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Identification of volatile organic chemicals in diseased and damaged
vegetables.
James Charles Fothergill
MSc by research
August 2016
Abstract
The main objective of this project was to see if volatile organic compounds could be identified in unprocessed vegetables. Once the identification of possible marker compounds was completed, a variety of vegetables with either disease, damage or physiological changes associated with aging were analysed.
Potatoes, onions and broccoli were analysed, these vegetables were chosen by some of the project’s co-funders as being economically important
The sample of vegetable was placed in an airtight container and the sample was allowed to equilibrate at room temperature for 45 minutes, then a solid phase microextraction fibre (SPME) was inserted through the valve and the fibre exposed for 50 minutes. The fibre was then retracted into its holder prior to analysis using a Gas Chromatograph/Mass Spectrometer (GC/MS). The sample was then analysed using the GC/MS and the peaks identified using the built-in library in the instrument software.
In the case of potatoes, no changes in volatiles were observed during the sprouting process or in the case of physical damage. However, changes were identified in the case of potatoes with a variety of diseases, these changes in volatiles were the same regardless of the disease present. The compounds found for potatoes were trimethylamine, 2-butanone, 2,3-butanedione, 3-hydroxy-2-butanone and 2,3-butanediol.
The analysis of onions showed differences in the volatiles between uninfected/control samples and those with thick neck, basal rot, internal rot and neck rot. The compounds found were 1-propanethiol, methyl propyl sulphide, methyl propyl disulphide and dipropyl sulphide However, the change in volatiles could not be used to differentiate between the different rots.
For broccoli differences were found between control and samples with wet rot. The compounds found included dimethyl sulphide, dimethyl disulphide, dimethyl trisulphide and 1-undecene. The differences were then used to investigate these changes in volatiles in relation to use by dates of pre-packaged broccoli, this investigation showed none of the marker compounds at significant levels for those samples analysed before or on their use by date.
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Certificate of originality
This is to certify that I am responsible for the work submitted in this thesis, that the original work
is my own, except where specified in the acknowledgements and in references, and that neither
the thesis nor the original work contained therein has been previously submitted to any
institution for a degree.
Signature: _______________________________
Name: _______________________________
Date: _______________________________
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Acknowledgements
I would like to express my gratitude to my supervisors, Professor Tony Taylor and Dr Bukola
Daramola, for their useful comments, contributions and most importantly for their faith in my
ability to carry out this work. I would also like to thank Professor Val Braybrooks and everybody at
the National Centre for Food Manufacturing at the University of Lincoln’s Holbeach campus for
funding my masters.
Thanks to the Technology Strategy Board for funding the work which lead to this project and to
the Potato council Sutton bridge storage research centre and Produce World for supplying the
samples.
My thanks also to Dr William Hayes for teaching me how to use the GC/MS system used in this
project and for allowing me instrument time when I needed it, also to Dr Ciara Casey and all the
staff at the Lindsey centre on the Riseholme campus of the University of Lincoln.
Final thanks to my family for their love, support and encouragement.
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Table of contents
Contents
Abstract............................................................................................................................................ II
Certificate of originality...................................................................................................................III
Acknowledgements.......................................................................................................................... IV
Table of contents..............................................................................................................................V
1. Introduction..............................................................................................................................1
2. Literature review.......................................................................................................................4
2.1 Vegetables.............................................................................................................................4
2.1.1 Potatoes............................................................................................................................4
2.1.2 Onions...............................................................................................................................4
2.1.3 Broccoli..............................................................................................................................4
2.1.4 Economic impact of disease..............................................................................................5
2.2 Instrumental Techniques.......................................................................................................5
2.2.1 Headspace analysis............................................................................................................5
2.2.1.1 SPME.................................................................................................................................6
2.2.2 GC/MS...............................................................................................................................8
2.2.2.1 Gas Chromatograph...........................................................................................................8
2.2.2.2 Gas Chromatograph Inlet..................................................................................................9
2.2.2.3 Gas Chromatograph column..............................................................................................9
2.2.2.4 GC Detector.....................................................................................................................10
2.2.3 Mass Spectrometer.........................................................................................................11
2.2.3.1 Ion source........................................................................................................................11
2.2.3.2 Mass analyser..................................................................................................................12
2.2.3.3 Detector..........................................................................................................................13
2.3 Volatile Organic Compounds found in potatoes..................................................................13
2.3.1 Sprouting.........................................................................................................................15
2.3.2 Diseases...........................................................................................................................15
2.3.2.1 Soft rot.............................................................................................................................15
2.3.2.2 Dry rot.............................................................................................................................16
2.3.2.3 Gangrene.........................................................................................................................17
2.3.2.4 Rubbery rot.....................................................................................................................17
2.3.2.5 Black spot (dot)................................................................................................................17
2.3.2.6 Pit rot...............................................................................................................................18
2.3.2.7 Blackheart........................................................................................................................19
2.4 Volatile Organic Compounds (VOCs) found in Onions.........................................................19
V
2.4.1 Diseases...........................................................................................................................19
2.4.1.1 Neck Rot..........................................................................................................................19
2.4.1.2 Basal Rot..........................................................................................................................20
2.4.1.3 Internal Rot......................................................................................................................20
2.4.1.4 Thick Neck.......................................................................................................................21
2.5 Volatile Organic Compounds found in Broccoli...................................................................22
2.5.1 Wet Rot...........................................................................................................................22
3. Methodology...........................................................................................................................24
3.1 Sampling methodology........................................................................................................24
3.2 Sampling procedure............................................................................................................26
3.3 Gas Chromatography methodology.....................................................................................26
3.4 Mass Spectrometer methodology.......................................................................................27
3.5 Data analysis methodology.................................................................................................27
4. Results and discussion.............................................................................................................28
4.1 Potatoes..............................................................................................................................28
4.1.1 Methods and Samples.....................................................................................................30
4.1.2 Potato results and discussion..........................................................................................31
4.1.2.1 Results of non-sprouting and sprouting sample batches.................................................31
4.1.2.2 Results and discussion of damaged sample batches.......................................................40
4.1.2.3 Results and discussion of infected sample batches.........................................................45
4.1.2.4 Effect of time and temperature on bacterial soft rot.......................................................52
4.1.3 Conclusion.......................................................................................................................53
4.2 Onions.................................................................................................................................55
4.2.1 Methods and samples.....................................................................................................55
4.2.2 Onions results and discussion..........................................................................................55
4.2.2.1 Control samples...............................................................................................................55
4.2.2.2 Basal rot...........................................................................................................................58
4.2.2.3 Internal Rot......................................................................................................................60
4.2.2.4 Neck Rot..........................................................................................................................62
4.2.2.5 Thick Neck.......................................................................................................................64
4.2.2.6 Comparison of rots and thick neck..................................................................................66
4.2.3 Discussion........................................................................................................................68
4.2.4 Potential differentiation of onion diseases......................................................................69
4.2.5 Conclusion.......................................................................................................................74
4.3 Broccoli................................................................................................................................75
4.3.1 Methods and samples.....................................................................................................75
4.3.2 Broccoli results and discussion........................................................................................76
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4.3.2.1 Control sample................................................................................................................76
4.3.2.2 Slight wet rot...................................................................................................................78
4.3.2.3 Severe wet rot.................................................................................................................80
4.3.2.4 Extent of wet rot in broccoli............................................................................................82
4.3.2.5 Use by date of broccoli samples......................................................................................82
4.3.3 Conclusion.......................................................................................................................83
5. Conclusions.............................................................................................................................84
6. Further work............................................................................................................................85
6.1 Replicate samples................................................................................................................85
6.2 Deliberate infection of all samples......................................................................................85
6.3 Climatic control...................................................................................................................85
6.4 Larger sampling container...................................................................................................85
6.5 Use of glass sampling container..........................................................................................85
7. References...............................................................................................................................86
VII
1. Introduction
There is a sizeable economic and societal impact from the diseases of vegetables, which includes
the vegetables infected during storage. This has been made more challenging by the restriction in
the use of pesticides that have been identified as being potentially harmful to either humans or
the environment in general. Currently identification of diseases is carried out visually and can be
both time consuming and expensive, therefore, if it is viable to identify diseases electronically
there could be financial benefits for the producers in reducing spoilage. Secondary infection can
occur when infected vegetables are stored with uninfected vegetables and conditions allow for
the transmission of the disease, these secondary infections could spoil an entire storage area if
not identified. Also as the vegetables age during storage, do they produce chemicals which render
the vegetable either inedible or unsaleable due to either changes in appearance or taste? This
reduces the food security of a nation and requires increases in the import of food, potentially
from less developed countries, which can suppress their development increasing the potential for
famine and driving up emigration from these nations.
This importance of early detection of crop diseases cannot be overstated, with some of the
diseases having the potential to wipe out an entire storage facility. So if a means of objectively
analysing potato samples to look for these disease is possible then reduction on the reliance of
subjective testing by humans could have the possibility of reducing losses in storage, as the
testing is not reliant on the training and skill level of the testing operative.
This work is looking, partly, at vegetables in storage, therefore it is necessary to carry out any
chemical analysis on the vegetable in the state that they would be stored in. This presents a
challenge as most vegetables in their natural state are not particularly odiferous, to try and
overcome this issue, several vegetables will be analysed at the same time. This is a major
departure from most of the work carried out on vegetables which has focussed on either the
impact of cooking methods on the taste of the vegetable or the identification of compounds
found within the vegetable by the analysis of homogenised samples.
This project ran concurrently with another project looking at the feasibility of using an electronic
nose to try and identify if any diseases and or aging has occurred. The work presented here
underpins the electronic nose project by providing target compounds for the electronic nose
sensors to be built to identify. Limitations on the type of compounds amenable to detection by
electronic nose means that only those compounds with functional groups, such as aldehydes,
ketones, amines and sulphides will be examined in greater detail.
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The first part of this project was the identification of volatile organic compounds (VOCs) from
vegetables. The vegetables were placed into a sealed containers which were modified with the
addition of a needle port. A solid phase microextraction fibre (SPME), within a suitable housing,
was then inserted through the needle port and then exposed to the headspace above the
vegetable for a set amount of time. This will allow the VOCs to be trapped on a SPME fibre, which
adsorbs the VOCs from the headspace in the sampling container. This adds to the complexity of
the work as it introduces a further variable in the sampling process. The key variables in the
sample preparation process are the surface area of the vegetables under examination, the volume
of the headspace remaining in the sampling container and length of time that the SPME fibre is
exposed for.
As the VOCs are volatile, the analysis will be carried out by gas chromatography-mass
spectrometry (GC-MS), this will allow for the separation of the VOCs on a capillary column prior to
analysis. This involved inserting the fibre into a heated injection port to desorb the VOCs which
are then separated on a fused silica capillary column. The compounds transit through the column
into a mass spectrometer where they are ionised by an electron beam, then they are repelled into
the mass spectrometer where separation by mass to charge ratio occurs. Compounds detected
will then be identified by comparison to reference spectra contained within the operating
software of the GC-MS. The mass spectra of all the peaks found within a total ion chromatogram
were automatically search by the operating software, the list of compounds produced by the
software was then manually checked and any compounds with a poor match quality, less than
80%, were excluded.
Once identified, the VOCs associated with each vegetable and condition will be examined to try
and identify any marker compounds for these vegetables and conditions. These identified
compounds will then be used to re-process the data acquired for the vegetables by selectively
extracting out the ions associated with each compound at their identified retention times. This
enables small peaks associated with these compounds to be detected, where they might be
missed if only the full scan data is used.
The aims of this project are to identify the volatile organic compounds found within a variety of
vegetables, paying particular attention to those compounds that would be amenable to detection
by electronic nose, for example, organic compounds that contain either a heteroatom or a degree
of unsaturated. To apply the VOCs found for each vegetable to conditions associated to each type
of vegetable, to try and identify any specific marker compounds for the conditions, either
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indicators of freshness or spoilage. To look for trends in the levels of marker compounds to see if
relative responses of these compounds can be used in the identification of particular diseases.
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2. Literature review
2.1 Vegetables
2.1.1 Potatoes
The potato (Solanum tuberosum L.) is a member of the Solanacaea family of plants, this family
incorporates a wide diversity of flowering plants including deadly nightshade and the tomato
(UNFAO, 2009), and it produces branching stems with pairs of ovate leaves. The modern or
“European” potato is derived from a cultivated variety first grown in the Chilca canyon south of
Lima, Peru and had spread worldwide by the 1800’s (Natural History Museum, undated).
The edible part of the potato is the tuber; these tubers are produced from the underground stems
(Rhizomes) of the plant and occur when the stem becomes enlarged at the tip. The biological
purpose of this tuber is to store starch to provide the energy required to regrow the plant in the
following growing season; this starch is stored with specialized cells in the tuber known as storage
parenchyma.
Potatoes are comprised of 80% water, 18% carbohydrate and 2% protein and they are a good
source of vitamin C. The most abundant carbohydrate in potatoes is starch (United States
Department of Agriculture, undated).
There is a vast variety of potato cultivars, which show a diverse mix of skin colour and size, but
most importantly in their texture in relation to the differing cooking methods that can be used for
potatoes.
2.1.2 Onions
The onion (Allium cepa) is another vegetable that is cultivated and eaten worldwide, but they are
more widely associated with cooler climates as prolonged hot weather can cause them to “bolt”,
where the plant’s energy is directed towards producing a flowering stem rather than production
of the bulb. The cultivation of onions has been going on for at least 5000 years, and its medicinal
properties have been written about in most ancient civilisations (The National Onion Association,
2011). In 2010, annual consumption of onions was estimated to be 13.67 pounds per person; this
means that the onion is the sixth most eaten vegetable in the world (Gills Onions, 2010).
2.1.3 Broccoli
Broccoli is a member of the Brassicaceae family which also includes cauliflower and cabbage. The
parts of the plant most typically eaten are the immature flower and the stem supporting them
(Botanical online, undated). Broccoli being more associated with moderate to cool climate can be
grown year-round, however it is considered to be at its best between January and March
(MDidea, 2014). There are only three main varieties grown; Calabrese, which has thick stems and
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florets; Sprouting, which has thinner stems and small individual heads and Romanesco, which has
small cone shaped heads in a spiral formation (New World Encyclopaedia, 2008).
2.1.4 Economic impact of disease
Potatoes and Onions are grown in large quantities around the world. Data for 2012 puts an
estimate of over 365 million tonnes of potatoes and over 82 million tonnes of onions were
produced (United Nations, 2013). Production in the United Kingdom for the same period was just
over 4.5 million tonnes for potatoes and 370 thousand tonnes of onions. A value for total Broccoli
production is hard to come by as the statistics clump all the Brassicae together (United Nations,
2013).
Prices for potatoes in 2012 in the United Kingdom were approximately £200/tonne (Clayton,
2012), giving a UK value of £900 million for potato production. Storage losses in potatoes in the
USA have been on average 7.5% (Olsen et al., 2006), which if applied to the UK production figures
for 2012 would have an economic cost of approximately £67.5 million.
Onion values are harder to come by as there is a much greater variation in the value of the crop,
for example, in 2014 the wholesale onion value in the United Kingdom varied from £0.38/kg to
£0.25/kg (DEFRA, 2014). Based upon a mean value of £0.30/kg, then the onion crop in the United
Kingdom is worth in the region of £110 million. The effect of Wet (or Spear) rot on broccoli was
estimated in 2012 to be over £15 million per year in the UK (HDC, 2012).
2.2 Instrumental Techniques
2.2.1 Headspace analysis
There are several ways of analysing volatile organic compounds from gaseous samples (Kim and
Reineccius, 2002), they are Solid Phase Micro-Extraction (SPME), Adsorption onto a solid material
such as activated carbon, static headspace and dynamic headspace. As this project is based upon
the identification of volatiles given off by vegetables, some of these techniques can be discounted
relatively easily.
Dynamic headspace requires a sample through which an inert gas can be bubbled, the headspace
above the sample is removed throughout the sampling process and any volatile compounds are
cryo-focussed prior to analysis. As this work aims to analyse whole and untreated vegetables it is
not possible to use this approach.
Static headspace involves heating and agitating a sample for a set time period to establish
equilibrium between the sample and the headspace, then a small air sample is taken and analysed
directly by GC/MS. The disadvantage of this technique for the work presented here is that the
sensitivity of this technique is better suited to the analysis of known compounds where a specific
detector can be used, as the identification of compounds is under investigation there may not be
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the required sensitivity for the identification of unknown compounds and for this reason static
headspace has been discounted.
Adsorption onto a stationary phase such as Activated Carbon has the advantage over static
headspace in that there is a concentration effect which would allow for the identification of more
compounds, and there are two ways of recovering the unknown compounds from the stationary
absorbent. The recovery methods are either the extraction of unknowns using carbon disulphide
or the thermal desorption of the unknowns. Chemical recovery could introduce more interfering
compounds which would then have to be identified and discounted, with the possibility that they
would obscure some important components from the vegetables being analysed. Thermal
recovery from the sampling tubes requires specialised equipment which was not available within
the laboratory where this work was carried out.
Solid Phase Micro-Extraction allows for a pre-concentration step and although there is a thermal
desorption step this can be carried out on any GC instrument that has a heated injector capable of
taking a standard syringe needle. For this combination of pre-concentration and ease of use, Solid
Phase Micro-Extraction was chosen as the sampling technique.
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2.2.1.1 SPME
Solid Phase Micro-Extraction (SPME) is a sampling technique that can be used for the
concentration of analytes from liquid and gaseous samples (Pawliszyn, 2000). The principle is that
a small amount of the extracting material, bound onto a solid support or fibre, is inserted into the
sampling vessel. This fibre is then exposed to the sample matrix, either by positioning it below the
liquid surface or in the headspace above a liquid or solid sample.This project has solid samples
and therefore only this aspect of headspace sampling by SPME will be discussed. Headspace
sampling by SPME is a three phase system. There is the interaction between the sample and the
headspace and the interaction between the headspace and the sampling fibre. This leads to two
competing thermodynamic systems, the sample and sampling fibre both seek to achieve
equilibrium with the headspace (Tipler, 2013).
Figure 1. SPME Fibre holder (Chromedia analytical sciences, undated)
The SPME fibre can be housed within a fibre holder, as shown in Figure 1; this allows the needle
to pierce the sample container prior to depression of the plunger which will then expose the fibre
to the headspace above the sample under analysis.
Molecules within the headspace of the sample are either adsorbed or absorbed onto the fibre
coating, the process is dependent on the nature of the fibre coating (Wercinski and Pawliszyn,
1999). The nonpolar polydimethylsiloxane (PDMS) and the polar polyacrylate (PA) fibre both rely
on absorption for the retention of analytes. Other fibre types such as
polydimethylsiloxane/divinylbenzene (PDMS/DVB) retain analytes via adsorption. Absorption is
the process whereby the analytes dissolve in the coating of the fibre; this process occurs at a
uniform rate and is independent of temperature. Adsorption is a surface effect; the analytes are
either trapped or form chemical bonds at the surface of the material. For an adsorption process it
is important, therefore, to have a material that is porous with a high surface area
(Chromatography today, 2014). Therefore, one of the most critical factors in SPME is the choice of
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fibre. There are a large variety of fibres available, these fibre coatings range from non-polar such
as polydimethylsiloxane to the polar polyethylene glycol. It is important that the polarity of the
fibre matches the polarity range of the analytes expected to be found in the sample.
Table 1. SPME fibres and range of application (Supelco, undated)
The organic compounds that were expected to be found were volatiles compounds, some with
heteroatomic functional group, it was decided that the 65µm
polydimethylsiloxane/divinylbenzene fibre would offer the best compatibility for the type of
compounds that were expected to be present. Bicchi et al. (2000) examined the influence of fibre
coating in the analysis of aromatic and medicinal plants and concluded that PDMS-DVB 65µm was
one of the most effective fibres overall.
2.2.2 GC/MS
The combination of Gas chromatography/mass spectrometry has provided a sensitive and robust
system for the analysis of thermally stable, volatile and semi-volatile organic chemicals. This two
part system uses a series of components within each part to provide the separation and
identification of organic chemicals.
2.2.2.1 Gas Chromatograph
The Gas chromatograph is comprised of an inlet, an oven containing the separation column and
the detector, a simple schematic is shown in figure 2. There is a variety of inlets that can be used
with the gas chromatograph, and the type selected for use is dependent on the nature of the
sample being introduced to the system and the concentration of the analytes within the sample.
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Figure 2. Simple schematic of a Gas chromatograph (Urban, 2009)
2.2.2.2 Gas Chromatograph Inlet
For the work carried out in this project a split/splitless injector was used as the analytes were
being introduced by SPME fibre. As the SPME fibre is fragile it is not practicable to introduce the
sample directly on the column, so by inserting the fibre into the liner of a split/splitless injector it
can be protected from harm. The liner in a split/splitless injector is usually kept at a high
temperature to promote volatilisation of all the components contained within the sample. The
split/splitless injector has two separate modes of operation. In split mode a high flow of carrier
gas (usually helium) is passed through the injector liner and most of this flow is diverted to waste,
this can be useful in the analysis of concentrated samples as most of the sample can be sent to
waste so that the column and detector are not overloaded. In splitless mode, the entire sample
injected is passed through the column to the detector, this is normally used when samples
containing low levels of the desired analytes are being analysed. In splitless mode it is normal for
the split vent to be opened after a pre-determined time to minimise the amount of less volatile
material going on the column (Klee and Sandra, 2005).
2.2.2.3 Gas Chromatograph column
The earliest gas chromatography columns were based upon column chromatography designs and
normally incorporated a large bore column (metal or glass) containing packing material used for
column chromatography. Packed columns are still used today, but are normally reserved for
either gas analysis or when robustness and/or reproducibility are the main priorities (Proovost,
undated). Where resolution is the main requirement of the column then it is normal to use a
fused silica capillary column. The fused silica column is comprised of three parts, the fused silica
structure of the column, the stationary phase and a polyimide coating, as shown in figure 3. The
polyimide coating is used to allow the column to be coiled up in a frame; this allows the gas
chromatograph’s oven to be made smaller, without breaking due to any imperfections in the
structure of the fused silica. The interior surface of the fused silica column is normally chemically
treated to remove any active site that could affect the chromatographic performance of the
9
column, and to provide the stationary phase. The choice of which stationary phase to use is
primarily determined by the nature of the analytes that are expected to be found in the samples
of interest.
Figure 3. Cross section of a capillary GC column (Taylor and Hinshaw, undated)
Of all the varieties of stationary phase used, the most common is polysiloxane based stationary
phases; these can be further chemically modified to produce a range of stationary phases with
differing polarities. The stationary phase has been further improved by the use of low-bleed
phases, such as arylenes, which reduce the amount of background noise attributable to the
column and also by the cross-linking of the polymer chains by covalent bonds. Current examples
such as the HP-5ms (Agilent Technologies) claim low bleed levels and column inertness, this is
achieved by cross bonding diphenyl dimethyl polysiloxane. (Agilent Technologies, 2012).
2.2.2.4 GC Detector
The choice of detector to use would depend on the nature of the analytes and system
requirements such as operating environment. A wide range of GC detectors exist ranging from
non-destructive detector such as the thermal conductivity detector , through ionising detector
such as the electron capture detector and the nitrogen-phosphorus detector through to
destructive detectors such as the mass spectrometer (Bhanot, 2012). When choosing a detector
to use, consideration should be given to the following areas; the chemical nature of the analytes;
do they contain heteroatoms such as chlorine or phosphorus; the expected working range
required, for example the flame ionisation detector has a very large linear range in comparison to
other detectors and are the analytes unknown prior to analysis (Klee, undated). A summary of the
characteristics is listed in Table 2.
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Table 2. Attributes and performance of common GC detectors (Klee, undated)
For the analysis of unknown compounds the choice narrows down to nuclear magnetic resonance
(NMR), Fourier transform infrared (FTIR) and mass spectroscopy (MS). There are large libraries
available containing the mass spectra of thousands of volatile organic compounds. For this work a
mass spectrometer was the most appropriate choice as one of the main aims of the project was to
identify the volatile compounds given off by vegetables.
2.2.3 Mass Spectrometer
A mass spectrometer consists of three parts; the ion source, the mass analyser and the detector.
There are variations in each of the three components which then determine the size, cost and
application range of the mass spectrometer.
2.2.3.1 Ion source
The ion source is the part of the mass spectrometer that receives the column flow from the GC
and from the GC flow ionises analyte molecules which are then moved to the mass analyser. The
mass spectrometer used in this project utilised an electron impact source (EI).
11
Figure 4. Ion source schematic (Gates, 2008)
Figure 4 shows a schematic of an electron impact (EI) ion source. The EI source uses a stream of
electrons produced from a filament to interact with the GC column flow. The electron stream is
perpendicular to the GC column flow and would usually have a higher energy than the molecular
bond strengths of the analytes. This excess energy leads to ionisation and fragmentations
occurring within the ion source, these charged particles are then pushed towards the mass
analyser by a repeller. A repeller is an ion source component that is held at the same charge as
the ions produced in the source. The repeller is normally mounted perpendicular to both the
electron stream and the GC column flow (Scott, undated).
2.2.3.2 Mass analyser
The general principles for a mass analyser are to generate gas-phase ions, separate the ions based
on their mass to charge ratio and to measure the amount of each set of ions with the same mass
to charge ratio (Lee, 2005). There are several different types of mass analyser ranging from the
simple yet robust quadrupole to the highly mass accurate time of flight (TOF). A quadrupole mass
analyser was used for this project. The design of the quadrupole mass analyser is very simple, as
shown in figure 5.
Figure 5. Schematic of a quadrupole mass spectrometer (Shimadzu, 2015)
It consists of four parallel metal rods, preferably with a hyperbolic cross section, although
cylindrical cross sections have also been used. Each opposite pair of rods is connected electrically
and a radio frequency is applied between the two sets of rods. A constant direct current voltage is
applied and modified by the applied radio frequency. For a given combination of DC voltage and 12
modifying radio frequency, only ions with the corresponding stable beam path can pass through
the mass analyser to the detector (Silverstein et al., 2005). The effect of these applied voltages is
that one pair of rods acts as a high-pass mass filter, i.e. ions of a certain mass to charge ratio and
above, can pass through the quadrupoles. The other pair of rods act as a low-pass mass filter, the
combination of these two filters turns the quadrupole into a narrow-band filter during routine
operation (Skoog et al., 1998).
2.2.3.3 Detector
Mass spectrometers normally use either an electron multiplier or a photomultiplier to detect,
amplify and record the transmission of ions through the mass analyser. Although these two types
of multipliers operate in different ways they can be described using the same broad principles.
When an ion passes through the mass analyser it strikes the surface of a material which then
causes a number of secondary electrons to be emitted. The number of secondary electrons is
dependent on the nature of the incident ion and its energy, the angle of incidence and the
material used (SGE, 2015). In the case of the discrete dynode electron multiplier between 10 and
25 Plates can be used to achieve a signal factor increase of between 106 and 108 (Shimadzu,
undated), although operation at the upper end requires higher voltages and will lead to the
multiplier requiring replacement much quicker. A schematic of a discrete dynode electron
multiplier is shown in figure 6.
Figure 6. Discrete dynode electron multiplier (Shimadzu, undated)
2.3 Volatile Organic Compounds found in potatoes
The vast majority of work associated with flavour and odours in potatoes can be split into two
areas. The first is the analysis of homogenised potatoes to determine the chemical composition of
the potato; this would not be an option for this project as one of the main aims is too see if the
odour compounds would be applicable to technology transfer to hand held devices for use in the 13
field and as such the work is required to be carried out on whole tubers. The other main area of
most work is the changes in flavour and odour compounds that occur during various cooking
processes. Again this approach would not be applicable to this project.
Majcher and Jeleń (2009) examined a number of factors relating to the odour compounds
obtained from extruded potato snacks and included work that showed that excess SPME fibre
exposure can lead to a loss in response. From their data presented they inferred that exposure
times between 45 and 60 minutes was optimal.
There is a large amount of published work looking at the area of volatile organic compounds
(VOCs) in potatoes; some of the earliest work by Buttery et al. (1970) examined the volatiles
obtained from the steam distillation of cut strips of potatoes under two different sets of
conditions. These yielded two markedly different sets of compounds which the author notes have
smells associated with raw and cooked potatoes. Further work was carried out to identify some of
the stronger smelling, but low concentration, compounds such as 2-methoxy-3-isopropylpyrazine
identified by Buttery and Ling (1973), this work used small cubes of raw potato, from which the
compounds were extracted via steam distillation. Similar work was carried out by Gumbmann and
Burr (1964), which was specifically focussed on the production of sulphur containing compounds.
This body of work has provided a starting point for a lot of the subsequent work carried out on
potatoes but is still reliant on the processing of samples prior to the extraction of volatiles being
carried out.
Boyd (1984) examined various extraction and sampling techniques, before deciding on the use of
steam distillation under vacuum for the extraction of potato volatiles. Some work was carried out
using Gas chromatography-flame ionisation detection (GC-FID) examining the effect of sprouting
on the volatile production from two different varieties of potato. Unfortunately this work was not
did not include Gas chromatography-mass spectroscopy (GC-MS) identification of the volatiles
due to time constraints. The authors found twenty to thirty unidentified compounds that could be
related to sprouting. Part of the planned work for this project will be to examine the effect of the
sprouting process on the VOCs produced.
Petersen et al. (1988) looked at the differences in VOCs between raw and cooked potatoes, again
using homogenised samples of both. Whilst the extraction techniques used are different from the
planned extraction technique in this project, it does provide a starting point for the determination
and identification of volatiles that could be found in raw potatoes. The main VOCs identified were
2-methylbutanol, 2-pentylfuran, 1-pentanol, hexanoic acid, hexanal and (E)-2-octenal. It also
provides the possibility to examine whether differences between homogenised and whole tubers
can be attributed to the sample processing techniques used. Additionally Petersen et al. (1999)
looked at potato off-flavour in boiled potatoes and part of the results found that there are
significant variations in the VOC composition depending on the age of the potatoes used to
14
prepare the mash. The most significant changes in compound concentration were for hexanal and
1-pentanol, which showed twenty five and fivefold increase respectively. Therefore any work in
this area must bear in mind that as work continues throughout the year, there will be a natural
variation in the starting concentrations of the compounds. This conclusion can be supported by
Duckham et al. (2002) who examined these differences in VOCs of baked potatoes made from 2, 3
and 8 month old potatoes. The results from this work show a degree of agreement with the
previously discussed work, but additionally identified a significant increase in 2-methylbutanal and
3-methylbutanal concentrations over the storage periods examined.
2.3.1 Sprouting
The biological function of the potato tuber is as a starch storage reservoir for the future
production of a new plant, tuber growth follows a set pattern and once the mature tuber attains
its final size it enters a period of dormancy (Aksenova et al., 2013). The tubers are physiologically
dormant at harvest and for an unspecified time post-harvest (Destefano-Beltran et al., 2006). The
first stage of sprouting is the development of “eyes” which are the buds from which the next
season’s growth will occur (Western potato council, 2003), the sprouts then develop from the
eyes of the tubers and the first phase of growth ends with emergence from the soil of the sprout.
Destefano-Beltran et al. (2006) examined the effect of abscisic acid (ABA) on dormancy status of
potato tubers and found that ABA is metabolized by the tuber during dormancy and that the
levels of ABA usually decline during storage. The ABA content is affected by a variety of
environmental, developmental and phytohormonal stimuli. This results in the dormant phase of
the tuber being unpredictable.
Coleman (2000) reviewed potential ways of examining and describing tuber aging at the
morphological, physiological and biochemical levels, however his review found no single theory
that has achieved complete acceptance for the start of the sprouting process.
2.3.2 Diseases
De Lacy Costello et al. (1999) carried out a series of experiments dealing with the infection of
potatoes with bacteria associated with causing soft rot under typical storage conditions. This VOC
work required long setup time, 12 hours equilibration, and whilst it gives good data as to the type
of compounds that could be expected to be found which included aldehydes, ketones, alcohols,
organic acids, sulphides and aliphatic hydrocarbons, its application towards a rapid assessment
technique is limited, however it did also identify differences between the volatile organic
compounds produced by various bacteria. Laothawornkitkul et al. (2010) looked at VOCs as
markers of late blight in potatoes but also relied on long sampling times, 14 hours in this case, but
did identify (E)-2-hexenal, 5-ethyl-2(5H)-furanone and benzene-ethanol. Lyew et al. (2001) also
15
carried out work looking at the VOCs produced from potatoes infected with soft rot, with repeat
determinations being carried out at set time intervals up to 144 hours; however the majority of
volatiles produced were not identified. The only tentative identification provided was that one
peak was possibly a furan.
2.3.2.1 Soft rot
Soft rot in potatoes is the result of a bacterial infection by Pectobacterium carotovora, which can
present itself at any stage during the growing cycle of the potato plant. If the infection occurs
during the growing stage of the plant, then this bacteria can also cause blackleg. This disease is
more common in wet seasons or if the tubers are harvested from wet fields (FERA, 2009). When
the tuber is infected then soft rot develops which leads to blackening and softening of the tissue,
see plate 1.
Plate 1. Potato tuber with soft rot (FERA, 2009)
Rutolo et al (2014) examined soft rot in potatoes and showed that there is a difference in the VOC
profile of infected and uninfected potatoes, however, the technique used for the analysis (Field
asymmetric ion mobility spectrometry) provide no information on the chemicals present. Whilst
there are no chemical treatments available for the prevention of this disease, good housekeeping
in storage can help prevent its spread by minimising any physical damage and by storing in a
facility with good ventilation to allow the quick drying of the tubers and to prevent any
condensation forming (ADHB Potato council, 2013).
2.3.2.2 Dry rot
Dry rot is a major fungal disease, caused by various Fusarium spp., associated with the storage of
potato, although infection is unlikely to occur without some form of wound on the tuber (ADHB,
undated). Treatment with thiabendazole can prove effective in some cases, although when the
dry rot is caused by Fusarium sulphureum then this treatment is ineffective. Again preventative
measures when storing tubers, such as proper temperature control and good handling procedures
can prevent infection, as shown in plate 2, from developing (Peters and Lee, 2004).
16
Plate 2. Fusarium dry rot (ADHB, undated)
2.3.2.3 Gangrene
Gangrene is a fungal disease caused by Phoma foveata which rots both the surface and flesh of
the tuber during storage, as shown in plate 3, and is evidenced by irregular, dark sunken areas on
the surface of the tuber and can also present as large rotted cavities once the tuber is cut (JBA
seed potatoes, undated). Infection is normally through unhealed wounds in the skin.
Plate 3. Gangrene (CSR Sutton Bridge, undated a)
2.3.2.4 Rubbery rot
Rubbery rot is a fungal disease cause by Geotrichum candidum which causes the tuber to have a
rubbery texture, a sour milk and/or vinegar smell and discolouration of the cut flesh within a few
hours to give a greyish hue, see plate 4.
17
Plate 4.Rubbery rot (Crop diagnostic centre, 2010)
Rubbery rot is a soil born disease which is most commonly seen in tubers from water logged soils
combined with warm temperatures close to harvest (United Nations, 2014).
2.3.2.5 Black spot (dot)
Black spot is a mild disease that show as irregular shaped silvery blemishes on the surface of the
tuber and is caused by Colletotrichum coccodes. Small pinhead sized black dots, see plate 5, are
found on the tubers, either visually or with the aid of a magnifying glass (United Nations, 2014).
Plate 5. Black spot (Wharton, 2013)
2.3.2.6 Pit rot
Pit rot can be caused by either a lack of CO2 during storage or by infection with Pectobacterium
atrosepticum, both routes cause a collapse of the surface tissue around the small openings in the
tuber surface (lenticels) that allow respiration, as shown in plate 6. A secondary wound barrier is
produced in response to this collapse, which if this barrier is breached will result in soft rot (Wale,
2014).
18
Plate 6. Pit rot (CSR Sutton Bridge, undated b)
2.3.2.7 Blackheart
Blackheart is a physiological condition that results from lack of oxygen due to either compacted
soil during warm weather, or poor storage facilities which have either insufficient airflow or are
over-packed (Wharton, 2013). This results in the blackening of the potato tissue from the inside
out, as shown in plate 7.
Plate 7. Blackheart
19
2.4 Volatile Organic Compounds (VOCs) found in Onions
As described above, the majority of work associated with the analysis of VOCs in onions and other
alliums has been concentrated on homogenised samples. Coley-Smith (1986), conducted a
comparison of flavour and odour compounds present in onions, leeks and garlic. The main
reported volatile compounds were methyl, propyl and propenyl sulphides. These results have
been further enhanced by Colina-Coca et al. (2013), who found the compounds described above
as well as propanethiol, 2-methyl-2-butanal, 2-methyl-2-pentanal and 2-pentylfuran.
2.4.1 Diseases
Three diseases of onions were studied during this project. They were Neck rot, Basal rot and
Internal rot. The first two of these are fungal diseases caused by Botrytis allii and Fusarium
oxysporum respectively. Internal rot is a bacterial disease caused by Pseudomonas aeruginosa
(The American Phytopathological Society). A condition known as Thick neck was also examined.
2.4.1.1 Neck Rot
Onion Neck Rot has the potential for significant economic impact, on a crop of onions, during
post-harvest storage. The bacterial infection is believed to be carried on the seeds and results in
the cotelydon leaves becoming infected during germination, but any plants that have been
infected normally remain symptomless during the growing cycle. Plate 8 shows a cross section of
an onion infected with Neck Rot.
Plate 8. Onion Neck Rot (OMAFRA, 1995)
High levels of Neck Rot can be found in stores and there are a number of contributory factors,
most of these related to inadequate drying of the crop prior to storage (Royal Horticultural
Society, undated). Maude et al. (1984), demonstrated that direct harvesting, with mechanical
removal of the foliage (topping), of onion crops followed by post-harvest drying at ambient
temperatures (c. 18°C) resulted in an increase in the incidence of onion neck rot (Botrytis allii).
20
2.4.1.2 Basal Rot
Fusarium oxysporum is a soil based fungus, which can survive in the soil for a long time.
Symptoms of Basal rot infection show during the growth cycle, with weak growth and wilting
being the most obvious above ground symptoms (Pacific Northwest Plant disease management
handbook, undated).Plate 9 shows a cross section of an onion infected with Basal rot.
Plate 9. Fusarium basal rot (OMAFRA, 1995)
2.4.1.3 Internal Rot
Pseudomonas aeruginosa has been identified as the dominant bacterium isolated from onions
affected by internal brown rot (Watson and Hale, 1984). However, there is a number of other
bacterium that can cause internal soft rot in onions (American Phytopathological Society,
undated). Plate 10 shows a cross section of an onion infected with internal rot.
Plate 10. Bacterial soft rot/internal rot (Schwartz, 2008)
2.4.1.4 Thick Neck
Thick neck whilst not a disease increases the chance of disease affecting the plant. Thick neck can
be a result of the plant growing slowly and the soil lacking in phosphorus (The National Gardening
Association, undated). As the neck of the bulb does not close fully, as shown in plate 11, the bulb
21
does not dry properly and this provides more favourable conditions for the establishment of
infection. Plate 12 shows an onion with a closed neck.
Plate 11. Thick necked onion (Pollygarter, 2014)
Plate 12. Normal onion (Pollygarter, 2014)
2.5 Volatile Organic Compounds found in Broccoli
Buttery (1976) analysed the steam volatile oils in Broccoli and identified amongst the major
components dimethyl disulphide, dimethyl trisulphide and hexen-3-ol, although the majority of
22
components identified were isothiocyanates and cyanide which are likely to be present due to the
pre-treatment of the samples and the extraction technique used. Forney et al. (1991) examined
the volatiles produced by broccoli under anaerobic conditions and found methanethiol, dimethyl
sulphide, ethyl acetate, ethanol and dimethyl disulphide. Kremr et al. (2015) carried out a
comparison of volatile sulphur compounds from a variety of plants, including broccoli, and for
broccoli found that the three main species detectable by HS-SPME were found to be dimethyl
sulphide, dimethyl disulphide and dimethyl trisulphide.
2.5.1 Wet Rot
Wet Rot in Broccoli can also be known as either Spear rot or Head rot can is caused by a complex
mix of bacterial pathogens including, but not limited to, Erwinia Carotovora and Pseudomonas
fluorescens (Koike et al., 2007). Plate 13 shows an example of bacterial head rot in broccoli, the
initial symptoms on immature broccoli heads show as small group of water soaked unopened
flower heads (Koike et al., 2010).
Plate 13. Bacterial head rot of broccoli (Koike et al., 2010)
23
3. Methodology
3.1 Sampling methodology
A number of techniques are available for use in the analysis of volatiles emitted by vegetables
during the aging process and/or disease. In this project one of the main aims is to identify those
compounds that could then be detectable using an electronic nose to examine the whole
vegetable.
This requirement to use no sample pre-treatment of the vegetable and a hand held “sniffer”
device immediately rules out some extraction techniques. For example, dicing and
homogenization of the sample follow by a solvent extraction technique, whilst giving good
sensitivity, reproducibility and quantifiable results, is not amenable to transfer to the electronic
nose.
The decision to use solid phase micro-extraction (SPME) allows the headspace around the whole
vegetables to be sampled in a controlled manner providing a sealed system can be constructed.
Most of the commercially available equipment for sampling of headspace by SPME is based
around small scale vials with a sealable screw cap. One of these commercially available screw caps
is produced by Supelco under the brand name Mininert®.
Plate 14. Mininert valves (Supelco, undated)
The Mininert valve provides a leak free seal with a replaceable rubber septum. As the Mininert
valve is designed for use with the Supelco SPME fibre holder, it made sense to use the two in
conjunction.
Consequently a leak free container had to be found or designed on which to mount the Mininert
valve. Ease of loading and having an adequate volume in which to place a representative sample
of the vegetables under question were essential considerations. The decision was taken to use
clip seal food containers for samples preparation, and a 2.3 litre square sided container was
chosen. The Mininert valve, shown in plate 14, was disassembled and the widest part of the valve
measured. A diameter of 12 mm was measured, so a 12 mm hole was drilled through the lid of
the storage container. The Mininert valve was reassembled in the lid of the container and sealed
in place using Evo Stik Epoxy rapid resin, as shown in plate 15. This sealant was chosen as it only
24
contains two components, epichlorohydrin and bisphenol A, neither of which are expected to be
seen in the samples, therefore the presence of either of the compounds can readily be attributed
to the sealant.
The main limitation of this design is the use of a plastic container, whilst the container is designed
to stored food in and as such should not leach high quantities of organic molecules; it was an
accepted design flaw that any analysis would not be particularly appropriate for aliphatic
hydrocarbons. However, since most short chain aliphatic hydrocarbons are not particularly
odiferous, it was decided that the ease of use and cleaning of this sampling apparatus outweighed
this acknowledged flaw, an example of the sampling container is shown in plate 16.
Plate 15. Sealed Mininert valve
Plate 16. Finished sampling container
25
The last remaining decision is which SPME fibre coating to use that would provide a good range
for molecular weight and compound polarity. Bicchi et al. (2000) examined the influence of fibre
coating in the analysis of aromatic and medicinal plants and concluded that PDMS-DVB 65µm was
one of the most effective fibres overall, this fibre is recommended for the analysis of volatiles with
a molecular weight range of 50 -300 (Supelco, undated). The majority of volatile compounds that
could reasonably be expected to give a significant odour belong to classes of compounds that
would be adsorbed by the PDMS/DVB fibre. These classes of compounds include alcohols,
aldehydes, hydrocarbons and amines. Brunton et al. (2000) examined a range of fibres for the
analysis of hexanal and pentanal in cooked turkey, and concluded that the PDMS/DVB fibre
provided the best mix of linearity, sensitivity and reproducibility. Carboxen/PDMS showed similar
sensitivity but a much larger capacity, although this was cancelled out by a much higher relative
standard deviation in the results obtained.
Lecanu et al. (2002) carried out analysis of the odour of surface ripened cheese, although in this
work the chosen fibre was Carbowax/Divinylbenzene (CAR/DVB), this was because of the ability of
this fibre to determine ketones which appears to have been the primary concern for this work.
However, when the results are examined from this work it shows that although there is less
sensitivity for ketone using a PDMS/DVB fibre, the PDMS/DVB fibre shows a good sensitivity
across multiple compound classes in comparison to the CAR/DVB.
3.2 Sampling procedure
Where possible a subsample of each vegetable type was transferred to the sampling container,
the lid sealed and the sample allowed to equilibrate for 10 minutes before the introduction of the
SPME fibre through the Mininert valve. The fibre was then exposed for 50 minutes before the
fibre was withdrawn prior to GC/MS analysis.
3.3 Gas Chromatography methodology
A GC/MS system (Shimadzu corporation, Model QP2010), equipped with a Split/Splitless injection
port which was operated in Splitless mode, at a constant temperature of 250°C, with a splitless
time of 1 minute after which time the split vent opened and any residual compounds were vented
from the injector.
Chromatographic separation was performed on a capillary column (30m x 0.25mm I.D., 0.25µm
film thickness, DB-5MS 5% Methyl Phenyl siloxane, Agilent 122-5532, Agilent Technologies,
Avondale, PA, USA). Helium (purity 99.999%) was used as a carrier gas, operating at a constant
flow of 1 ml/min. The temperature programme used was as follows: 40°C held for 1 minute, then
a temperature ramp of 10°C/min to 240°C with a final hold time of 10 minutes. The total analysis
time run time was 31 minutes.
26
3.4 Mass Spectrometer methodology
The mass spectrometer was operated in Electron impact (EI) ionization mode at 70eV using full
scan mode from m/z 35 to 500. The interface was maintained at a temperature of 240°C and the
source at a temperature of 200°C. Peaks found on the chromatographic trace were identified by
automated comparison of the mass spectra obtained with those stored in the National Institute
Standards and Technology (NIST) 2011 Mass Spectral library, compound identification was based
upon a minimum match quality of 80%. Table 3 shows a summary of the instrumental conditions
used
Table 3. GC-MS Operating conditions
Analysis method summaryCapillary column used DB-5MS 30m x 0.25mm, 0.25µm film thickness
Temperature programme 40°C (1min) → 240°C, at 10°C/min, hold 10 min
Carrier gas Helium, constant flow at 1ml/minInjector Splitless, 1 min initial time, T=250°CDetector Mass spectrometer, +EIScan range m/z 35 - 500
27
4. Results and discussion
4.1 Potatoes
The samples analysed comprised a mixture of sample types. Some batches were analysed to
determine if there was any change in the volatile composition based upon sprouting stage. Other
batches were analysed for volatile composition changes caused by either physical damage or by
disease. If composition changes are detected then these changes could form the basis of a
monitoring system that would allow for better management of stored potatoes by either
prioritising the use of potatoes that are starting to sprout or by the removal of infected potatoes
to avoid further contamination with the storage facility.
As the sample batches cover a variety of conditions, a single list of compounds detected across
the range of samples was collated, and this list was used to create a processing method in the
GC/MS software and all of the samples were reprocessed using this method.
Samples to be analysed for sprouting were supplied at three stages, these are, no sprouting, eyes
open (when the potato eyes have opened but no sprouts were visible) and sprouting, where
visible sprouts were observed. Plates 17, 18 and 19 show an example of each type of sprouting
Plates 17, 18 & 19. Potatoes with no sprouting, eyes open and sprouting (l-r)
The infected samples were prepared by puncturing the skin of the potato with an implement that
had previously been exposed to a solution containing the bacterial agent responsible for the
selected disease, this procedure was carried out by Potato council staff at the Sutton bridge
storage research centre. Mock inoculation samples were prepared by puncturing the skin of the
potato with a clean implement. Plates 20 & 21 show an example of a mock infected and infected
potato respectively.
28
Plates 20 & 21. Mock infected and infected potato (l-r)
The damaged samples were prepared by impacting the surface of the potato without breaking the
skin from either 60cm, for light/mild damage, or from 120cm for heavy/severe damage.
29
4.1.1 Methods and Samples
Twenty batches of samples of potatoes comprising one hundred and fourteen samples were
analysed between the 5th November 2013 and 29th July 2014 and are listed in table 4. All samples
were analysed by the procedure described in section 3.2 – 3.4.
Table 4. Potato samples analysed
Batch Number
Date of analysis
Total number of samples
Samples analysed
1 05/11/2013 7 Maris Piper, washed, No sprouting; Desiree, washed, No sprouting; King Edward, washed, No sprouting; King Edward, unwashed, No sprouting; King Edward, unwashed, Eyes open; King Edward, unwashed, Sprouting;King Edward (Different stock), unwashed, No sprouting.
2 11/11/2013 7 Desiree, soaked; Desiree, mock inoculation; Desiree, inoculated; Maris Piper, washed; Maris Piper, mock inoculation; Maris Piper, inoculated; Maris Piper, long term inoculation.
3 12/11/2013 9 Maris Piper, washed, No sprouting; Desiree, washed, No sprouting; King Edward, washed, No sprouting; King Edward, unwashed, No sprouting; King Edward, unwashed, Eyes open; King Edward, unwashed, Sprouting;King Edward (Different stock), unwashed, No sprouting; Maris Piper, inoculated, extended solvent delay; Maris Piper, inoculated, 10:1 split injection.
4 13/11/2013 6 Maris Piper, unwashed, no sprouting; Maris Piper, unwashed, eyes open; Maris Piper, unwashed, sprouting; Maris Piper, washed, no sprouting; Maris Piper, washed, eyes open; Maris Piper, washed, sprouting.
5 14/11/2013 3 SBCSR Desiree, soaked; SBCSR Desiree, mock inoculation; SBCSR Desiree, inoculated.
6 19/11/2013 6 Desiree, washed, no sprouting; Desiree, washed, eyes open; Desiree, washed, sprouting; King Edward, washed, no sprouting; King Edward, washed, eyes open; King Edward, washed, sprouting.
7 25/11/2013 6 Maris Piper, unwashed, no sprouting; Maris Piper, unwashed, eyes open; Maris Piper, unwashed, sprouting; Maris Piper, washed, no sprouting; Maris Piper, washed, eyes open; Maris Piper, washed, sprouting.
8 26/11/2013 7 Damaged, control; Damaged, slight damage; Damaged, severe damage; Diseased, control; Diseased, mock no fungi; Diseased, dry rot; Diseased, gangrene.
9 28/11/2013 3 Damaged, control; Damaged, slight damage; Damaged, severe damage.10 13/01/2014 7 Desiree, control; Desiree, mock inoculation; Desiree, dry rot; Desiree,
gangrene; Maris Piper, mock inoculation; Maris Piper, dry rot; Maris Piper, gangrene.
11 11/02/2014 7 Charlotte, healthy; Charlotte, black spot; Melody, no inoculation; Melody, mock inoculation; Melody, bacterial inoculation.
12 17/02/2014 3 Melody, no inoculation; Melody, mock inoculation; Melody, bacterial inoculation.
13 10/03/2014 6 Charlotte EK, healthy; Charlotte EK, gangrene; Melody LA, healthy; Melody LA, gangrene; Melody MD, healthy; Melody MD, rubbery.
14 11/03/2014 3 Melody MD, rubbery; Sunrise WC, washed, healthy; Sunrise WC, washed, pit rot.
15 17/03/2014 3 VR808 S342, no spouting; VR808 S342, eyes open; VR808 S342, sprouting.16 14/04/2014 6 Maris Piper, no damage; Maris Piper, light damage; Maris Piper, heavy
damage; Estima, no damage; Estima, light damage; Estima, heavy damage.17 29/04/2014 7 Potato BH1; Potato BH2; Potato BH3; Potato BH11; Potato 12; Potato 13;
Potato 14.18 07/07/2014 6 No damage; Mild damage 60cm; Severe damage 120cm; Analysed in
duplicate19 08/07/2014 7 Mock 240614; Infection 240614; Wash 270614; Mock 300614; Infection
300614; Mock 020714; Infection 020714.20 29/07/2014 7 Travel Blank; Mock 4°C 290714; Inoculated 4°C 290714; Mock 10°C 290714;
Inoculated 10°C 290714; Mock 20°C 290714; Inoculated 20°C 290714.
30
4.1.2 Potato results and discussion
There are three distinct groups of sample type present for the potato, so the results and
discussion will be sub-divided into these groups. The full batch results for all sample batches are
shown in appendix A.
The results for all the sample batches were analysed to determine the most prevalently occurring
volatile organic compounds, these compounds were then used to create a single processing
method that all of the sample batches were then re-processed against. The list of compounds
used to create the reprocessing method is shown in table 5. This list of components is in broad
agreement with Buttery et al. (1970), although that work was based of the steam distillation of
potato oil.
Table 5. Volatile organic compounds found in potatoes
Ret Time Compound1.57 Acetone1.78 2-Methylpropanal1.91 2-Butanone1.93 Acetic acid1.94 2,3-Butanedione2.34 3-Methylbutanal2.42 2-Methylbutanal2.45 1-Butanol2.80 3-Hydroxy-2-butanone3.13 1,2-Propanediol3.19 3-Methyl-1-butanol3.26 2-Methyl-1-butanol3.30 Dimethyl disulphide3.60 1-Pentanol3.75 2,3-Butanediol3.96 Hexanal5.12 1-Hexanol5.37 2-Heptanone5.53 Heptanal5.70 1-Octene6.20 2-Methyl-3-heptanone6.36 Benzaldehyde6.40 alpha-pinene6.92 6-Methyl-5-hepten-2-one7.02 2-Octanone7.22 Octanal7.45 3-Hexenyl acetate7.62 Fenchene7.75 2-Ethyl-1-hexanol7.89 Limonene8.87 Nonanal8.96 1-Undecene
10.24 2-Decanone10.43 Decanal
31
4.1.2.1 Results of non-sprouting and sprouting sample batches
A typical GC chromatogram for a sample, with no sprouting, with eyes open and with sprouting is
shown, respectively in figures 7, 8 and 9 (other examples are shown in appendix B).
32
Figure 7. TIC of Maris Piper, washed, no sprouting batch 1
33
Figure 8. King Edward, unwashed, eyes open batch 1
34
Figure 9. King Edward, unwashed, sprouting batch 1
35
The results from each sample type (no sprouting/eyes open/sprouting) and (washed/unwashed)
are combined to give an average value and a relative standard deviation for sample set and the
results are shown in tables 6 and 7 and figures 10 and 11.
Table 6. Average VOC results for washed potato samples (11 samples from 5 different cultivars)
Washed No Sprouting Washed Eyes Open Washed SproutingCompound Average area %RSD Average area %RSD Average area %RSDTrimethylamine 229 332 1801 139 0 -Acetone 51026 95 42385 129 56641 1022-Methylpropanal 1612 332 1358 224 1438 2242-Butanone 10207 159 0 - 6830 164Acetic acid 64317 111 79543 72 76870 932,3-Butanedione 6429 215 11604 118 14696 993-Methylbutanal 23318 66 11768 42 19082 412-Methylbutanal 39232 74 17327 67 25037 571-Butanol 46409 332 51660 224 26915 2243-Hydroxy-2-butanone 54639 150 92505 91 116545 1451,2-Propanediol 65016 110 70268 192 33359 1053-Methyl-1-butanol 6793 92 34841 123 66768 1292-Methyl-1-butanol 3028 256 7821 180 20456 167Dimethyl disulphide 0 - 0 - 0 -1-Pentanol 34408 281 93373 180 58143 1822,3-Butanediol 12810 158 26144 103 40725 119Hexanal 70818 59 36068 68 38863 1081-Hexanol 14056 80 41465 67 39023 47Butyrolactone 5352 97 7355 67 7904 442-Heptanone 48555 253 19498 224 40125 198Heptanal 19522 75 10558 84 21238 591-Octene 992 332 8174 126 5139 2242-Methyl-3-heptanone 22815 64 22879 19 27960 55Benzaldehyde 49073 92 92539 86 97480 89alpha-pinene 104552 45 86304 35 84761 536-Methyl-5-hepten-2-one 44321 46 74716 74 97548 832-Octanone 18538 240 32795 185 49981 181Octanal 21127 120 33463 146 42721 1683-Hexenyl acetate 0 - 0 - 0 -Fenchene 26135 38 25009 45 25251 522-Ethyl-1-hexanol 301426 126 619366 64 488736 75Limonene 41310 69 37388 46 45545 50Nonanal 65627 61 36262 138 59836 1611-Undecene 21028 133 0 - 26252 2242-Decanone 2576 119 13262 174 12404 187Decanal 36905 88 4828 224 14228 157
36
Table 7. Average VOC results for unwashed potato samples (4 samples from 2 cultivars)
Unwashed No Sprouting Unwashed Eyes Open Unwashed SproutingCompound Average area %RSD Average area %RSD Average area %RSDTrimethylamine 5730 121 5045 134 5612 181Acetone 39430 33 34660 41 30724 392-Methylpropanal 1726 245 0 - 1062 1392-Butanone 0 - 13238 200 0 -Acetic acid 81929 56 48700 35 54550 922,3-Butanedione 10126 245 4783 200 5812 773-Methylbutanal 8778 81 4463 40 4157 612-Methylbutanal 11137 160 1921 200 5199 1181-Butanol 21178 87 32793 17 34554 833-Hydroxy-2-butanone 17326 194 38589 97 18981 1981,2-Propanediol 288865 149 303962 145 247291 1263-Methyl-1-butanol 3941 83 2542 72 1342 2002-Methyl-1-butanol 746 245 0 - 2755 200Dimethyl disulphide 0 - 0 - 0 -1-Pentanol 12929 188 15439 151 0 -2,3-Butanediol 3595 245 3222 200 4948 200Hexanal 62370 39 67977 47 55008 651-Hexanol 22418 57 27053 55 18031 61Butyrolactone 4823 90 3995 119 2410 1192-Heptanone 16388 84 13467 116 16228 98Heptanal 22285 66 28132 69 19092 651-Octene 3208 157 0 - 8464 2002-Methyl-3-heptanone 12056 80 25837 21 14336 74Benzaldehyde 61508 57 60123 51 51031 82alpha-pinene 119550 37 121594 34 110492 586-Methyl-5-hepten-2-one 50141 42 57444 29 51971 362-Octanone 6690 121 11177 42 11774 92Octanal 16024 54 15743 79 19277 343-Hexenyl acetate 0 - 0 - 0 -Fenchene 28567 43 33439 40 31395 542-Ethyl-1-hexanol 370603 106 511903 106 609285 150Limonene 34587 39 38092 41 30344 41Nonanal 88937 54 69879 77 60613 681-Undecene 24437 197 21984 200 0 -2-Decanone 9949 124 12454 132 9569 126Decanal 35132 72 17808 126 6025 200From the data, presented in tables 6 and 7 and figures 10 and 11, there are no statistically
significant changes in the volatile organic compounds emitted from the potato tubers during the
onset of the sprouting process, also that by comparing the two sets of data there is no difference
between the results obtained for washed and unwashed potatoes. Samples were provided
washed and unwashed to see if any difference was detectable between the two sets of samples
that would require the potatoes to be in one state or the other. That no substantial differences
could be determined suggests that the use of a volatile organic compound monitoring system
would not be of use for detecting the start of the sprouting process and that washing the samples
has no effect on the VOC profile produced. Looking at 2-ethyl-1-hexanol, the average areas are
higher for samples with eyes open and sprouting, however the large relative standard deviation of
these values leads to the potential for an overlap between the results. This large error value is in
37
part due to the relatively small sample sizes used in this project as well as the number of different
cultivars used, but it could also be in part to other aging mechanisms at work within the samples
which were beyond the scope of this project, as no information was provided regarding the
harvest date of the samples.
38
Trimeth
ylamine
Acetone
2-Meth
ylpro
panal
2-Butanone
Acetic a
cid
2,3-Butaned
ione
3-Meth
ylbutan
al
2-Meth
ylbutan
al
1-Butanol
3-Hyd
roxy-2-butan
one
1,2-Propaned
iol
3-Meth
yl-1-butan
ol
2-Meth
yl-1-butan
ol
Dimeth
yl disu
lphide
1-Pentan
ol
2,3-Butaned
iol
Hexanal
1-Hexa
nol
Butyrolac
tone
2-Hep
tanone
Heptan
al
1-Octe
ne
2-Meth
yl-3-hep
tanone
Benzal
dehyd
e
alpha-p
inene
6-Meth
yl-5-hep
ten-2-one
2-Octa
none
Octanal
3-Hexe
nyl acet
ate
Fenchen
e
2-Ethyl-
1-hexan
ol
Limonen
e
Nonanal
1-Undece
ne
2-Deca
none
Decanal
0
100000
200000
300000
400000
500000
600000
700000
Washed sprouting potatoes
Washed No SproutingWashed Eyes OpenWashed Sprouting
Compounds
Area
Figure 10. Average area for washed potatoes (including error bars) n=11
39
Trimeth
ylamine
Acetone
2-Meth
ylpro
panal
2-Butanone
Acetic a
cid
2,3-Butaned
ione
3-Meth
ylbutan
al
2-Meth
ylbutan
al
1-Butanol
3-Hyd
roxy-2-butan
one
1,2-Propaned
iol
3-Meth
yl-1-butan
ol
2-Meth
yl-1-butan
ol
Dimeth
yl disu
lphide
1-Pentan
ol
2,3-Butaned
iol
Hexanal
1-Hexa
nol
Butyrolac
tone
2-Hep
tanone
Heptan
al
1-Octe
ne
2-Meth
yl-3-hep
tanone
Benzal
dehyd
e
alpha-p
inene
6-Meth
yl-5-hep
ten-2-one
2-Octa
none
Octanal
3-Hexe
nyl acet
ate
Fenchen
e
2-Ethyl-
1-hexan
ol
Limonen
e
Nonanal
1-Undece
ne
2-Deca
none
Decanal
0
100000
200000
300000
400000
500000
600000
700000
Unwashed sprouting potatoes
Unwashed No SproutingUnwashed Eyes OpenUnwashed Sprouting
Compound
Area
Figure 11. Average area for unwashed potatoes (including error bars) n=6
40
4.1.2.2 Results and discussion of damaged sample batches
A typical GC chromatogram for a samples, with no damage, slight damage and with severe
damage are shown, respectively in figures 12, 13 and 14 (other examples are shown in appendix
B). Figures showing the average response for each compound can be found in table 8.
Table 8. Average VOC results for damaged potatoes (5 samples from 2 cultivars)
Control samples Average
area
Control samples % RSD
Light damage Average
area
Lightly damaged
% RSD
Severe damage Average
area
Severely damaged
% RSDCompound Trimethylamine 0 - 0 - 0 -Acetone 68323 101 60321 103 63165 1502-Methylpropanal 0 - 0 - 390 2452-Butanone 2719 245 0 - 7434 156Acetic acid 69067 62 68450 56 80479 722,3-Butanedione 6078 113 3539 161 3558 1603-Methylbutanal 17366 116 15267 83 13885 1182-Methylbutanal 5003 137 15113 130 26793 1371-Butanol 147600 118 144573 126 88676 1163-Hydroxy-2-butanone 73696 125 35098 137 50023 891,2-Propanediol 273933 91 290348 50 218116 813-Methyl-1-butanol 0 - 3601 245 3239 1822-Methyl-1-butanol 1569 126 2469 132 1104 245Dimethyl disulphide 0 - 0 - 14641 2041-Pentanol 45838 146 43766 141 25587 1562,3-Butanediol 25436 224 21825 240 34522 177Hexanal 91529 104 97995 59 68060 671-Hexanol 76631 74 53515 84 45068 82Butyrolactone 8132 102 4176 120 3061 1372-Heptanone 31418 96 17968 71 14363 128Heptanal 33483 71 36740 47 33369 711-Octene 3618 245 7854 245 0 -2-Methyl-3-heptanone 15209 104 19449 82 15826 115Benzaldehyde 107961 80 91927 42 70385 71alpha-pinene 157239 106 138854 88 81205 856-Methyl-5-hepten-2-one 143273 54 111016 44 109258 352-Octanone 3185 166 2297 245 4169 192Octanal 32840 50 27071 47 28261 473-Hexenyl acetate 0 - 0 - 0 -Fenchene 42601 96 31934 80 20819 692-Ethyl-1-hexanol 966824 81 615309 85 425187 98Limonene 58428 54 47778 62 50823 74Nonanal 247831 86 183549 65 232982 701-Undecene 74005 131 72924 132 84383 1332-Decanone 35748 172 5533 155 14344 147Decanal 25337 103 8207 157 23873 81
The results for the analysis of damaged potatoes show no obvious indicator VOCs for damage. An
increase is seen in 2-methylbutanal, but due to the high relative standard deviation of the results
it is not possible to attribute this to the damage process. Increasing either the number of
replicates or increasing the amount of damage may provide more information as to whether or
not 2-methylbutanal is an indicator of damage.
41
Figure 12. TIC of No damage control sample, batch 9
42
Figure 13. TIC of slight damage sample, batch 9
43
Figure 13. TOC of severe damage sample, batch 9
44
Trimeth
ylamine
Acetone
2-Meth
ylpro
panal
2-Butanone
Acetic a
cid
2,3-Butaned
ione
3-Meth
ylbutan
al
2-Meth
ylbutan
al
1-Butanol
3-Hyd
roxy-2-butan
one
1,2-Propaned
iol
3-Meth
yl-1-butan
ol
2-Meth
yl-1-butan
ol
Dimeth
yl disu
lphide
1-Pentan
ol
2,3-Butaned
iol
Hexanal
1-Hexa
nol
Butyrolac
tone
2-Hep
tanone
Heptan
al
1-Octe
ne
2-Meth
yl-3-hep
tanone
Benzal
dehyd
e
alpha-p
inene
6-Meth
yl-5-hep
ten-2-one
2-Octa
none
Octanal
3-Hexe
nyl acet
ate
Fenchen
e
2-Ethyl-
1-hexan
ol
Limonen
e
Nonanal
1-Undece
ne
2-Deca
none
Decanal
0
200000
400000
600000
800000
1000000
1200000
Damaged potato results
ControlSlight damageSevere damage
Compound
Area
Figure 14. Average areas for undamaged/damaged potatoes n=6
45
4.1.2.3 Results and discussion of infected sample batches
Example TIC traces for uninfected and infected potato sample are shown in figures 15 - 19, other
examples, where available, are shown in appendix B.
Batches 2, 5, 11 and 12 contained potatoes which were either soaked in a solution containing
bacteria responsible for causing soft rot (Pectobacterium carotovorum), were mock inoculated or
inoculated as previously described. Five compounds showed a significant increase in levels
between the soaked, mock inoculated and inoculated samples, and these results are shown in
table 9. Effantin et al. (2011) reported high levels of 2,3-butanediol production during plant
infection by Pectobacterium and included results based upon skin puncturing of potato tubers and
infection with Pectobacterium carotovorum. The high levels of 3-hydroxy-2-butanone detected in
the inoculated samples would be expected as well as this compound is converted by the enzyme
2,3-butanediol dehydrogenase to 2,3-butanediol as reported by Marquez-Villavicencio et al..
(2011) as a requirement for Pectobacterium carotovorum pathogenesis.
Table 9. Infected potatoes from sample batches with soft rot (5 samples from 3 cultivars)
Soaked Mock inoculation Inoculated
CompoundAverage
area %RSDAverage
area %RSDAverage
area %RSDTrimethylamine 1749 173 17162 160 889272 1042-Butanone 2388 173 0 - 284116 762,3-Butanedione 9333 24 16096 112 303211 683-Hydroxy-2-butanone 6096 173 153972 139 6353313 652,3-Butanediol 19875 73 110108 100 14171005 158
The data in table 9 suggests that the skin of the tuber acts as a barrier to prevent infection
occurring when the potato is soaked in a bacterial solution, and are in line with the findings of
Barel and Ginsberg (2008), which found that potato skin is composed of suberized phellem cells
which prevent mechanical or chemical invasion by micro-organisms. This would suggest that there
needs to be a break in the skin for the infection to take hold, which would be important in the
handling of potatoes during harvest and storage.
46
Figure 15. TIC of Soaked Desiree potato sample from batch 5
47
Figure 16. TIC of Mock inoculated Desiree potato from batch 5
48
Figure 17. TIC of inoculated Desiree potato sample from batch 5
49
Figure 18. TIC of Dry rot Maris piper potato from batch 10
50
Figure 19. TIC of gangrene Charlotte EK potato sample from batch 13
51
Trimeth
ylamine
2-Butanone
2,3-Butaned
ione
3-Hyd
roxy-
2-butanone
2,3-Butaned
iol0
2000000
4000000
6000000
8000000
10000000
12000000
14000000
16000000
SoakedMock inoculationInoculated
Figure 20. Soft rot compounds (n=3 for soaked & n=5 for mock inoculation and inoculated)
Although the %RSD values for these results are high, when the data is examined on a batch by
batch basis there is always an increased area for these compounds in the inoculated samples
when compared with their respective mock inoculation samples. Amongst the reasons for the
high %RSD are the lack of an environmentally control storage cabinet in which the disease can
progress, as well as the low number of replicates for these sample types.
Batches 8, 10 and 13 contained potatoes that had been infected with either dry rot (Fusarium
genus) or gangrene (Phoma foveata fungus), and using the five compounds identified for bacterial
soft rot it can be seen that 2,3-butanediol is again more prevalent in samples that have been
infected, as shown in table 10.
Table 10. Dry rot and gangrene infected potatoes
Control Mock inoculation Dry rot Gangrene
CompoundAverage
area %RSDAverage
area %RSDAverage
area %RSDAverage
area %RSD
Trimethylamine 15610 166 275787 173 265711 173 579411 211
2-Butanone 9206 200 0 - 37405 140 103143 218
2,3-Butanedione 136999 187 40358 164 65578 164 415153 1223-Hydroxy-2-butanone 165503 113 315661 173 622387 170 760047 221
2,3-Butanediol 178203 158 157348 170 3075562 173 3499070 105
Some other potato diseases were looked at via a single sample which had field identified diseases,
these disease were pit rot (multiple causes), black spot (Colletotrichum coccodes), and rubbery rot 52
(Geotrichum candidum). The samples with either pit rot or rubbery rot again showed increased
levels of the five compounds found in bacterial soft rot. The results for these samples are shown
in table 11.
Table 11. Diseased potato samples
Melody MD
HealthyMelody rubbery
Charlotte Healthy
Charlotte Black spot
Sunrise WC (washed) Healthy
Sunrise WC (washed)
Pit rotCompound Area Area Area Area Area AreaTrimethylamine 7246 89748 0 0 0 567452-Butanone 70614 0 6087 12376 0 3427112,3-Butanedione 29397 393810 0 0 22487 976303-Hydroxy-2-butanone 84077 9541792 56036 0 305600 11256022,3-Butanediol 74627 45204277 21530 18394 37576 81036
The lack of any noticeable increase in the sample with black spot could be attributable to the
disease not having taken hold yet, although it is possible that this was a misidentification of the
disease.
From the data acquired for this project is appears that there are a number of marker compounds
that could be used in the identification of disease in potato tubers, of the compounds the two
best compounds based on increase in response due to infection (either bacterial or fungal) are
3-hydroxy-2-butanone and 2,3-butanediol.
4.1.2.4 Effect of time and temperature on bacterial soft rot
Sample batches 19 and 20 require separate discussion as they include a first look at the changes
in volatile organic compounds based on either the time from inoculated (batch 19) or the storage
temperature from samples with the same inoculation date.
The results from batch 19 are shown in table 12. This batch was analysed on the 8/7/2014,
therefore each sample had a minimum of six days for any infection to develop. None of the mock
inoculation samples showed any increase in the compounds discussed in this work as being
indicative of infection in potatoes. The sample that was infected on the 2/7/2014, 6 days prior to
analysis, also showed no increase, this could be due to the small levels of volatile organic
compounds being produced at the start of the infection being insufficient to be detected by this
methodology. The sample infected on the 30/6/2014, 8 days prior to analysis, has small quantities
of the expected compounds, and these levels were just above the limit of detection for these
compounds, and the sample infected on the 24/06/2014, two weeks prior to analysis, shows the
significant levels that were found in samples with the other diseases examined in this work.
53
Table 12. Result from potato sample batch 19 analysed 08/07/2014
WashMock
inoculationMock
inoculationMock
inoculation Infected Infected InfectedDays after inoculation thatAnalysis occurred - 14 8 6 14 8 6Compound Area Area Area Area Area Area AreaTrimethylamine 0 0 0 0 249308 13938 02-Butanone 0 0 0 0 186992 10282 02,3-Butanedione 0 0 4224 0 116074 10067 454943-Hydroxy-2-butanone 338 0 0 0 431538 66807 02,3-Butanediol 0 0 0 0 56287 7332 0
Sample batch 20 was conducted at the Sutton Bridge storage research centre and comprised
three set of potatoes being infected at the sample time, these samples were then stored, with
their corresponding control samples, at either 4°, 10° or 20°C. The samples were all stored at 20°C
over a weekend to allow the infection to take hold then they were transferred to stores held at
different temperatures. All of the SPME fibre sampling was conducted on the same day
(24/7/2014) with the sampling taking place inside each cold store. The results for these samples
are shown in table 13.
Table 13. Results for infected potatoes stored at different temperatures, sample batch 20
Travel blank
Mock inoculation
4°C
Mock inoculation
10°C
Mock inoculation
20°CInfected
4°CInfected
10°CInfected
20°CCompound Area Area Area Area Area Area AreaTrimethylamine 0 5566 1245 0 469291 1428579 37821082-Butanone 0 0 8959 0 0 116947 02,3-Butanedione 0 0 8959 0 16694 116947 3345623-Hydroxy-2-butanone 0 24218 0 0 242619 25358 95694852,3-Butanediol 1294 0 13726 0 14994 51872 4845668
The results from this sample batch showed that the temperature of storage for infected potatoes
has a direct effect on the progression of the disease. The progression of the disease is markedly
slowed by a reduction in storage temperature to 4°C, this was also observed visually as the
sample stored at 20°C had some brown liquid pooled at the bottom of the sampling container.
4.1.3 Conclusion
The results found in this work showed no clear evidence of changes in the volatile organic
compound composition of potatoes that are either sprouting or have suffered physical damage.
A group of compounds was found to have increased levels when either a bacterial or fungal
infection was present, of these compounds 2,3-butanediol usually gave the highest response.
Other compounds include trimethylamine, 2,3-butanedione and 3-hydroxy-2-butanone. Three of
the compounds associated with diseases have the same hydrocarbon backbone. There is not any
indication that it would be possible to differentiate diseases based upon their volatile organic
compound profile, but the presence of these compounds would be indicative of an infection.
54
The infection of potatoes show clear marker compounds that could be used in association with an
electronic nose for the early detection of disease prior to storage. This may help to reduce any
storage losses associated with secondary infection.
55
4.2 Onions
The onion samples analysed were all supplied from the field, with the determination of any
disease present carried out post-harvest by visual inspection by the suppliers. The samples were
analysed to try and identify any volatile compounds that are associated with the different
diseases. These compounds could then be used to monitor batches of harvested onions to
prevent further infections occurring in storage.
The results from the sample analysis was used to try to determine if there is any characteristic
pattern of volatile compounds that relate to a specific disease. If each disease has a VOC
fingerprint, this information could then be used to determine future planting pattern on the farm,
as some diseases, particularly basal rot, have spores that can survive for a long time in the soil.
4.2.1 Methods and samples
Six batches of samples of onions comprising thirty three samples were analysed between the 3 rd
December 2013 and 15th April 2014. All samples were analysed using the procedure described in
sections 3.2 – 3.4 and are shown in table 14.
Table 14. Sample batches for analysis of onions
Batch Number
Date of analysis
Total number of samples
Samples analysed
1 03/12/2013 4 Control, Slight Basal rot, Severe Basal rot, Thick Neck2 04/02/2014 9 Control, 8 Samples possibly infected with internal rot3 18/02/2014 4 Control, internal rot, neck rot, basal rot4 11/03/2014 5 Control, neck rot, internal rot, basal rot, thick neck5 18/03/2014 4 Control, internal rot for both red and brown onions6 15/04/2014 8 Control, internal rot, neck rot, basal rot for red and brown onions
The first task was to compile a list of potentially odorous compounds that could be detected in
control/uninfected onions using the protocol described earlier.
4.2.2 Onions results and discussion
4.2.2.1 Control samples
A typical GC chromatogram from a healthy, uninfected onion sample is shown in figure 21 (other
examples are shown in appendix C)
56
Figure 21. Onion control sample 03/12/2013
57
The compounds identified from the control sample are listed below in Table 15.
Table 15. VOCs identified in Onion control sample 03/12/2013
Ret Time Area Name2.009 938842 Acetic acid2.095 148388 1-Propanethiol2.214 49115 2-Methyl-1-propanol2.484 127171 1-Butanol2.576 78648 1-Methoxy-2-propanol2.708 2667474 Dimethyl silanediol*2.977 73026 n-Heptane3.217 80918 3-Methyl-1-butanol3.267 20562 2-Methyl-1-butanol3.405 476551 1-Ethoxy-2-propanol3.808 294090 2,3-Butanediol3.869 12341 Butanoic acid3.967 951438 Hexanal4.263 22186 Butyl acetate4.301 200671 n-Octane4.499 17252 2-Butanone4.664 1082085 2,4-Dimethylheptane4.727 252065 1-Propoxy-2-propanol4.924 68993 2,4-Dimethyl-1-heptene5.042 126907 o-Xylene5.128 64009 1-Hexanol5.181 248587 m+p-Xylene5.313 489714 4-Methyloctane5.379 28559 2-Heptanone5.46 47430 Styrene
5.543 205987 Heptanal5.746 54720 Hexylene glycol5.825 126698 Pentyl acetate6.317 179072 1-Butoxy-2-propanol6.36 62522 Benzaldehyde
6.401 301912 alpha-pinene6.966 268630 2-Methylnonane7.138 181970 4-Cyanocyclohexene7.935 696263 4-Methyldecane8.866 1016394 Nonanal
10.428 257926 Decanal13.282 51766 Dodecanal
* Dimethyl silanediol is an artefact from the SPME fibre
Løkke et al. (2012) carried out analysis on freshly cut onions and found sulphides at higher levels
(namely methanethiol, propanethiol, dimethyl disulphide, dimethyl thiosulphinate, dipropyl
disulphide, di-2-propenyl disulphide, di-2-propenyl thiosulphinate and dipropyl thiosulphinate)
than in this work. Additionally found were acetaldehyde, acetone and propanal. Järvenpää et al.
(1998) analysed onions which were sliced into water (1:5, w/w) and again reported sulphur
containing compounds almost exclusively, the exceptions being prop(en)yl aldehydes. Boelens et
al. (1971) analysed a steam distilled onion oil and identified around fifty compounds and again the
vast majority of these compounds were sulphur containing, including mon, di-, tri-, and
tetrasulphides, thiophene derivatives and thiols. Only six non-sulphur containing compounds
were identified: propanal, dimethylfuran, 2-methylpentanal, 2-methylpent-2-enal, tridecan-2-one
58
and 5-methyl-2-n-hexyl-2,3-dihydrofuran-3-one. Similar reports of predominately sulphur
containing compounds were also reported by Lanzotti (2006), Mondy et al. (2002) and Tokitomo
and Kobayashi (1992) and again all of these works carried out some form of sample pre-treatment
prior to analysis. There is a wide variety of volatile organic compounds present, however when
compared to previously obtained results there are some differences that are due to this work
being based upon volatiles obtained from the whole onion bulb rather than any sample pre-
treatment being carried out. The predominance of sulphur containing compounds is caused by
the sample pre-treatment process and that a normal healthy whole onion does not have a strong
onion smell.
4.2.2.2 Basal rot
A typical GC chromatogram is shown in figure 22 (other examples are shown in appendix C)
59
Figure 22. Onion with severe basal rot 03/12/2013
60
When a sample with severe basal rot is analysed the following compounds are found and listed in
table 16.
Table 16. VOCs identified in an onion with severe basal rot 03/12/2013
Ret Time Area Name Origin of compound1.98 674774 Acetic acid Control
2.037 221146 2-Butanol Sample2.09 1267330 1-Propanethiol Control + Sample
2.208 1366658 2-Methyl-1-propanol Control2.637 300868 2-Pentanone Sample2.773 1074513 3-Hydroxy-2-butanone Sample2.978 35286298 Methyl propyl sulphide Sample3.06 416002 Allyl methyl sulphide Sample
3.212 4100932 3-Methyl-1-butanol Control + Sample3.261 1866511 2-Methyl-1-butanol Control + Sample3.406 406924 1-Ethoxy-2-propanol Control3.667 576806 2,3-Butanediol Control + Sample3.752 1499870 Methyl isovalerate Sample3.97 232351 Hexanal Control
4.898 695375 Ethyl 3-methylbutanoate Sample5.129 409726 1-Hexanol Control5.313 832564 Bis(methylthio)methane Sample5.38 748672 2-Heptanone Control5.46 6002726 Styrene Control6.09 4471132 Methyl propyl disulphide Sample
6.402 242454 alpha-pinene Control7.034 92568 2-Octanone Sample7.084 1011569 Methylpropyl sulphoxide Sample7.688 10457317 2,2-bis(methylthio)propane Sample7.88 1357000 Sabinene Sample
8.157 1436841 Z-Ocimene Sample8.529 1561276 3,7-Dimethyldecane Sample8.987 6452277 Dipropyl disulphide Sample
10.087 2266068 Naphthalene Sample11.711 854560 2-Undecanone Sample
Origin of compound:
Control: Detected in infected sample at similar levels to control sampleControl + Sample: Detected in both control and infected sample, but at much higher levels in infected sample than control sample.Sample: Only detected in infected sample.
4.2.2.3 Internal Rot
A typical GC chromatogram is shown in figure 23 (other examples are shown in appendix C)
61
Figure 23. Onion with internal rot 18/02/2014
62
The analysis of samples with internal rot gives the following results listed below in table 17.
Table 17. VOCs identified in Onion with internal rot 18/02/2014
Ret Time Area Name Origin of compound2.018 1724866 Acetic acid Control2.12 3855616 1-Propanethiol Control + Sample
2.503 367272 1-Butanol Control + Sample2.589 1430966 2-Pentanone 2-Pentanone2.789 21879286 3-Hydroxy-2-butanone Sample2.995 535023 Methyl propyl sulphide Sample3.228 4163771 3-Methyl-1-butanol Control3.277 1388283 1,2-Propanediol Sample3.42 581044 Propylene glycol Sample
3.711 11733054 2,3-Butanediol Control + Sample3.855 14497190 2,3-Butanediol Control + Sample3.979 1566443 2-Propoxy ethanol Sample4.737 234589 1-Propoxy-2-propanol Sample5.05 2250717 1-Methoxy-2-propyl acetate Sample5.16 677033 1-Hexanol Sample
5.289 62199943 Cyclohexanone + Cyclohexanol Sample5.465 1098605 Styrene Control6.089 3309135 Methyl propyl disulphide Sample6.36 593629 Benzaldehyde Sample6.4 664046 alpha-pinene Control
8.866 1722498 Nonanal Sample8.985 8742788 Dipropyl disulphide Sample
Origin of compound:
Control: Detected in infected sample at similar levels to control sampleControl + Sample: Detected in both control and infected sample, but at much higher levels in infected sample than control sample.Sample: Only detected in infected sample.
4.2.2.4 Neck Rot
A typical GC chromatogram is shown in figure 24 (other examples are shown in appendix C).
63
Figure 24.Onion with neck rot 18/02/2014
64
Analysis of a sample of onion with neck rot gives the following compounds listed in table 18.
Table 18. VOCs identified in sample with neck rot
Ret Time Area Name Origin of compound2.132 4337501 1-Propanethiol Control + Sample2.78 7115458 3-Hydroxy-2-butanone Sample
3.225 1004268 3-Methyl-1-butanol Control3.275 615577 2-Methyl-1-butanol + Dimethyl disulphide Control + Sample3.418 302803 Propylene glycol Sample3.822 15819416 2,3-Butanediol (2 peaks) Control + Sample5.264 31110160 Cyclohexanone Sample5.302 12515106 Cyclohexanol Sample5.666 268514 3,4-Dimethylthiophene Sample6.09 12907096 Methyl propyl disulphide Sample
6.196 1376340 1,3-Dithiane Sample8.995 25775798 Dipropyl disulphide Sample
11.702 1412771 2-Undecanone SampleOrigin of compound:
Control: Detected in infected sample at similar levels to control sampleControl + Sample: Detected in both control and infected sample, but at much higher levels in infected sample than control sample.Sample: Only detected in infected sample.
4.2.2.5 Thick Neck
A typical GC chromatogram is shown in figure 25 (other examples are shown in appendix C).
65
Figure 25. Onion with thick neck 11/03/2014
66
The analysis of onion with thick necks gives the following results shown in table 19.
Table 19. VOCs identified in onion with thick neck
Ret Time Area Name Origin of compound1.995 406385 Acetic acid Control2.477 716196 1-Butanol Control2.565 603797 1-Methoxy-2-propanol Control2.755 4438841 3-Hydroxy-2-butanone Control3.201 211009 3-Methyl-1-butanol Control3.25 72789 2-Methyl-1-butanol Control3.389 420420 1-Ethoxy-2-propanol Control3.789 9204998 2,3-Butanediol (2 peaks) Control + Sample3.945 581471 Hexanal Control11.678 1199348 2-Undecanone Control
Origin of compound:
Control: Detected in infected sample at similar levels to control sampleControl + Sample: Detected in both control and infected sample, but at much higher levels in infected sample than control sample.Sample: Only detected in infected sample.
4.2.2.6 Comparison of rots and thick neck
In tables 8, 9, 10 and 11, where compounds have been identified in both the control sample and
the infected sample at the same approximate level, then they have been identified as originating
from the control sample, e.g. acetic acid. Other peaks were detected in both the control and the
infected sample but were found to be present at significantly higher levels in the infected sample,
e.g. 1-propanethiol. Some compounds were only detected in the infected samples, e.g. dipropyl
disulphide.
The next stage of the analysis was to identify the compounds that are the result of infection or
defects. Table 20 gives a combined table based upon all the individually listed results above.
67
Table 20. Combined VOC results for all onion types
Ret Time Name Control Basal Rot Internal Rot Neck Rot Thick Neck2.009 Acetic acid 2.037 2-Butanol 2.095 1-Propanethiol 2.214 2-Methyl-1-propanol 2.484 1-Butanol 2.576 1-Methoxy-2-propanol 2.637 2-Pentanone 2.789 3-Hydroxy-2-butanone 2.708 Dimethyl silanediol* 2.977 n-Heptane 2.978 Methyl propyl sulphide 3.06 Allyl methyl sulphide
3.217 3-Methyl-1-butanol 3.267 2-Methyl-1-butanol 3.275 Dimethyl disulphide 3.277 1,2-Propanediol 3.405 1-Ethoxy-2-propanol 3.752 Methyl isovalerate 3.808 2,3-Butanediol 3.869 Butanoic acid 3.967 Hexanal 4.263 Butyl acetate 4.301 n-Octane 4.499 2-Butanone 4.664 2,4-Dimethylheptane 4.727 1-Propoxy-2-propanol 4.898 Ethyl 3-methylbutanoate 4.924 2,4-Dimethyl-1-heptene 5.042 o-Xylene 5.05 1-Methyoxy-2-propyl acetate
5.128 1-Hexanol 5.181 m+p-Xylene 5.289 Cyclohexanone 5.305 Cyclohexanol 5.313 4-Methyloctane 5.379 2-Heptanone 5.46 Styrene
5.543 Heptanal 5.666 3,4-Dimethylthiophene 5.746 Hexylene glycol 5.825 Pentyl acetate 6.09 Methyl propyl disulphide
6.196 1,3-Dithiane 6.317 1-Butoxy-2-propanol 6.36 Benzaldehyde
6.401 alpha-pinene 6.966 2-Methylnonane 7.034 2-Octanone 7.084 Methyl propyl sulphoxide 7.138 4-Cyanocyclohexene 7.688 2,2-bis(methylthio)propane 7.88 Sabinene
7.935 4-Methyldecane 8.157 Z-Ocimene 8.529 3,7-Dimethyldecane 8.866 Nonanal 8.987 Dipropyl disulphide
10.087 Naphthalene 10.428 Decanal 11.711 2-Undecanone 13.282 Dodecanal
= Not detected = Detected = Detected at much higher levels than in control
68
4.2.3 Discussion
Examination of the data shows that sulphur containing compounds are present in substantial
quantities for the diseased onions, especially methyl propyl sulphide, methyl propyl disulphide
and dipropyl disulphide. Some of the smaller sulphur compounds detected appear to be related
to the type of disease that the onion is infected with, for example, 3,4-dimethylthiophene and
1,3-dithiane appear to be associated with onions infected with Neck rot. Prithiviraj et al. (2004)
examined onions infected with Botryris allii (Neck rot), Fusarium oxysporum (Basal rot) and
Erwinia carotovora (Soft rot), two of which can be responsible for the diseases analysed in this
project, and identified a large number of sulphur containing compounds related to these onion
diseases, the most abundant of these sulphur compounds were methyl propyl disulphide and
dipropyl disulphide, but it should also be noted that not all of these compounds were found with
all diseases and not necessarily with every batch of samples with the same disease. Løkke et al.
(2012), looking at volatiles emitted from uninfected freshly cut onions, identified propanethiol as
the main component. Changying et al. (2011) analysed onions post-harvest for Neck rot and sour
skin, and found that the major volatile component from B. Allii (Neck rot) inoculated samples was
dipropyl disulphide which accounted for 61% of the total volatile compounds in these samples.
Additionally he detected 1-propanethiol and methylpropyl disulphide which is similar to this
project. One major difference between the compounds identified in the paper by Changying et al.
(2011) and this project is the identification of a substantial peak corresponding to 2,3-butanediol,
this major peak was found in this work but missed by Changying et al.. This is because the work
reported here used a mass spectral scan range of m/z 35 – 500, whereas the work carried out by
Changying et al. used a scan range of m/z 50 – 300. Whilst using a larger scan range can sacrifice
some sensitivity it can be worth it in identifying volatile organic compounds that only produce
mass spectra below m/z 50, particularly as a lot of oxygen containing volatiles give mass spectra
with only one or two ions, usually within the m/z 35-50 range.
(m a in lib ) 2 ,3 -B u ta n e d io l1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0 7 5 8 0 8 5 9 0 9 5 1 0 0
0
5 0
1 0 0
1 3 1 5 1 71 9
2 62 7 2 9
3 1 3 7 3 9 4 14 3
4 5
4 7 5 0 5 3 5 55 7
5 8 6 0 7 1 7 3 7 5 8 9 9 1
O H
H O
Figure 26. NIST 11 Database mass spectrum of 2,3-Butanediol
69
Based upon the compounds detected, a short list of compounds with potential to analyse samples
for these diseases was determined. The compounds were chosen based upon their prevalence in
the samples as well as their amenity to detection via an electronic nose. The compounds were
also chosen as potential indicators of disease and are listed in table 21.
Table 21. VOCs identified as potential indicators of onion diseases.
Acetic acid 1-Propanethiol 1-Butanol 1-Methoxy-2-propanol
3-Hydroxy-2-butanone
Methyl propyl sulphide
1,2-Propanediol 3-Methyl-1-butanol Propylene glycol 2,3-Butanediol
Hexanal 1-Propyl-2-propanol 1-Methoxy-2-propyl acetate
1-Hexanol Cyclohexanone
Styrene Methyl propyl disulphide
Benzaldehyde Nonanal Dipropyl disulphide
Full details of the analyses for the individual batches of infected onions are shown in appendix D
4.2.4 Potential differentiation of onion diseases
As the infected samples were all supplied by a commercial partner, and they had identified the
diseases visually, there is no way of knowing how progressed the infection was. Hence this may
account for difference in the absolute areas found for each sample, and as dipropyl disulphide is
usually the most abundant peak the data will be normalised to the dipropyl disulphide peak to
enable relative responses to be compared between diseases. Samples of both red and brown
onions were supplied for this work
The data for onions with Internal Rot, focussing on the sulphur containing compounds is shown in
table 22. The data was then normalised to the dipropyl disulphide peak and shown in table 23.
Table 22. Sulphur compounds detected in onions with internal rot
Internal Rot Batch 3 Batch 4 Batch 5 Brown Batch 5 Red Batch 6 Brown Batch 6 Red1-Propanethiol 321653 1006936 224327 911606 141153 0Methyl propyl sulphide 130835 949391 32763 64487 139221 125056
Methyl propyl disulphide 663801 5066937 382246 1188217 257430 255425
Dipropyl disulphide 3481653 11002244 6407660 6001483 2815784 1771172
Internal Rot Batch 3 Batch 4 Batch 5 Brown Batch 5 Red Batch 6 Brown Batch 6 Red1-Propanethiol 9.24 9.15 3.50 15.19 5.01 3.27Methyl propyl sulphide 3.76 8.63 0.51 1.07 4.94 7.06
Methyl propyl disulphide 19.07 46.05 5.97 19.80 9.14 14.42
Dipropyl disulphide 100.00 100.00 100.00 100.00 100.00 100.00
70
The normalised data shows that for Internal rot the major peak is dipropyl disulphide with the
other sulphide compounds generally giving less than 20% of the dipropyl disulphide peak, the only
exception being the sample analysed on the 11/03/2014 and in most cases the level of 1-
propanethiol is greater than that of the methyl propyl sulphide peak.
Batch 3 Batch 4 Batch 5 Brown
Batch 5 Red
Batch 6 Brown
Batch 6 Red
0.00
20.00
40.00
60.00
80.00
100.00
120.00
1-PropanethiolMethyl propyl sulphideMethyl propyl disulphideDipropyl disulphide
Figure 27. Normalised data for internal rot in onions
Repeating this sample treatment for each of the diseases gives the following tables
For Neck rot
Table 24. Sulphur containing compounds detected in onions with neck rot
Neck Rot Batch 3 Batch 4 Batch 6 Brown Batch 6 Red1-Propanethiol 0 115365 29122 75058Methyl propyl sulphide 94130 168838 85588 249050Methyl propyl disulphide 2865796 127946 205555 940349Dipropyl disulphide 11226516 1862556 572232 1352481
Again this data has been normalised to the dipropyl disulphide peak and gives
Table 25. Normalised data for samples infected with neck rot
Neck Rot Batch 3 Batch 4 Batch 6 Brown Batch 6 Red1-Propanethiol 0.00 6.19 5.09 5.55Methyl propyl sulphide 0.84 9.06 14.96 18.41Methyl propyl disulphide 25.53 6.87 35.92 69.53Dipropyl disulphide 100.00 100.00 100.00 100.00
The data shows more variation than the data from onions infected with internal rot, it does show
that most of the areas for methylpropyl disulphide peak are greater than 25% of the dipropyl
disulphide peak and that for Neck rot the amount of methyl propyl sulphide is greater than the
amount of 1-propanethiol.
71
Batch 3 Batch 4 Batch 6 Brown Batch 6 Red0.00
20.00
40.00
60.00
80.00
100.00
120.00
1-PropanethiolMethyl propyl sulphideMethyl propyl disulphideDipropyl disulphide
Figure 28. Normalised data for neck rot
The final disease under examination is Basal rot, the results are shown in table 26. When the data
is normalised to dipropyl disulphide the results shown in table 27 are obtained. The data obtained
for basal rot appear to be more random than the data obtained for the other diseases.
Table 26. Sulphur containing compounds detected in onions with basal rot
Basal Rot Batch 1 Slight Basal Rot
Batch 1 Severe Basal Rot Batch 3 Batch 4 Batch 6 Brown Batch 6 Red
1-Propanethiol 189789 230239 0 68721 0 155550Methyl propyl sulphide 749932 8445338 138370 46491 3568586 360524
Methyl propyl disulphide 152494 1013691 135345 307781 1282434 571286
Dipropyl disulphide 3292991 2249121 3799632 1148148 1427761 2869635
Basal Rot Batch 1 Slight Basal Rot
Batch 1 Severe Basal Rot Batch 3 Batch 4 Batch 6 Brown Batch 6 Red
1-Propanethiol 5.76 10.24 0.00 5.99 0.00 5.42Methyl propyl sulphide 22.77 375.50 3.64 4.05 249.94 12.56
Methyl propyl disulphide 4.63 45.07 3.56 26.81 89.82 19.91
Dipropyl disulphide 100.00 100.00 100.00 100.00 100.00 100.00
72
Batch 1 Slight
Basal Rot
Batch 1 Severe
Basal Rot
Batch 3 Batch 4 Batch 6 Brown
Batch 6 Red
0
50
100
150
200
250
300
350
400
1-PropanethiolMethyl propyl sulphideMethyl propyl disulphideDipropyl disulphide
Figure 29. Normalised data for basal rot
Comparing the two samples analysed in batch 1 which were described as having either slight or
severe basal rot, it would appear that as the disease progresses there is a change in the dominant
sulphide, as methyl propyl sulphide overtakes dipropyl disulphide. This can also be seen in the
sample of Brown onion analysed in batch 6, and shows one of the issues with analysing these
samples.
All of the samples were supplied from the field and as such there is no way of knowing how far
the infection has progressed on each sample. This could be addressed in a couple of ways either
by finding a way of introducing the infection in the samples in a controlled environment and
following the progression of the disease, or by greatly increasing the sample group within each
growing season and by carrying out this work over a number of growing seasons.
The samples from batch 2 were supplied with suspected internal rot. If only the sulphur
containing compounds are considered, as shown in table 28, and the results compared with the
data obtained for samples with confirmed internal rot then sample 3 appears to be the sample
with the highest likelihood of an internal rot infection, whilst sample 5 appears to be uninfected.
Whole and cross-sectional photographs of these two samples are shown in plates 22 - 25. On the
cross-sectional photograph of sample 3, slight discolouration can be seen at the centre of the
onion, this discolouration is not present in the cross-sectional photograph of sample 5. This could
indicate the early stage of an internal rot infection in sample 5, this is supported by the relatively
low abundance of the marker compounds found compared to the results obtained in other
samples with internal rot.
73
Plates 22 & 23. Whole and cross section of sample 5
Plates 24 & 25. Whole and cross section of sample 3
Table 28. Sulphur containing compounds detected in onions batch 2
Analysis of onions 04/02/2014
Compound RT (min)
Sample 1
Sample 2
Sample 3
Sample 4
Sample 5
Sample 6
Sample 7
Sample 8
1-Propanethiol 2.095 0 0 0 0 0 0 0 0
Methyl propyl sulphide 2.979 0 0 2412 0 0 0 0 565
Methyl propyl disulphide 6.084 1682 0 10373 0 0 0 2415 0
Dipropyl disulphide 8.991 19851 36497 31552 12702 0 5876 3202 1387
74
4.2.5 Conclusion
From the analysis of these six batches of infected onion, the data shows that the sulphur
containing compounds are indicative markers of these diseases in onions. The four main sulphur
compounds identified; 1-propanethiol, methyl propyl sulphide, methyl propyl disulphide and
dipropyl disulphide are found in all infected samples but at varying levels, but always at higher
levels than detected in the control samples. There is some evidence of VOC fingerprint being
associated with neck rot and internal rot, but there is not sufficient data points to make a
definitive conclusion on this point, and as the onions were naturally infected in the field there is
no way of knowing whether the progression of the disease has an effect on the volatile
composition. This degree of diseases progression may explain the more varied results obtained
from samples infected with basal rot.
From the samples analysed that were described as having thick neck there is an absence of the
sulphur containing compounds described above, but there were increased levels of 3-hydroxy-2-
butanone and 2,3-butanediol when compared with the control samples. This could be used in a
monitoring system as onions with thick neck are more susceptible to infection which would
increase the chances of infection taken hold within a storage facility.
75
4.3 Broccoli
The initial samples for broccoli were analysed to determine marker compounds for the
presence/absence of wet rot. These compounds would then be used to determine the freshness
of pre-cut broccoli florets which are pre-packaged in soft plastic bags.
The pre-packaged samples were analysed over a range of dates relative to the use by date. The
oldest samples were analysed nine days after the use by date printed on the packaging and the
newest samples were analysed four days before the use by date printed on the packaging. The
data acquired from these sample batches was then used to examine whether the use by date for
the broccoli florets is an accurate reflection of potential shelf life.
4.3.1 Methods and samples
Nine batches of samples of broccoli comprising forty six samples were analysed between the 8 th
November 2013 and 28th July 2014. All samples were analysed using the procedure described in
sections 3.2 – 3.4.
Table 29. Broccoli samples analysed
Batch number
Date Total number of samples
Samples analysed
1 08/11/2013 3 Helen’s, Agromark, Pasqual – Broccoli possibly infected with wet rot.
2 21/11/2013 3 Control, Slight rot, Severe rot3 25/03/2014 6 Use before date 27/03/2104, 28/03/2014, 29/03/2014,
analysed in duplicate4 01/04/2014 8 Use before date 31/03/2014 x2, 01/04/2014 x2, 02/04/2014,
03/04/2014, 04/04/2014, 05/04/20145 27/05/2014 4 Use before date 20/05/2014, 22/05/2014, 24/05/2014,
26/05/20146 16/06/2014 2 Use before date 14/06/2014, 16/06/20147 17/06/2014 4 Use before date 14/06/2014, 18/06/2014, 19/06/2014,
21/06/20148 21/07/2014 8 Use before date 12/07/2014, 13/07/2014, 14/07/2014,
15/07/2014, 16/07/2014, 17/07/2014, 18/07/2014 x29 28/07/2014 8 Use before date 19/07/2014, 20/07/2014, 21/07/2014,
22/07/2014, 23/07/2014, 24/07/2014, 25/07/2014, 26/07/2014
The batches analysed from the 25th March 2014 consisted of samples of pre-packaged florets with
a selection of use by dates. These samples were analysed to examine if there is a correlation
between the assigned use by date and the freshness of the florets contained within the
packaging.
The first task was to compile a list of potentially odorous compounds that could be detected in
uninfected and infected broccoli using the protocol described earlier; this list was then used to
examine broccoli samples with varying use before dates to see if any of these samples are
showing signs of developing rot.
76
4.3.2 Broccoli results and discussion
4.3.2.1 Control sample
In the examination of the results obtained from broccoli, the volatile compounds in the control
sample were identified. The Total ion chromatogram for the control sample analysed on the 21st
November 2013 is presented in figure 30. Although there are a large number of peaks only a few
have been identified as coming from the control sample. This is because the vast majority of the
peaks in the TIC come are aliphatic hydrocarbons and are likely to have come from either the
plastic that the broccoli heads were wrapped in or from the sampling container itself. Buttery et
al. (1976) identified several compounds present in steam volatile oil of broccoli including dimethyl
disulphide, dimethyl trisulphide, hex-3-enal, nonanal and hex-cis-3-enol, although the major
components were 4-methylthiobutyl isothiocyanate (14% of total), 4-methylthiobutyl cyanide
(20% of total) and 2-phenylethyl cyanide (13% of total). These compounds were from a large
sample size (1.8 Kg) which was boiled in 6L of water then extracted with hexane.
The compounds identified from the control sample are listed in table 30.
Table 30. Compounds identified in broccoli control sample 21/11/2013
Retention time Peak area Name3.279 30281 Dimethyl disulphide3.909 45437 3-Methyl-2-pentanol6.404 348784 alpha-Pinene7.260 302273 beta-Myrcene7.324 54650 3-Hexenyl acetate8.867 61407 Nonanal8.962 284934 1-Undecene
77
Figure 30. TIC of broccoli control sample 21/11/2013
78
4.3.2.2 Slight wet rot
The second set of Broccoli samples analysed contained two samples that were characterised as
having slight wet rot and severe wet rot, and the results of the analysis are shown below, both
have been included to try and determine if the composition of odoriferous compounds changes as
the disease becomes more advanced. The TIC in figure 31 is from the sample with slight wet rot
and it is evident that more compounds were detected and these compounds are shown in table
31. The dimethyl disulphide and 1-undecene were again detected but at much higher levels.
Although Kremr et al. (2015) examined a number of vegetables in the Brassicaceae family, and
detected dimethyl sulphide, dimethyl disulphide and dimethyl trisulphide in Broccoli, the
significant increase in the amount of dimethyl disulphide detected in this sample compared to the
control would suggest that infection of broccoli with wet rot leads to an increase in the
production of sulphur containing compounds. There appears to be a lack of previously published
work looking at the volatile organic compounds given off by broccoli infected with wet rot. The
papers either focus on the identification of the bacterial causal agents for wet rot and methods
for its control or on the VOCs given off in fresh broccoli that contribute to its flavour. Derbali et al.
(1988) examined the biosynthesis of sulphur compounds in broccoli seedlings under anaerobic
conditions, focussing on hydrogen sulphide, methanethiol, dimethyl sulphide and dimethyl
disulphide.
Table 31. Compounds identified in broccoli sample with slight wet rot 21/11/2013
Retention time Peak area Name1.657 212700 Dimethyl sulphide3.282 36695029 Dimethyl disulphide3.904 169175 3-Methyl-2-pentanol4.903 182105 3-Hexen-1-ol6.402 474473 alpha-pinene6.616 267166 Dimethyl trisulphide7.256 182628 beta-myrcene7.325 46071 cis-3-Hexenyl acetate7.347 107167 1-Decene8.854 214395 1,4-Undecadiene8.961 4113924 1-Undecene
79
Figure 31. TOC of broccoli sample with slight wet rot 21/11/2013
80
4.3.2.3 Severe wet rot
The same compounds were detected in the sample with severe wet rot as for the sample with
slight wet rot and three additional compounds were also detected, these were 3-methyl-1-
butanol, 1-dodecene and indole. TIC of sample of Broccoli with severe wet rot analysed on
21/11/13 is shown in figure 32. The results for this compound are listed in table 32.
Table 32. Compounds detected in broccoli sample with severe wet rot 21/11/2013
Retention time Peak area Name1.698 1858629 Dimethyl sulphide3.222 106132 3-Methyl-1-butanol3.272 21428370 Dimethyl disulphide3.901 404731 3-Methyl-2-pentanol4.902 159310 3-Hexen-1-ol6.401 326523 alpha-pinene6.615 1463221 Dimethyl trisulphide7.256 299426 beta-Myrcene7.333 120456 3-Hexenyl acetate7.348 464423 1-Decene8.846 819458 1,4-Undecadiene8.956 12695178 1-Undecene10.472 246205 1-Dodecene11.417 2195129 Indole
Dimethyl sulphide and dimethyl trisulphide were only detected in the samples with wet rot along
with 3-methyl-1-butanol, 3-hexen-1-ol, 1-decene, 1,4-undecadiene, 1-dodecene and indole,
although Buttery et al.. (1976) reported finding most of these compounds via steam distillation.
This suggests that these compounds are normally present at low levels in healthy broccoli
samples, but at levels below the limit of detection of the methodology used in this work.
Although dimethyl disulphide was detected in all three samples there was a thousand fold
increase in the peak area from the control to the sample with slight wet rot, and for the sample
with severe wet rot this peak was overloaded. This increase in peak area as the infection
progressed can also be seen in the increase in dimethyl sulphide and dimethyl trisulphide areas
between the slight wet rot and severe wet rot samples.
The increased levels of VOCs found in samples with wet rot compared to the control sample
would suggest that the increased levels are indicative of an infection although whether this is due
to these compounds being produced by the bacteria or due to the physiological changes the
infection causes in the broccoli is beyond the scope of this work, which was solely to identify VOCs
that could be used to identify diseases.
81
Figure 32. TIC of broccoli sample with severe wet rot
82
4.3.2.4 Extent of wet rot in broccoli
The full results for all batches of broccoli samples can be found in appendix E.
The data from batch 1 was examined and it appears that the samples labelled Helen’s and Pasqual
have some evidence of wet rot infection which is not present in the Agromark sample. This is
based upon the presence of a significant quantity of dimethyl disulphide in the samples, which
when compared to the results obtained from batch 2 suggest that the Helen’s and Pasqual
samples have only a slight wet rot infection as there was no dimethyl trisulphide detected which
was found in both the samples in batch 2 with wet rot. There was no obvious visible evidence of
wet patches on these samples which is normally indicative of an infection with wet rot.
4.3.2.5 Use by date of broccoli samples
The full results for all batches of broccoli samples can be found in appendix E. Example
chromatograms can be found in appendix F.
Batch 3 contained samples that were all analysed prior to their use by dates and all of the samples
had results similar to those obtained for the control sample in batch 2. This suggests that there is
no wet rot in these samples. This was found to be the case for all samples in all the batches that
were analysed before their use by dates.
When samples that were past their use by date were analysed, the results became more variable
although an increased level of dimethyl disulphide was detected across the range of samples, the
levels detected did not follow a clear progression.
If the data from batches 3 - 9 are collated and summarised based upon use by date relative to
date of analysis and those compounds that were predominantly not detected were excluded then
figure 33 is obtained. The use by date in relation to injection date axis is calculated based upon
the packaging label and a value of -4 means that the use by date was four days after the analysis
date, and a value of 5 corresponds to a use by date five days before the analysis date.
83
-4 -3 -2 -1 0 1 2 3 4 5 6 7 8 90
500000
1000000
1500000
2000000
2500000
3000000
3500000
4000000
Broccoli use by date results
Dimethyl sulphide3-Methyl-1-butanolDimethyl disulphide3-Methyl-2-pentanol3-Hexen-1-olalpha-PineneDimethyl trisulphidebeta-Myrcene3-Hexenyl acetate1-Undecene
Use by date in relation to injection date (days)
Abun
danc
e
Figure 33. Broccoli use by date results
4.3.3 Conclusion
From all of the batches of packaged samples analysed there can be seen no clear correlation
between the use by date given to a sample and the amount of sulphides present in that sample,
this is partly due to the small sample sizes for each data point. Koike (2007) stated that bacterial
soft rot in broccoli is due to a combination of bacteria that favour wet, cool conditions, and as the
broccoli is packed in sealed packaging that is normally stored at refrigerator temperature, it could
be suggested that the packaging process for broccoli would produce favourable conditions for the
bacteria responsible for soft rot to thrive. Di Pentima et al. (1995) examined the biogenesis of off-
odour in broccoli stored under anaerobic conditions, and reported increased concentrations of
sulphur containing compounds in these samples. Lucera et al. (2010), Jacobsson et al. (2004) and
Esturk et al. (2014) have all examined the influence of different packaging materials on the flavour
of vegetables. Lucera et al. (2011) also examined the shelf-life of freshly cut florets and reported
that the cut florets had a noticeably shorter shelf-life than a whole head of broccoli due to a
higher rate of metabolism.
From the results presented above, uninfected broccoli produces much lower levels of the
dimethyl sulphides found and these compounds could be used in an electronic nose sensor for
testing the freshness of the broccoli prior to packaging, however it appears that the choice of use
by date for the pre-packaged broccoli has been correctly chosen since high levels of sulphides do
not start to appear until after the use by date has been passed.
84
5. Conclusions
No observable differences in volatile organic compounds produced by the difference
stages of spouting examined in this work were found in potatoes. There was also no
difference in samples that were supplied for analysed having been washed or not.
No observable differences in volatile organic compounds were observed in potatoes that
had suffered differing degrees of physical damage.
It may be possible to differentiate between onion diseases based upon the ratio of
sulphur containing compounds, although further work involving more sample replicates
would be required to test this hypothesis.
Thick neck in onions did not produce any sulphides but a strong response for 2,3-
butanediol was observed. This could be used as an indicator of susceptibility for onions to
develop diseases during storage.
Wet rot in broccoli produced a very strong response for methyl, dimethyl and trimethyl
sulphides.
The analysis of broccoli samples with respect to their use by dates indicated that once the
samples start to go off they then start to produce sulphides.
The compounds detected in infected samples give strong responses using the
methodology provided in the work, and it should be possible to upscale to develop an in
situ monitoring system for the storage areas for these vegetables.
It may be possible to use the compounds detected for infected samples as the basis for
detectors contained with a handheld electronic nose. This would allow batches of
vegetables to be assessed for being placed into a storage facility.
85
6. Further work
In all the vegetables analysed there are areas for improvement that could be investigated in the
future.
6.1 Replicate samples
Large scale replicate sampling of samples with the same condition would reduce the variability of
the results obtained in this work, which potentially, would allow for smaller changes in the volatile
organic compound composition to be identified as significant.
6.2 Deliberate infection of all samples
Methods would need to be developed to allow the deliberate infection of vegetable samples with
any disease. This would allow the progression of the disease to be monitored and any changes in
the volatile profile of the disease to be measured, as well as potentially allow for differentiation of
diseases by their volatile profile.
6.3 Climatic control
As shown in this work, the rate of disease progression can be influenced by the temperature of
storage, so being able to control these conditions would allow for a more accurate measure of the
volatile organic compounds to be achieved as the condition under investigation proceeds.
6.4 Larger sampling container
The type of sampling container used in this work is available in sizes up to and including 12 litres.
Increasing the sample size by the use of a larger container would allow for more compounds to be
detected as more sample could be used, this would need to be combined with the use of a
sampling system that could handle the increased amount of volatiles present as the SPME fibres
used only have a limited capacity. Potential drawback of this approach is that background levels
compounds associated with the sampling container would also increase significantly.
6.5 Use of glass sampling container
Glass sampling containers could be used to reduce the background interference seen from the
sampling containers in this work, although there would be challenges to be overcome with this
approach. It would be likely that any sampling container for this work would need to be custom
made especially in order to make it air tight. The sampling apparatus would most likely have to be
changed as it would be difficult to create an attachment for the Mininert valve used in this work.
86
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Wercinski, S., A., S., Pawliszyn, J. (1999) Solid Phase Microextraction: A Practical Guide. Marcel
Dekker Inc.
Wharon, P., S. (2013) Tuber and Stem Diseases/Conditions of Potato. Michigan State
University. Available from http://www.potatodiseases.org/tuberdiseases.html [accessed 17th
August 2016].
97
Appendix A Analysis results for potato samples
Maris Piper
WashedNo
sprouting
DesireeWashed
No sprouting
King EdwardWashed
No sprouting
King Edward
UnwashedNo
sprouting
King Edward
UnwashedEyes open
King Edward
UnwashedSprouting
King Edward
(Different stock)
UnwashedNo
sproutingCompound Area Area Area Area Area Area AreaAcetone 24989 61201 69982 52327 54381 18270 283112-Methylpropanal 21243 n.d. n.d. n.d. n.d. 1125 103542-Butanone n.d. n.d. n.d. n.d. n.d. 7999 n.d.Acetic acid 21692 37625 51771 48315 34838 16163 234592,3-Butanedione 5909 37625 n.d. n.d. n.d. 9037 n.d.3-Methylbutanal 39436 25929 45922 5971 4789 2863 129652-Methylbutanal 93227 49074 74605 n.d. 7683 8984 266631-Butanol n.d. n.d. n.d. 44940 30669 n.d. n.d.3-Hydroxy-2-butanone
n.d. 1568 12721 20178 16359 456 n.d.
1,2-Propanediol 67839 172051 209565 1146060 941646 687902 1472503-Methyl-1-butanol 7838 4829 15205 7676 n.d. n.d. 51312-Methyl-1-butanol 2642 n.d. n.d. n.d. n.d. 11021 n.d.Dimethyl disulphide n.d. n.d. n.d. n.d. n.d. n.d. n.d.1-Pentanol 10498 n.d. n.d. n.d. n.d. n.d. 168462,3-Butanediol 2013 n.d. n.d. n.d. n.d. n.d. n.d.Hexanal 35585 72893 81026 37079 52915 6237 419571-Hexanol 5097 6804 19539 36252 40535 14232 153482-Heptanone 10473 9695 20222 27681 24825 23746 16033Heptanal 8936 15491 18295 9018 13552 2288 112131-Octene n.d. n.d. n.d. n.d. n.d. n.d. 109072-Methyl-3-heptanone
224 13385 20392 23607 25503 12203 14109
Benzaldehyde 14886 26509 55176 43975 47026 8655 49889alpha-pinene 56299 72680 104660 132163 139158 65768 919836-Methyl-5-hepten-2-one
65179 38794 48943 55498 60621 53730 31760
2-Octanone 4483 6597 5728 21097 16014 25980 n.d.Octanal 2891 9755 14167 4993 4741 12160 119393-Hexenyl acetate 658 n.d. n.d. n.d. n.d. n.d. n.d.Fenchene 13912 15434 28821 32421 38047 25058 189952-Ethyl-1-hexanol 37122 73138 132954 363614 549650 241684 412588Limonene 28424 39376 37367 45503 55166 34586 39136Nonanal 43077 56810 69880 53886 61011 n.d. 1125391-Undecene n.d. n.d. n.d. n.d. n.d. n.d. n.d.2-Decanone n.d. 5290 8420 32034 36615 27162 16111Decanal 37484 43689 48650 35571 n.d. n.d. 48613
VOC results from potato sample batch 1 analysed on 05/11/2013
n.d. = Compound not detected
98
Desiree soaked
Desiree Mock
inoculationDesiree
Inoculated
Maris Piper
soaked
Maris Piper Mock
inoculation
Maris Piper
Inoculated
Maris Piper Long
term inoculated
Compound Area Area Area Area Area Area AreaTrimethylamine n.d. n.d. 1576785 n.d. 63218 2150637 659844Acetone 82145 175284 1740378 2405382 168649 4105938 949282-Methylpropanal n.d. n.d. n.d. n.d. n.d. 32508 n.d.2-Butanone n.d. n.d. 251808 n.d. n.d. 634433 1329787Acetic acid n.d. n.d. n.d. 9476 n.d. n.d. n.d.2,3-Butanedione 8967 43484 613965 7279 21218 386033 1403143-Methylbutanal 832 2079 9944 1290 6378 17218 31832-Methylbutanal n.d. n.d. n.d. n.d. 22630 n.d. n.d.1-Butanol n.d. 29632 521131 n.d. 12117 n.d. n.d.3-Hydroxy-2-butanone n.d. 113858 10944218 n.d. 58225 9493766 32279981,2-Propanediol 2326 40456 118007 9993 37162 76941 336293-Methyl-1-butanol 6526 n.d. 85685 n.d. n.d. 513319 828572-Methyl-1-butanol n.d. 5695 57202 n.d. n.d. 353327 32973Dimethyl disulphide n.d. n.d. 47693 n.d. n.d. n.d. n.d.1-Pentanol n.d. 61557 48955 n.d. 16393 n.d. n.d.2,3-Butanediol 3454 270901 16125757 30555 173101 52306012 663416Hexanal 1001 27109 96809 3791 32300 n.d. n.d.1-Hexanol n.d. 53542 73746 n.d. 18571 n.d. n.d.Butyrolactone n.d. 10576 31060 n.d. n.d. 336 n.d.2-Heptanone 12024 43008 337679 n.d. 13474 n.d. n.d.Heptanal n.d. 11222 44217 1593 12881 n.d. n.d.1-Octene n.d. n.d. n.d. n.d. 12763 n.d. n.d.2-Methyl-3-heptanone 34966 43883 30254 29231 28683 n.d. 13397Benzaldehyde n.d. 120646 185619 n.d. 45550 n.d. n.d.alpha-pinene 93135 196534 176658 181662 165037 n.d. 2031346-Methyl-5-hepten-2-one 115950 136930 150096 74931 70791 n.d. 750962-Octanone n.d. 21572 n.d. n.d. n.d. n.d. 5697Octanal 16822 31218 11358 14840 8170 387 176213-Hexenyl acetate n.d. n.d. n.d. n.d. n.d. n.d. n.d.Fenchene 40170 62921 59224 49634 42240 n.d. 646952-Ethyl-1-hexanol 68875 641448 862144 42336 128214 n.d. 352397Limonene 92664 172622 166445 79332 87939 n.d. 83937Nonanal 104159 n.d. 362072 n.d. 71623 n.d. n.d.1-Undecene n.d. n.d. 309614 n.d. n.d. n.d. n.d.2-Decanone n.d. n.d. 1268797 n.d. n.d. n.d. n.d.Decanal n.d. n.d. n.d. n.d. n.d. n.d. n.d.
VOC results from potato sample batch 2 analysed on 11/11/2013
n.d. = Compound not detected
Maris Piper inoculated sample overloaded the detector after the 2,3-butanediol peak.
Maris Desiree King King King King King
99
PiperWashed
No sprouting
WashedNo
sprouting
EdwardWashed
No sprouting
EdwardUnwashed
No sprouting
EdwardUnwashedEyes open
EdwardUnwashedSprouting
Edward(Different
stock)Unwashed
No sprouting
Compound Area Area Area Area Area Area AreaAcetone 55590 62542 37934 57912 24612 42994 354962-Methylpropanal n.d. n.d. n.d. n.d. n.d. 3124 n.d.2-Butanone 6884 17831 19856 n.d. n.d. n.d. 16698Acetic acid 41337 90355 60890 116170 46403 50715 1137072,3-Butanedione 14817 n.d. 10993 n.d. n.d. 8311 460183-Methylbutanal 19424 39184 40774 9596 6864 7490 203672-Methylbutanal 29104 54929 62970 n.d. n.d. 11811 401561-Butanol n.d. n.d. n.d. 35506 37234 53715 n.d.3-Hydroxy-2-butanone
101534 21226 28277 n.d. 15115 n.d. n.d.
1,2-Propanediol 34138 102528 88853 250514 261431 241928 1744553-Methyl-1-butanol 16100 6765 16439 6525 3901 n.d. 43162-Methyl-1-butanol 4205 n.d. 3185 n.d. n.d. n.d. 4477Dimethyl disulphide n.d. n.d. n.d. n.d. n.d. n.d. n.d.1-Pentanol n.d. n.d. n.d. n.d. n.d. n.d. n.d.2,3-Butanediol n.d. 57705 n.d. n.d. n.d. n.d. n.d.Hexanal 38275 125402 119046 57286 110354 88651 1017781-Hexanol 11461 16955 17929 17382 19910 18398 146422-Heptanone 32428 27109 17014 22244 29042 34702 32369Heptanal 15823 47195 46730 21003 39290 27158 356831-Octene n.d. n.d. n.d. n.d. n.d. n.d. n.d.2-Methyl-3-heptanone
59101 37455 30721 2457 33538 2944 n.d.
Benzaldehyde n.d. 69824 79627 49190 69990 74772 108112alpha-pinene 221181 148719 99522 96880 126808 150327 1726366-Methyl-5-hepten-2-one
51924 60660 69068 73713 75809 71987 68801
2-Octanone 18211 10430 n.d. 10218 12332 12888 n.d.Octanal 20734 26595 26174 17223 31398 25418 312443-Hexenyl acetate n.d. n.d. n.d. n.d. n.d. n.d. n.d.Fenchene 43760 30638 26646 24090 32938 38246 416302-Ethyl-1-hexanol 192104 184820 211122 152817 167887 162117 143302Limonene 59497 46955 31831 29748 34697 33899 43761Nonanal 55222 125711 145989 60788 126512 84077 1683061-Undecene 37492 85656 n.d. n.d. 87934 n.d. 1205192-Decanone n.d. n.d. 6648 6960 7173 6173 n.d.Decanal 65533 87026 85545 24116 46760 n.d. 75080
VOC results from potato sample batch 3 analysed on 12/11/2013
n.d. = Compound not detected
Maris Piper Maris Piper Maris Piper Maris Piper Maris Piper Maris Piper
100
WashedNo
sprouting
WashedEyes open
WashedSprouting
UnwashedNo
sprouting
UnwashedEyes open
UnwashedSprouting
Compound Area Area Area Area Area AreaAcetone 18765 12048 38438 35893 35505 387342-Methylpropanal n.d. n.d. 7191 n.d. n.d. n.d.2-Butanone n.d. n.d. n.d. n.d. 52951 n.d.Acetic acid 38264 139053 81787 136990 72948 1268712,3-Butanedione n.d. n.d. 30757 60758 19133 102163-Methylbutanal 7366 11096 23431 1440 2962 46442-Methylbutanal 17089 31051 32839 n.d. n.d. n.d.1-Butanol n.d. n.d. n.d. 21229 25945 618163-Hydroxy-2-butanone 50518 99995 n.d. 83780 93815 754681,2-Propanediol n.d. n.d. n.d. n.d. n.d. 403963-Methyl-1-butanol 3167 14211 40027 n.d. 3895 53662-Methyl-1-butanol n.d. n.d. 7384 n.d. n.d. n.d.Dimethyl disulphide n.d. n.d. n.d. n.d. n.d. n.d.1-Pentanol 13769 52705 30935 60730 49219 n.d.2,3-Butanediol 22539 60767 44962 21568 12887 19792Hexanal 53989 41577 23892 57854 36273 728321-Hexanol 40245 79229 59933 40844 38221 329222-Heptanone 12835 n.d. n.d. n.d. n.d. n.d.Heptanal 15688 9660 5521 12001 10152 171421-Octene n.d. n.d. n.d. 8340 n.d. n.d.2-Methyl-3-heptanone 14061 18961 19552 21437 23539 28644Benzaldehyde 132039 212658 230236 99350 97667 97583alpha-pinene 108619 139452 158077 163525 158322 1794756-Methyl-5-hepten-2-one
42169 51139 42661 52054 58010 55722
2-Octanone 4480 7524 13583 6630 11666 8226Octanal 14289 4804 4899 14307 6612 243213-Hexenyl acetate n.d. n.d. n.d. n.d. n.d. n.d.Fenchene 30766 43054 46492 41930 47326 509772-Ethyl-1-hexanol 1373123 1108982 442605 1116180 1265752 1974724Limonene 34769 46068 51952 39993 44391 40778Nonanal 55971 n.d. n.d. 40106 n.d. 685911-Undecene 34168 n.d. n.d. 26104 n.d. n.d.2-Decanone 3812 4814 5131 4588 6027 4940Decanal 17317 n.d. n.d. n.d. n.d. n.d.
VOC results from potato sample batch 4 analysed on 13/11/2013
n.d. = Compound not detected
101
Desiree soakedDesiree Mock
inoculationDesiree
InoculatedCompound Area Area AreaTrimethylamine 5248 22593 465011Acetone 25220 7955 19441242-Methylpropanal n.d. n.d. 30332-Butanone 7165 n.d. 85950Acetic acid n.d. n.d. n.d.2,3-Butanedione 11752 15780 782093-Methylbutanal 2275 2427 70142-Methylbutanal 3779 n.d. 105691-Butanol 19161 8340 n.d.3-Hydroxy-2-butanone 18288 26573 6066961,2-Propanediol 26430 32840 437393-Methyl-1-butanol n.d. 1961 175482-Methyl-1-butanol 1580 n.d. n.d.Dimethyl disulphide n.d. n.d. 10104771-Pentanol n.d. n.d. n.d.2,3-Butanediol 25616 67928 1933171Hexanal 62455 44890 658061-Hexanol 10562 21174 22912Butyrolactone n.d. 1377 n.d.2-Heptanone 10806 11338 26656Heptanal 28245 26481 883891-Octene n.d. n.d. n.d.2-Methyl-3-heptanone 17380 20956 22328Benzaldehyde n.d. n.d. 64780alpha-pinene 133198 128327 1014936-Methyl-5-hepten-2-one 47278 45030 749592-Octanone n.d. 3027 n.d.Octanal 14738 16995 202783-Hexenyl acetate n.d. n.d. n.d.Fenchene 31553 32743 303132-Ethyl-1-hexanol 22320 52868 107886Limonene 23623 31138 36734Nonanal 50225 54141 988481-Undecene n.d. n.d. 2904612-Decanone n.d. 3051 11330Decanal 39398 35728 49626
VOC results from potato sample batch 5analysed on 14/11/2013
n.d. = Compound not detected
102
King EdwardWashed
No sprouting
King EdwardWashed
Eyes open
King EdwardWashed
Sprouting
DesireeWashed
No sprouting
DesireeWashed
Eyes open
DesireeWashed
Sprouting
Compound Area Area Area Area Area AreaAcetone 3589 21002 26319 27894 21002 194872-Methylpropanal n.d. 6792 n.d. n.d. 6792 n.d.2-Butanone 6661 n.d. n.d. n.d. n.d. 8295Acetic acid 167836 143154 193796 223394 143154 501102,3-Butanedione 23078 8418 71147 n.d. 8418 156703-Methylbutanal 11825 16864 26655 7035 16864 224602-Methylbutanal 19259 18408 32741 11616 18408 325311-Butanol n.d. n.d. n.d. n.d. n.d. n.d.3-Hydroxy-2-butanone 55092 65571 102316 45442 65571 728211,2-Propanediol 28873 21166 53720 9061 21166 127993-Methyl-1-butanol 3007 10275 21861 n.d. 10275 406442-Methyl-1-butanol n.d. n.d. 4400 n.d. n.d. 6166Dimethyl disulphide n.d. n.d. n.d. n.d. n.d. n.d.1-Pentanol 31146 22015 n.d. n.d. 22015 140162,3-Butanediol 9177 13639 28089 5150 13639 8861Hexanal 55031 64968 110242 49300 64968 296391-Hexanol 22556 25974 49117 10904 25974 333032-Heptanone 10911 n.d. n.d. n.d. n.d. 19532Heptanal 11506 15292 32586 13780 15292 161631-Octene 10911 15521 n.d. n.d. 15521 n.d.2-Methyl-3-heptanone 18930 23992 35883 12772 23992 23504Benzaldehyde 104564 123272 131702 57579 123272 75735alpha-pinene 86359 76834 88700 67649 76834 594656-Methyl-5-hepten-2-one
47698 74037 102797 46499 74037 80652
2-Octanone n.d. n.d. 5778 4473 n.d. 12705Octanal 14718 20415 15594 n.d. 20415 155473-Hexenyl acetate n.d. n.d. n.d. n.d. n.d. n.d.Fenchene 28328 25950 27640 22351 25950 210592-Ethyl-1-hexanol 451693 697197 682128 306081 697197 251856Limonene 27510 31217 58650 18694 31217 31487Nonanal 71247 80814 221500 57506 80814 n.d.1-Undecene n.d. n.d. 131262 39060 n.d. n.d.2-Decanone n.d. 3715 n.d. n.d. 3715 1733Decanal n.d. n.d. 51172 n.d. n.d. n.d.
VOC results from potato sample batch 6 analysed on 19/11/2013
n.d. = Compound not detected
103
Maris PiperWashed
No sprouting
Maris PiperWashed
Eyes open
Maris PiperWashed
Sprouting
Maris PiperUnwashed
No sprouting
Maris PiperUnwashedEyes open
Maris PiperUnwashedSprouting
104
Compound Area Area Area Area Area AreaAcetone 22712 21056 39586 26639 24141 228982-Methylpropanal n.d. n.d. n.d. n.d. n.d. n.d.2-Butanone 6810 6326 25853 n.d. n.d. n.d.Acetic acid 17028 28062 58658 52935 40610 244502,3-Butanedione n.d. 6937 n.d. 21959 n.d. 47193-Methylbutanal 15092 10381 16098 2329 3235 16312-Methylbutanal 22717 14186 27073 n.d. n.d. n.d.1-Butanol n.d. n.d. n.d. 25390 37325 226863-Hydroxy-2-butanone n.d. n.d. n.d. n.d. 29065 n.d.1,2-Propanediol 7941 11113 15468 14908 12772 189363-Methyl-1-butanol 2366 3867 12486 n.d. 2373 n.d.2-Methyl-1-butanol n.d. 1216 2735 n.d. n.d. n.d.Dimethyl disulphide n.d. n.d. n.d. n.d. n.d. n.d.1-Pentanol n.d. n.d. n.d. n.d. 12536 n.d.2,3-Butanediol n.d. n.d. n.d. n.d. n.d. n.d.Hexanal 141204 50221 30540 78268 72367 523101-Hexanol 3884 7607 10856 10039 9547 65732-Heptanone 6869 n.d. n.d. n.d. n.d. 6462Heptanal 21502 22834 16402 44790 49532 297781-Octene n.d. n.d. n.d. n.d. n.d. n.d.2-Methyl-3-heptanone 10123 21924 10835 10723 20768 13554Benzaldehyde n.d. 23548 25389 18530 25808 23113alpha-pinene 64976 63216 39549 60114 62089 463966-Methyl-5-hepten-2-one
16781 31865 28755 19022 35336 26443
2-Octanone 2231 3300 6006 2192 4697 n.d.Octanal 10754 10607 6707 16435 20221 152093-Hexenyl acetate n.d. n.d. n.d. n.d. n.d. n.d.Fenchene 12445 13594 11196 12336 15445 112982-Ethyl-1-hexanol 29456 61342 63363 35118 64323 58615Limonene 12372 14599 14239 9378 18113 12113Nonanal 52950 100494 77680 97997 91991 897831-Undecene 34931 n.d. n.d. n.d. n.d. n.d.2-Decanone n.d. 1135 1394 n.d. n.d. n.d.Decanal 25515 24141 19966 27410 24470 24098
VOC results from potato sample batch 7 analysed on 25/11/2013
n.d. = Compound not detected
Diseased Control
Diseased Mock no fungi
Diseased Gangrene
Diseased Dry rot
Compound Area Area Area Area
105
Trimethylamine n.d. n.d. n.d. n.d.Acetone 99759 129188 175258 2681472-Methylpropanal n.d. n.d. n.d. n.d.2-Butanone n.d. n.d. n.d. 14733Acetic acid 18226 4400 n.d. n.d.2,3-Butanedione n.d. n.d. 2772 n.d.3-Methylbutanal 1229 3101 997 36722-Methylbutanal n.d. 3356 2255 n.d.1-Butanol n.d. 2264 1120 35423-Hydroxy-2-butanone n.d. n.d. n.d. n.d.1,2-Propanediol 9256 23517 13944 303263-Methyl-1-butanol n.d. 1255 n.d. 37152-Methyl-1-butanol n.d. n.d. n.d. n.d.Dimethyl disulphide n.d. n.d. n.d. n.d.1-Pentanol n.d. n.d. n.d. n.d.2,3-Butanediol n.d. 1964 n.d. n.d.Hexanal 3784 6924 4564 117671-Hexanol n.d. n.d. n.d. n.d.Butyrolactone n.d. 844 788 30102-Heptanone 3205 n.d. 6614 9821Heptanal n.d. 1561 1412 42311-Octene n.d. n.d. n.d. n.d.2-Methyl-3-heptanone 8137 1104 12044 19162Benzaldehyde 4641 9394 11814 32514alpha-pinene 34439 46955 70004 1117396-Methyl-5-hepten-2-one 19226 23303 29956 379542-Octanone n.d. n.d. n.d. n.d.Octanal 2714 3896 5462 33823-Hexenyl acetate n.d. n.d. n.d. n.d.Fenchene 7443 13006 16888 234562-Ethyl-1-hexanol 32478 40574 105242 242616Limonene 51814 56701 80919 113799Nonanal 31738 n.d. n.d. n.d.1-Undecene n.d. n.d. n.d. n.d.2-Decanone 6458 5701 n.d. 15002Decanal 12714 n.d. n.d. n.d.
VOC results from potato sample batch 8 analysed on 26/11/2013
n.d. = Compound not detected
Control No
damage Light damage Severe damageCompound Area Area Area
106
Trimethylamine n.d. n.d. n.d.Acetone 206413 182227 2549522-Methylpropanal n.d. n.d. n.d.2-Butanone n.d. n.d. n.d.Acetic acid n.d. n.d. n.d.2,3-Butanedione 3990 13152 83543-Methylbutanal 3428 17729 37802-Methylbutanal 4509 20392 n.d.1-Butanol n.d. 21028 n.d.3-Hydroxy-2-butanone n.d. n.d. n.d.1,2-Propanediol 9191 201505 258403-Methyl-1-butanol n.d. n.d. 48622-Methyl-1-butanol 2083 n.d. 6621Dimethyl disulphide n.d. n.d. n.d.1-Pentanol n.d. n.d. n.d.2,3-Butanediol 1437 n.d. n.d.Hexanal 14985 39255 81391-Hexanol 6693 18999 3646Butyrolactone n.d. n.d. n.d.2-Heptanone 12917 17087 24006Heptanal 7597 16789 n.d.1-Octene n.d. n.d. n.d.2-Methyl-3-heptanone 25086 39351 41487Benzaldehyde 25692 74435 n.d.alpha-pinene 79145 142220 1330756-Methyl-5-hepten-2-one 48838 60913 501552-Octanone 12501 13779 20023Octanal 19674 29643 197893-Hexenyl acetate n.d. n.d. n.d.Fenchene 25347 40018 356592-Ethyl-1-hexanol 184690 207379 166738Limonene 43621 50345 51866Nonanal n.d. n.d. n.d.1-Undecene n.d. n.d. n.d.2-Decanone 19832 16807 21035Decanal n.d. n.d. n.d.
VOC results from potato sample batch 8 analysed on 26/11/2013
n.d. = Compound not detected
Control No
damage Light damage Severe damageCompound Area Area Area
107
Trimethylamine n.d. n.d. n.d.Acetone 60367 54387 181022-Methylpropanal n.d. n.d. n.d.2-Butanone n.d. n.d. n.d.Acetic acid 64267 83194 758782,3-Butanedione 7750 n.d. n.d.3-Methylbutanal 10045 13402 44312-Methylbutanal 17179 20616 94151-Butanol 23237 n.d. n.d.3-Hydroxy-2-butanone 9647 n.d. 650601,2-Propanediol 245031 264612 1704493-Methyl-1-butanol n.d. n.d. n.d.2-Methyl-1-butanol 2393 2609 n.d.Dimethyl disulphide n.d. n.d. n.d.1-Pentanol n.d. n.d. n.d.2,3-Butanediol n.d. 2311 n.d.Hexanal 37060 41852 252691-Hexanol 11963 11919 8174Butyrolactone 5659 5155 15772-Heptanone n.d. 10295 n.d.Heptanal 13167 17070 183461-Octene n.d. n.d. n.d.2-Methyl-3-heptanone 24783 24711 n.d.Benzaldehyde 44608 54187 30821alpha-pinene 43988 26646 262416-Methyl-5-hepten-2-one 62225 71625 961382-Octanone 6608 n.d. 4991Octanal 14445 8362 71013-Hexenyl acetate n.d. n.d. n.d.Fenchene 17327 13483 112562-Ethyl-1-hexanol 93475 42813 205580Limonene 23741 14790 16526Nonanal 78298 67255 639741-Undecene 54383 48688 534302-Decanone 37141 16393 11454Decanal n.d. 27781 30898
VOC results from potato sample batch 9 analysed on 28/11/2013
n.d. = Compound not detected
Desiree Control
Desiree Mock
inoculation
Desiree Dry Rot
Desiree Gangrene
Maris Piper Mock
Maris Piper
Dry Rot
Maris Piper
Gangrene
108
inoculationCompound Area Area Area Area Area Area AreaTrimethylamine 54027 0 0 32471 827360 797132 2761161Acetone 73158 30525 26324 19067 0 0 431662-Methylpropanal 0 0 0 0 0 0 02-Butanone 36823 0 0 10910 0 97481 504805Acetic acid 0 0 0 19699 7596 0 02,3-Butanedione 14358 4419 6694 0 116656 190041 7036653-Methylbutanal 2448 1398 2503 1354 0 2202 87622-Methylbutanal 0 3040 6013 0 0 0 115541-Butanol 76452 12612 32330 113812 17753 20638 230523-Hydroxy-2-butanone 141508 2230 21255 14747 944752 1845906 01,2-Propanediol 9748 0 12442 12525 23404 18609 657623-Methyl-1-butanol 5289 3039 6572 0 7232 38612 2703932-Methyl-1-butanol 2909 1006 5242 0 0 12962 117908Dimethyl disulphide 0 0 0 563 0 0 01-Pentanol 30150 8869 24429 0 0 0 02,3-Butanediol 39862 3590 6232 0 466490 9220454 5606636Hexanal 30982 11826 19057 21778 12965 14869 111641-Hexanol 6518 0 0 0 0 0 0Butyrolactone 0 0 1583 1366 0 2878 02-Heptanone 12245 4475 7404 10616 10358 12739 24710Heptanal 8892 3068 6218 6215 4552 6344 42301-Octene 9412 0 5399 0 0 0 02-Methyl-3-heptanone 13707 10796 10747 13099 2811 2077 10251Benzaldehyde 0 20993 24240 0 0 0 19888alpha-pinene 130802 97282 112232 128629 119314 171722 837846-Methyl-5-hepten-2-one 17084 10794 25589 6391 21363 44562 88512-Octanone 0 1295 0 0 0 5341 0Octanal 2085 1099 0 8976 8470 4419 18773-Hexenyl acetate 0 0 0 0 0 0 0Fenchene 22842 18608 20837 24326 23640 33482 173202-Ethyl-1-hexanol 120688 97225 104460 133285 126235 151129 96406Limonene 15334 11023 13567 16150 16610 24653 15789Nonanal 45567 16630 23279 39522 29669 27441 194611-Undecene 25101 0 16593 0 0 0 02-Decanone 3112 0 0 2069 3181 4151 0Decanal 8782 2104 7209 0 0 0 0
VOC results from potato sample batch 10 analysed on 13/01/2014
n.d. = Compound not detected
Charlotte Healthy
Charlotte Black spot
Melody No inoculation
Melody Mock inoculation
Melody Bacterial
inoculationCompound Area Area Area Area Area
109
Trimethylamine n.d. n.d. n.d. n.d. 18384Acetone 16753 20728 21842 19039 330582-Methylpropanal n.d. n.d. n.d. n.d. n.d.2-Butanone 6087 12376 n.d. n.d. 130955Acetic acid 94788 50982 25757 63654 n.d.2,3-Butanedione n.d. n.d. n.d. n.d. 2568093-Methylbutanal 26674 42246 3378 2405 50892-Methylbutanal n.d. 62068 n.d. n.d. n.d.1-Butanol 226476 162519 172670 110868 1452133-Hydroxy-2-butanone 56036 n.d. 27067 38847 62836691,2-Propanediol 247809 96108 79287 68561 1639333-Methyl-1-butanol 3045 11519 4423 4585 1454332-Methyl-1-butanol n.d. 4507 n.d. 2209 35977Dimethyl disulphide n.d. n.d. n.d. n.d. n.d.1-Pentanol n.d. 32336 n.d. 15832 453212,3-Butanediol 21530 18394 n.d. n.d. 337620Hexanal 118900 139997 38223 33762 439131-Hexanol 10158 26268 17833 16757 24168Butyrolactone n.d. 3929 5686 2134 62802-Heptanone n.d. n.d. 9298 n.d. n.d.Heptanal 72224 75885 23428 30903 509501-Octene n.d. n.d. n.d. n.d. n.d.2-Methyl-3-heptanone 37868 33270 10596 41131 32368Benzaldehyde 47623 55849 31244 26991 25347alpha-pinene 36499 39455 54682 36402 356596-Methyl-5-hepten-2-one 186783 305952 131939 176377 1692982-Octanone 7230 n.d. 5503 n.d. 14150Octanal 36196 32834 11715 26388 231853-Hexenyl acetate n.d. n.d. n.d. n.d. n.d.Fenchene 11059 10700 11342 10379 82932-Ethyl-1-hexanol 47555 79536 71026 62776 45322Limonene 29186 31433 33458 29916 32663Nonanal 220185 253588 105485 85948 1336881-Undecene n.d. n.d. 77374 n.d. n.d.2-Decanone 168880 154079 191066 87414 55102Decanal 127878 162436 34511 n.d. 88304
VOC results from potato sample batch 11 analysed on 11/02/2014
n.d. = Compound not detected
Melody No inoculation
Melody Mock inoculation
Melody Bacterial
inoculation
110
Compound Area Area AreaTrimethylamine n.d. n.d. 235542Acetone 28200 42293 n.d.2-Methylpropanal n.d. n.d. n.d.2-Butanone n.d. n.d. 317434Acetic acid 58394 255754 n.d.2,3-Butanedione n.d. n.d. 1810373-Methylbutanal 5947 7484 155972-Methylbutanal n.d. n.d. n.d.1-Butanol 149482 382282 941493-Hydroxy-2-butanone 310713 532355 44382181,2-Propanediol 106357 175626 3242773-Methyl-1-butanol 23621 13356 3356542-Methyl-1-butanol 3777 n.d. 118564Dimethyl disulphide n.d. 3963 20468061-Pentanol 36764 32251 595462,3-Butanediol n.d. 38611 152463Hexanal 50265 56584 513351-Hexanol 63620 40109 73394Butyrolactone 8365 4013 n.d.2-Heptanone n.d. n.d. 57019Heptanal 17575 23654 186751-Octene n.d. n.d. n.d.2-Methyl-3-heptanone 16157 18478 37948Benzaldehyde 62080 45208 27278alpha-pinene 89878 62332 814956-Methyl-5-hepten-2-one 78441 93466 1201742-Octanone n.d. n.d. 7220Octanal 18054 20099 278073-Hexenyl acetate n.d. n.d. n.d.Fenchene 17931 12927 177792-Ethyl-1-hexanol 48763 89774 101807Limonene 59800 42168 58628Nonanal 175185 171892 1765651-Undecene 113584 113993 8063402-Decanone 93589 64590 133128Decanal 20902 21592 28961
VOC results from potato sample batch 12 analysed on 17/02/2014
n.d. = Compound not detected
Charlotte EK Healthy
Charlotte EK
Melody LA Healthy
Melody LA Gangrene
Melody MD Healthy
Melody MD Rubbery
111
GangreneCompound Area Area Area Area Area AreaTrimethylamine 8413 77820 n.d. 25604 7246 1232786Acetone 12583 24336 29656 17235 75292 n.d.2-Methylpropanal n.d. n.d. n.d. n.d. n.d. n.d.2-Butanone n.d. n.d. n.d. n.d. 70614 113590Acetic acid n.d. 24614 53351 18327 n.d. 836662,3-Butanedione 520970 210761 12669 1158568 29397 4717073-Methylbutanal 972 4227 5716 3674 9494 24022-Methylbutanal n.d. n.d. n.d. n.d. 54937 n.d.1-Butanol 114176 55672 192011 n.d. 83575 130303-Hydroxy-2-butanone 433228 3771191 87276 14298 84077 126258741,2-Propanediol 5884 56141 35710 41429 36859 1007303-Methyl-1-butanol 32597 n.d. 9281 221543 145412 5341752-Methyl-1-butanol 8179 54092 n.d. 115778 56672 263174Dimethyl disulphide n.d. 240141 n.d. n.d. n.d. n.d.1-Pentanol n.d. 76458 127020 29345 332001 525212,3-Butanediol 597091 3357440 75860 8531275 74627 91296789Hexanal 18134 65918 46461 21664 43087 n.d.1-Hexanol 10618 176126 234928 65816 298623 n.d.Butyrolactone 4462 11516 8535 143012 27374 n.d.2-Heptanone n.d. n.d. n.d. 32417 144042 n.d.Heptanal 4758 19089 23738 6857 26729 n.d.1-Octene n.d. n.d. n.d. n.d. n.d. n.d.2-Methyl-3-heptanone n.d. n.d. n.d. n.d. n.d. n.d.Benzaldehyde 12327 66670 84547 49758 186532 n.d.alpha-pinene 17405 137739 168145 37774 71823 n.d.6-Methyl-5-hepten-2-one 7994 88476 83442 89069 421223 n.d.2-Octanone n.d. 37604 24504 14237 96687 n.d.Octanal 3500 30271 8237 22609 63015 n.d.3-Hexenyl acetate n.d. n.d. n.d. n.d. n.d. n.d.Fenchene 2580 33561 19978 10771 24109 n.d.2-Ethyl-1-hexanol 19103 338928 227006 361376 709449 n.d.Limonene 8385 263166 44996 38399 40266 n.d.Nonanal 17996 n.d. n.d. n.d. n.d. n.d.1-Undecene n.d. 288168 n.d. 149428 n.d. n.d.2-Decanone 2869 15347 116003 55480 265948 n.d.Decanal 3289 n.d. n.d. n.d. n.d. n.d.
VOC results from potato sample batch 13 analysed on 10/03/2014
n.d. = Compound not detected
Melody MD rubbery sample overloaded the detector after the 2,3-butanediol peak.
Sunrise WC (washed)
Sunrise WC (washed) Pit
Melody rubbery
112
Healthy rotCompound Area Area AreaTrimethylamine n.d. 56745 89748Acetone 24444 37851 708192-Methylpropanal n.d. n.d. n.d.2-Butanone n.d. 342711 n.d.Acetic acid 50538 n.d. 1205272,3-Butanedione 22487 97630 3938103-Methylbutanal 16592 7786 32042-Methylbutanal 20751 n.d. n.d.1-Butanol 338056 167416 1550613-Hydroxy-2-butanone 305600 1125602 95417921,2-Propanediol 10242 8305 454523-Methyl-1-butanol 8654 47604 1642922-Methyl-1-butanol n.d. 18619 112101Dimethyl disulphide n.d. n.d. n.d.1-Pentanol 34374 n.d. 1752892,3-Butanediol 37576 81036 45204277Hexanal 37565 19938 1067641-Hexanol 26654 38889 101481Butyrolactone n.d. 3164 88792-Heptanone n.d. n.d. 99865Heptanal 12662 13408 332761-Octene n.d. n.d. n.d.2-Methyl-3-heptanone n.d. n.d. n.d.Benzaldehyde 30446 23242 56764alpha-pinene 36834 41686 573896-Methyl-5-hepten-2-one 65274 61254 911482-Octanone n.d. n.d. 33549Octanal 7689 1430 221743-Hexenyl acetate n.d. n.d. n.d.Fenchene 7040 10201 172162-Ethyl-1-hexanol 105250 123519 121122Limonene 21032 23271 42515Nonanal 65380 54651 1076351-Undecene n.d. 49002 695372-Decanone 3314 5293 8973Decanal n.d. 9467 n.d.
VOC results from potato sample batch 14 analysed on 11/03/2014
n.d. = Compound not detected
VR808 S342 VR808 S342 VR808 S342
113
WashedNo sprouting
WashedEyes open
WashedSprouting
Compound Area Area AreaAcetone 181879 139753 1593762-Methylpropanal n.d. n.d. n.d.2-Butanone 54237 n.d. n.d.Acetic acid n.d. n.d. n.d.2,3-Butanedione 44905 32806 270533-Methylbutanal 5333 4634 67672-Methylbutanal n.d. n.d. n.d.1-Butanol 510499 258301 1345743-Hydroxy-2-butanone 284648 227370 4075861,2-Propanediol 62164 311047 848063-Methyl-1-butanol n.d. 108385 2188232-Methyl-1-butanol 25921 32791 81596Dimethyl disulphide n.d. n.d. n.d.1-Pentanol 324176 392145 2457632,3-Butanediol 44325 48823 121713Hexanal 8400 3076 n.d.1-Hexanol n.d. 56486 419072-Heptanone 417248 97490 181093Heptanal n.d. n.d. 355161-Octene n.d. n.d. n.d.2-Methyl-3-heptanone 21285 29973 50026Benzaldehyde n.d. 19888 24336alpha-pinene 120238 77635 780126-Methyl-5-hepten-2-one n.d. 169747 2328752-Octanone 151766 140723 211832Octanal 93315 120529 1708573-Hexenyl acetate n.d. n.d. n.d.Fenchene 36768 18143 198692-Ethyl-1-hexanol 333871 804033 1003726Limonene 117661 60696 71395Nonanal n.d. n.d. n.d.1-Undecene n.d. n.d. n.d.2-Decanone 1903 54455 53760Decanal n.d. n.d. n.d.
VOC results from potato sample batch 15 analysed on 17/03/2014
n.d. = Compound not detected
Maris Piper Maris Piper Maris Piper Estima Estima Estima
114
No DamageLight
damageSevere
damage No DamageLight
damageSevere
damageCompound Area Area Area Area Area AreaTrimethylamine n.d. n.d. n.d. n.d. n.d. n.d.Acetone 48861 51275 37847 31615 41835 349842-Methylpropanal n.d. n.d. n.d. n.d. n.d. n.d.2-Butanone n.d. n.d. 20574 16312 n.d. 24028Acetic acid 104742 74015 178179 51802 60384 556272,3-Butanedione n.d. n.d. n.d. n.d. 8084 n.d.3-Methylbutanal 32041 23345 28719 51849 34153 401422-Methylbutanal n.d. n.d. 64726 n.d. 49668 818741-Butanol 442520 472624 281688 271259 241342 957233-Hydroxy-2-butanone 190126 80543 82777 194801 109684 1088251,2-Propanediol 120243 112386 181195 392415 345573 1990253-Methyl-1-butanol n.d. n.d. n.d. n.d. 21604 145732-Methyl-1-butanol n.d. n.d. n.d. n.d. 8175 n.d.Dimethyl disulphide n.d. n.d. 13178 n.d. n.d. n.d.1-Pentanol 171194 140938 99271 63677 101650 444352,3-Butanediol n.d. n.d. n.d. 141482 128639 150767Hexanal 276064 192229 127312 95159 92521 638461-Hexanol 141311 104887 77672 86670 114546 53657Butyrolactone 9805 n.d. n.d. n.d. n.d. n.d.2-Heptanone 54174 35469 n.d. n.d. n.d. n.d.Heptanal 66443 47803 41644 32981 33268 231791-Octene n.d. 47126 n.d. n.d. n.d. n.d.2-Methyl-3-heptanone 37138 27200 29607 4248 25430 23862Benzaldehyde 259217 162005 142649 125024 110643 95922alpha-pinene 184828 157678 150107 148784 140270 1473536-Methyl-5-hepten-2-one 235555 135697 145409 145668 122811 1019042-Octanone n.d. n.d. n.d. n.d. n.d. n.d.Octanal 54861 43304 42751 37448 38130 338883-Hexenyl acetate n.d. n.d. n.d. n.d. n.d. n.d.Fenchene 37454 30929 30737 31661 29065 345282-Ethyl-1-hexanol 1823278 1527063 1129096 781551 792551 753109Limonene 103009 76692 72567 86178 85173 112705Nonanal 338224 269845 315386 246315 282276 2949211-Undecene 213935 190593 234324 175713 198265 2185442-Decanone n.d. n.d. n.d. n.d. n.d. n.d.Decanal 47309 n.d. 43946 21501 n.d. 40467
VOC results from potato sample batch 16 analysed on 14/04/2014
n.d. = Compound not detected
Potato Potato Potato Potato Potato 12 Potato 13 Potato 14
115
BH1 BH2 BH3 BH11Compound Area Area Area Area Area Area AreaTrimethylamine n.d. 10321 n.d. n.d. 2158 10811 7340Acetone 151380 162963 121791 4031 92839 92401 1718392-Methylpropanal n.d. n.d. n.d. n.d. n.d. n.d. 159412-Butanone 78209 n.d. n.d. 165983 n.d. n.d. n.d.Acetic acid n.d. 129303 n.d. n.d. n.d. 84851 855822,3-Butanedione 56351 29103 32671 15117 17284 n.d. 301193-Methylbutanal 13490 14989 24089 2715 3501 3715 128352-Methylbutanal n.d. n.d. n.d. n.d. n.d. n.d. n.d.1-Butanol 731022 622709 313140 484963 536723 13795 7128893-Hydroxy-2-butanone 302371 549708 452259 139432 118586 75309 2747671,2-Propanediol 1458145 2842117 1683795 671242 1102601 333108 11567033-Methyl-1-butanol 116884 n.d. n.d. 83033 125667 46160 678072-Methyl-1-butanol n.d. n.d. n.d. n.d. n.d. 19852 n.d.Dimethyl disulphide 242556 42854 147481 n.d. 229912 87514 n.d.1-Pentanol 222342 156584 n.d. 239695 476741 n.d. 2652222,3-Butanediol 1035923 1718839 818507 1571442 2191820 1829362 5395505Hexanal 59931 105798 36942 130387 114781 32611 943271-Hexanol 161555 92167 41202 45289 67093 31666 67111Butyrolactone n.d. n.d. 14952 136558 n.d. n.d. n.d.2-Heptanone 108968 147532 39650 143245 146130 57132 90424Heptanal 33027 51181 n.d. 64350 52567 11183 442991-Octene n.d. n.d. n.d. n.d. n.d. n.d. 414052-Methyl-3-heptanone 90974 95638 94961 12124 70650 70392 102018Benzaldehyde 155185 149159 140406 101033 74552 n.d. 101392alpha-pinene 90604 101634 99685 71718 81716 74496 993406-Methyl-5-hepten-2-one 273822 299254 190081 175031 254962 167007 2560632-Octanone n.d. 77416 n.d. 45617 n.d. 54790 n.d.Octanal 39890 64653 61788 49871 39852 47495 850273-Hexenyl acetate n.d. n.d. n.d. n.d. n.d. n.d. n.d.Fenchene 15034 25698 11575 10951 11028 12490 127952-Ethyl-1-hexanol 2049225 1284548 601696 647465 635284 1007399 952618Limonene 41407 35874 28794 38030 35725 33712 36702Nonanal 417676 572645 132383 421844 291775 153617 3394961-Undecene 348144 330660 87712 304100 238196 99470 2208212-Decanone 615794 384584 169281 178205 93145 264615 234263Decanal n.d. n.d. n.d. 54168 n.d. n.d. n.d.
VOC results from potato sample batch 17 analysed on 29/04/2014
n.d. = Compound not detected
No damage No damage Mild damage
Mild damage
Severe damage
Severe damage
116
60cm 60cm 120cm 120cmCompound Area Area Area Area Area AreaTrimethylamine n.d. n.d. n.d. n.d. n.d. n.d.Acetone 24655 38026 22066 10138 14391 187112-Methylpropanal n.d. n.d. n.d. n.d. n.d. 23382-Butanone n.d. n.d. n.d. n.d. n.d. n.d.Acetic acid 72025 121564 114872 78234 79427 937612,3-Butanedione 18454 6274 n.d. n.d. n.d. 129923-Methylbutanal 2886 3948 1910 1062 2159 40812-Methylbutanal n.d. 8330 n.d. n.d. n.d. 47421-Butanol 96844 51737 68438 64006 74591 800513-Hydroxy-2-butanone 20860 26739 20358 n.d. n.d. 434731,2-Propanediol 168913 707805 276883 541127 554123 1780653-Methyl-1-butanol n.d. n.d. n.d. n.d. n.d. n.d.2-Methyl-1-butanol 4938 n.d. 4030 n.d. n.d. n.d.Dimethyl disulphide n.d. n.d. n.d. n.d. n.d. 746681-Pentanol n.d. 40156 n.d. 20007 9813 n.d.2,3-Butanediol 9697 n.d. n.d. n.d. n.d. 56362Hexanal 46890 79013 131933 90182 76861 1069351-Hexanol 83063 130086 43410 27326 32933 94327Butyrolactone 11197 22130 11706 8192 8880 79072-Heptanone 57539 63879 28621 16336 16813 45361Heptanal 23219 57491 57606 47904 53929 631141-Octene 21706 n.d. n.d. n.d. n.d. n.d.2-Methyl-3-heptanone n.d. n.d. n.d. n.d. n.d. n.d.Benzaldehyde 58764 134463 77819 72474 73235 79682alpha-pinene 14567 472123 353653 12654 11223 192316-Methyl-5-hepten-2-one 144986 222365 190263 84784 103134 1588062-Octanone n.d. n.d. n.d. n.d. n.d. n.d.Octanal 22915 47695 19584 23403 26747 392883-Hexenyl acetate n.d. n.d. n.d. n.d. n.d. n.d.Fenchene 18807 125009 75934 2176 9485 32512-Ethyl-1-hexanol 991539 1926409 550703 571344 150870 145730Limonene 29372 64648 44013 15656 14504 36771Nonanal 215958 608193 216975 264945 301400 4222111-Undecene n.d. n.d. n.d. n.d. n.d. n.d.2-Decanone n.d. 157517 n.d. n.d. n.d. 53575Decanal 18343 64871 n.d. 21462 n.d. 27926
VOC results from potato sample batch 18 analysed on 07/07/2014
n.d. = Compound not detected
Wash Mock Mock Mock Infected Infected Infected
117
270614inoculation
240614inoculation
300614inoculation
020714 240614 300614 020714Compound Area Area Area Area Area Area AreaTrimethylamine n.d. n.d. n.d. n.d. 249308 13938 n.d.Acetone 4332 7988 6753 9433 558762 73128 86102-Methylpropanal n.d. n.d. n.d. n.d. n.d. n.d. n.d.2-Butanone n.d. n.d. n.d. n.d. 186992 10282 n.d.Acetic acid n.d. 13053 n.d. 15647 n.d. 20081 207752,3-Butanedione n.d. n.d. 4224 n.d. 116074 10067 454943-Methylbutanal n.d. 574 n.d. n.d. n.d. n.d. n.d.2-Methylbutanal n.d. n.d. n.d. n.d. n.d. n.d. n.d.1-Butanol n.d. n.d. n.d. 2525 n.d. 104096 n.d.3-Hydroxy-2-butanone 338 n.d. n.d. n.d. 431538 66807 n.d.1,2-Propanediol n.d. 9413 9864 2036 332261 7635 43393-Methyl-1-butanol n.d. n.d. n.d. n.d. 13461 20839 13282-Methyl-1-butanol n.d. n.d. n.d. n.d. 6856 6553 n.d.Dimethyl disulphide n.d. 8610 n.d. n.d. 451955 2208 8671-Pentanol n.d. n.d. n.d. n.d. n.d. 1388 n.d.2,3-Butanediol n.d. n.d. n.d. n.d. 56287 7332 n.d.Hexanal n.d. 1261 1040 1684 1236 789 15421-Hexanol n.d. n.d. n.d. n.d. n.d. n.d. n.d.Butyrolactone n.d. n.d. n.d. 1151 n.d. n.d. n.d.2-Heptanone n.d. 1121 1193 2850 24075 2396 n.d.Heptanal n.d. n.d. n.d. n.d. n.d. n.d. n.d.1-Octene n.d. n.d. n.d. n.d. n.d. n.d. n.d.2-Methyl-3-heptanone n.d. n.d. 1472 n.d. 10083 258 1590Benzaldehyde n.d. n.d. n.d. n.d. n.d. n.d. n.d.alpha-pinene 29460 27333 8976 56380 38507 29012 700006-Methyl-5-hepten-2-one 21377 1798 1763 3212 6939 42615 109422-Octanone n.d. n.d. n.d. n.d. n.d. n.d. n.d.Octanal 3040 1973 1984 3885 3467 2652 22613-Hexenyl acetate n.d. n.d. n.d. n.d. n.d. n.d. n.d.Fenchene 5886 7148 1310 11767 10292 6401 161242-Ethyl-1-hexanol 15264 24097 6831 96898 29078 10225 43353Limonene 17134 13915 9338 22274 11517 18976 24286Nonanal n.d. n.d. 5549 n.d. 4904 n.d. n.d.1-Undecene n.d. n.d. n.d. n.d. 8452 n.d. n.d.2-Decanone n.d. n.d. n.d. 1013 135 1099 1897Decanal n.d. 5136 6385 n.d. 4826 n.d. n.d.
VOC results from potato sample batch 19 analysed on 08/07/2014
n.d. = Compound not detected
Travel blank
Mock inoculation
4°C
Mock inoculation
10°C
Mock inoculation
20°CInfected
4°CInfected
10°CInfected
20°C
118
Compound Area Area Area Area Area Area AreaTrimethylamine n.d. 5566 1245 n.d. 469291 1428579 3782108Acetone 14877 8663 13210 21462 n.d. n.d. n.d.2-Methylpropanal n.d. n.d. n.d. n.d. n.d. n.d. n.d.2-Butanone n.d. n.d. 8959 n.d. n.d. 116947 n.d.Acetic acid 234379 153844 84794 111206 171721 97558 1741752,3-Butanedione n.d. n.d. 8959 n.d. 16694 116947 3345623-Methylbutanal n.d. n.d. n.d. 953 n.d. n.d. 60562-Methylbutanal n.d. n.d. n.d. n.d. n.d. n.d. n.d.1-Butanol 26698 17507 6769 14143 19457 7998 26948933-Hydroxy-2-butanone n.d. 24218 n.d. n.d. 242619 25358 95694851,2-Propanediol 15402 35986 8836 11428 45651 43257 201693-Methyl-1-butanol n.d. 926 n.d. n.d. n.d. n.d. 1369792-Methyl-1-butanol n.d. 1060 901 n.d. 9230 n.d. 133114Dimethyl disulphide n.d. n.d. n.d. n.d. n.d. 1378837 5768741-Pentanol n.d. n.d. n.d. n.d. n.d. n.d. n.d.2,3-Butanediol 1294 n.d. 13726 n.d. 14994 51872 4845668Hexanal 9497 12377 3873 3285 8601 5760 n.d.1-Hexanol n.d. n.d. n.d. n.d. n.d. n.d. n.d.Butyrolactone 12850 2330383 4867612 1923619 5411215 6868508 3144472-Heptanone n.d. n.d. n.d. n.d. 8562 41808 1792280Heptanal 3026 n.d. 2297 1665 4440 n.d. n.d.1-Octene n.d. n.d. n.d. n.d. n.d. n.d. n.d.2-Methyl-3-heptanone 2291 8394 7576 8873 12107 26758 793016Benzaldehyde 24544 35402 22355 15254 40460 45130 24164alpha-pinene 7904 81697 24220 15027 99867 29989 440966-Methyl-5-hepten-2-one 9791 25192 2649 5362 5532 29819 454142-Octanone n.d. n.d. n.d. n.d. n.d. n.d. n.d.Octanal 4076 5777 5135 5956 7193 5231 185313-Hexenyl acetate n.d. n.d. n.d. n.d. n.d. n.d. n.d.Fenchene 1811 28118 9743 9323 40154 14113 231812-Ethyl-1-hexanol 58183 45180 61667 30051 111882 140089 197079Limonene 3137 12533 9557 8556 22593 17115 19683Nonanal 48123 42324 63485 n.d. 77217 86430 2806041-Undecene n.d. n.d. n.d. n.d. n.d. 97612 1950402-Decanone n.d. 1161 n.d. n.d. n.d. n.d. n.d.Decanal 12769 8053 10907 n.d. 25161 18601 n.d.
VOC results from potato sample batch 20 analysed on 29/07/2014
n.d. = Compound not detected
119
Appendix B Typical potato sample chromatograms
Desiree no sprouting batch 6
120
VR808 S342 no sprouting batch 15
121
Desiree eyes open batch 6
122
VR808 S342 eyes open batch 15
123
Desiree sprouting batch 6
124
VR808 S342 sprouting batch 15
125
No damage control sample, batch 8
126
Estima no damage control sample, batch 16
127
Light damage sample, batch 6
128
Maris Piper light damage sample, batch 16
129
Estima heavy damage sample, batch 16
130
Desiree Severe damage sample, batch 19
131
Desiree soaked batch 3
132
Melody no inoculation batch 11
133
Desiree mock inoculation batch 3
134
Melody mock inoculation batch 11
135
Desiree inoculated batch 3
136
Melody bacterial inoculation batch 11
137
Charlotte black spot batch 11
138
Melody MD rubbery batch 14
139
Sunrise WC pit rot batch 14
140
Appendix C Typical onion sample chromatograms
Onion Control sample 18/03/2014
141
Onion Control sample 15/04/2014
142
Onion sample with internal rot 18/03/2014
143
Onion sample with internal rot 15/04/2014
144
Onion sample with basal rot 11/03/2014
145
Onion sample with basal rot 15/04/2014
146
Onion sample with neck rot 11/03/2014
147
Onion sample with neck rot 15/04/2014
148
Appendix D Analysis results of infected onions
The results of the analysis below, the value listed for each compound refers to the area of peak
for each compound.
Analysis of infected onions 03/12/2013 Batch 1
Compound RT (min) Control Thick Neck Slight Basal rot Severe Basal rot
Acetic acid 2.009 395440 191351 172463 01-Propanethiol 2.095 28747 0 189789 230239
1-Butanol 2.483 39375 20398 27868 01-Methoxy-2-propanol 2.576 38576 26917 25499 4657283-Hydroxy-2-butanone 2.772 131742 501539 177140 564614Methyl propyl sulphide 2.979 5104 0 749932 8445338
1,2-Propanediol 3.16 51955 78656 140404 03-Methyl-1-butanol 3.216 17996 46748 207640 673716
Propylene glycol 3.405 186154 144536 189107 1566221-Pentanol 3.623 16127 11581 22503 12822
2,3-Butanediol 3.8 96577 1112829 122503 359304Hexanal 3.967 192984 212954 237046 54890
1-Propoxy-2-propanol 4.727 98173 0 0 989291-Methoxy-2-propyl acetate 5.037 25760 14530 31099 87596
1-Hexanol 5.127 17063 18809 52449 0Cyclohexanone 5.314 16277 15800 16992 20504
Styrene 5.458 15892 19560 151194 1800215Methyl propyl disulphide 6.084 2137 0 152494 1013691
Benzaldehyde 6.362 35983 0 35842 21232Nonanal 8.866 116184 94605 98221 44750
Dipropyl disulphide 8.991 0 0 3292991 2249121Onions batch 1: Infected brown onions
149
Analysis of onions 04/02/2014 Batch 2
Compound RT (min)
Sample 1
Sample 2
Sample 3
Sample 4
Sample 5
Sample 6
Sample 7
Sample 8
Acetic acid 2.009 41932 41647 46084 67039 64250 64940 60887 918551-
Propanethiol 2.095 0 0 0 0 0 0 0 0
1-Butanol 2.483 1621159 204643 297193 189666 253364 140182
4 387605 280217
1-Methoxy-2-propanol 2.576 132444 70642 80973 56208 46236 187260 20247 30266
3-Hydroxy-2-butanone 2.772 98362 55841 88872 58506 42767 66931 0 59384
Methyl propyl sulphide 2.979 0 0 2412 0 0 0 0 565
1,2-Propanediol 3.16 54853 70222 76488 61213 63933 44732 35888 27586
3-Methyl-1-butanol 3.216 0 2048 4120 2015 0 1821 0 0
Propylene glycol 3.405 41309 16808 27937 0 13663 0 9854 11382
1-Pentanol 3.623 10319 9114 10569 7596 9565 6944 6298 60652,3-Butanediol 3.8 569133 152086 249967 185143 172171 356855 158423 204294
Hexanal 3.967 65008 55416 73339 51048 73870 48918 77966 510291-Propoxy-2-
propanol 4.727 50936 0 23788 13337 0 0 0 8492
1-Methoxy-2-propyl acetate 5.037 10074 0 7188 0 4083 6139 4885 0
1-Hexanol 5.127 0 0 0 0 0 0 0 0Cyclohexanon
e 5.314 6099 3675 4230 3160 4268 3770 3863 2569
Styrene 5.458 23529 28087 51366 43034 39661 29533 25094 24209Methyl propyl
disulphide 6.084 1682 0 10373 0 0 0 2415 0
Benzaldehyde 6.362 35786 23055 32457 28626 28314 25983 25295 21343Nonanal 8.866 116576 90648 124529 101783 119805 107593 155952 103864Dipropyl
disulphide 8.991 19851 36497 31552 12702 0 5876 3202 1387
Onions batch 2: Infected brown onions
150
Analysis of infected onions 18/02/2014 Batch 3Compound RT (min) Control Internal Rot Neck Rot Basal RotAcetic acid 2.009 100712 259136 288061 63889
1-Propanethiol 2.095 0 321653 0 01-Butanol 2.483 249860 76287 6802 71667
1-Methoxy-2-propanol 2.576 1200956 808337 365357 2953423-Hydroxy-2-butanone 2.772 3935179 10588456 3899276 7278401Methyl propyl sulphide 2.979 0 130835 94130 138370
1,2-Propanediol 3.16 76662 50301 0 03-Methyl-1-butanol 3.216 305733 737802 287940 904072
Propylene glycol 3.405 303631 177881 122010 1582461-Pentanol 3.623 86221 65037 0 0
2,3-Butanediol 3.8 2166778 6189018 6916068 51464170Hexanal 3.967 191854 177750 91982 0
1-Propoxy-2-propanol 4.727 32654 21896 0 211891-Methoxy-2-propyl acetate 5.037 703536 1075094 332619 432761
1-Hexanol 5.127 128480 140156 83172 128558Cyclohexanone 5.314 3823787 11727117 7369631 1874505
Styrene 5.458 37415 337004 69473 74765Methyl propyl disulphide 6.084 22537 663801 2865796 135345
Benzaldehyde 6.362 331902 109089 68298 135793Nonanal 8.866 113139 118593 100760 70665
Dipropyl disulphide 8.991 379955 3481653 11226516 3799632Onions batch 3: Infected brown onions
Analysis of infected onions 11/03/2014 Batch 4Compound RT (min) No Defects Internal Rot Basal Rot Neck Rot Thick NeckAcetic acid 2.009 149495 0 302985 56581 161294
1-Propanethiol 2.095 0 1006936 68721 115365 01-Butanol 2.483 206632 75264 35723 93188 212705
1-Methoxy-2-propanol 2.576 485013 209155 157930 295816 3574653-Hydroxy-2-butanone 2.772 1644363 3921518 10099578 5876720 2467580Methyl propyl sulphide 2.979 0 949391 46491 168838 0
1,2-Propanediol 3.16 54291 175093 385796 0 3440263-Methyl-1-butanol 3.216 42675 414771 423265 266524 50718
Propylene glycol 3.405 318026 0 123760 241492 1716411-Pentanol 3.623 113427 58062 26474 70728 54900
2,3-Butanediol 3.8 594344 32470837 38623229 10519486 4183591Hexanal 3.967 195993 117819 0 110218 166204
1-Propoxy-2-propanol 4.727 0 5434 0 7493 01-Methoxy-2-propyl acetate 5.037 726765 420528 232435 296061 292167
1-Hexanol 5.127 54122 81321 36033 94396 43800Cyclohexanone 5.314 54817 32939 18400 29861 24889
Styrene 5.458 29647 293340 37031 79764 22596Methyl propyl disulphide 6.084 8400 5066937 307781 127946 0
Benzaldehyde 6.362 52200 39714 36857 26799 65879Nonanal 8.866 62440 110730 48508 41838 67777
Dipropyl disulphide 8.991 93770 11002244 1148148 1862556 45153Onions batch 4: Infected brown onions
151
Analysis of infected onions 18/03/2014 Batch 5Compound RT (min) Good Brown Internal Rot Brown Good Red Internal Rot RedAcetic acid 2.009 441556 238837 220952 0
1-Propanethiol 2.095 31577 224327 42048 9116061-Butanol 2.483 136820 441727 187602 99804
1-Methoxy-2-propanol 2.576 67173 94716 345521 166393-Hydroxy-2-butanone 2.772 545593 3422414 365318 4503263Methyl propyl sulphide 2.979 3208 32763 2486 64487
1,2-Propanediol 3.16 322258 327886 334973 2833673-Methyl-1-butanol 3.216 32481 211551 21817 358687
Propylene glycol 3.405 64689 222178 22561 723461-Pentanol 3.623 31900 42699 35021 34330
2,3-Butanediol 3.8 1450709 8203892 3809471 45201637Hexanal 3.967 168716 512518 644652 56522
1-Propoxy-2-propanol 4.727 16808 195579 13859 295401-Methoxy-2-propyl acetate 5.037 19825 102420 15504 91660
1-Hexanol 5.127 26458 55059 18363 56358Cyclohexanone 5.314 339681 89632 96681 21465
Styrene 5.458 16477 28699 20820 35774Methyl propyl disulphide 6.084 10553 382246 5320 1188217
Benzaldehyde 6.362 94394 74496 46563 22718Nonanal 8.866 224597 457411 568432 407822
Dipropyl disulphide 8.991 147846 6407660 128897 6001483Onions batch 5: Infected red and brown onions
Analysis of infected brown onions 15/04/2014 Batch 6Compound RT (min) Good Internal Rot Neck Rot Basal RotAcetic acid 2.009 374553 0 134952 239268
1-Propanethiol 2.095 0 141153 29122 01-Butanol 2.483 619583 412741 83308 73448
1-Methoxy-2-propanol 2.576 233365 125872 233534 1598953-Hydroxy-2-butanone 2.772 167430 5757482 1568210 3950406Methyl propyl sulphide 2.979 0 139221 85588 3568586
1,2-Propanediol 3.16 76939 81178 110987 13822363-Methyl-1-butanol 3.216 32028 488029 240368 139401
Propylene glycol 3.405 146258 68485 126980 01-Pentanol 3.623 60721 33062 12893 19042
2,3-Butanediol 3.8 737080 3670432 2480692 21853768Hexanal 3.967 244652 158035 25284 0
1-Propoxy-2-propanol 4.727 21440 0 0 281901-Methoxy-2-propyl acetate 5.037 279047 110672 32126 54625
1-Hexanol 5.127 39191 48985 16125 0Cyclohexanone 5.314 2558044 887082 778109 983798
Styrene 5.458 48108 124111 75303 697960Methyl propyl disulphide 6.084 11397 257430 205555 1282434
Benzaldehyde 6.362 121818 52762 14115 27542Nonanal 8.866 134513 137589 61482 105328
Dipropyl disulphide 8.991 75784 2815784 572232 1427761Onions batch 6: Infected brown onions
Analysis of infected red onions 15/04/2014 Batch 6
152
Compound RT (min) Good Internal Rot Neck Rot Basal RotAcetic acid 2.009 319571 171438 163456 156506
1-Propanethiol 2.095 71457 57840 75058 1555501-Butanol 2.483 556070 237215 282185 133454
1-Methoxy-2-propanol 2.576 260391 156040 243211 1821703-Hydroxy-2-butanone 2.772 226832 764291 3032481 1013983Methyl propyl sulphide 2.979 15296 125056 249050 360524
1,2-Propanediol 3.16 84067 71126 88150 1566433-Methyl-1-butanol 3.216 30363 361092 1430899 615019
Propylene glycol 3.405 162641 91238 163448 959601-Pentanol 3.623 56835 42070 39362 0
2,3-Butanediol 3.8 395327 961353 3326720 6668849Hexanal 3.967 287821 168696 107972 86564
1-Propoxy-2-propanol 4.727 0 0 0 01-Methoxy-2-propyl acetate 5.037 268450 122689 113177 49142
1-Hexanol 5.127 49371 33754 60486 18794Cyclohexanone 5.314 2230265 1205419 1556407 618172
Styrene 5.458 41333 54135 218626 76138Methyl propyl disulphide 6.084 51855 255425 940349 571286
Benzaldehyde 6.362 98316 50952 46741 31809Nonanal 8.866 147863 169194 136256 108711
Dipropyl disulphide 8.991 410237 1771172 1352481 2869635Onions batch 6: Infected red onions
153
Appendix E Analysis results for broccoli samples
Agromark Helen’s PasqualName Retention time Peak area Peak area Peak area
Dimethyl sulphide 1.698 12827 10200 n.d.3-Methyl-1-butanol 3.222 n.d. n.d. 1836Dimethyl disulphide 3.272 n.d. 558416 3682553-Methyl-2-pentanol 3.901 n.d. 161097 n.d.
3-Hexen-1-ol 4.902 482492 242460 271707alpha-Pinene 6.401 108203 83585 113314
Dimethyl trisulphide 6.615 n.d. n.d. n.d.beta-Myrcene 7.256 30842 n.d. n.d.
3-Hexenyl acetate 7.333 540142 262623 n.d.1-Decene 7.348 n.d. n.d. n.d.
1,4-Undecadiene 8.846 n.d. n.d. n.d.1-Undecene 8.956 n.d. 39855 66391-Dodecene 10.472 8587 5019 4161
Indole 11.417 70 423 n.d.VOCs from broccoli sample batch 1 analysed 08/11/2013
n.d. = not detected
Control Slight wet rot Severe wet rotName Retention time Peak area Peak area Peak area
Dimethyl sulphide 1.698 16277 53957 5507113-Methyl-1-butanol 3.222 n.d. 3574 33171Dimethyl disulphide 3.272 11722 3361455 59009993-Methyl-2-pentanol 3.901 17736 132181 260175
3-Hexen-1-ol 4.902 n.d. 32059 33807alpha-Pinene 6.401 68674 108590 82290
Dimethyl trisulphide 6.615 n.d. 75692 418399beta-Myrcene 7.256 75192 47934 76054
3-Hexenyl acetate 7.333 n.d. n.d. 229711-Decene 7.348 n.d. 12037 60096
1,4-Undecadiene 8.846 n.d. 41781 1292171-Undecene 8.956 29550 432231 13519121-Dodecene 10.472 n.d. n.d. 102618
Indole 11.417 960 2412 685040VOCs from broccoli sample batch 2 analysed 21/11/2013
n.d. = not detected
154
Use by date relative to analysis date (days)-2 A -2 B -3 A -3 B -4 A -4 B
Name Retention time
Peak area Peak area Peak area Peak area Peak area Peak area
Dimethyl sulphide
1.698 33728 40159 59204 67621 27760 37553
3-Methyl-1-butanol
3.222 n.d. n.d. n.d. 2861 n.d. n.d.
Dimethyl disulphide
3.272 22914 13502 31738 9584 5335 5783
3-Methyl-2-pentanol
3.901 32414 15522 25956 15544 58506 73445
3-Hexen-1-ol 4.902 23022 10689 14991 13542 14973 n.d.alpha-Pinene 6.401 133601 100661 44062 52434 197522 157439
Dimethyl trisulphide
6.615 n.d. n.d. n.d. n.d. n.d. n.d.
beta-Myrcene 7.256 47650 28559 n.d. 27123 n.d. 272143-Hexenyl
acetate7.333 34322 13412 29294 20899 16638 16570
1-Decene 7.348 n.d. n.d. n.d. n.d. n.d. n.d.1,4-Undecadiene 8.846 n.d. n.d. n.d. n.d. n.d. n.d.
1-Undecene 8.956 n.d. n.d. 20504 26671 n.d. n.d.1-Dodecene 10.472 n.d. n.d. n.d. n.d. n.d. n.d.
Indole 11.417 2510 1792 2840 809 486 591VOCs from broccoli sample batch 3 analysed 25/03/2014
n.d. = not detected
Use by date relative to analysis date (days)1 A 1 B 0 A 0 B -1 -2 -3 -4
Name Ret time
Peak area Peak area
Peak area
Peak area
Peak area
Peak area
Peak area
Peak area
Dimethyl sulphide
1.698 88458 24003 89714 56285 29906 38617 47883 61737
3-Methyl-1-butanol
3.222 n.d. 2568 n.d. 4185 n.d. n.d. n.d. n.d.
Dimethyl disulphide
3.272 39270 19736 17280 49247 4404 3781 44627 43324
3-Methyl-2-pentanol
3.901 55028 74322 9610 26339 19253 20637 8287 116537
3-Hexen-1-ol 4.902 23351 17028 19059 n.d. n.d. 18015 n.d. n.d.alpha-Pinene 6.401 90200 87818 96402 118183 84414 221352 147565 218564
Dimethyl trisulphide
6.615 n.d. n.d. n.d. n.d. n.d. n.d. n.d. 1221
beta-Myrcene
7.256 32347 22540 24512 58925 23533 n.d. 63896 30081
3-Hexenyl acetate
7.333 63187 24549 42235 49393 18795 37683 n.d. 28769
1-Decene 7.348 n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.1,4-
Undecadiene8.846 n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
1-Undecene 8.956 n.d. n.d. n.d. n.d. n.d. 32323 46390 n.d.1-Dodecene 10.47
2n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
Indole 11.417
1971 430 524 n.d. 1294 3519 1710 1666
VOCs from broccoli sample batch 4 analysed 01/04/2014
n.d. = not detected
155
Use by date relative to analysis date (days)7 5 3 1
Name Retention time Peak area Peak area Peak area Peak areaDimethyl sulphide 1.698 16435 80165 32405 450562
3-Methyl-1-butanol 3.222 n.d. n.d. n.d. n.d.Dimethyl disulphide 3.272 35697 28258 34437 19782043-Methyl-2-pentanol 3.901 n.d. 95099 70274 22514
3-Hexen-1-ol 4.902 n.d. n.d. n.d. 83673alpha-Pinene 6.401 17648 53737 25095 34921
Dimethyl trisulphide 6.615 n.d. 497 n.d. n.d.beta-Myrcene 7.256 39469 50949 n.d. n.d.
3-Hexenyl acetate 7.333 3609 48188 21944 1150031-Decene 7.348 n.d. n.d. n.d. n.d.
1,4-Undecadiene 8.846 n.d. n.d. n.d. n.d.1-Undecene 8.956 n.d. n.d. 19110 n.d.1-Dodecene 10.472 n.d. n.d. n.d. n.d.
Indole 11.417 362 612 3651 284VOCs from broccoli sample batch 5 analysed 27/05/2014
n.d. = not detected
Use by date relative to analysis date (days)2 0
Name Retention time Peak area Peak areaDimethyl sulphide 1.698 60821 45099
3-Methyl-1-butanol 3.222 n.d. n.d.Dimethyl disulphide 3.272 602802 637353-Methyl-2-pentanol 3.901 7689 140504
3-Hexen-1-ol 4.902 36393 33506alpha-Pinene 6.401 134574 153854
Dimethyl trisulphide 6.615 n.d. n.d.beta-Myrcene 7.256 135350 162224
3-Hexenyl acetate 7.333 94600 1387281-Decene 7.348 n.d. n.d.
1,4-Undecadiene 8.846 n.d. n.d.1-Undecene 8.956 n.d. n.d.1-Dodecene 10.472 n.d. n.d.
Indole 11.417 437 923VOCs from broccoli sample batch 6 analysed 16/06/2014
n.d. = not detected
Use by date relative to analysis date (days)156
3 -1 -2 -4Name Retention time Peak area Peak area Peak area Peak area
Dimethyl sulphide 1.698 50282 18593 34905 148353-Methyl-1-butanol 3.222 1846 n.d. n.d. n.d.Dimethyl disulphide 3.272 1775466 185999 n.d. 1300993-Methyl-2-pentanol 3.901 28764 27935 33224 3771
3-Hexen-1-ol 4.902 n.d. 57158 n.d. 17720alpha-Pinene 6.401 90234 235241 137152 410010
Dimethyl trisulphide 6.615 n.d. 113 966 n.d.beta-Myrcene 7.256 85234 51042 42245 n.d.
3-Hexenyl acetate 7.333 17362 93486 21508 360701-Decene 7.348 n.d. n.d. n.d. n.d.
1,4-Undecadiene 8.846 n.d. n.d. n.d. n.d.1-Undecene 8.956 19908 98437 5568 514341-Dodecene 10.472 n.d. n.d. n.d. n.d.
Indole 11.417 n.d. 341 289 192VOCs from broccoli sample batch 7 analysed 17/06/2014
n.d. = not detected
Use by date relative to analysis date (days)9 No. 10 8 No. 3 7 No. 7 6 No. 8 5 4 3 No. 3 3 No. 10
Name Ret time
Peak area Peak area
Peak area
Peak area
Peak area
Peak area
Peak area
Peak area
Dimethyl sulphide
1.698 140997 13351 55053 18684 22913 19007 14272 o.d.
3-Methyl-1-butanol
3.222 148700 49395 160189 24451 64430 33459 76138 o.d.
Dimethyl disulphide
3.272 531615 95084 873998 22936 66015 335417 5746379 o.d.
3-Methyl-2-pentanol
3.901 62735 7669 27696 n.d. 11841 14659 35332 o.d.
3-Hexen-1-ol 4.902 264306 190468 691598 153998 209938 87601 208242 2150578alpha-Pinene 6.401 1300 3281 4657 4483 7090 10997 8950 133247
Dimethyl trisulphide
6.615 22409 57398 430240 12319 19915 41957 672775 2461865
beta-Myrcene
7.256 6107 8224 6286 n.d. n.d. n.d. 5905 54689
3-Hexenyl acetate
7.333 11220 13811 6682 21485 49067 11033 n.d. 116777
1-Decene 7.348 n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.1,4-
Undecadiene8.846 n.d. n.d. n.d. n.d. n.d. n.d. 6602 n.d.
1-Undecene 8.956 51504 1737 n.d. n.d. 7990 13910 30054 3363781-Dodecene 10.47
2n.d. n.d. n.d. n.d. 1398 n.d. 2200 32836
Indole 11.417
24052 608 666 n.d. n.d. n.d. 347 497
VOCs from broccoli sample batch 8 analysed 21/07/2014
n.d. = not detected
The sample labelled use by date 18/07/14 No. 10 overloaded the mass spectrometer at the start of the run and so no
data was collected for the peaks labelled o.d.
Use by date relative to analysis date (days)
157
9 No. 9 8 No. 10 7 6 5 No. 10 4 No. 10 3 2Name Ret
timePeak area Peak
areaPeak area
Peak area
Peak area
Peak area
Peak area
Peak area
Dimethyl sulphide
1.698 8272 14580 34559 19451 6366 6915 8552 6077
3-Methyl-1-butanol
3.222 30074 23851 48489 n.d. 7302 n.d. n.d. n.d.
Dimethyl disulphide
3.272 714029 6815393 1768658 2120554 342230 55663 427024 54670
3-Methyl-2-pentanol
3.901 16363 18098 39864 75036 17704 15835 10867 20790
3-Hexen-1-ol 4.902 265786 11341 314427 39042 53257 68736 96566 20693alpha-Pinene 6.401 2486 2188 38661 20011 26452 77829 99009 71406
Dimethyl trisulphide
6.615 36512 5107987 35088 103021 11614 882 1595 1802
beta-Myrcene
7.256 2606 n.d. 20485 23221 n.d. 29223 n.d. 23116
3-Hexenyl acetate
7.333 49099 n.d. 228764 18807 55387 167300 98553 22044
1-Decene 7.348 n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.1,4-
Undecadiene8.846 n.d. n.d. 12964 n.d. n.d. n.d. n.d. n.d.
1-Undecene 8.956 8939 n.d. 246439 154517 33747 34281 80231 290451-Dodecene 10.47
2n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d.
Indole 11.417
756 479 2579 2308 2306 n.d. 134 713
VOCs from broccoli sample batch 9analysed 28/07/2014
n.d. = not detected
158
Appendix F Typical broccoli sample chromatograms
Broccoli sample use by date 05/04/2014
159
Broccoli sample use by date 24/05/2014
160
Broccoli sample use by date 14/06/2014
161
Broccoli sample use by date 19/06/2014
162
Broccoli sample use by date 12/07/2014
163
Broccoli sample use by date 24/07/2014
164