the percentage yield and composition of the oil extracted
varied in different sections of the tree (roots, buttwood, and branches) ' ' ' . To
examine this in more detail, core samples were taken every 5 c m along the length of the
tree from the roots to branches. Samples were extracted using the conditions described
in Table 2.14.
The percentage yield and volatiles of the oil extracted from samples taken along the
length of three trees is shown in Figures 3.37- 3.39 (Appendices A15- A17). The results
varied from tree to tree, even though the three trees were situated within a radius of each
other of 50 m, however similar trends in oil yield were observed over the length of the
trees. In all three trees the highest amount of oil was found in the roots below ground
level (Tree 1, 5.9%; Tree 2, 6.9%; Tree 3, 5.0%). Tree 3 showed an exceptionally low
percentage yield between 15 and 10 c m below ground level, decreasing to a minimum of
0.59. The reason for this is that a grub, which infects the heartwood had infected part of
the root system.
The amount of oil extracted from the wood above ground level decreased slightly along
the length of each tree. The buttwood, which is the region of the tree from just below
ground level to 20 cm above ground level, contained a slightly higher oil content in
Trees 2 and 3, than the upper sections of the tree. This confirms previous studies 41,62'71.
The higher oil content in the roots and buttwood reflects the greater proportion of
heartwood in these sections of the tree. The roots are composed mainly of heartwood,
whereas in the stem and branches the heartwood content is variable, ranging from 90%
to negligible amounts 68. Since the heartwood contains the majority of the oil, the
sections of the tree containing the highest proportion of heartwood would contain the
highest percentage of oil. It has also been shown that, along the length of the tree, the
o
ratio of heartwood/sapwood decreases from the roots to the branches . This can explain
the decrease in percentage yield of oil in samples taken along the length of the tree.
The percentage of volatiles in the oil fluctuates considerably between 40 and 65%. No
clear conclusions could be made about the effect of the different sections of the tree on
the percentage of volatile compounds in the oil.
137
co c\2 -^ | • < ^ c \ 2 c o - ^ L r 3 c o c ^ c o a ^ c 3 ' - - ' C \ 2 c o - ^ ' L O c o r ^ c o I I I _ _ ^ _ r - . ^ _ _ _
Distance of Core Sample from Ground Level (cm)
Figure 3.37. Oil yield and percentage volatiles of sandalwood oil along Tree 1
T3
LO CO 1
o> C\2 1
lO 1
C3 lO CV2
O ^h
o CO
lO Z>-
C3
OT>
Distance of Core Sample from Ground Level (cm)
Figure 3.38. Oil yield and percentage volatiles of sandalwood oil along Tree 2
138
• l ° o yield
• — ° o volatiles
70
Distance of Core Sample from Ground Level (cm)
Figure 3.39. Oil yield and percentage volatiles of sandalwood oil along Tree 3
3.8.1.1. Effect on Composition
Figures 3.40- 3.42 (Appendices A15- A17) shows the major compositional changes in
the oil extracted from the core samples taken along the length of the three trees.
Although the composition of the oils varied between the trees, similar trends in the
changes of compounds along the trees were observed.
The most noticeable trend was the change in the percentage composition of a- and P-
santalol. In all cases the combined santalol content was greatest in the roots, with a-
santalol being the major constituent of the oil. Moving above ground level from the roots
a dramatic decrease in the amount of a- and 0- santalol was observed. The amount of
each compound decreased by more than 5 fold to below 5 % over a distance of 25 cm,
from the roots (-15 cm) to the buttwood (10 cm) in all three trees. These results
differed from those observed by Piggott , who found a-santalol to be the major
constituent (17.7%) in the buttwood. Moving further up the tree, the amount of a- and
P- santalol decreased to below 1%, in agreement with the results found by Piggott.
This sharp decrease in the amount of a- and P- santalol from the roots to the buttwood
was accompanied by subsequent increases in the amount of a- bisabolol and/or t,t-
farnesol. The relative increase in these compounds was very much dependent on the tree
examined, and for this reason the results for each tree will be discussed separately.
Tree 1 (Figure 3.40) showed that the sharp decrease in the santalol content between -10
and 10cm was accompanied by an increase in the amount of a-bisabolol. A decrease in
a- and P- santalol of 26.1% between -10 and 10 cm, corresponded to an increase in a-
bisabolol of 18.7%. The increase in t,t- farnesol (2.0%) was much less over this region.
Above ground level, a-bisabolol was the major component (~30%) of the extracted oil.
This value remained unaffected by further small decreases in a- and p- santalol,
however the amount oft,t- farnesol increased.
Results from Tree 2 (Figure 3.41) show a similar changes in the composition of the oil,
however t,t- farnesol was the major component of the oil above ground level (-35%).
The 14.7 % decrease in santalol content between -10 and 10 cm had a more pronounced
effect on the change in the percentage of t,t- farnesol than seen in Tree 1. The
percentage of t,t- farnesol increased 8.3%, while a- bisabolol increased 10.6%. As seen
in Tree 1 these compounds fluctuated along the length of the tree.
140
Tree 3 (Figure 3.42) had a very low amount of a- bisabolol compared to the other two
trees. Consequently there was little increase in the percentage of a- bisabolol moving
from the roots to above ground level where the santalol content decreased. The major
constituent of the oil above ground level, t,t- farnesol, increased by 21.8% between -15
and 10 cm and the percentage of santalols decreased by 37.1%. As the santalol content
declined below 1%, the amount of t,t- farnesol increased further and fluctuated along the
length of the tree.
There are also numerous consistent changes occurring in the composition in the minor
components of the oil along the length of the tree. Minor compositional changes
occurring in samples taken from the trees between the roots and branches are shown in
Table 3.6.
a- bisabolol
a- santalol
tt- farnesol
P- santalol
o o cs
v> '
o v~t e»
o T
v> >o
O t-
i/-> o «o O v-j O "~> 00 O —< r»> •* VO t-
Distance from ground level (cm)
Figure 3.40. Major compositional changes along Tree 1
141
451 40
Distance from ground level (cm)
Figure 3.41. Major compositional changes along Tree 2
-X-
a- bisabolol
a- santalol
tt- lamesol
P- santalol
Distance from ground level (cm)
Figure 3.42. Major compositional changes along Tree 3
Compound
Dendrolasin
a- trans- bergamotol No 20
cis- lanceol Nuciferol No 27 No 28
No 30
Dendrolasin
a- trans- bergamotol cis- lanceol No 28
No 30
Dendrolasin
a- trans- bergamotol No 20 No 30
Percentage of Compound in Roots
Percentage of
Compound in Branches
Treel
<1 3.3
11.5 4.8 4.3 8.2
3.5 3.8
4.1
<1
5.4 7.4 8.0 4.3 6.6
<1
Tree 2
<1
7.3
<1 <1 6.5
4.1
<1
6.7 6.4
<1
Tree 3
<1 6.7
6.5
7.1
10.2 <1
2.1 <1
Table 3.6. Minor compositional changes along the three trees
In summary, the following was observed for all three trees;
• A sharp decrease in the amount of santalols from the roots to the butwood
• Increases in the amount of a- bisabolol and t,t- farnesol as the santalol content
decreased
• A decrease in a- trans- bergamotol, No 20, 27, and 30 along the length of the tree
• An increase in dendrolasin, cis- lanceol and No 28 along the length of the tree
These results are of some interest when considered together with the biosynthesis of
sandalwood sesquiterpenes. It is worthwhile noting that the majority of the known
sesquiterpenes in sandalwood are isoprenologues of widely occurring monoterpenes. In
other words, the third isopreniod unit does not take part in the elaboration of the carbon
skeleton (Figure 3.43). The acyclic (t,t- farnesol, nerolidol, p- farnesene) and
143
monocyclic (a- and P- bisabolol, a- and y- curcumene, cis- lanceol, nuciferol) can be
considered to arise by simple processes from farnesyl diphosphate. The formation of the
bicyclic (P-santalene, epi-P- santalol, cw-P-santalol, Z-a-frvms-bergamotoi) and tricyclic
(a- santalol) sesquiterpene requires rearrangements of carbonium ions (Figure 3.44).
This second pathway can be considered to reflect a more evolved process.
In view of this, it is not surprising that the composition of oil obtained from the higher
reaches of the trees (younger portion of the plant) is characterised by the presence of the
simpler acyclic and monocyclic sesquiterpenes. The roots and more mature hardwood
are capable of more elaborate biosynthetic processes which results in sesquiterepenes
that are unique to sandalwood.
Presuming these hypothetical pathways are correct, the precursors to some of the
unidentified compounds in Table 3.6 can be assumed. As compounds No 20,27 and 30
decrease along the length of the tree, it is assumed that the biosynthesis of these
compounds follow the pathway shown in Figure 3.44 and would be closely related to the
structure of the santalols. Compound No 28 however, since it decreases along the length
of the tree would presumably be synthesised using the pathway described in Figure 3.43,
its structure would be acyclic or monocyclic.
144
PPO
PPO
a-curcumene Z-nuciferol
a-farnesene
epi-a-bisabolol
p-bisabolol
cis-lanceol
y-curcumene
Figure 3.43. Hypothetical derivation of acyclic and monocyclic sesquiterpenes in sandalwood
145
R1 = H;p-santalene R1 = OHp-santalol
a-santalol
Figure 3.44. Hypothetical derivation of bicyclic and tricyclic sesquiterpenes from the bisabolonium cation in sandalwood
146
Cross Sectional Variation
Variation in Oil Content and Percentage Volatiles
To examine the variation in oil content and composition across the diameter of the three
trees, a 5 cm section of the tree was removed between 5 and 10 cm above ground level.
The cross section was sampled as described in Section 2.6.3.3. The results showing the
changes in percentage yield and volatiles across the tree are shown in Figures 3.45- 3.47
(Appendices A18- A20). The sampling positions across each of the trees are shown in
Figure 3.48.
Figure 3.48 also shows the light coloured sapwood surrounding the darker inner
heartwood. Generally, the outer positions of the cross section contained the least amount
of oil. This is best seen in tree 3, which has a greater proportion of sapwood compared
to the other trees. The percentage yield of oil from the sapwood at positions 1 and 6 was
below 0.4%. An exception to this can be seen in tree 2, where the oil content at position
7 was greater than at position 4. The lower percentage yield found at position 4 was due
to heartwood rot, caused by infection of a grub. This can also be seen by the split across
position 4 in tree 3 (Figure 3.48). Areas of heartwood rot are evident in the centre of the
heartwood in tree 1 and tree 3, which made sampling difficult.
Apart from the areas of heartwood affected by heartwood rot, the percentage yield of oil
across the heartwood remained essentially similar. Values ranged from 5.1-6.9% (tree
1), 5.5-7.6% (tree 2), and 4.8-5.3% (tree 3). This shows that the heartwood oil content is
unaffected by the distance across the tree. Further evidence to support this can be seen
from Figure 3.44, where the percentage yield of oil from position 7 for tree 2 was 6.3%.
Figure 3.46 shows that only a thin layer of sapwood surrounds the heartwood, and the
sample from position 7 consisted predominately of heartwood. Even though this
147
position was on the outer of the tree, the yield was comparable to that from the inner
heartwood.
I°o yield
•°o volatiles
1 2 3 4 5 6
Sampling Position
Figure 3.45. Variation in oil yield and percentage volatiles across the diameter of Tree 1
~ 5
a 4 -
O 3
• • " o vie Id
- • — ° o volatiles
3 4 5
Sampling Position
Figure 3.46. Variation in oil yield and percentage volatiles across the diameter of Tree 2
148
3 4 5
Sampling Position
I °o yield
•°o volatiles
Figure 3.47. Variation in oil yield and percentage volatiles across the diameter of Tree 3
Tree 1
Tree 2
Heartwood Rot
Heartwood Rot
/l 2 3 4 5 6 )m
Heartwood Rot
Tree 3
Figure 3.48. Sampling positions across the diameter of the three trees
149
Composition
Figures 3.49- 3.51 (Appendices A18- A20) shows the variation on the 4 major
components of sandalwood across the diameter of the three trees. Trees 1 and 3 show
little variation (<7%) in a-bisabolol, and a- and P-santalol across the diameter of the
tree. Greater variation was noted for in the amounts of ?,/-farnesol (10.9%, treel; 14.2%,
tree 3). It appears that the relative percentage of t, /-farnesol was greater on the outside
of the tree in the sapwood regions than the inner heartwood.
The results from tree 2 are interesting. At position 4, where the oil yield was significantly
lower due to heartwood rot, the amount of a-bisabolol increased 6 fold and was devoid
of a- and P-santalol. This suggests the operation of a 'phytoalexin' response. It is well
known that plants challenged by biotic or abiotic factors, can respond by diverting their
metabolism to the formation of defence compounds 170. If this is so, it indicates that a-
bisabolol might have some biological activity towards the grub infection.
3 4
Sampling Position
-•— u- bisabolol
- • — a- santalol
tt- farnesol
- X — P- santalol
Figure 3.49. Major compositional changes across the diameter of Tree 1
150
a- bisabolol
a- santalol
tt-farnesol
P- santalol
3 4 5
Sampling Position
Figure 3.50. Major compositional changes across the diameter of Tree 2
— K -
" a- bisabolol
i i
tt- farnesol
_ P- santalol
1 2 3 4 5 6 7
Sampling Position
Figure 3.51. Major compositional changes across the diameter of Tree 3
3.9. Geographic Variation
S. spicatum is distributed over an area of 161 million hectares throughout Western
Australia ( W A ) 19. Brand has found genetic differences to exist between S. spicatum
ecotypes 171172. It is possible that some populations of sandalwood contain better sources
of genes for heartwood development, oil production, and oil composition arising from
these genetic differences. Considering the importance of both oil yield and
composition in relation to commercial viability, it is surprising that no extensive studies
have been conducted examining variations in oil yield and composition from different
geographic locations in Western Australia.
Geographic Variation in Oil Yield and Volatile Composition
Core samples were taken from numerous sandalwood trees from 12 geographic
locations throughout Western Australia and extracted by SFE as previously described
(Section 2.6.1.3). The percentage yield and santalol content of all the trees samples are
given in Table 3.7 (the total composition of the extracted volatile oil from each tree and
percentage volatiles is given in Appendix A21). There was found to be a great deal of
tree to tree variation. The oil yields and santalol contents ranged from 0.82 to 6.05 %,
and 0 to 84.6 % respectively. The average oil yield from the 87 tree sampled was 2.86 ±
1.14 % % which is significantly greater than the reported 2% average of S. spicatum 13.
The average santalol content was 24.89 ± 23.24 %. As can be seen from the large
standard deviation, much more variation occurred between the santalol contents than the
oil yields. Although the average was low compared to the reported values of santalol in
S. album, it was encouraging to find that 10 of the 87 trees sampled contained santalol
contents above 60 %.
Differences in the oil yield and percentage volatiles due to the geographic location were
determined through measuring the average oil yield and percentage volatiles from each
of the 12 geographical locations (Figures 3.52 and 3.53). Trees from Katanning contain
the highest average amount of oil (4.6%). This value was similar to the 4.8% yield
reported from the SFE of East Indian Sandalwood 73'74. Trees from Wanjarrie, Shark
Bay and Mulgul, afforded the next highest average yields (3.8, 3.5, and 3.4%). The
lowest average yields (2.0%) were found in trees from Jaurdie and Burnerbinmah.
152
Sample
Wan
jarrie 1.1.1
1.1.2
1.1.3
1.1.4
1.2.1
1.2.2
1.23 1.3.1 1.3.2
1.33 Mulgul
1.4.1
1.4.2
1.43 1.5.1 1.5.2
1.53 Gas-coyne Junction 1.6.1 1.6.2
1.63 1.6.4
1.6.5
Shark Bay
1.7.1
1.7.2
1.73 1.7.4
1.8.1
1.8.2
1.83 Murch-ison
1.9.1
1.9.2
1.9.3
1.10.1
1.10.2
1.103
Yield (%)
2.42
1.12
3.74
3.26
3.81
3.91
5.59
3.54
2.56
5.77
2.67
5.07
3.09
1.58
4.69
3.12
1.84
1.70
2.54
2.60
1.81
3.42
3.54
3.07
3.75
2.66
3.32
4.76
3.40
2.21
1.15
2.38
3.62
2.92
Santalol
(%)
15.71
33.60
46.64
60.94
39.58
37.57
11.40
31.31
48.53
55.35
73.31
64.77
65.38
54.96
50.91
68.98
40.08
28.55
10.56
30.24
53.18
62.43
84.62
70.64
76.72
55.43
43.02
73.51
6.00
38.16
7.54
2.19
6.96
15.66
Sample
Burner-binmah
1.11.1
1.11.2
1.11.3
1.11.4
1.12.1
1.12.2
1.12.3
1.13.1
1.13.2
1.133 Mt Elvire
1.14.1
1.14.2
1.143 1.14.4
1.15.1
1.15.2
1.153
1.16.1 1.16.2
1.16.3
Goongarrie
1.17.1
1.17.2
1.17.3
1.18.1
1.18.2
1.18.3
1.19.1
1.19.2
1.19.3
Yield
(%)
2.30
0.82
1.22
1.60
3.07
2.30
1.38
1.82
2.73
2.62
2.07
2.79
3.75
2.46
4.19
4.51
2.34
1.63
1.83
1.30
2.77
4.42
2.00
2.78
2.94
2.05
3.23
3.77
4.00
Santalol
(%)
2.82
0 0 2.03
2.00
10.90
12.12
2.07
0 0
3.39
9.97
10.56
21.61
11.34
10.61
21.00
23.46
17.58
31.73
6.36
24.20
26.07
21.74
41.12
16.34
3.75
10.68
17.67
Sample
Bullock
Holes
1.20.1
1.20.2
1.20.3
1.21.1
1.21.2
1.213
1.22.1
1.22.2
1.22.3
Katanning
1.23.1
1.23.2
1.23.3
1.23.4
1.23.6
Ning-han
1.24.1
1.24.2
1.24.3
1.24.4
1.24.5
Jaurdie
1.25.1
1.25.2
1.25.3
1.26.1
1.26.2
1.26.3
Yield
(%)
1.98
2.50
2.71
2.31
2.27
1.98
4.32
2.69
"2.16
4.83
4.52
6.05
3.22
4.50
1.14
2.25
3.64
3.53
1.93
2.48
1.03
2.97
2.08
1.96
1.49
Santalol
(%)
4.83
20.41
36.21
2.41
9.49
7.25
17.39
69.22
55.37
14.65
9.66
5.39
16.06
29.60
2.30
3.70
11.94
8.70
3.56
1.36
1.36
0.81
5.02
24.90
2.89
Table 3.7. Oil yield and santalol content of trees sampled in geographical survey Dimensions and locations of trees are given in Table 2.17
153
The trees with the greatest yields also contained the highest percentage volatiles. The
sandalwood oil from MulguL Shark Bay, Katanning and Wanjarrie contained average
volatile percentage compositions of 66.5, 65.9, 63.4, and 60.4% respectively. In fact, a
strong linear correlation was found between the percentage yield and percentage volatiles
(p=0.000, rM).538).
1 3 bo f-s
" 2 xn S3
2 3
o
s e? PQ
S3 O
J3
.g <s fi g
a 3
m
2 » 00
s o g o
X/l
o
o o "3
00
a 'S £
S St .13 00
c
Figure 3.52. Variation in the oil content of sandalwood trees from various geographic locations
St
3 _op
2
S a >>.2 en S3 si 3 03
a o .13 a
•3 a
e 3 03
">
3 St 00 S3
o o O
OS
O
J4
o 3 CO
00 S3 S3
1 W
E en J3 00 S3
3 St
Figure 3.53. Variation in the percentage volatiles of sandalwood trees from various geographic locations
154
One-way analysis of variance (ANOVA) revealed significant differences for the oil yield
and percentage volatiles (p=0.000) between geographic locations. It can be seen from
the large standard deviations in Figures 3.52 and 3.53 that there was large variation
within locations. Similar variability was seen in the genotype, measured by allele
frequencies at 3 polymorphic loci in S. spicatum from 8 locations 171. The variation
however maybe random, and due to the small sample sets from each location. Fisher's
pairwise comparisons were performed on the data and locations to determine which
locations differed significantly. The results from these tests are shown in Figures 3.54
and 3.55. The identification numbers corresponding to each location used in the Figures
3.54 and 3.55 are shown in Table 3.8.
2 3 4 5 6 7 8 9 10 11 12
1 n X
0
X
X
X
0
X
0
X
X
?.
0
0
0
X
0
0
0
X
0
X
3
X
0
0
0
0
0
X
0
0
4
0
X
0
0
X
X
0
X
5
0
0
0
0
X
0
0
a
0
X
0
X
0
0
7
0
0
X
0
0
8
0
X
0
X
Q
X
0
0
10
X
X
11
0
Figure 3.54. Fisher's pairwise comparison for statistical differences in oil yields between locations (o= no significant difference: x= significant difference)
1 3 4 5 6 7 8 9 10 11 12
1 n 0
0
X
X
X
X
0
0
X
X
?
X
0
X
X
X
X
X
0
X
X
1
X
0
0
0
0
0
X
0
0
4
X
X
X
X
X
o X
X
5
0
0
o 0
X
0
0
a
0
0
0
X
0
0
7
0
0
X
0
0
8
0
X
0
X
q
0
X
X
m
X
X
11
0
Figure 3.55. Fisher's pairwise comparison for statistical differences in percentage volatiles between locations
(o= no significant difference: x= significant difference)
Identification Geographic Location Number
1 Wanjarrie 2 Mulgul
3 Gascoyne Junction 4 Shark Bay 5 Murchison
6 Burnerbinmah 7 M t Elvire
8 Goongarrie 9 Bullock Holes 10 Katanning 11 Ninghan 12 Jaurdie
Table 3.8. Identification numbers corresponding to the geographic locations used in Fisher's pairwise comparisons (Figures 3.54 and 3.55, and 3.61 to 3.64)
Brand found there was genotypic and phenotypic variation in sandalwood trees from
different locations, and the genetic distance between ecotypes increased linearly with
increased geographical distance 171,172. No such linear relationship was found between
percentage yield and percentage volatiles with geographic distance. Therefore, rather
than geographic location being the cause of the observed differences, other factors such
as environmental conditions may influence the amount of oil and volatiles found within
a location.
Differences in climatic conditions have been shown to cause variation amongst the
171
phenotypic characteristics of sandalwood such as nut size, leaf size and growth rate
The rainfall and temperature from each location are given in Figure 3.56. Trees with the
highest percentage yields from Katanning also have the highest average annual rainfall
(395 mm) and coolest climate (22.7°C). However, there does not appear to be a
correlation between the percentage yields and rainfall or temperature for the other
locations that experience an average annual rainfall and temperature between 213 and
294 mm, and 25.2 and 32.0°C. There also appears to be no correlation between
percentage volatiles and these environmental conditions.
156
450
100
50
0
•Rainfall
35
30
25 3
1 15 ha
20 | H
15
10
3 8 a CO 3
<U CU C« tlQ
IS
s-~ CO tan c o o o
o 3C ^£ o
3 D3
Figure 3.56. Average rainfalls and temperatures for sandalwood sampling locations
A number of other factors may contribute to the variation observed between locations.
Although care was taken to choose trees of similar size, the maturity of a tree is
determined by the formation of heartwood rather than size72. It is generally considered
that heartwood content tends to be higher for a given size tree in lower rainfall
conditions 13'35. It is therefore possible that trees from arid regions may reach maturity at
sizes far smaller than in areas of higher rainfall, which may bias the results from these
regions as trees of similar sizes were chosen for sampling. The proportion of heartwood,
and hence, the maturity of the trees could not be determined by the sampling method
used.
Another factor that may contribute to the variation is disease. Heartwood rot is caused
by the infection of the heartwood with a grub. This results in hollow pockets within the
heartwood, as was noticed during the core sampling of some trees. The effect this has on
the yield is not known, but it seems reasonable to suggest that it would decrease the
heartwood/sapwood ratio, and decrease the yield. Also as has previously been shown in
157
Figure 3.50, heartwood rot can cause considerable variation in the composition of the oil
extracted from the infection area.
Other factors such as soil type, host species and genetics may be responsible for
variations yet are outside the scope of this thesis.
3.9.1.1. Geographic Variation in Oil Composition
The average percentage composition of the 5 major compounds of the volatile oil of S.
spicatum from each of the 12 locations is shown in Figures 3.57- 3.60. The amounts of
a- and p-santalol were added to give the total santalol content. One-way A N O V A
showed significant differences to exist between locations for a- and P-santalol, t,t-
farnesol and nuciferol (p=0.00). Fisher's pairwise comparisons were performed on the
data and locations to determine which locations differed significantly. The results from
these tests are shown in Figures 3.61 and 3.64. The identification numbers
corresponding to each location used in the Figures 3.61 and 3.64 are shown in Table 3.8.
N o significant difference was found between a-bisabolol from different locations
(p=0.062), which was due to the large standard deviations relative to the means.
158
a- santalol
(3- santalol
in 11 m 60
^
J3 00
•S
Figure 3.57. Variation in the percentage santalol from sandalwood trees from various geographic
locations
30 -,
Figure 3.58. Variation in the percentage a-bisabolol from sandalwood trees from various
geographic locations
159
Figure 3.59. Variation in the percentage /,f-farnesol from sandalwood trees from various
geographic locations
2
Figure 3.60. Variation in the percentage nuciferol from sandalwood trees from various geographic locations
Of most interest is the santalol content, since this determines the quality and value of the
oil. Previous studies have shown that the santalol content of S. spicatum ranges between
7 and 82%38'41. These large variations may be due to a number of environmental factors
as well as different sampling, extraction and analytical techniques between studies. In
160
this study, the same sampling, extraction and analytical techniques on a large number of
trees were used, with the advantage that direct comparisons between results could be
made.
The average santalol content from each location was shown to vary considerably (3.3%
to 66.6%). The trees with the highest santalol content were found in Shark Bay, closely
followed by trees from Mulgul (63.0%). There was no relationship between the oil yield
and santalol content. The high oil yielding trees from Katarming and Wanjarrie had
santalol contents of 15.1 and 38.6% respectively. There was also no evidence of a
relationship between the santalol content and climatic data (temperature and rainfall).
This suggests that other factors such as genetic differences may cause the variation
amongst trees from different locations.
2 3 4 5 6 7 8 9 10 11 12
1 T
o X
X
X
X
X
X
X
X
X
2
X
0
X
X
X
X
X
X
X
X
7,
X
0
X
o 0
o 0
X
X
4
X
X
X
X
X
X
X
X
5
o o 0
0
0
0
0
a
X
X
X
0
0
o
7
0
o o o o
8
o o 0
0
Q
0
X
X
in
o o
11
o
Figure 3.61. Fisher's pairwise comparison for statistical differences in a- santalol between locations (o= no significant difference: x= significant difference)
2 3 4 5 6 7 8 9 10 11 12
1 •x
o X
X
X
X
X
X
X
X
X
2
X
0
X
X
X
X
X
X
X
X
3
X
0
X
0
0
0
0
0
0
4
X
X
X
X
X
X
X
X
5
0
o 0
0
0
0
o
6
X
X
X
o 0
o
7
0
o 0
0
o
8
0
0
0
0
Q
0
X
X
in
0
o
11
0
Figure 3.62. Fisher's pairwise comparison for statistical differences in P- santalol between locations (o= no significant difference: x = significant difference)
2 3 4 5 6 7 8 9 10 11 12
i n o 0
0
0
0
0
X
X
0
X
2
0
0
0
0
0
0
X
X
X
X
1
0
0
0
0
0
X
X
0
X
4
o 0
X
X
X
X
X
X
5
0
0
0
X
X
X
X
a
X
X
X
X
X
X
7
0
0
0
0
o
8
0
X
0
o
0
0
0
0
in
0
o
11
o
Figure 3.63. Fisher's pairwise comparison for statistical differences in t,t- farnesol between locations
(o= no significant difference: x= significant difference)
2 3 4 5 6 7 8 9 10 11 12
1 n O
0
X
X
X
0
0
X
X
X
2
X
0
X
X
X
X
o X
X
X
3
X
o X
o o 0
0
X
0
4
X
X
X
X
0
X
X
X
5
o 0
X
X
0
X
o
a
0
X
X
X
X
X
7
0
X
0
X
0
8
0
0
X
0
0
X
X
X
in
X
o
11
X
Figure 3.64. Fisher's pairwise comparison for statistical differences in nuciferol between locations (o= no significant difference: x= significant difference)
Results in Section 3.8 showed that along the length of the tree, in particular just above
and below ground level, the santalol content decreased significantly, accompanied by an
increase in the amount of a-bisabolol, ^-farnesol and nuciferol. Since core sampling of
the trees was performed 10 cm above ground level, many of these compositional
changes may be occurring at this position within the tree. Moreover, locations that are
subjected to greater erosive forces may have a ground level much closer to the roots
than in other locations, which may result in higher santalol contents. This may explain
the higher santalol content found at Shark Bay. These trees were the only ones in the
study situated on the coast in sand dunes. Since sand dunes themselves are a product of
erosion, the topsoil in this location is likely to be more prone to erosion than the more
compact loamy soil found in more typical locations.
162
A strong linear relationship was found between the amount of a- and P- santalol in each
tree sampled (p=0.000,1^=0.988), showing that the ratio of a- to p- santalol is consistent
in the oil extracted from all 87 trees.
Of particular interest, were the relationships between the amounts of the five major
compounds found in the extracted oil from each tree. Regression analysis showed strong
negative correlation between the santalols and a- bisabolol, U-farnesol and nuciferol
(pO.OO), as those trees with highest santalol contents typically contained the lowest
amounts of a- bisabolol, £f-farnesol and nuciferol and vice versa. This supports the
presence of two biosynthetic pathways (Figures 3.43 and 3.44), which may be regulated
by certain feedback mechanisms.
3.10. Seasonal Variation in Oil Yield and Volatile Composition
Variations in percentage yields of oils have been measured in the leaves from eucalypts
1 TX 1 *7A.
and geranium during different seasons ' . The percentage yields were lowest in the
dryer warmer months and highest in the wetter cooler months. No such variation was
found in the amount of oil and volatiles from sandalwood from 5 locations (Figures 3.64
and 3.65, Appendices A22- 24) using two-way ANOVA (p>0.05). This may be due to
the fact that essential oil in the sandalwood is situated in the heartwood, whereas the oil
of eucalypts and geranium is present in the leaves. Since the leaves are found at the
extremities of the plant, and are the structures of the plant used in photosynthesis,
environmental conditions such as temperature and sunlight, which vary with season,
will have a greater impact on the formation and loss of oil.
163
D Spring
• Summer
•Autumn
•Winter
Wanjarrie Mt Elvire Goongarrie Bullock Holes Katanning
Figure 3.64. Variation in oil yield from 5 locations sampled during 4 different seasons
D Spring
• Summer
• Autumn
• Winter
Wanjarrie Mt Elvire Goongarrie Bullock Holes Katanning
Figure 3.65. Variation in percentage volatiles from 5 locations sampled during 4 different seasons
It is important to bear in mind that the effect of the core sampling procedure is not
known. Since the same trees were sampled four times over the period of 18 months, the
damage to the tree may have affected results. Moreover, the core samples for each
season were taken from different regions of the tree. Samples were taken 5 cm above the
previous sample point, which after four samples spans a length of 20 cm. As discussed in
Section 3.7, the percentage yield and percentage volatiles can vary considerably over
such a distance.
3.10.1.1.Seasonal Variation in Oil Composition
Two-way ANOVA showed no significant differences in the amount of a- bisabolol, a-
and p-santalol, t,t- farnesol, or nuciferol between the seasons.
4. Conclusion
Optimal trapping and extraction conditions were established for the extraction of
sandalwood oil from Western Australian sandalwood. The trapping conditions, were
optimised by measuring the recovery of a standard mixture representative of
sandalwood oil. Results showed that the polar trapping materials more effectively
trapped these compounds. Poorer recoveries of the more volatile compounds (limonene
and citronellal) were observed on the inert and non-polar traps, however decreasing the
trap temperature and flow rate in some instances was able to improve the recoveries of
these compounds.
Once trapped the compounds must be eluted from the trapping material by a rinse
solvent. The ability of numerous solvents of various polarity to desorb the components
of the standard mixture from the traps was determined. It was found that the polar
solvents (ethyl acetate, MTBE, and ethanol), were capable of desorbing each compound
from all the traps by the first 1.5 mL rinse volume. This was because the polar solvents
were more effective in disrupting the interactions between the compounds and the
sorbents. The non-polar solvents (hexane and iso-octane) were less efficient at
desorbing the more polar compounds from the active traps. Poor rinsing efficiencies
were observed from the non-polar traps due to the ability of the analytes to hydrogen
bond to the residual silanol groups of the solid supports.
Optimal trapping conditions were with Isolute diol as the trapping material at a
temperature of 20°C and CO2 flow rate of 1 mL/min. Ethanol provided an easily
available, cheap rinse solvent. These conditions were used to examine the effect of the
extraction parameters on the percentage yield, percentage volatiles and oil composition
of the oil extracted by SFE from sandalwood.
An increase in the extraction density was shown to increase the percentage yield. This
increase was mainly due to an increase in the amount of non-volatile material extracted,
as the amount of volatile oil extracted remained constant over the density range
examined (0.45 to 0.95 g/mL). Over this density range, the composition of the volatile
oil was found to differ in only the two least volatile compounds, which are currently not
identified, whose amounts decreased as the density fell below 0.65 g/mL. Hence 0.75
g/mL was chosen as the optimal density to completely extract the volatile oil from
sandalwood. The identification of the compounds present in the non-volatile oil would
be a focus of future work.
The particle size of the wood matrix was shown to have an effect on the percentage
yield and percentage volatiles, but it had no effect on the composition of the extracted
volatile oil. Decreasing the particle size increased in part the amount of non-volatile
compounds extracted, and also to a lesser extent the volatile compounds, thereby
increasing the overall percentage yield. This was thought to be due to the increased
surface area and smaller internal diffusion pathlengths as the particle sizes decreased.
The sandalwood oil extracted using the optimised SFE conditions was compared to the
oil extracted using hydrodistillation and solvent extraction. The percentage yield of total
oil extracted by SFE was comparable to that extracted by hydrodistillation and hexane
extraction. A much greater percentage yield was extracted using ethanol, however the
oil was visually unattractive. The composition of the volatile oils varied slightly with
hydrodistillation extracting a greater amount of nuciferol and ethanol a lower amount of
santalols.
The SFE and GC methods developed served as fast, robust, routine techniques for the
extraction of large numbers of sandalwood samples. These methods were used to
examine variation in the oil extracted every 5 cm along the length of 3-trees from the
roots to the branches. The oil content was highest in the roots below ground level and
decreased along the length of the tree. A greater santalol content was also found in the
roots, which decreased 5 fold in the wood above ground level. This sharp decrease was
accompanied by a significant increase in the amount of a- bisabolol and t,t- farnesol.
These results are thought to be due to differences in the biosynthetic pathways occurring
in the more mature roots and less mature stems of the trees. Further studies are required
to validate the biosynthetic pathways occurring within sandalwood.
The major commercial focus of the work was to examine variations in the sandalwood
oil extracted from trees found in 12 different geographic locations throughout Western
Australia. Oil content, percentage volatiles, and oil composition were all found to vary
between locations. An attempt was made to correlate these differences with temperature
and rainfall variations between locations without success. No correlation could be
established. These results can serve as a starting point to further examine variables that
may cause variation in the oil amongst sandalwood trees, such as soil type, host species
and ecotypes.
168
Recommendations for Future Work
Many of the results from the trapping studies were influenced by the residual silanol
groups on the solid supports, in particular the non-polar supports. A greater
understanding of the interactions of the non-polar bonded phase could be achieved by
using end-capped supports, where the residual silanol groups are replaced by non-polar
functionalities.
With the current core sampling technique used, no differentiation could be made
between the heartwood and sapwood. The results therefore reflect what is found in both
the heartwood and sapwood. For instance, the results showing the decrease in oil yield
along the length of the tree maybe due to the decreasing proportion of heartwood. A
sampling technique that can distinguish heartwood from sapwood would be able to
assess changes only occurring on the heartwood.
Advantages would also be gained from the development of a completely non-evasive
technique for the sampling of volatile oil composition. As it is unknown as to the effect
of core sampling on the tree, this would better serve as a comparison in the volatile oil
composition between seasons on a longer term. Such techniques could include solid
phase microextraction (SPME), where the volatile compounds of the oil could be
adsorbed onto a fibre positioned within close proximity to the tree in the field, and
brought back to the lab for analysis by GC. Another more expensive technique could be
through the use of a portable micro-GC that could be used in the field which samples the
volatile oil directly from the tree.
The results showing the variation in oil content, percentage volatiles and oil
composition from different geographical locations can serve as a starting point to
169
examine variables that may cause these variations. The focus of further work would
involve elemental analysis of the soil, to find if any correlations exist. This could be
closely linked to the elemental analysis of the wood, which may also have an influence
on oil variation.
Another possible source of variation could be due to differences in the-genetic make up
of the trees. These studies would examine any relationships between differences in DNA
sequence or DNA expression and oil variation. If a particular genotype was found to
produce a better quality oil, this may lead to the cloning of trees. Along the same lines, it
would be interesting to see if the seed collected from the better trees would also produce
a similar quality oil.
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6. Appendix
Table of Appendix
Al Extraction time course ofstandardniixture at 0.30, 0.65, and 0.95 g/mL 184
A 2 Recoveries of standard mixture from stainless steel beads trap 185
A 3 Recoveries of standard mixture from Hypersil O D S trap 186
A 4 Recoveries of standard mixture from Isolute CI 8 trap : 187
A 5 Recoveries of standard mixture from Isolute silica trap 188
A 6 Recoveries of standard mixture from Isolute cyano trap 189
A 7 Recoveries of standard mixture from Isolute diol trap 190
A 8 Recoveries of standard mixture following hydrodistillation 191
A 9 Extraction time course of total and volatile sandalwood oil at various densities 191
A 1 0 Yield, volatiles and composition of sandalwood oil extracted at various densities 192
A l 1 Yield, volatiles and composition of sandalwood oil extracted using various particle size ranges
(Study 1) 193
A 1 2 Yield, volatiles and composition of sandalwood oil extracted using various particle size ranges
(Study 2) 195
A13 Yield, volatiles and composition of sandalwood oil extracted using different extraction
techniques 196
A14 Cumulative oil yield extracted at various densities over 800 minutes using large-scale SFE
apparatus 197
A15 Yield, volatiles and composition of sandalwood oil extracted every 5 cm along length of tree 1.. 198
A16 Yield, volatiles and composition of sandalwood oil extracted every 5 c m along length of tree 2.. 203
A 1 7 Yield, volatiles and composition of sandalwood oil extracted every 5 c m along length of tree 3.. 208
A18 Yield, volatiles and composition of sandalwood oil extracted across diameter of tree 1 213
A19 Yield, volatiles and composition of sandalwood oil extracted across diameter of tree 2 124
A20 Yield, volatiles and composition of sandalwood oil extracted across diameter of tree 3 215
A21 Yield, volatiles and composition of sandalwood oil extracted from tress from various geographic
locations (samp 1 ed during spring) 216
A22 Yield, volatiles and composition of sandalwood oil extracted from tress from various geographic
locations (sampled during autumn) 226
A23 Yield, volatiles and composition of sandalwood oil extracted from tress from various geographic
locations (sampled during winter) 230
A24 Yield, volatiles and composition of sandalwood oil extracted from tress from various geographic
locations (sampled during summer) 235
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