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1. 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.
2. Page 2 of 37
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.
Contents
Acknowledgments...................................................................................................................... 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
3. Page 3 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.
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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 volatile vapours, such as those exhibited
in Table 1, emitted from the drug (Hood, Dames and Barry, 1973). However, drug
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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).
Figure 1. The training process for drug detection dogs, adapted from Sorg, Rebmann
and David (2000)
Step 1:
The dog is
introduced to the
scentand is taught
to develop a
committmentto
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 scentis 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
6. Page 6 of 37
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 Britannica Inc., 2016).
Borge et al. (2016) explains that the diversity of terpenes varies between plants,
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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).
Compound
Chemical
Formula
Type 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-
Caryophyllene
C15H24 Sesquiterpene 1.2 +/- 0.2
α-
Phellandrene
C10H16 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
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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.
9. Page 9 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.
10. Page 10 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.
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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-Pinene
7.65 436276 3.46% Camphene
8.33 1265399 10.02% β-Pinene
8.53 1331218 10.55% β-Myrcene
9.50 2533314 20.07% Limonene
9.79 331889 2.63% β-Ocimene
10.87 654371 5.18% Linalool
11.35 918579 7.28% Fenchol
11.50 231983 1.84% Trans-2-pinanol
12.32 101420 0.80% Borneol
12.67 168043 1.33% α-Terpineol
15.99 691196 5.48% β-Caryophyllene
16.04 105919 0.84%
Trans-α-
Bergamotene
16.49 195067 1.55% α-Humulene
17.54 172193 1.36% δ-Cadinene
17.59 282870 2.24% γ-Cadinene
*Unidentified compounds accounted for 5.55% of the total headspace
Peak
Area
(Mv)
Time (Minutes)
12. Page 12 of 37
Analysis of the dried cannabis leaf provided a profile which displayed good
chromatography, shown in Figure 2. Using the chromatogram, percentages of each
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 headspace. The second of the
Peak Retention
Time (mins)
Peak Area
Total Percentage (%)
Identification
9.41 302105 25.95% ρ-Cymene
10.09 829591 71.25% γ-Terpinene
*Unidentified compounds accounted for 2.80% of the total headspace
Peak
Area
(Mv)
Time (Minutes)
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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
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.
Dried Cannabis Leaf
Sigma Aldrich® Marijuana Scent Formulation
Peak
Area
(Mv)
Peak
Area
(Mv)
Time (Minutes)
Time (Minutes)
14. Page 14 of 37
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, Dames and Barry
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(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 most prominent
terpenes found within the headspace of cannabis (mixtures were composed of α-
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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 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
17. Page 17 of 37
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.
Conclusion
From 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,
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
18. Page 18 of 37
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.
19. Page 19 of 37
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