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Investigation of the odour profile of Cannabis sativa,
in relation to the training of drug detection dogs
Clare Shave
Supervisor: Dr Gillian Taylor
TEESSIDE UNIVERSITY
School of Science and Engineering
2016
Keywords: Cannabis, Gas Chromatography, Headspace, Drug Detection, Pseudo Scent
Author Biography
I am currently undertaking a bachelor honours degree in Forensic Science at Teesside University and hope to go on to study Forensic Science at Master’s degree
level.
Acknowledgments
I would like to thank Dr Gillian Taylor for the help and support she has given me.
Without her dedication and hard work, I do not believe this work would have been
possible.
ContentsAcknowledgments...............................................................................................................................2
Document Information........................................................................................................................2
Abstract................................................................................................................................................3
Introduction..........................................................................................................................................4
Experimental........................................................................................................................................9
Reagents and materials.....................................................................................................................9
Preparation of laboratory cannabis oil..............................................................................................9
Preparation of standards for analysis................................................................................................9
HS-GC-MS analysis.............................................................................................................................9
Testing of Laboratory Cannabis Oil with Drug Detection Dogs........................................................10
Results...............................................................................................................................................10
Discussion..........................................................................................................................................14
Conclusion.........................................................................................................................................17
References........................................................................................................................................19
Appendices........................................................................................................................................23
Document Information
Total Word Count: 4500
Number of Pages: 37
Number of References: 39
Page 2 of 37
Abstract
Cannabis sativa L. is often detected using drug detection canines (Canis lupus var.
familiaris) due to the highly sensitive olfactory system of the animal. Training drug
detection canines is usually performed using aged cannabis samples and pseudo
scents produced by Sigma Aldrich®, known as Narcotic Scent Marijuana
Formulation. A lack of information regarding these pseudo scents has caused
speculation into the effectiveness of these compounds as training aids.
This research was conducted to determine if the pseudo scent is an effective training
aid for canines, the pseudo scent was tested in comparison to odour profiles of
cannabis, scented oils and soaps and cannabis oil produced within the laboratory.
Gas chromatography – mass spectrometry coupled with headspace (Head Space -
GC/MS) was utilised to analyse limonene, myrcene, frankincense, cannabis burning
oil, soap, candle and laboratory produced cannabis oil. The samples were placed
directly into headspace vials ready for analysis.
The analysis of the pseudo scent headspace profile showed that it contained two
terpenes, in comparison to the sixteen found in the cannabis profile. Alternatively,
the odour profile of cannabis oil produced results comparable to that of cannabis.
Preliminary testing using a canine trained in cannabis detection provided by
Cleveland Police, proved that drug detection canines respond positively to the oil
when used as a training aid.
Page 3 of 37
Introduction
Cannabis sativa L., is a dioecious plant which originates from Eastern and Central
Asia, but is actively grown worldwide (Jagadish, Robertson and Gibbs, 1996; de
Cassia Mariotti et al., 2015). Tropical climates allow the plant to be cultivated outside
naturally, however, temperate climates such as those exhibited in the UK require
indoor cultivation – allowing for year round production (de Cassia Mariotti et al.,
2015; Negrusz and Cooper, 2013). The spread of cannabis from Eastern and Central
Asia is thought to have taken place over the last 10000 years (Jagadish, Robertson
and Gibbs, 1996). Throughout this time there has been many different uses for a
multitude of different civilisations, these include: medicinal, intoxicant, ritual
purposes, sources of fibre, food and oil (de Cassia Mariotti et al., 2015). The use of
cannabis for the recreational purposes is what it is most infamous for in modern
times, the effects of which vary from person to person and the reaction time is
determined by the method of administration (Baggio et al., 2014). Inhalation of
cannabis allows for rapid speeds of absorption allowing the first effects to be felt
within seconds and the full effect within minutes; oral ingestion, however, delays the
affects as absorption is slower within the gut (Vale, 2012).
Cannabis is the most commonly used illicit drug worldwide (Baggio et al., 2014) with
the World Drug Report (2015) stating that the current number of cannabis users,
globally, was approximately 181.8 million, in 2013. The European Drug Report
(2015) also showed an increase in the worldwide seizure of both herbal and
cannabis resin, finding cannabis to be the most commonly seized drug accounting
for eight out of ten seizures. It is suggested that the cause for this fluctuation was an
increase in law enforcement activities, or a possible overall increase in the
production and trafficking of cannabis, with two-thirds of all European seizures being
reported by the United Kingdom and Spain (World Drug Report, 2015; European
Drug Report, 2015). There is also growing evidence to support the opinion that
cannabis is becoming more potent with rising levels of THC within newer varieties,
with current studies showing cannabis with THC levels of up to 30% - triple the levels
from the 1980s (Handwerk, 2015). The detection of cannabis can be performed with
the use of an electronic “sniffer” which uses a portable mass spectrometer to detect
Page 4 of 37
volatile vapours, such as those exhibited in Table 1, emitted from the drug (Hood,
Dames and Barry, 1973). However, drug detection canines are the most recognised,
fast, flexible, mobile and durable form of detecting illicit substances such as cannabis
(Jezierski et al., 2014). Detection dogs are selected upon several factors including;
gender, instinct to hunt, sense of smell, ability to be trained and general stamina
(Ensminger, 2012). They are used for a variety of tasks such as drug detection and
in the detection of human remains, due to their exceptionally sensitive olfactory
senses (Sorg, Rebmann and David, 2000). In comparison to the average sense of
smell within humans (approximately five million receptor cells), the dog’s sense of
smell is highly superior with breeds such as the Bloodhound displaying 100 million
receptor cells (Sorg, Rebmann and David, 2000).
The olfactory system of a dog works through the passing of air molecules over the
olfactory neurons within the nose, receptors residing upon the neurons bond to
molecules within the air. The air pathway within a canine is distinctly different from
when a dog is breathing to when it is sniffing; sniffing allows for a larger amount of
air to pass over the olfactory mucosa. This larger amount of air provides a larger
amount of molecules available to bond with the olfactory receptors which send
signals to the brain (Jensen, 2007). Certain properties of the molecules are thought
to affect what causes the neurons to fire once the molecules have bound to the
receptors; the suggestion is that physical properties including solubility and volatility
are key factors, but it is not fully understood (Sorg, Rebmann and David, 2000).
Page 5 of 37
Step 1:The dog is
introduced to the scent and is taught
to develop a committment to
locating the source of the scent
Step 2: The dog is taught to
give an easily identifiable signal to
its handler that it has identified the
source
Step 3:The scent is hidden
from the dog, causing the dog to learn to search for
the scent
Step 4:The dog is
introduced to realistic scenarios
and taught to search under
differing conditions
Figure 1. The training process for drug detection dogs, adapted from Sorg, Rebmann
and David (2000)
A study by Jezierski et al. (2014) found that the German shepherd is the best breed
in terms of giving a correct indication, whilst Terriers give poor all round detection
performance. However, the study also shows a large variation in the effectiveness of
dogs within breeds with the German shepherd having a correct indication time of 61
seconds +/- 74 seconds. This variation between and within breeds shows the need
for efficient and effective training in dog detection in order to produce dogs which are
able to consistently detect drugs. Despite this research, Correa (2011) describes the
use of breeds including: German shepherds, Labradors and Golden retrievers, within
customs and border controls. The use of detection dogs has recently been extended
to use in medical diagnostics, a study by Gordon et al. (2008) states that the strong
olfactory sense of the dog can be used to detect human cancers. This is thought to
be possible due to the volatile organic compounds emitted by cancer patients within
their breath or urine (Gordon et al., 2008).
The analysis of cannabis has determined more than 525 different chemical
compounds which are categorised into: monoterpenes, sesquiterpenes, sugars,
hydrocarbons, steroids, flavonoids, nitrogenous compounds and amino acids
(ElSohly and Slade, 2005). A further category of molecules found within cannabis
are cannabinoids, there are believed to be more than 90 of these found within the
plant; the most prominent of which is Tetrahydrocannabinol (THC) (Fischedick et al.,
2010). Cannabinoids are psychoactive substances which act upon the CB1
receptors in the brain responsible for functions such as: motor activity; emotion,
sensory perception and automatic / endocrine functions (Leonard, 2003). It is also
thought that the interaction of the cannabinoids with the CB1 receptors can strongly
reduce pain responses within the spinal cord, brain and sensory neurons (Leonard,
2003). The relevant class within this study is terpenes, volatile organic compounds
(VOCs) which are synthesised and stored within herbaceous plants (Borge et al.,
2016). VOCs are defined as being carbon based chemicals which easily evaporate,
an example of a group of VOCs is terpenes (Minnesota Department of Health, 2016).
Terpenes are classed as mono- or sesqui- terpenes according to the number of
isoprene (C5H8) groups there are within the molecule, for example monoterpenes
and sesquiterpenes are commonly C10H16 and C15H24, respectively (Encyclopaedia
Page 6 of 37
Britannica Inc., 2016). Borge et al. (2016) explains that the diversity of terpenes
varies between plants, depending upon factors such as; maturity of the plant,
environmental conditions, and the general composition of the plant itself.
Table 1. Commonly found terpenes within the headspace of Cannabis sativa,
adapted from Casano et al. (2011).
CompoundChemical
FormulaType of Terpene
Percentage found in
cannabis headspace
(average)
β-Myrcene C10H16 Monoterpene 46.1 +/- 2.6
α-Pinene C10H16 Monoterpene 7.3 +/- 1.3
α-Terpinolene C10H16 Monoterpene 10.2 +/- 1.8
Limonene C10H16 Monoterpene 7.3 +/- 1.3
β-Ocimene C10H16 Monoterpene 6.6 +/- 0.7
β-Pinene C10H16 Monoterpene 6.1 +/- 0.4
α-Terpinene C10H16 Monoterpene 3.6 +/- 1.0
β-
CaryophylleneC15H24 Sesquiterpene 1.2 +/- 0.2
α-
PhellandreneC10H16 Monoterpene 0.7 +/- 0.1
Δ-3-Carene C10H16 Monoterpene 0.6 +/- 0.1
Many investigations into the odour profiles of cannabis, such as those conducted by
Rice and Koziel (2015), Marchini et al. (2014) and Da Porto, Decorti and Natolino
(2014), use Solid Phase Microextraction (SPME) as a method of extracting the
volatile compounds such as those seen in Table 1. This is the use of a fused silica
fibre coated with a layer of a silica such as Polydimethylsiloxane. The fibre coating is
extremely important in the effectiveness of the SPME method, and therefore the fibre
coating is designed specifically for the desired analytes (Bicchi, Drigo and Rubiolo,
2000). This fibre is exposed to the vaporous headspace for a predetermined time
and temperature allowing compounds within the headspace to absorb into the silica
layer. Once equilibrium has been reached between the sample and the fibre coating,
the fibre is injected into the manual injection port of the gas-chromatographer – mass
spectrometer (GC-MS) (Pawlinszyn, 1997). Exposure of the fibre to a high
Page 7 of 37
temperature causes the compounds to desorb allowing for identification (Sporkert
and Pragst, 2000). Within this investigation, static headspace analysis coupled with
GC-MS was utilised, this was due to it being a much faster, simpler, more efficient
and environmentally friendly method of sampling (Cai et al., 2016). This involves the
sampling of the gas phase whilst in equilibrium with either a solid or liquid phase,
once equilibrium is achieved a sample of the headspace / gas phase is extracted for
analysis (Restek, 2000). Another method used in the extraction of headspace
compounds is Thermal Desorption, this is similar to SPME and static headspace in
that it is a simple and rapid method (Kuwayama et al., 2007). There are three
different methods used in thermal desorption, these are: indirect heat; indirect fired
and direct fired – these are different methods of heating the sample to volatilise the
VOCs (VertaseFLI, 2016).
Sigma Pseudo Marijuana Formulation is a trademarked product of Sigma-Aldrich Co.
LLC, and is used as a substitute for controlled substances within the training of drug
detection dogs. It is stated that the formulation is designed to mimic the odour of
cannabis. Sigma Aldrich has provided no evidence as to the odour profile of the
formulation, however Rice and Koziel (2015) states that the composition is listed as:
Pyrogenic Collodial Silica (1%), Cellulose (98.5%), Butane-2,3-diol (0.4%), and p-
mentha-1,4-diene (0.1%). They go on to claim that all of their “Sigma Pseudo Canine
Training Aids” are being used by dozens of agencies in the training of detection
dogs, however, no data pertaining to the odour of the formulation is given.
The aim of the investigation was to identify odour compounds within Sigma Pseudo
Marijuana Scent and to compare it to the odour profile of the Cannabis plant. The
odour profiles of both the pseudo formulation and that of the cannabis plant were
used to determine if the pseudo cannabis scent is the most effective training aid for
drug detection dogs, and to establish whether a more efficient alternative is
conceivable.
Page 8 of 37
Experimental
Reagents and materials
The following reagents were procured from Sigma Aldrich®: limonene standard, β-
myrcene standard, Δ-3-carene standard, frankincense standard, cannabis burn oil
standard, cannabis scented soap oil standard, cannabis scented candle oil.
Laboratory cannabis oil was prepared within the laboratory using cannabis plant
material provided by Cleveland Police.
Preparation of laboratory cannabis oil
A single cannabis leaf was removed from the plant provided by the Cleveland Police,
placed into a headspace vial filled with sunflower oil and sealed. The cannabis leaf /
oil combination was left for several months to allow the essential oils within the
cannabis matrix to transfer into the oil.
Preparation of standards for analysis
Laboratory cannabis oil was prepared by extracting 100μl of the oil from the vial
using a Gilson pipette, the sample was placed into a fresh headspace vial, capped
and sealed. Limonene, β-myrcene, frankincense, cannabis burning oil, cannabis
scented soap oil and cannabis scented candle oil were all prepared by extracting 1μl
of the sample using a Gilson pipette and placing it into individual, fresh headspace
vials. The headspace vials were all capped and sealed.
HS-GC-MS analysis
The GC-MS analysis was performed using Perkin Elmer Clarus 500 GC system
linked to a Perkin Elmer TurboMatrix 40 Trap Headspace sampler. The detector
used was a Perkin Elmer Clarus 500 mass spectrometer with a Zebron ZB-5MS
capillary column (30m x 0.25mm x 0.25μm). The carrier gas was 99.999% Helium.
The analyses were performed using Total Ion Count (TIC) mode. Sample volume of
1μl was injected into split mode (20:1). Injector temperature was set to 320°C. Initial
carrier flow was 1ml/min, initial oven temperature was set to 60°C held for 5 min,
ramped to 250°C at 10°C/min and held for 11 min.
Page 9 of 37
Testing of Laboratory Cannabis Oil with Drug Detection Dogs
The laboratory cannabis oil was tested using a trained law enforcement drug
detection dog supplied by the canine unit of Cleveland Police, using standard
training methods known to the dog.
Results
Dried cannabis leaf was analysed using HS-GC-MS in order to create a comparison
against the pseudo scent produced by Sigma Aldrich. The percentage of different
compounds found within the headspace of the dried cannabis leaf was calculated
using peak area in order to determine the overall composition. Frankincense
standards, cannabis burning oil standards, cannabis scented soap oil standards and
cannabis scented candle oil standards were all analysed using HS-GC-MS in order
to compare against the true cannabis leaf and against the pseudo scent. The
analysis of all but frankincense produced two peaks in common with dried cannabis
leaf and one peak in common with the pseudo scent, these peaks were identified as
α-pinene, β-pinene and γ-cymene, respectively. Frankincense produced a profile
with five peaks in common with dried cannabis leaf which were identified as; α-
pinene, β-pinene, β-myrcene, limonene and β-caryophyllene. Two peaks were also
identified to correspond to peaks found within the profile of the pseudo scent, which
was identified as γ-cymene and γ-terpinene. The laboratory prepared cannabis oil
originally produced a chromatogram similar to that of the dried cannabis leaf,
however further analysis was not able to reproduce the initial results.
The laboratory cannabis oil was tested using trained law enforcement drug detection
dogs. The dog responded positively to the cannabis oil, signalling to its handler that it
detected the cannabis scent.
Page 10 of 37
Figure 2. Gas Chromatogram of Dried Cannabis Leaf
Table 2. Total percentage of compounds within the headspace of Dried Cannabis Leaf
Peak Retention Time (Mins) Peak Area Total Percentage
(%) Identification
7.19 2502738 19.83% α-Pinene7.65 436276 3.46% Camphene8.33 1265399 10.02% β-Pinene8.53 1331218 10.55% β-Myrcene9.50 2533314 20.07% Limonene9.79 331889 2.63% β-Ocimene
10.87 654371 5.18% Linalool11.35 918579 7.28% Fenchol11.50 231983 1.84% Trans-2-pinanol12.32 101420 0.80% Borneol12.67 168043 1.33% α-Terpineol15.99 691196 5.48% β-Caryophyllene
16.04 105919 0.84% Trans-α-Bergamotene
16.49 195067 1.55% α-Humulene17.54 172193 1.36% δ-Cadinene17.59 282870 2.24% γ-Cadinene
*Unidentified compounds accounted for 5.55% of the total headspace
Analysis of the dried cannabis leaf provided a profile which displayed good
chromatography, shown in Figure 2. Using the chromatogram, percentages of each
Page 11 of 37
1.50 3.50 5.50 7.50 9.50 11.50 13.50 15.50 17.50 19.50 21.50 23.50 25.50 27.50 29.50 31.50 33.50Time0
100
%
0
100
%
pseudo b Scan EI+ TIC
3.14e7Area
10.09;93;829591
9.41119
302105
1.4684
1161363.65207
13776
7.97281
6003
5.7976
4110
33.9797
13806
22.0897
7180
19.1797
6056
14.0589
5305
10.28146
8763
15.6497
3506
16.73106
8223
27.9392
2076
26.9073
3085
25.80102
3768
31.96150
5235
29.52125
4988
30.26102
8303
34.9573
3143
Dried plant b Scan EI+ TIC
9.50e7Area
9.48;93;2483137
7.1893
2488809
1.4891
591665 6.3584
32805
3.63207
30854
11.3681
90714416.00133
65965911.5093
21534515.67
9128504
17.58161
254912 32.5573
170426
26.4991
20540
33.9491
96277
Peak Area (Mv)
Time (Minutes)
compound were calculated using peak areas to create an odour profile of sixteen
compounds which can be seen in Table 2. It was found that the highest percentage
compound found within the headspace was Limonene, composing 20.07% of the
total headspace. The lowest identifiable compound was calculated to be Borneol,
composing 0.80% of the total headspace. Each of the peaks were identified using
Restek (2016) and NIST Webbook (2016).
Figure 3. Gas chromatogram of Sigma Aldrich® marijuana scent formulation
Analysis of the Sigma Aldrich® marijuana scent formulation produced a
chromatogram which displayed good chromatography, shown in Figure 3. Using the
chromatogram, percentages were calculated using peak areas, an odour profile was
created for the pseudo scent which can be seen in Table 3. Only two identifiable
compounds were found within the pseudo scent profile, the more prominent of the
two was found to be γ-terpinene which accounted for 71.25% of the overall
Page 12 of 37
1.50 3.50 5.50 7.50 9.50 11.50 13.50 15.50 17.50 19.50 21.50 23.50 25.50 27.50 29.50 31.50 33.50Time0
100
%
0
100
%
pseudo b Scan EI+ TIC
3.14e7Area
10.09;93;829591
9.41119
302105
1.4684
1161363.65207
13776
7.97281
6003
5.7976
4110
33.9797
13806
22.0897
7180
19.1797
6056
14.0589
5305
10.28146
8763
15.6497
3506
16.73106
8223
27.9392
2076
26.9073
3085
25.80102
3768
31.96150
5235
29.52125
4988
30.26102
8303
34.9573
3143
Dried plant b Scan EI+ TIC
9.50e7Area
9.48;93;2483137
7.1893
2488809
1.4891
591665 6.3584
32805
3.63207
30854
11.3681
90714416.00133
65965911.5093
21534515.67
9128504
17.58161
254912 32.5573
170426
26.4991
20540
33.9491
96277
Peak Area (Mv)
Time (Minutes)
Peak Retention Time (mins) Peak Area Total Percentage (%) Identification
9.41 302105 25.95% ρ-Cymene10.09 829591 71.25% γ-Terpinene
*Unidentified compounds accounted for 2.80% of the total headspace
headspace. The second of the compounds identified within the headspace was
determined to be ρ-cymene, making up 25.95% of the overall profile. Each of the
peaks were identified using Restek (2016) and NIST Webbook (2016).
Table 3. Total percentage of compounds within the headspace of Sigma Aldrich Marijuana Scent Formulation
1.50 3.50 5.50 7.50 9.50 11.50 13.50 15.50 17.50 19.50 21.50 23.50 25.50 27.50 29.50 31.50 33.50Time0
100
%
0
100
%
pseudo b Scan EI+ TIC
3.14e7Area
10.09;93;829591
9.41119
302105
1.4684
1161363.65207
13776
7.97281
6003
5.7976
4110
33.9797
13806
22.0897
7180
19.1797
6056
14.0589
5305
10.28146
8763
15.6497
3506
16.73106
8223
27.9392
2076
26.9073
3085
25.80102
3768
31.96150
5235
29.52125
4988
30.26102
8303
34.9573
3143
Dried plant b Scan EI+ TIC
9.50e7Area
9.48;93;2483137
7.1893
2488809
1.4891
591665 6.3584
32805
3.63207
30854
11.3681
90714416.00133
65965911.5093
21534515.67
9128504
17.58161
254912 32.5573
170426
26.4991
20540
33.9491
96277
Figure 4. Gas chromatogram comparison of dried cannabis leaf and Sigma Aldrich®
marijuana scent formulation
Further examination into the odour profiles of both the dried cannabis leaf, and the
Sigma Aldrich® marijuana scent formulation showed no comparison between the
identifiable peaks of both profiles, this can be seen in Figure 4.
Page 13 of 37
Dried Cannabis Leaf
Sigma Aldrich® Marijuana Scent FormulationPeak Area (Mv)
Peak Area (Mv)
Time (Minutes)
Time (Minutes)
Discussion
The study found sixteen identifiable VOCs within the headspace of dried cannabis
leaf, this is a small number compared to literature from Marchini et al. (2014) who
reported a total number of 186 constituents within their samples and Rice (2015)
who reported 233. However, the studies by Marchini et al. (2014) and Rice and
Koziel (2015) used an SPME method in conjunction with HS-GC-MS. A study by
Pfannkoch and Whitecavage (2016) showed that SPME can prove to be ten to fifty
times more sensitive than headspace analysis, this is, however, dependent upon the
fibre coating being used. This loss of sensitivity from using the headspace method
could explain the inability to detect further VOCs. HS-GC-MS analysis of dried
cannabis leaf also found limonene to be the most dominant VOC within the sample
(20.07%). The study by Marchini et al. (2014) analysed different strains of cannabis
herbs which found varying levels of limonene between the samples from 0.83% -
8.26%. In comparison, a study by Hood, Dames and Barry (1973) showed the
headspace as being 5.4% limonene, and the largest percentage of the headspace
was α-pinene at 55.5%, in comparison to this study which showed α-pinene as
composing 19.83% of the headspace. A further study by Rothschild, Bergstrom and
Wangberg (2005) also showed a varying limonene percentage within the headspace
of different plants (0%-18.6%). The obvious differences between the percentages of
each of the cannabis samples used within each of these studies shows an obvious
difference in headspace composition between strains of cannabis. This difference
shows how complex a synthetic training aid would have to be in order to ensure the
detection of the many different varieties of cannabis which are currently available.
This study compared the headspace of dried cannabis leaf (the most likely form to
be found in the search for illicit cannabis), to the Sigma Aldrich® marijuana
formulation which is designed to be used in the training of drug detection dogs. The
analysis showed no evidence to suggest the pseudo cannabis scent would be an
effective training aid for dogs, due to the complete lack of corresponding peaks
between the chromatograms produced for both substances. The pseudo scent
produced two identifiable peaks at 9.41 and 10.09 mins which were identified as ρ-
cymene and γ-terpinene, respectively. These two terpenes were not found within the
cannabis sample this study analysed, however, studies by Hillig (2004), Hood,
Page 14 of 37
Dames and Barry (1973), and Ross and ElSohly (1996) identified γ-terpinene but not
ρ-cymene. Restek (2016) provides an elution order and chromatogram of terpenes
within cannabis which shows both ρ-cymene and γ-terpinene as compounds found
within the headspace of cannabis. This is supported by a study by Marchini et al.
(2014) which also shows the two compounds as having been found within the
headspace. As previously stated, there is an obvious difference in terpene
composition between strains and even individual plants, this could be the reason as
to why this study did not find the two peaks present in the pseudo scent, within the
cannabis (Hillig, 2004). Again, this also could be down to the method in which the
headspace was extracted, it could be possible that the compounds are within this
particular plant, but are undetectable due to the restrains of static headspace
analysis. However, with such a variety of studies which either do or do not find ρ-
cymene and/or γ-terpinene, it can be said that it is impractical to use these particular
VOCs within a training aid used specifically to train dogs to locate cannabis.
Especially compounds which despite being found within the plants, are not of high
concentrations. For example, the study by Marchini et al. (2014) found the
concentration of ρ-cymene within the headspace to range from trace amounts to
0.33%, an insignificant amount in comparison to other VOCs.
As previously stated, the odour profile of the pseudo scent varies greatly from the
odour profile of the dried cannabis leaf. A study by Macias, Harper and Furton (2008)
showed the use of the pseudo scent in field experiments with certified law
enforcement drug detection dogs. The results of the investigation determined that
the pseudo scent was not reliably detected. This was confirmed within a study by
Rice and Koziel (2015) which also stated that 1g of Sigma Pseudo Marijuana scent
is not a representative odour mimic for the illicit samples of marijuana that were
tested during their investigation. The study by Macias, Harper and Furton (2008)
states that this may be due to the training aid not producing the same volatile odour
as the illicit cannabis product. Should any drug detection canines be trained upon the
pseudo scent, it is highly likely that they are not efficiently detecting hidden stores of
cannabis. This possibility has repercussions in law enforcement wherever these
dogs are being utilised, as a larger amount of illicit cannabis could possibly be
transported without detection, contributing to the already high usage of cannabis
worldwide. The study also goes on to describe a lack of response to a mixture of the
Page 15 of 37
most prominent terpenes found within the headspace of cannabis (mixtures were
composed of α-pinene, β-pinene, myrcene, limonene and β-caryophyllene). The
study suggests that the lack of response is due to a short amount of time in which
the headspace is detectable by the dogs and that the longer the retention time of the
compound, the slower the rate of dissipation is. It is necessary to further study the
drug detection dogs themselves, to determine what it is the dog is honing in on when
it detects cannabis. This could be done by testing the dogs upon individual
components of the headspace to identify the exact substance(s) that the dog is
smelling. Using this information in relation to the two compounds (ρ-cymene and γ-
terpinene) found within the pseudo scent which have relatively short retention times;
they are still not a sufficient choice to have as a training aid for the detection of
cannabis.
To create a suitable synthetic training aid for dogs in the detection of cannabis,
several components are important; it should first be determined whether or not dogs
are honing in on a particular compound or upon the cannabis odour profile as a
whole. Secondly, a large variety of cannabis strains would need to be analysed in
order to create an average percentage of each compound found within the plant,
from this a “general” odour profile for cannabis could be determined. A general
profile for cannabis could, in theory, be used in order to manufacture a synthetic
cannabis training aid which is more specific to the cannabis plant. Another method
that was explored in the search for an alternative training aid was a laboratory
produced cannabis oil. Preliminary testing upon the cannabis oil produced a profile
comparable to that of the cannabis leaf, however further testing failed to reproduce
these results. An explanation for the lack of reproducibility is currently not fully
understood, however it is thought to be caused by the VOCs being trapped within the
oil and is not being efficiently separated. As the oil was also tested using headspace
analysis, it may be an issue with the method which could be solved by using a more
sensitive method such as SPME or thermal desorption. A study by Lerch and
Hasselbach (2014) describes the use of thermal desorption in conjunction with slitted
microvials. This technique allows for the important volatile compounds within the oil
to be transferred to the GC-MS whilst leaving the non-volatile oil matrix behind,
preventing contamination of the sample. Using this technique it may be possible to
truly analyse the profile of the laboratory produced cannabis oil, and allow further
Page 16 of 37
study into the possible use of it as a new training aid for drug detection dogs. Also,
despite the failure to produce good chromatography results, the oil tested positive
during preliminary field tests with a law enforcement drug detection dog. This
suggests that the oil may be a better choice than the pseudo scent as the study by
Macias, Harper and Furton (2008) reported that no dogs responded to the pseudo
scent. However, there is a large variation in concentrations of terpenes within
different strains of cannabis plants (Hillig, 2004). This is suggestive that different
strains of cannabis would need to be used in order for the drug detection dogs to be
able to detect them, as the study by Macias, Harper and Furton (2008) proved that
dogs do not respond to the main constituents of cannabis when they are in the
wrong concentrations.
This study was based upon the odour emitted directly from the cannabis leaf, which
in real-life scenarios is not often the case. The cannabis is commonly found
packaged in plastic, Johnson (2016) states that “plastic is a huge part of the
packaging dynamic in the cannabis industry and it’s only getting bigger”. Rice and
Koziel (2015) used three different forms of packaging to test the effect of packaging
upon the odour profile (a US military style duffel bag, a sample of dried cannabis with
no packaging and a plastic zip top sandwich bag). 134 volatiles were detected
through all three of the packaging, however over time key components such as β-
caryophyllene were no longer detected and after 68 hours only 51 compounds were
detected through the packaging. This effect of time on the odour profile of cannabis
certainly suggests further study into the degradation of any surrogate scents, also it
suggests that different formulas need to be created to allow for this difference in
compounds at different stages of degradation.
ConclusionFrom this investigation it can be stated that, in agreement with previous studies, the
cannabis leaf has a complex mixture of mono and sesquiterpenes, which makes the
synthesis of a substitute compound a difficult task to undertake. Considering this, the
lack of a corresponding odour profile produced by the pseudo scent in comparison to
the odour profile of the dried cannabis leaf, with the consideration that different
cannabis strains do not always have the terpenes seen within the pseudo scent,
Page 17 of 37
suggests that the Sigma Aldrich marijuana formulation is an unsuitable tool in the
training of drug detection dogs and that a suitable alternative is necessary.
This study determined that the synthesis of a cannabis pseudo scent, other than the
formulation produced by Sigma Aldrich® is possible. However, it is complex in the
different variables that will need to be considered such as; the percentages of
terpenes, the variation in the number of compounds found in the headspace over
time, as well as the number of compounds released through packaging. As the odour
profile of cannabis is thought to change over time, this could be suggestive that a
range of training aids need to be produced in order to account for this change in the
profile, to ensure that the dogs are sensing the cannabis whether it has been stored
for a short or long period of time.
The laboratory prepared cannabis oil is a definite possibility as a replacement for the
pseudo scent. However, greater investigation needs to be conducted upon the
substance, a detailed and reproducible odour profile is required to determine its
similarity to the cannabis leaf. Further investigation is also required into the
degradation of the sample, to determine whether or not the number of compounds
released in the headspace does not reduce over time, and if they do, is this
mimicked by the cannabis leaf.
Despite the strong results produced using the headspace technique, when these
results are compared to those of studies which used an SPME method, it is clear to
see that SPME is the stronger and more sensitive method. In order to create a more
detailed odour profile of both the dried cannabis and possibly the pseudo scent, it
would be important for future studies to implement the use of SPME. The level of
detail gained from the use of SPME greatly outweighs the simplicity and efficiency of
the headspace method.
This study also determined that most commercially bought scents which proclaim
that they are cannabis scented are, in terms of odour, fall short of matching the smell
produced by the true cannabis leaf. The odour profiles of the scents produced very
few compounds in common with cannabis, and as previously mentioned, it is the
complexity of cannabis which produces its distinctive odour.
Page 18 of 37
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Appendices
Page 23 of 37
Gas Chromatogram for Headspace Analysis of Dried Plant
Page 24 of 37
Time (Minutes)
Peak Area (Mv)
Gas Chromatogram for Headspace Analysis of Myrcene Standard
Page 25 of 37
1.50
3.50
5.50
7.50
9.50
11.5
013
.50
15.5
017
.50
19.5
021
.50
23.5
025
.50
27.5
029
.50
31.5
033
.50
Tim
e0
100 %
drie
d pl
ant a
Scan
EI+
TI
C4.
77e7
9.49
;93
7.17 93
1.48 91
0.01 91
3.65
207
8.52 93
7.64 93
11.3
581
10.8
871
9.80 93
16.0
091
11.4
981
12.6
893
17.5
916
1
17.5
491
34.7
773
26.9
073
25.0
497
1.50
3.50
5.50
7.50
9.50
11.5
013
.50
15.5
017
.50
19.5
021
.50
23.5
025
.50
27.5
029
.50
31.5
033
.50
Tim
e0
100 %
myr
cene
aS
can
EI+
T
IC6.
92e9
8.59
;93 8.94 93
Time (Minutes)
Gas Chromatogram for Headspace Analysis of Laboratory Cannabis Oil
Page 26 of 37
Peak Area (Mv)
1.50
3.50
5.50
7.50
9.50
11.5
013
.50
15.5
017
.50
19.5
021
.50
23.5
025
.50
27.5
029
.50
31.5
033
.50
Tim
e0
100 %
oil a
Sca
n E
I+
TIC
8.55
e61.
48;9
1
0.06 91
8.53 93
3.66
207
1.76 91
4.41 91
7.17 91
5.61 91
33.6
997
32.8
591
28.9
820
79.
57 9119
.17
9711
.45
9115
.36
9112
.70
91
16.0
291
17.4
691
25.4
191
20.1
491
30.1
091
Peak Area (Mv)
Time (Minutes)
Gas Chromatogram of Headspace Analysis of Laboratory Cannabis Oil
Page 27 of 37
Time (Minutes)
Gas Chromatogram of Headspace Analysis of Limonene Standard
Page 28 of 37
1.50
3.50
5.50
7.50
9.50
11.5
013
.50
15.5
017
.50
19.5
021
.50
23.5
025
.50
27.5
029
.50
31.5
033
.50
Tim
e0
100 %
lim a
Sca
n EI
+ T
IC9.
90e9
9.54
;93
Time (Minutes)
Gas Chromatogram of Headspace Analysis of Frankincense Standard
Page 29 of 37
Peak Area (Mv)
1.50
3.50
5.50
7.50
9.50
11.5
013
.50
15.5
017
.50
19.5
021
.50
23.5
025
.50
27.5
029
.50
31.5
033
.50
Tim
e0
100 %
fran
aSc
an E
I+
TIC
6.62
e97.
21;9
3
6.97 93
9.49 93
9.42
119
8.19 93
16.0
093
Peak Area (Mv)
Time (Minutes)
Gas Chromatogram of Headspace Analysis of “Cannabis” Burning Oil Standard
Page 30 of 37
1.50
3.50
5.50
7.50
9.50
11.5
013
.50
15.5
017
.50
19.5
021
.50
23.5
025
.50
27.5
029
.50
31.5
033
.50
Tim
e0
100 %
burn
ing
aSc
an E
I+
TIC
3.75
e815
.20;
82
14.7
082
7.19 93
6.96 93
8.34 93
9.42
119
18.1
014
9
16.1
310
517
.03
107
Peak Area (Mv)
Time (Minutes)
Gas Chromatogram of Headspace Analysis of “Cannabis” Soap Oil Standard
Page 31 of 37
1.50
3.50
5.50
7.50
9.50
11.5
013
.50
15.5
017
.50
19.5
021
.50
23.5
025
.50
27.5
029
.50
31.5
033
.50
Tim
e0
100 %
soap
Sca
n E
I+
TIC
9.56
e87.
19;9
3
6.96 93
15.1
982
14.6
982
8.34 93
9.41
119
18.0
914
916
.12
105
Peak Area (Mv)
Time (Minutes)
Gas Chromatogram of Headspace Analysis of “Cannabis” Candle Oil Standard
Page 32 of 37
1.50
3.50
5.50
7.50
9.50
11.5
013
.50
15.5
017
.50
19.5
021
.50
23.5
025
.50
27.5
029
.50
31.5
033
.50
Tim
e0
100 %
cand
leSc
an E
I+
TIC
1.35
e97.
19;9
3
6.96 93
15.2
082
14.7
082
8.34 93
9.42
119
18.1
014
916
.13
105
Time (Minutes)
Gas Chromatogram of Headspace Analysis of Caryophyllene Oxide Standard
Page 33 of 37
Peak Area (Mv)
1.50
3.50
5.50
7.50
9.50
11.5
013
.50
15.5
017
.50
19.5
021
.50
23.5
025
.50
27.5
029
.50
31.5
033
.50
Tim
e0
100 %
cary
o ox
idSc
an E
I+
TIC
6.60
e818
.16;
79
Time (Minutes)
Gas Chromatogram of Headspace Analysis of Δ-3-Carene Standard
Page 34 of 37
Peak Area (Mv)
1.50
3.50
5.50
7.50
9.50
11.5
013
.50
15.5
017
.50
19.5
021
.50
23.5
025
.50
27.5
029
.50
31.5
033
.50
Tim
e0
100 %
care
ne a
Sca
n E
I+
TIC
1.95
e10
9.08
;79
Peak Area (Mv)
Time (Minutes)
Gas Chromatogram of Headspace Analysis of Cannabis Leaf Removed from Laboratory Cannabis Oil
Page 35 of 37
1.50
3.50
5.50
7.50
9.50
11.5
013
.50
15.5
017
.50
19.5
021
.50
23.5
025
.50
27.5
029
.50
31.5
033
.50
Tim
e0
100 %
wet
pla
nt a
Sca
n E
I+
TIC
2.75
e715
.99;
93
1.46 84
9.59 81
8.54 93
15.8
894
16.0
593
17.5
816
1
17.5
316
1
Peak Area (Mv)
Time (Minutes)
Complete Table of Compounds and their Percentages Pertaining to the Headspace of the Dried Cannabis Leaf
Peak Retention Time (Mins)
Peak Area
Total Percentage
(%)Identification
3.64 35489 0.28% Unknown (91, 105, 207 mz)6.35 38790 0.31% Unknown (72, 82, 84, 91, 105 mz)6.94 13460 0.11% Unknown (77, 91, 105 mz)7.19 2502738 19.83% α-Pinene7.41 11753 0.09% Unknown (91, 105 mz)7.65 436276 3.46% Camphene7.98 15228 0.12% Unknown (83, 91, 105, 281 mz)8.33 1265399 10.02% β-Pinene8.53 1331218 10.55% β-Myrcene8.98 15629 0.12% Unknown (77, 91, 93, 105 mz)9.20 14215 0.11% Unknown (77, 91, 93, 105, 121,207 mz)9.50 2533314 20.07% Limonene9.79 331889 2.63% β-Ocimene10.08 14054 0.11% Unknown (91, 93, 105, 119 mz)10.34 55822 0.44% Unknown (81, 91, 94, 111, 217 mz)10.62 26588 0.21% Unknown (77, 91, 93, 105, 121, 136 mz)10.79 86577 0.69% Unknown (81, 91, 152 mz)10.87 654371 5.18% Linalool11.35 918579 7.28% Fenchol11.50 231983 1.84% Trans-2-pinanol12.06 20021 0.16% Unknown (91, 96, 105, 111, 115 mz)12.32 101420 0.80% Borneol12.67 168043 1.33% α-Terpineol15.24 26652 0.21% Unknown (91, 105, 119, 120, 161, 207 mz)15.67 33388 0.26% Unknown (91, 105, 108, 133 mz)15.79 24354 0.19% Unknown (91, 93, 105, 119 mz)15.88 16671 0.13% Unknown (91, 94, 105 mz)15.99 691196 5.48% β-Caryophyllene16.04 105919 0.84% Trans-α-Bergamotene16.22 53050 0.42% Unknown (79, 91, 93, 105, 120, 133 mz)16.49 195067 1.55% α-Humulene16.84 13985 0.11% Unknown (91, 105, 119, 133 mz)16.94 43785 0.35% Unknown (79, 91, 105,161 mz)17.02 43785 0.35% Unknown (79, 91, 93, 105 mz)17.21 33702 0.27% Unknown (79, 91, 105, 121 mz)17.31 37189 0.29% Unknown (79, 91, 105, 119, 161, 204 mz)17.42 25813 0.20% Unknown (91, 105, 119 mz)17.54 172193 1.36% δ-Cadinene17.59 282870 2.24% γ-Cadinene
Page 36 of 37
Page 37 of 37