ministry of agriculture fisheries and food csg 15...

CSG 15 (Rev. 12/99) 1

MINISTRY OF AGRICULTURE, FISHERIES AND FOOD CSG 15Research and Development

Final Project Report(Not to be used for LINK projects)

Two hard copies of this form should be returned to:Research Policy and International Division, Final Reports UnitMAFF, Area 6/011A Page Street, London SW1P 4PQ

An electronic version should be e-mailed to [email protected]

Project title Electronic nose detection of invertebrate and mycological contaminants ingrain

MAFF project code AR0601

Contractor organisationand location

Silsoe Research InstituteWrest ParkSilsoe, Bedford, MK45 4HS

Total MAFF project costs £ £64286.00

Project start date 01/10/00 Project end date 31/03/01

Executive summary (maximum 2 sides A4)

The purpose of this work is to determine if insect and mite infestation of grain can be detected at an early stageusing the GASP instrument (shown to be useful for detection of mould in grain). This project addresses thepolicy objective of MAFF programme CE03 to maintain and improve the quality of stored grain in order tomeet food safety regulations and the increasingly demanding commercial requirements for pest-free grain.

The collaborative work between Silsoe Research Institute, UMIST, Manchester and Cranfield University hasresulted in the prototype grain sampling system GASP (Grain automated sampling prototype), (Report toMAFF, ce0315, 2000). This instrument consists of an automated sampling system that presents the grainsample headspace gases to the electronic nose sensor array in a very repeatable way, the data from the sensorarray is processed through a radial basis function artificial neural network (RBFann) to descriminate the variouscategories of contaminant. The expertise of CSL (Central Science Laboratories) in the area of invertebrateinfestations was included in this project.

Scientific objective

To assess the feasibility of using the GASP system for detection of invertebrate grain pests in clean grain and ingrain with mould growth.

In this project we have been able to determine that the sensor array that was successful in discriminatingmouldy and clean grain could not discriminate A. siro or O. surinamensi infestations in irradiated grain. Thevolatiles released by these invetebrates were below the LDL of the conducting polymer sensors. However thekey volatiles could be detected using an array of metal oxide sensors and infestations of A. siro could bediscriminated from irradiated grain.

Projecttitle

Electronic nose detection of invertebrate and mycologicalcontaminants in grain

MAFFproject code

AR0601

CSG 15 (1/00) 2

Literature ReviewThis was a literature review and analyses of insect volatiles and comparison with existing volatile patternsproduced by spoilage fungi for any similarities and differences in patterns and key marker volatiles. This wascarried out mainly by Cranfield and CSL, the full text is appended to this report. In summary, the informationreviewed suggests that in addition to the detection of moulds, potential does exist for the development ofelectronic nose devices to detect invertebrate contaminants in grain. This knowledge of the types of volatilesassociated with infestation and their likely concentrations will allow devices to be optimised for invertebratedetection. Once the method is optimised, limits in sensitivity can be determined.

SUMMARY OF FINDINGS

Sensor suitability

The standard conducting 32-polymer array was not suited to detecting the chemicals shown to be present byGC-MS analysis of the odours from mite and insect infested grain.

The MOS array within the GASP system for detection of mite contamination in grain samples has provedeffective for discrimination between laboratory test samples. Detection of infestation was clearly visible at run-time, with 90% and 95% classification accuracy directly achievable for unshaken and shaken samplesrespectively. Such results are encouraging, however, further system improvements and extensive testing arerequired for development of a measurement system applicable to trade practice.

Numbers of mites present in samples at time of analysis

In general, mites multiplied more slowly than expected under the conditions in which the samples were held,with counted mite numbers after 3 or 4 weeks being close to or even below the number of mites added.However, some mites could possibly have been missed during counting as many would have been severelycrushed and desiccated by the shaking/heating procedure used in analysing them. In later experiments, theaverage concentration of mites in the infested grain samples when scanned by the GASP instrument wasdetermined to be approximately 5,500 mites/kg grain. Even allowing for the possibility that it is anunderestimate, this level of infestation is sufficiently low to be of direct relevance to the needs of the cerealtrade.

Changes in headspace of grain samples with insect infestationThe fact that no volatiles were observed to be associated with the presence of the insects, even at the ratherextreme concentrations of insects used, suggests that a method based on grain volatile profiling will not workfor the detection of O. surinamensis.

Determination of mite-volatile concentrations reaching the GASP instrument sensor array, by Tenax-tube headspace analysisThe results suggest that the GASP instrument detection of A. siro in wheat can be improved immensely byshaking the sample and heating and analysis at 40oC. However, it should be noted that for 2-hydroxy-6-methylbenzaldehyde to be released by shaking, it is probable that the mites must be intact (i.e. alive)beforehand. Therefore, shaking specifically for the detection of this compound may not be of such a benefit ifthe detection method is required to include the determination of dead mites also. On the other hand, however, itis potentially a very useful way of discriminating between the presence of live and dead mites (for example, byanalysis the grain sample both before and after shaking).

The presence of levels of tridecane between 0.6 and 2 ppm in the headspace from samples infested witharound only 2,000 mites/kg to which the GASP instrument sensors are exposed is very encouraging. This isespecially so when considering that the volatiles from the wheat itself occur at only similar or lowerconcentrations, such that tridecane is a, if not the, major constituent of the headspace of the mite-infestedwheat. Hence a device which could reliably detect this concentration of tridecane (and/or 2-hydroxy-6-

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MAFFproject code

AR0601

CSG 15 (1/00) 3

methylbenzaldehyde at 0.06-0.3 ppm concentrations or citral at 0.03-0.07 ppm) would have a sensitivity veryclose to that required by the cereal trade.

Citral (both isomers) is an alarm pheromone known to be released by several species of stored-productmites when disturbed or crushed. Citral has been detected previously in grain infested with mixed populationsof A. siro and two other mite species.

Odour threshold values for the headspace volatiles were determined using the CEN prEN 17325 draftstandard method in the SRI olfactometry laboratory. The odour thresholds were Citral 0.23 µg/l and Tridecane24 µg/l. The selected assessors were also used to perform a triangular forced-choice odour assessment of cleanand mite infested grain samples to determine human response to mite infested grain. The test was performed ontwo occasions at the lower infestation level of 115 mites / 25g the panel were unable to distinguish the infestedgrain. At a mite infestation level of 546 mites / 25g e infested grain was discriminated.

The Main Implications of the findings

• Conducting polymers array was found to be inadequate for determining if mite or insect infested grain waspresent.

• Metal oxide sensors can discriminate well between mite infested and clean irradiated grain at around just5,500mites/kg.

• There are three key indicator compounds that discriminate mite infestations:- Tridecane, citral and 2-hydroxy-6-methylbenzaldehyde.

• Mite infestations of about 22,000 mites / kg can be disciminated by a BS prEN13725 selected odour panel,infestations of 4,600 mites/kg can not be discriminated

• This work has shown the feasibility of using an electronic nose (with metal oxide sensors) sensor todiscriminate between infested and clean grain, the previous project illustrated the capability of using aconducting polymer array for mould detection. The work is however only at the feasibility stage andresearch into the interferences is required. The instrument is a working prototype that requires refinement toproduce a reliable and robust device with which to carry out laboratory screening of feed or foodstuffs.

Projecttitle


MAFFproject code

AR0601

CSG 15 (1/00) 4

Scientific report (maximum 20 sides A4)

CSG 15 (Rev. 12/99) 5

The purpose of this work is to determine if insect and mite infestation of grain can be detected at an early stageusing the GASP instrument shown to be useful for detection of mould in grain. This project addresses thepolicy objective of MAFF programme CE03 to maintain and improve the quality of stored grain in order tomeet food safety regulations and the increasingly demanding commercial requirements for pest-free grain.

The collaborative work between Silsoe Research Institute, UMIST, Manchester and Cranfield University hasresulted in the prototype grain sampling system GASP (Grain automated sampling prototype), (Report toMAFF, 2000). This instrument consists of an automated sampling system that presents the grain sampleheadspace gases to the electronic nose sensor array in a very repeatable way, the data from the sensor array isprocessed through a radial basis function artificial neural network (RBFann) to descriminate the variouscategories of contaminant.

Scientific objective

To assess the feasibility of using the GASP system for detection of invertebrate grain pests in clean grain andgrain with mould growthIn this project we have been able to determine that the sensor array that was successful in discriminatingmouldy and clean grain could not discriminate A. siro or O. surinamensi infestations in irradiated grain. Thevolatiles released by these invetebrates were below the LDL of the conducting polymer sensors. However thekey volatiles could be detected using an array of metal oxide sensors and infestations of A. siro could bediscriminated from irradiated grain.

MethodsThe project as proposed consisted of three specific investigative phases and two disemination phases:1. Literature review2. Analysis of infested, irradiated grain.3. Analysis of natural (non-irradiated grain)4. Contact with potential manufacturers and users5. Demostration of the device.

Following consideration of the results of phase 2 and in consultation with the project officer phase 3 wasabandoned and phase 2 was extended to allow optimisation of the GASP instrument and the development of anadditional metal oxide sensor (MOS) array. And also because the instrument was not sufficiently developed andits robustness not determined phases 4 and 5 were omitted. However the projects will be presented at a MAFFworkshop in June 2001 and at the ISOEN’01 conference (ANNEX 5)

Phase 1: This was a literature review and analyses of insect volatiles and comparison with existing volatilepatterns produced by spoilage fungi for any similarities and differences in patterns and key marker volatiles.This was carried out mainly by Cranfield and CSL, the full text is appended to this report. In summary, theinformation reviewed suggests that in addition to the detection of moulds, potential does exist for thedevelopment of electronic nose devices to detect invertebrate contaminants in grain. This knowledge of thetypes of volatiles associated with infestation and their likely concentrations will allow devices to be optimisedfor invertebrate detection. Once the method is optimised, limits in sensitivity can be determined.

Phase 2: Analysis of infested, irradiated grain.

The GASP instrument

The GASP instrument was used to collect and analyse samples from mite and insect infested grain to determinethe sensor response and to measure whether mite and insect infested grain could be detected. Initially the

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MAFFproject code

AR0601

CSG 15 (1/00) 6

GASP was as developed from MAFF project, code ce0315, (Report to MAFF, 2000) but during the course ofthis project several modifications were made to the GASP which are detailed below.

Modifications made to the GASP system during the course of the project

A second activated charcoal filter was added to the circuit so that the 30% RH air and the 100% RH air supplylines were each fed from a separate clean air source. This allowed each supply line to have its own clean airsupply and to eliminate any interaction between the circuits.

At the start of the current work it was noticed that water was condensing in the 100 % RH line and thiscoincided with the trace having a distinct ‘hump’, before returning to a normal trace, figures 1 and 2. It wassupposed that water was also condensing out in parts of the odour collecting system which were not flushedwith 30% RH air prior to sampling, i.e. the short needle and connecting tube, and it was this water, which waspicked up by the odour sample at the start of sampling, that was responsible for the hump as the sensors arevery sensitive to water. This was confirmed by changing the circuit to include a third manual valve whichallowed backflushing of the system with 30% RH air to clear the deposited water in the short needle andconnecting tube. When backflushing was used the ‘humps’ disappeared but reappeared if backflushing wasomitted.

Fig 1 GASP signal from the conducting polymer array showing the hump caused by condensation in the sampleline

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MAFFproject code

AR0601

CSG 15 (1/00) 7

Fig 2 GASP signal after the circuit modification

Fig 3 The GASP circuit with the metal oxide array added and the extra back flush value arrangement

GASP with alternative metal oxide sensors included.

During the course of the experiment it became obvious that the standard conducting 32-polymer array was notsuited to detecting the chemicals shown to be present by GC-MS analysis of the odours from mite and insectinfested grain and that metal oxide sensors would be worth investigating. UMIST were working on metal oxide

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MAFFproject code

AR0601

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sensors to detect dry rot moulds and it was possible to incorporate a header with a set of eight metal metal oxidesensors (MOS) into the existing GASP circuit, in series with the conducting polymer sensors. The MOSsensors used their own data capture and analysis software, but their addition allowed two sets of the GASPinstrument response from each sample. The circuit with the additional MOS sensors is shown in figure 3.

GASP with Tenax tube sampler included

Tenax tubes were connected to the GASP system in place of the MOS sensor array to collect samples whichwere then analysed using a GC-MS at CSL. The Tenax tubes were connected to the sample line after thepolymer array by making a temporary connection. The temporary connection was removed to allow normalwashing and backflushing. An additional pump was used to draw air through the Tenax tube in order toovercome the extra resistance to airflow. The flowrate through the Tenax tube was adjusted to give the sameflowrate, 35 ml/min, as that without the Tenax tube in circuit. This was carried out as part of experiment 7.

Table 1 Events sequence used for invertebrate work. (File name 241100.mtd)

Event ID Position TimeV1 reset 3 0 1V2 reset 4 0 2Valve 1 1 1 4Clear valve 1 11 0 6Valve 1 1 1 8 30% rhPulse 0 0 10 baselinePulse 0 0 20Start acq 5 0 30Valve 1 1 0 60Clear valve 1 11 0 62Valve 1 1 0 64 30% rhDbase start 8 0 175 samplingDbase end 9 0 210End acq 6 0 250Pulse 0 0 252Valve 2 2 1 255Clear valve 2 12 0 257 100% rhValve 2 2 1 259 washingV1 reset 3 1 311V2 reset 4 1 313Reset acq 7 1 315Cycle end 10 1 317Valve 3 manual 1 320 30% rhValve 3 manual 0 340 backflush

MethodPreparation and analysis of samples

Preparation of irradiated grainThe wheat used was unmilled, variety Riband, irradiated by Isotron, Swindon, U.K. at 12 kGry using a gammaradiation source. The grain was subsequently checked to ensure that it was free of mould contaminants, butwith retained germinative capacity. The grain was used to construct a water absorption curve to accuratelymodify the water availability to different treatment conditions (Appendix 2). Grain with retained germinativecapacity was successfully achieved using this treatment and provided to CSL York for inoculation with mites.Wheat was used either at approximately 16% moisture content (mc) as received or conditioned to

Projecttitle


MAFFproject code

AR0601

CSG 15 (1/00) 9

approximately 19% mc (CSL Standard Operating Procedure IREG number 006, 1990). Grain was stored insealed jars at 4oC for at least 1 week before use. Mites used were Acarus siro L, sex and age undetermined.Insects used were adult Oryzaephilus surinamensis, known sex (both male and female), aged approximately 0-2week from eclosion.

Preparation of infested samples for analysisA summary of the samples analysed in each experiment performed is given in Table 2. For Experiment 1,twelve replicate 32 g samples at each infestation level of 0, 16 and 32 mites were prepared both for wheat atapproximately 16% mc and wheat at approximately 19% mc, giving a total of 72 separate samples of sixdifferent types. Mites were separated manually from their food of culture, counted and added without mixingto the wheat in 55ml PET tubes. The tubes were then fitted with muslin covers secured by wire. The sampleswere then held in a controlled-environment room at 75% relative humidity and 20oC until being despatched(courier) for analysis by the GASP instrument (SRI). Samples were despatched approximately 0, 1, 2 and 4weeks after being prepared. At each of these times, 3 replicate samples of each sample type were despatched.

For Experiment 2, samples were prepared, held and despatched in the same way as in Experiment 1, butadding 0, 2 or 10 insects in place of mites. Here, the number of male and female insects added to each infestedsample was made equal.

For Experiment 3, samples were prepared as for Experiment 1, but with only 2 replicates per sampletype (12 samples total). Samples were held as above until being subjected to SPME headspace analysis (CSL).After approximately 1 week from preparation, one replicate of each sample type was analysed. The remainingsamples were analysed after approximately 3 weeks from preparation.

For Experiment 4, samples were prepared and analysed as for Experiment 3, but adding 0, 2 or 10insects in place of mites (as above).

For Experiments 5-8, replicate 25 g samples at each infestation level of 0 and 100 mites were preparedfor wheat at approximately 19% only, and held as above. For Experiment 5, the number of replicates was 18.Nine replicate samples of each sample type were despatched for analysis by the GASP instrument both atapproximately 3 weeks and at approximately 5 weeks from preparation. For Experiment 6, the number ofreplicates was 20 and all samples were despatched for analysis by the GASP instrument at approximately 4weeks from preparation. For Experiment 7, three replicates were prepared of each sample type and all sampleswere despatched for analysis by the GASP instrument/Tenax-tube headspace analysis (SRI) at approximately 4weeks from preparation. For Experiment 8, three replicates were prepared of each sample type and all sampleswere despatched for assessment by odour panel (SRI) at approximately 7 weeks from preparation.

Table 2. Summary of samples prepared and experiment description

Expt. No.samples

Experiment description Wheat type Contaminant type Sample age whenscanned

1 72 GASP instrument analysisof mite-infested grain over4-weeks

16 and 19% initialmc; 32 g/sample

0,16 and 32 addedmites/sample

0,1,3 and 4 weeksfrom adding mites

2 72 GASP instrument analysisof insect-infested grain over4-weeks


0,2 and 10 addedinsects/sample

0,1,3 and 4 weeksfrom adding insects

3 12 SPME headspace analysisof mite-infested grain



1 and 3 weeks fromadding mites

4 12 SPME headspace analysisof insect-infested grain



1 and 3 weeks fromadding insects

5 36 Modification of the GASPinstrument methodology (a)analysis of samples +determination of odour-panel response to mite-

19% initial mc;25 g/sample

0 and 100 addedmites/sample


Projecttitle


MAFFproject code

AR0601

CSG 15 (1/00) 10

infested wheat (a)6 40 Modification of the GASP

instrument methodology (b)analysis of samples



4 weeks fromadding mites

7 6 Determination of mite-volatile concentrations towhich the GASP instrumentsensor array is exposed




8 6 Determination of odour-panel response to mite-infested wheat (b)




Samples for counting by laboratory reference methodFor Experiments 1-4, 6 and 7, analytical samples (see above) were chilled to -10oC immediately after analysisand held at this temperature until analysed by the appropriate laboratory reference method. For Experiments 5and 8, however, replicates additional to those described above were prepared at the same time as the analyticalsamples for the purpose of estimating contaminant levels. Two such replicates of each sample type wereprepared for Experiment 5 and these were chilled and held at -10oC after 3 weeks from preparation. Similarly,for Experiment 8, two such replicates were prepared and these were chilled and held at -10oC after 7 weeksfrom preparation.

SPME headspace analysis of grain samples

Sampling methodA 75 µm carboxen/PDMS Supelco SPME portable field sampler was used. The SPME fibre was conditioned at270oC under helium for at least 30 min prior to sampling (spare GC injection port). Immediately beforeanalysis, exactly 7 g from the top portion of the grain sample was removed by gentle tipping. The samplevessel was then sealed with a thin, Teflon lined septum (35-45 Duromer with 3mil teflon. Supplied bySpeciality Silicone Products, product code SSP119IT-35D-SS) and the sample maintained at 40oC (heatedwater bath) for 1 h. After this time, the freshly conditioned SPME fibre was inserted into the sample vessel, leftfor 30 min then removed and immediately analyzed by GC-MS.

GC-MS methodGC-MS analysis was conducted on a Hewlett Packard 5890 series II gas chromatograph coupled to a VG Trio-1mass spectrometer. After sampling, the SPME fibre was immediately desorbed for 1 min at 270oC in splitlessmode (purge on after 1 min) onto a 50 m Chrompack CPSil19CB column (0.32 mm i.d., 1.2 µm film thickness).Helium was used as the carrier gas. The oven temperature was held at 30oC for 1 min rising at 5oC/min to130oC, then increased to 190oC at 2oC/min, then increased to 270oC at 10oC/min and finally held at thistemperature for 2 min. The initial head pressure was 5.3 psi and the gas chromatograph operated in constantflow mode. The mass spectrometer source and interface temperatures were 200oC and 275oC respectively. Themass spectrometer was operated in Electron Impact mode (EI+) at 70 eV and scanned once a second from m/z33-350 with no solvent delay.

Determination of mite-volatile concentrations reaching the GASP instrument sensor array, by Tenax-tube headspace analysis

Sampling method

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MAFFproject code

AR0601

CSG 15 (1/00) 11

Grain samples were scanned by the GASP device following the normal procedure, but with simultaneousTenax-tube sampling of the sensor array exhaust.

All samples were held at 30oC for 15 min immediately before being scanned, again at 30oC. Two of thethree replicates containing mites were then re-analysed, this time vigorously shaking the sample by hand(approx. 30 s) immediately before both holding and then analysis at 40oC.

GC-MS methodExposed Tenax tubes were desorbed onto the GC-MS using a Chrompack Thermal Cold Trapping (TCT)device.

Amounts of volatiles obtained were used to calculate volatile headspace concentrations (ppm) based on theGASP instrument airflow and the sampling time, following standard methods. In order to confirm thatdesorption of sampled volatiles from the Tenax tube into the GC was quantitative, one of the tubes obtainedfrom the shaken, 40oC-heated mite-infested samples was desorbed twice.

SPME headspace analysis to investigate the origin of 2-hydroxy-6-methylbenzaldehyde

One additional 25 g grain sample (16% mc) containing 25 A. siro was prepared, together with one uninfestedcontrol sample. These were analysed by SPME as above, but only one day after adding the mites. Afteranalysing, each sample was shaken vigorously for 30 s and then immediately re-analysed.

Laboratory reference method for estimating mite numbers

The wheat sample was tipped into a clean glass beaker (400 ml capacity), rinsing out the empty sample vesselinto the same beaker with 50% water/ethanol (100 ml). Water (150 ml) was added to the beaker, and the beakerand contents sonicated by ultrasonic bath for 10 min. The liquid was then decanted onto a gridded filter paper(12.5 cm diameter) held under suction in an Hartley funnel. The filter paper was then stained using approx.1%w/w 50% water/IMS methylene blue solution (5 ml) and examined under a stereoscopic microscope(approx. ×10-×15 magnification). The total number of A. siro which could be observed on the filter paper wasrecorded and the presence of any other mite/insect species noted.

Laboratory reference method for checking insect numbers

Grain samples were tipped out onto a white tray and the presence of adult O. surinamensis and other speciesrecorded.

Results

Numbers of mites/insects present in samples at time of analysis

Results from performing the laboratory reference method for A. siro or O. surinamensis on scanned samples aresummarised in Tables 2-5. Consistently low levels of tarsonimid mites were also found to be present in thewheat (around 17 tarsonimid mites/kg), together with a few field beetles (ground beetles, clover beetles androve beetles; around 4 adult insects/kg). However, these appeared quite desiccated and were almost certainlypresent in the pre-irradiated grain and killed during irradiation.

For the insect experiments, the number of adult insects present in the sample was not expected to changeover the 4 weeks from adding, as the life-cycle is likely to be longer than 28 days under the conditions in

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MAFFproject code

AR0601

CSG 15 (1/00) 12

which samples were held. However, the results show that some insects were removed along with the 7 g grainwhich was removed immediately before analysis by the GASP instrument (Experiment 2).

Table 3. Mite numbers in samples at time of analysis, Experiment 1

Average no. A. siro found (/25 g; n=3):Initial wheat mc (%) No. A. siro added (/32g) Week 0 Week 1 Week 2 Week 416 0 0 0 0 016 16 3 4.7 5.7 1416 32 5 10 8.7 25.319 0 0 0 0.3 0.319 16 2.3 8.3 5.7 77.319 32 4.3 15 11.7 134.3

Table 4. Insect numbers in samples at time of analysis, Experiment 2Average no. O. surinamensis found (/25 g; n=3):

Initial wheat mc (%) No. O. surinamensisadded (/32g)

Week 0 Week 1 Week 2 Week 4

16 0 0 0 0 016 2 3.3 1.7 1.7 1.716 10 3.7 7 4.7 6.319 0 0 0 0 019 2 1.3 1.7 1.7 1.719 10 7 5 5.3 4

Table 5. Mite numbers in samples at time of analysing, Experiment 3

Average no. A. siro found (/25 g; n=1):Initial wheat mc (%) No. A. siro added (/32g) Week 1 Week 316 0 0 016 16 - 1816 32 11 4219 0 0 019 16 5 12819 32 13 213

Changes in headspace of grain samples with mite infestation (Experiment 3)

Using SPME headspace analysis, it was found that 3 weeks from adding the mites, mite presence wasassociated with the appearance in the chromatogram of either one (16% initial mc wheat) or both (19% initialmc wheat) of two minor peaks (ANNEX 3 Figures 1-2 and 3-4 respectively). The peak at retention time(tR)=31.5 min was confirmed as tridecane, both by comparison with library spectra and by comparison with thetR and spectrum of tridecane standard. The peak at tR=33.2 min was tentatively identified as 2-methoxy-6-methylbenzaldehyde, based on comparison with library spectra only. No other differences in thechromatograms were detected. At 1 week from adding the mites, no such differences were observed(chromatograms not shown).

Interestingly, both here and in Experiment 4 (below), chromatograms from all samples at 19% initial mcgenerally possessed a number of additional/larger peaks compared to those from the 16% initial mc samples(for example, Figure 5). In particular, levels of ethanol were much higher for the 19% initial mc samples.

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MAFFproject code

AR0601

CSG 15 (1/00) 13

Changes in headspace of grain samples with insect infestation (Experiment 4)

No differences were observed between chromatograms from the infested and control samples, either at 1 weekor 3 weeks from adding the insects.

The data obtained with the GASP for these two experiments showed that the instrument could not discriminatemite or insect infested grain from clean grain.Analysis of the data revealed that the signal strength was too small to allow any discrimination between graininfested with mites or insects or clean grain.

Headspace gas analysisHeadspace gases were sampled using SPME fibres and analysed by GC-MS. The main compounds of interestfound in the mite infested grain were Tridecane, ethanol and 2-hydroxy-6-methyl-benzaldehyde. The ethanolcontent seems to be related to the higher moisture content grain but the other 2 compounds to infestation withmites. the concentrations of tridecane and 2-hydroxy-6-methyl-benzaldehyde with the non-polarnature of these main volatiles are close to the LDL of the conducting polymer array. This points to an other typeof sensor array being more suitable. Metal oxide sensors are more suitable for such compound types and wereused in the subsequent experiments.

Experiments 1(mites) and 2(insects) GASP analysis with conducting polymer sensors only

All samples prepared by CSL of 0, 1, 2 and 4 weeks of infestation at 16% and 19% mc grain with 0,2 and 10insects and grain with 0,16 and 32 mites per sample tube (described in Table 2) were analysed with the GASPusing the standard 30oC sample preparation temperature.

Results of experiments 1 and 2

There was no conclusive discrimination of the infected samples from the control samples with the GASP usingonly the conducting polymer sensors at the levels of infestation used.

When GC-MS analysis of the odours showed that 2-methoxy-6-methylbenzaldehyde and tridecane were presentit was concluded that metal oxide sensors would be more suitable for detection of these chemicals. The GASPsystem was modified to include metal oxide sensors in series with the polymer sensors

Conclusions from Phase 2 first stage

• The conducting polymers were not the optimum sensor array.• Headspace gas analysis had identified three indicator compounds for mite infested grain but no volatiles

were indentified in the insect infested grain.

Phase 2 second stage (experiments 5 to 8)

In the light of the conclusions drawn from Phase 2 first stage, changes were made to the GASP instrument toinclude a second sensor array of metal oxide sensors, a revised sample acquisition protocol including a revisedarray flushing procedure and analysis of higher temperature samples.

Experiment 5 GASP with conducting polymer sensors and preliminary metal oxide array

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MAFFproject code

AR0601

CSG 15 (1/00) 14

The 19% mc grain with 0 and 100 mites per sample tube prepared by CSL. The samples were first tested at30oC. They were then shaken for 15 seconds and tested. The samples were then tested using 40oC and 50oCpreparation temperatures.

Odour panel response to mite infested wheat

An odour panel, selected according to the European draft standard prEN 13725, was used to evaluate theanectdotal evidence that human detection of mite infestations is enhanced by crushing the grain sample. Twolevels of infestation were checked. The grain prepared in Expt. 5 and in Expt. 8 (Table 1).

A triangular forced choice procedure was used. Three sets of two odourless containers with duplicate samplesof un-infested irradiated grain and one container with an infested grain sample were prepared. The Trainedpanel were asked to first smell the samples and indicate one of each set of containers that had a characteristicodour ( to choose the odd one out from the three). The same samples were presented a three more times in arandomised order.

The procedure was carried out again with the panel being instructed to shake the sample before sniffing.The results are shown below, with the infested grain prepared in Expt 5 no characteristic odour could bedistinguished, however that prepared in Expt 8 could be clearly identified from the clean grain. (indicated bysignificantly more than one third true responses.)

Table 6. Results of the triangular forced choice odour panel testsExperiment Mite population/25g True responses False responses

5 115 Still 10 26115 Shaken 7 29

8 546 Shaken 51 19

Experiment 6 GASP with conducting polymer sensors and metal oxide sensors

Replicate samples of 19% mc grain with 0 and 100 mites per sample tube were tested at 30 oC with metal oxidesensors in series after the polymer sensors at 40oC unshaken and also shaken for 20 seconds.

The final series of samples examined with metal oxide sensor arrays (188-221) (ANNEX 2) contained nomould contamination. Thus the results obtained with these samples where good differentiation was obtained didnot have any interfering volatiles being produced by mould contaminants.

Experiment 7 GASP with conducting polymer sensors and tenax tubes

Grain with 0 and 100 mites per sample tube at19% mc were tested at 30oC and 40oC shaken, with Tenax tubesin circuit after polymer sensors.

Projecttitle


MAFFproject code

AR0601

CSG 15 (1/00) 15

Table 7. Mite numbers in samples at time of analysis, Experiments 5-8 (initial wheat mc=19% for all samples)

Average no. A. siro found (/25 g):Expt. No. A. siro added (/25g) Week 3 Week 4 Week 75 0 0 (n=2) - -

100 115 (n=2) - -6 0 - 0 (n=15) -

100 - 137 (n=15) -7 0 - 0 (n=3) -

100 - 43 (n=3) -8 0 - - 0 (n=2)

100 - - 546 (n=2)

Determination of mite-volatile concentrations reaching the GASP instrument sensor array, by Tenax-tube headspace analysis (Experiment 7)

Example chromatograms obtained from this experiment are given in Figures 4 and 5. It can be seen thatanalysis at 30oC and without first shaking the sample results in zero or negligible amounts of the mite-volatilestridecane and 2-hydroxy-6-methylbenzaldehyde reaching the GASP instrument sensor array (trace levels oftridecane were detected for both the control and unshaken mite-infested samples under these conditions, asshown in Figure 5, but this is thought to arise at least in part from an unavoidable low-level hydrocarbon bleedfrom the Tenax itself rather than from the sample). Analysis at 40oC, with shaking of the samples beforehand,results in surprisingly large amounts of tridecane and 2-hydroxy-6-methylbenzaldehyde reaching the sensorarray, especially when compared with other volatiles arising from the grain such as ethanol (Figure 4). Theknown mite-produced alarm pheromone citral (both isomers) was also detected (Figure 5). Repeat desorptionof one of the tubes from the shaken, 40OC-heated mite-infested samples did not show the presence of anyretained volatiles, confirming that the desorption method used was quantitative for the volatiles being studied.TCT30/1/5/130/2/190/10/270/2inj20033-350 15-Mar-2001

11:25:20TCT30/1/5/130/2/190/10/270/2inj20033-350TCT10mindes@250,10psi,CONTROL+newext.ref.~1ul

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Figure 4. Example chromatograms from determination of mite-volatile concentrations to which the GASPinstrument sensor array is exposed (Experiment 7); (a)=control wheat (0 added mites), (b)=100 added mites per

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MAFFproject code

AR0601

CSG 15 (1/00) 16

25 g sample scanned at 30OC without shaking), (c)=100 added mites per 25 g sample scanned at 40OC withshaking (all samples analysed at 4 weeks from adding mites; all samples are 19% initial mc wheat).

TCT30/1/5/130/2/190/10/270/2inj20033-350 15-Mar-200111:25:20TCT30/1/5/130/2/190/10/270/2inj20033-350TCT10mindes@250,10psi,CONTROL+newext.ref.~1ul

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Figure 5. Detail from Figure 4.

From these results, concentrations (ppm) of mite-volatiles reaching the sensor array during analysis of the mite-infested samples (shaken, 40OC) were calculated and are given in Table 8.

Table 8. Mite-volatile concentrations reaching the GASP instrument sensor array, as determined by Tenax-tubeanalysis, for sample at 40OC with shaking.

Volatile Concentration in sensor exhaust (ppm)tridecane 0.6-22-OH-6-Me-benzaldehyde 0.06-0.3citral (sum of both isomers) 0.03-0.07


Results from this additional experiment are given in Figure 6. It can be seen that 2-hydroxy-6-methylbenzaldehyde was only detected in the headspace of the shaken, mite-infested sample.

Projecttitle


MAFFproject code

AR0601

CSG 15 (1/00) 17

30/1/5/270/10 inj280 33-550,462445 15-Nov-200017:59:2930/1/5/270/10 inj280 33-550,46244525gcontrol, spme, 1h sample, 30deg, unshaken

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(d) scan no.1822=2-OH-6-Me-benzaldehyde

Figure 6. Investigation of the origin of the mite-volatile 2-hydroxy-6-methylbenzaldehyde; (a)=unshakencontrol wheat (0 added mites), (b) same sample as (a) after shaking, (c)=unshaken mite-infested wheat (25added mites per 25 g sample), (d) same sample as (c) after shaking (all samples analysed within 24 h fromadding mites; all samples are 16% initial mc wheat).

Odour threshold values for the headspace volatiles were determined using the CEN prEN 17325 draftstandard method in the SRI olfactometry laboratory.

Table 9. Odour threshold measurementsCitral Tri-decane

0.23 µg/l 24 µg/l

The selected assessors were also used to perform a triangular forced-choice odour assessment of clean and miteinfested grain samples to determine human response to mite infested grain. The test was performed on twooccasions at the lower infestation level of 115 mites / 25g the panel were unable to distinguish the infestedgrain. At a mite infestation level of 546 mites / 25g e infested grain was discriminated.

Results from MOS analysis

The metal oxide sensors were able to descriminate between infested and control samples at the 100 mite levelleft for 4 weeks, as part of experiment 6.

A summary of the results from the MOS sensor array are presented here (full account in ANNEX 4).Typical sensor response data corresponding to control and mite-infested grain samples are shown in figure 7.The general profiles reflect the GASP measurement protocol (baseline measurement, followed by sampleresponse measurement, followed by a series of wash cycles).

Projecttitle


MAFFproject code

AR0601

CSG 15 (1/00) 18

Figure 7. Typical MOS sensor array output obtained for (a) control and (b) infested grain samples.

To evaluate this correlation, normalised sensor response was analysed by averaging over the 10 second periodfollowing 190 seconds. All samples comprising the control group are correctly discriminated (S1 response > S4response). The majority of mite-infested samples are also correctly discriminated (S4 response > S2 response),with the exception of two samples, with incorrect and borderline responses respectively.

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MAFFproject code

AR0601

CSG 15 (1/00) 19

Figure 8. Discrimination within the infested sample group is improved subsequent to sample shaking.

Sample shaking clearly yielded discrimination improvement within the infested sample group (figure 8). Thepreviously incorrect and borderline classifications have been resolved, with a marked improvement in sensorresponse separation visible over all samples.

DISCUSSION

Sensor suitability

The standard conducting 32 polymer array was not suited to detecting the chemicals shown to be present byGC-MS analysis of the odours from mite and insect infested grain.

The MOS array within the GASP system for detection of mite contamination in grain samples has provedeffective for discrimination between laboratory test samples. Detection of infestation was clearly visible at run-time, with 90% and 95% classification accuracy directly achievable for unshaken and shaken samplesrespectively. Such results are encouraging, however, further system improvements and extensive testing arerequired for development of a measurement system applicable to trade practice.


In general, mites multiplied more slowly than expected under the conditions in which the samples were held.This was especially the case in Experiments 5-7, with counted mite numbers after 3 or 4 weeks being close toor even below the number of mites added. However, in Experiments 6 and 7 some mites could possibly havebeen missed during counting as many would have been severely crushed and desiccated by the shaking/heatingprocedure used in analysing them. In Experiment 6, the average concentration of mites in the infested grainsamples when scanned by the GASP instrument was determined to be approximately 5,500 mites/kg grain.Even allowing for the possibility that it is an underestimate, this level of infestation is sufficiently low to be ofdirect relevance to the needs of the cereal trade.

Changes in headspace of grain samples with mite infestation

The results from the SPME headspace sampling experiment (Experiment 3) show that the presence of even lowconcentrations of A. siro does impart a detectable change in the volatile profile of wheat. The observedassociation of tridecane with infestation by A. siro is in agreement with previous work (Curtis et al, 1981).Interestingly, the volatile 2-hydroxy-6-methylbenzaldehyde has not previously been reported as being

Comparison of Normalised Sensor Response (S1 & S4) for Unshaken and Shaken Mite-infested Grain Samples (40

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0.61

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MAFFproject code

AR0601

CSG 15 (1/00) 20

associated with the headspace of mite-infested wheat, but has been obtained by whole-body solvent extractionof A. siro. To investigate this further, an additional experiment was undertaken to determine the origin of thelatter compound. Surprisingly, shaking of a sample containing just 25 A. siro in 25 g wheat generated a smallbut definite chromatographic peak corresponding to 2-hydroxy-6-methylbenzaldehyde. This confirms that thecompound, present within the mites themselves, is released when the mites are crushed.

Changes in headspace of grain samples with insect infestation (Experiment 4)The fact that no volatiles were observed to be associated with the presence of the insects, even at the ratherextreme concentrations of insects used, suggests that a method based on grain volatile profiling will not workfor the detection of O. surinamensis.

Determination of mite-volatile concentrations reaching the GASP instrument sensor array, by Tenax-tube headspace analysisThe results of Experiment 7 suggest that the GASP instrument detection of A. siro in wheat can be improvedimmensely by shaking the sample and heating and analysis at 40oC. However, it should be noted that for 2-hydroxy-6-methylbenzaldehyde to be released by shaking, it is probable that the mites must be intact (i.e. alive)beforehand. Therefore, shaking specifically for the detection of this compound may not be of such a benefit ifthe detection method is required to include the determination of dead mites also. On the other hand, however, itis potentially a very useful way of discriminating between the presence of live and dead mites (for example, byanalysis the grain sample both before and after shaking).

The presence of levels of tridecane as high as 2 ppm in the headspace from infested samples to whichthe GASP instrument sensors are exposed is very encouraging. This is especially so when considering that thevolatiles from the wheat itself occur at only similar or lower concentrations, such that tridecane is a, if not the,major constituent of the headspace of the mite-infested wheat. The 2 ppm tridecane was generated by aninfestation level of around only 2,000 mites/kg. Hence a device which could reliably detect this concentrationof tridecane (and/or the lower concentrations of 2-hydroxy-6-methylbenzaldehyde or citral also likely to bepresent) would have a sensitivity very close to that required by the cereal trade.

Citral (both isomers) is an alarm pheromone known to be released by several species of stored-productmites when disturbed or crushed. Citral has been detected previously in grain infested with mixed populationsof A. siro and two other mite species.

The Main Implications of the findings

• Conducting polymers array was found to be inadequate for determining if mite or insect infested grain waspresent.

• Metal oxide sensors can discriminate between mite infested and clean irradiated grain at around just5,500mites/kg.

• There are three key indicator compounds that discriminate mite infestations. Tridecane, citral and 2-hydroxy-6-methylbenzaldehyde.

• Mite infestations of about 22,000 mites / kg can be disciminated by a BS prEN13725 selected odour panel,infestations of 4,600 mites/kg can not be discriminated.

• This work has shown the feasibility of using an electronic nose (with metal oxide sensors) sensor todiscriminate between infested and clean grain, the previous project illustrated the capability of using aconducting polymer array for mould detection. The work is however only at the feasibility stage andresearch into the interferences is required. The instrument is a working prototype that requires refinement toproduce a reliable and robust device with which to carry out laboratory screening of feed or foodstuffs.

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MAFFproject code

AR0601

CSG 15 (1/00) 21

Future work

Further research will be needed to demonstrate that a large range of important grain contaminants can bedetected by one instrument or an amalgamation of instruments using several sensors. Following this researchsignificant commercial development will be needed to enable an instrument to be made available to interestedusers. This work has shown the feasibility of using an electronic nose (with metal oxide sensors) sensor todiscriminate between infested and clean grain, the previous project illustrated the capability of using aconducting polymer array for mould detection. The work is however only at the feasibility stage and researchinto the interferences is required.The instrument is a working prototype that requires refinement to produce a reliable and robust device withwhich to carry out laboratory screening of feed or food stuffs. Eg identification of olive oils A pilot trial wascarried out with some examples of Extra Virgin and refined olive oils, and hazelnut oil from a supermarket. Nomodifications were made to the GASP instrument, only the conducting polymer sensor array used. The resultsin the form of a two dimensional PCA map are shown below. The extra virgin oils FP EV and Greek EV areclosely clustered, The hazelnut oil plots at the bottom with the refined oil to the right of the virgin oils.Mixtures of 10:5 olive oil and hazelnut oil plot between the olive and hazelnut data.Changes to the methodology used in the GASP instrument eg changes in sample scanning time, increasedsample temperature, inclusion of sensors specific to the key-compounds found and inclusion of the RBFnn arevery likely to improve the performance compared to the pilot trial.

PCA map of the data from the Grain contaminant instrument (GASP) used to analyse oil samples.

Action resulting from the researchDissemination by participation in ISOEN’01 is planned, a poster has been submitted.Dissemination by participation in MAFF Food LINK Food Quality and Safety Sensing Workshop 5 June2001 University College, London.

FP EV oliveoil

FP olive oil

Greek EV olive oil

Hazelnut oil

FP EV10 H5

FP10 H5

G EV10 H5

PC

A 2

PCA 1

-0.5

-1.0

-1.5

0.0

0.5

1.0

-0.5-1.0 0.0 0.5 1.0 1.5 2.0

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MAFFproject code

AR0601

CSG 15 (1/00) 22

REFERENCES

Report to MAFF (2000) Detection of contaminants in grain and infestations in bulk and in-transit grain bysensors and physical methods, ce0315.

Curtis R F, Hobson-Frohock A and Fenwick G R (1981) Volatile compounds from the mite Acarus siro L. infood. Journal of Stored Products Research, 17, 197.

Kuwahara Y, Matsumoto K and Wada Y (1980) Pheromone study on acarid mites IV. Citral: composition andfunction as an alarm pheromone and its secretory gland in four species of acarid mites, Jap. J. Sanit. Zool.,31(2), 73-80.

Tuma D, Sinha R N, Muir W E and Abramson D (1990) Odor volatiles associated with mite-infested bin-storedwheat. Journal of Chemical Ecology, 16(3), 713.

Ventura K, Dostal M and Churacek J (1993) Retention characteristics of some volatile compounds on TenaxGR. Journal of Chromatography, 642, 379.

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23

ANNEX 1

AR0601: Electronic nose detection of invertebrate and mycologicalcontaminants in grain.

Phase 1: Review of volatiles from invertebrates in post-harvest cereals andcomparison with moulds: the potential for detecting both contaminanttypes by electronic nose.

Dr. Christopher RidgwayPest Management Group, Central Science Laboratory, Sand Hutton, York YO41 1LZ

and

Prof. Naresh MaganApplied Mycology Group, Biotechnology Centre, Cranfield University, Silsoe, Bedford MK45 4DT

1. General introduction

During harvesting and storage, cereal grain can be colonised by invertebrate pests and moulds. Poor drying orcooling, or moist pockets of grain, can result in increasing pest or mould activity. This in turn can lead to asignificant loss in quality and contamination with substances harmful to health including mycotoxins, excretaand allergens.

There is a complex interaction between invertebrate pests and moulds, with fungal proliferation often linked toinfestation by invertebrates (Dunkel, 1988; Sinha, 1995). Insects can also invade correctly dried grain withwater contents too low for fungal growth, with their respiration producing metabolic heat and water insufficient amounts to enable spoilage moulds to grow. These interactions are quite complex, some moulds areharmful to grain mites or insects (Wright, 1979; Dunkel, 1988), while other fungi are food sources for insects.Some moulds (Eurotium and Penicillium spp.) can be adversely affected by the presence of mites, whileAspergillus restrictus and Wallemia sebi are more abundant in the presence of others (Armitage & George,1986; Dunkel, 1988). Some insects also carry mould spores and disperse them through the grain bulk.

An early warning system which can give relevant information on the presence of both moulds and invertebrateswould be an invaluable tool in post-harvest management, further guaranteeing the quality of UK grain andespecially that destined for human consumption. In particular, a rapid system is needed for assessing thequality of grain in transit. For the rapid detection of moulds in grain a number of methods have been previouslyexamined. For example, quantification of degradation products of grain components by fungi, changes in fungalenzyme activity, respiratory activity of moulds, changes in biomass indicators such as chitin and ergosterol,immunofluorescence, and more recently photoacoustic FTIR (Tothill et al, 1992; Magan, 1993; Gordon et al,1998). However, many of these techniques are time consuming, expensive or not sufficiently sensitive.Considerable progress has been made towards developing rapid, automated insect detectors for grain in transit(Ridgway and Chambers, 1996; Ridgway et al, 1999a). In particular, a machine vision method has recentlybeen reported which is capable of analysis wheat at a rate of 1 kg/min for the presence of pest beetles, rodentdroppings and ergot (Chambers et al, 1998). At present, however, trade methods for insects and mites stillremain limited to sieving and human visual inspection (Wilkin et al, 1993).

Projecttitle


MAFFproject code

AR0601

24

One promising approach for the detection of a wide range of grain spoilage organisms is that of monitoring forchanges in odour. Electronic nose systems, based on an array of different gas sensors with computer pattern-recognition of the array output, have recently been applied to this problem in efforts to develop a rapidautomated method for grain odour classification. Rapid detection and differentiation between spoilage mouldsin vitro and in grain (Borjesson et al, 1996; Keshri, Magan & Voysey, 1998; Evans et al, 2000), and betweenmycotoxigenic and non-mycotoxigenic species for Fusarium spp. (Keshri & Magan, 2000) have demonstratedthat this approach has potential for application in the grain industry for mould detection. Evaluation ofelectronic nose devices for the detection of pest insects (Ridgway, 1998) and mites (Ridgway et al, 1999b) inwheat has demonstrated similar potential, particularly for the detection of mites.

The volatiles generated by stored-grain moulds and their usefulness in the detection and identification ofspoilage fungi have been reviewed previously (Schnurer et al, 1999; Magan & Evans, 2000). The subject ofthe review presented here will be to consider the major invertebrate pests of UK stored grain and compare therange and type of volatiles produced with those produced by spoilage moulds. This will identify the potentialwhich exists for the early and rapid detection of important pests and their differentiation from graincontaminated by moulds, using an electronic nose system.

2. The major invertebrate pests of stored grain in the UK

Although around 50 species of invertebrates may occur in grain stores, just seven are at present considered tobe important grain-damaging (primary) pests. These are the saw-toothed grain beetle (Oryzaephilussurinamensis), the rust-red grain beetle (Cryptolestes ferrugineus), the grain weevil (Sitophilus granarius), theforeign grain beetle (Ahasverus advena), the lesser grain borer (Rhyzopertha dominica), the flour mite (Acarussiro) and the cosmopolitan food mite (Lepidoglyphus destructor). (Secondary pests, which are mould orhygiene-related species, include some moths and booklice as well as beetles. A third category, non-damagingor stray species, includes predators of grain-damaging pests.)

3. Characteristic volatiles known to be emitted directly from the important primary pests

3.1 BeetlesThe primary pest beetles listed above belong to families of stored-product beetles which are known tocommunicate chemically using aggregation pheromones. These pheromones are released by adult males andattract both the males and the females of the species. Reviews of pheromones produced by stored productinsects have been published by Chambers (1990) and Plarre (1998). O. surinamensis and C. ferrugineus,together with other cucujid and silvanid beetles, have a shared series of macrolide lactones as their aggregationpheromones. For the two species in question, the compounds and references are given in Table 1. For O.surinamensis, (R)-(-)-1-octen-3-ol has also been identified as an aggregation pheromone. The majorcomponent of the aggregation pheromone of S. granarius is (2S,3R)-1-ethylpropyl-2-methyl-3-hydroxypentanoate. Two similar compounds are the major components of the aggregation pheromone of R.dominica (Table 1).

3.2 MitesThe pheromones of stored-product mites have been reviewed recently by Dunn (2000). When disturbed orsquashed, some mites are known to release alarm pheromones to repel and therefore protect neighbouringmites. For A. siro, it has been suggested that the volatile perillen, a furanoid terpene, acts as an alarmpheromone (Curtis et al, 1981). Here, two strains of the mite, maintained on wheat germ/bran, were examined.Perillen was found in the headspace of both, together with the three hydrocarbons decane, undecane andtridecane. These are suggested as being possible sex attractant pheromones (Dunn, 2000), as undecane is knownto be the female sex pheromone of a different acarid mite, Caloglyphus rodriguezi (Mori et al, 1995).Tridecane has also been detected in grain infested with L. destructor (Tuma et al, 1990). In the study by Curtiset al, a fifth major volatile, 2-hydroxy-6-methylbenzaldehyde, was found by extracting whole mites withsolvent. This compound was not detected in the headspace, but has since been detected as the major component

Projecttitle


MAFFproject code

AR0601

25

in the headspace above live A. siro, in the absence of grain, by solid-phase microextraction (Bryning,unpublished results). This compound is known to be the sex pheromone for two other species of mite, Acarusimmobilis (Sato et al, 1993) and Aleuroglyphus ovatus (Kuwahara et al, 1992), and is the alarm pheromone fora third species, Tyrophagus perniciosus (Leal et al, 1988). In the study by Tuma et al, grain infested withmixed populations of the three mite species A. siro, L. destructor and Aeroglyphus robustus also containedcitral. Citral is known to be the alarm pheromone of several other stored-product mites (Kuwahara et al, 1980)and is a mixture of neral (Z)- and geranial (E)-3,7-dimethylocta-2,6-dienal. These findings are summarised inTable 2 but it must be emphasised that studies on mite pheromones are nowhere near as advanced as those onthe pheromones of insects. Mite behaviour is difficult to study in detail so the findings reported above shouldbe regarded with great caution as tentative rather than definitive.

4. Volatiles related to pest numbers and off-odours in infested grain

The studies reviewed above are mostly concerned with identifying insect or mite pheromones with a view tounderstanding or manipulating insect behaviour. However, other studies have been conducted with the aim ofidentifying and quantifying the volatiles responsible for the undesirable tainting of stored grain as a result ofinfestation. Here, the volatiles of interest may not necessarily be emitted from the pests themselves (whetherpheromones or not), but may arise from changes in the commodity brought about by the actions of the pests.

4.1 BeetlesGrain infested with R. dominica is generally known to have a characteristic “sweetish” odour (Pederson, 1992).This is likely to arise directly from contamination with the two major components of the aggregationpheromone, which are reported to have an “unusually intense, sticky-sweet fragrance” (Williams et al, 1981).Grain infested with any of the other species of important primary pest is not generally reported as having adistinctive odour. Grain evaluated for quality parameters using odour-assessment by the US Federal GrainInspection Service (FGIS) sensory panel can be assigned the descriptor “insect”. In a study of sorghum heavilyinfested with different numbers of several species of stored-grain insect (Seitz and Sauer, 1996), FGISinspectors consistently categorised samples containing large numbers of either R. dominica or Triboliumcastaneum (rust-red flour beetle) as “insect”, but not samples which were similarly infested with O.surinamensis, C. ferrugineus or Sitophilus oryzae (rice weevil). Sample headspace volatiles were also analysedchemically. For the species of interest, volatiles found which did not occur in normal, uninfested grain arelisted in Table 3, together with the infestation levels which produced them.

4.2 MitesStored products infested with A. siro are generally reported to have a characteristic odour often described as“minty” (Solomon, 1962). However, identification of the chemical responsible for this particular odourremains to be achieved. Tuma et al (1990) analysed volatiles related to mite numbers in ventilated and non-ventilated bin-stored wheat seeded with mixed populations of A. siro, L. destructor and A. robustus. The twobins were monitored over a one year period (August - August). Tridecane, neral and geranial were detected(the latter two compounds being the components of the known mite pheromone citral). Seasonal fluctuation inmite numbers differed between species and seasonal fluctuation in concentration was different for eachcompound. Tridecane was detected throughout the experiment. In both bins, levels of tridecane were relativelyhigh at the start of the experiment, when the grain contained mostly A. siro. At this time, neither neral norgeranial were detected. One or both of these latter two compounds were detected throughout most of theremainder of the experiment, but dropped back to zero concentration by the August of the following year.Absolute values for the amounts of volatiles detected are not given. Numbers of A.siro at the start of theexperiment were around 13000 mites/kg (non-ventilated) and 5000 mites/kg (ventilated). In this study, Tuma etal also analysed laboratory cultures of single species of A. siro or L. destructor on wheat samples inoculatedwith different fungi. Evidence is presented to suggest that some fungi were better diets than others for A. siro,based on levels of tridecane production. Tridecane production was highest for wheat infected with Fusariumsemitectum. However, relative mite numbers and rates of reproduction are not given. Conversely, citral issuspected of inhibiting the growth of certain moulds (Cole and Blum, 1975; Matsumoto et al, 1979).

Projecttitle


MAFFproject code

AR0601

26

5. Other possible factors influencing volatiles from infested grain

During storage, grain can slowly undergo chemical changes that are known to alter flavour and nutritive value.The actions of grain-damaging insects or mites can accelerate these changes (Howe, 1965), either by causingmechanical damage, heating the grain, spreading moulds or increasing grain moisture. For example,breakdown of fats can be accelerated by insect attack, leading to an increase in free fatty acids (FFAs) whichcause rancid off-flavours and (from the short chain FFAs) odours. However, it has been reported that the effectof infesting wheat with L. destructor was to in fact slow down the normal increase in fat acidity value (FAV)over time (White et al, 1979). Here, it is thought that the mites may have been feeding on grain fungi and thatin this study it was these fungi that were the most important causative agent for increases in grain FAV.

6. Comparison of volatiles produced by invertebrates with those from fungi

Recently, two extensive reviews have shown that there are a range of volatiles produced by spoilage fungiwhich have potential as markers of fungal activity in grain (Schnurer et al, 1999; Magan & Evans, 2000).Studies have been carried out both in vitro to identify the range of volatiles produced by individual spoilagefungi, and in situ in either artificially contaminated or naturally stored grain. From the available studies it hasbeen shown that the key volatiles produced in vitro and on a range of cereal grains are a range of classes ofvolatile compounds including alcohols, carbonyls and hydrocarbons. The major volatiles identified were 3-methyl-1-butanol, 1-octen-3-ol and other 8-carbon ketones and alcohols. Table 4 shows the key volatiles foundby different authors on inoculated cereal grains. This shows the wide range of alcohols in particular which arekey markers for fungal activity, based on the literature. Table 5 further shows the range of volatile compoundsproduced when individual fungi were grown on wheat grain (Bjorjesson et al,1992). This has enabled electronicnose systems which examine the qualitative patterns of volatile production to be used as a marker/indicator ofmould activity and as a quality criterion for grain.

Comparison with pest volatiles shows that perillen and citral, together with a range of hydrocarbons, areproduced by mites. The majority of these volatiles are thought to possibly have a role as pheromones. However,much less information is known for mites when compared to that available for moulds. With regard to otherpests such as beetles, the major volatiles found were mostly very different from those produced by spoilagemoulds. However, one exception appears to be 1-octen-3-ol, which has been reported to be produced by theinsect O. surinamensis. The only other similar compound is 2-pentanol, which was shown to be a minorcomponent of the total volatiles produced in R. dominica infested sorghum. This suggests that the volatilesidentified in the literature for a range of pest species are in general markedly different from those identified forspoilage fungi. Thus, potential does appear to exist for the differentiation between grain contaminated bymoulds and that contaminated by insects. A second, less encouraging conclusion from the results reviewedhere is that the major pest insect of UK stored grain, O. surinamensis, does not appear to impart an odour tograin which is detectable to humans. This appears to be the case even at very high levels of infestation. Thisdoes not necessarily rule out the possibility of developing a successful electronic nose method for this species,however, as electronic noses are capable of responding to volatiles additional to those which are humanodorants (i.e. which have low odour thresholds). From Table 1 it can be seen that O. surinamensis does emit arange of volatiles, albeit in low quantities.

In summary, the information reviewed suggests that in addition to the detection of moulds, potential does existfor the development of electronic nose devices to detect invertebrate contaminants in grain. This knowledge ofthe types of volatiles associated with infestation and their likely concentrations will allow devices to beoptimised for invertebrate detection. Once the method is optimised, limits in sensitivity can be determined.

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7. References

Armitage D M & George C L (1986) The effect of three species of mites upon fungal growth on wheat.Experimental and Applied Acarology 2, 111-124.

Borjesson T, Stolman, U., Adamek, P. & Kaspersson, A. (1989). Analysis of volatile compounds for detectionof moulds in stored cereals. Cereal Chem. 66, 300-304.

Borjesson T, Stollman U and Schnurer J (1992) Volatile metabolites produced by six different fungal speciescompared to other indicators of fungal growth on cereal grains. Appl. Environ. Microbiol. 58, 2599-2605.

Borjesson T A, Eklov T, Jonsson A, Sundgren H and Schnurer J (1996) An electronic nose for odorclassification of grains. Cereal Chem. 73, 457-461.

Chambers J, Ridgway C, Davies E R, Mason D R and Bateman M (1998) Rapid automated detection of insectsand certain other contaminants in cereals. London: Home Grown Cereals Authority, (HGCA Project Report no.156), 64p.

Chambers J (1990) Overview on stored-product insect pheromones and food attractants. J. Kansas Entomol.Soc. 63, 490-499.

Cole L K and Blum M S (1975) Antifungal properties of the insect alarm pheromones, citral, 2-heptanone, and4-methyl-3-heptanone, Mycologia, 67, 701-708.

Curtis R F, Hobson-Frohock A and Fenwick G R (1981) Volatile compounds from the mite Acarus siro L. infood. J. Stored Prod. Res., 17, 197-203.

Dunkel F (1988) The relationship of insects to the deterioration of stored grain buy fungi. International Journalof Food Microbiology 7, 227-244.

Dunn, J A (2000) Literature review identifying chemicals for testing as candidate attractants for mite pests ofstored grain. CSL Report No. 109, 17pp.

Evans P, Persaud K C, McNeish A S, Sneath R W, Hobson N and Magan N (2000) Evaluation of a radial basisfunction neural network for the determination of wheat quality from electronic nose data. Sensors andActuators B 69 348-358.

Gordon S, Wheeler B, Schuddy R, Wicklow DT and Greene R (1998) Neural network pattern recognition ofphotoacoustic FTIR spectra and knowledge-based techniques for detection of mycotoxigenic fungi in foodgrains. J. Food Prot. 61, 221-230.

Howe R W (1965) Losses caused by insects and mites in stored foods and feedingstuffs, Nutrition abstracts andreviews, 35, 285-293.

Kaminski, E., Wasowicz, E., Zawinska-Wojtasiak, R. & Gruchala, L. (1987). Volatile microflora metabolites asinduces of grain deterioration during storage. In Morton, I.D. (Editor), Cereals in a European Context. EllisHarwood, Chichester, UK., pp. 446-461.

Keshri G and Magan N (2000) Detection and differentiation between mycotoxigenic and non-mycotoxigenicstrains of two Fusarium spp. using volatile production profiles and hydrolytic enzymes. J. Appl. Microbiol. 89,825-833,

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Keshri G, Magan N and Voysey P (1998) Use of an electronic nose for the early detection and differentiationbetween spoilage fungi. Letts. Appl. Microbiol. 27, 261-264.

Kuwahara Y, Matsumoto K and Wada Y (1980) Pheromone study on acarid mites IV. Citral: composition andfunction as an alarm pheromone and its secretory gland in four species of acarid mites, Jap. J. Sanit. Zool., 31,73-80.

Kuwahara Y, Sato M, Koshii T and Suzuki T (1992) Chemical ecology of astigmatid mites XXXII. 2-hydroxy-6-methyl-benzaldehyde, the sex pheromone of the brown-legged grain mite Aleuroglyphus ovatus (Acarina:Acaridae), Appl. Entomol. Zool., 27, 253-260.

Leal W S, Nakano Y, Kuwahara Y, Nakao H and Suzuki T (1988) Pheromone study on acarid mites XVII.Identification of 2-hydroxy-6-methyl-benzaldehyde as the alarm pheromone of the acarid mite Tyrophagusperniciosus (Acarina: Acaridae) and its distribution among related mites, Appl. Entomol. Zool., 23, 422-427.

Magan N (1993) Early detection of fungal spoilage in grain. Int. Biodet. Biodegrad. 32, 145-160.

Magan N, and Evans P (2000) Volatiles as an indicator of fungal activity and differentiation between species,and the potential use of electronic nose technology for early detection of grain spoilage. J. Stored Prod. Res. 36,319-340.

Matsumoto K, Wada Y and Okamoto M (1979) The alarm pheromone of grain mites and its antifungal effect,In: Recent advances in acarology, ed. Rodriguez J G, Academic Press, New York, pp243-249.

Mori N, Kuwahara Y, Kurosa K, Nishida R and Fukushima T (1995) Chemical ecology of astigmatid mitesXLI. Undecane: the sex pheromone of the acarid mite Caloglyphus rodriguezi, Appl. Entomol. Zool., 30, 415-423.

Oehlschlager A C, King G G S, Pierce Jr. H D, Pierce A M, Slessor K N, Millar J G and Borden J H (1987)Chirality of macrolide pheromones of grain beetles in the genera Oryzaephilus and Cryptolestes and itsimplications for species specificity, J. Chem. Ecol., 13, 1543-1554.

Pederson (1992) Insects: identification, damage, and detection. In: Storage of Cereal Grains and TheirProducts, ed. Sauer D B, Amer. Assoc. Cereal. Chemists, St. Paul, Minnesota, pp 435-489.

Phillips J K, Chong J M, Anderson J F and Burkholder W E (1989) Determination of the enantiomericcomposition of (R*,S*)-1-ethylpropyl-2-methyl-3-hydroxypentanoate, the male produced aggregationpheromone of Sitophilus granarius, Entomol. Exp. Appl., 51, 149-153.

Pierce A M, Pierce Jr. H D, Oehlschlager A C and Borden J H (1985) Macrolide aggregation pheromones inOryzaephilus surinamensis and Oryzaephilus mercator (Coleoptera: Cucujidae), J. Agric. Food Chem., 33, 848-852.

Pierce A M, Pierce Jr. H D, Borden J H and Oehlschlager A C (1989) Production dynamics of cucujolidepheromones and identification of 1-octen-3-ol as a new aggregation pheromone for Oryzaephilus surinamensisand O. mercator (Coleoptera: Cucujidae), Environ. Entomol., 18, 747-755.

Plarre R (1998) Pheromones and other semiochemicals of stored product insects. A historical review, currentapplication, and perspective needs. Mitteilungen aus der Biologischen Bundesanstalt für Land- undForstwirtschaft No. 342, 13-84.

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Richard-Molard, D., Cahagnier, B., Poisson, J. & Drapron, R. (1976). Evolutions compare es des constituentsvolatils et de la microflora de mais stockes sous differentes conditions de temperature et d’humidite. Annals deTech. Agricole 25, 29-44.

Ridgway C (1998) Potential of an electronic nose to detect three species of pest insect in wheat. In: CropProtection and Food Quality: Meeting Customer Needs, BCPC-ANPP, September 1997, 349-356.

Ridgway C and Chambers J (1996) Detection of external and internal insect infestation in wheat by near-infraredspectroscopy. Journal of the Science of Food and Agriculture, 71, 251-264.

Ridgway C, Chambers J and Cowe I A (1999a) Detection of grain weevils inside single wheat kernels by a verynear infrared two-wavelength model. Journal of Near Infrared Spectroscopy, 7, 213-221.

Ridgway C, Chambers J, Portero-Larragueta E and Prosser O (1999b) Detection of mite infestation in wheat byelectronic nose with transient flow sampling. Journal of the Science of Food and Agriculture, 79, 2067-2074.

Sato M, Kuwahara Y, Matsuyama S and Suzuki T (1993) Male and female sex pheromones produced byAcarus immobilis (Acaridae: Acarina), Naturwissenschaften, 80, 34-36.

Schnurer J, Olsson J and Borjesson T (1999) Fungal volatiles as indicators of food and feed spoilage: AReview. Fungal Genetics and Biology 27, 209-217.

Seitz L M and Sauer D B (1996) Volatile compounds and odors in grain sorghum infested with commonstorage insects, Cereal Chem., 73, 744-750.

Sinha R N (1995) The Stored Grain Ecosystem. Chapter 1 in Stored Grain Ecosystems, eds. D.S. Jayas, N.D.G.White & W.E. Muir. Marcell Dekker, New York.

Solomon M E (1962) Ecology of the flour mite, Acarus siro L. (=Tyroglyphus farinae DeG.), Ann. appl. Biol.,50, 178-184.

Tothill IE, Harris D and Magan N (1992) The relationship between fungal growth and ergosterol content ofwheat grain. Mycological Research 11, 965-970.

Tuma D, Sinha R N, Muir W E and Abramson D (1990) Odor volatiles associated with mite-infested bin-storedwheat, J. Chem. Ecol., 16, 713-724.

White N D G, Henderson L P and Sinha R N (1979) Effects of infestation by three stored-product mites on fatacidity, seed germination and microflora of stored wheat, J. Econ. Entomol., 72, 763-766.

Wilkin D R, Catchpole D and Catchpole S (1993) The development of a practical method for removing insectsfrom large samples of grain. London: Home Grown Cereals Authority, (HGCA Project Report no. 82).

Wilkins, C.K. & Scholl, S. (1989). Volatiles metabolites of some barley storage moulds. Int. J. Food Microbiol.8, 11-17.

Williams H J, Silverstein R M, Burkholder W E and Khorramshahi A (1981) Dominicalure 1 and 2:components of aggregation pheromone from male lesser grain borer Rhyzopertha dominica (F.) (Coleoptera:Bostrichidae), J. Chem. Ecol., 7(4), 759-780.

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Wong J W, Verigin V, Oehlschlager A C, Borden J H, Pierce Jr. H D, Pierce A M and Chong L (1983)Isolation and identification of two macrolide pheromones from the frass of Cryptolestes ferrugineus(Coleoptera: Cucujidae), J. Chem. Ecol., 9(4), 451-474.

Wright V F (1979) Interactions of stored product insects with storage fungi of the genus Penicillium withemphasis on secondary metabolites. PhD Thesis, University of Minnesota.

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Table 1. Major components of the aggregation pheromones of primary pest beetlesSpecies Major components Rate of

production,per beetlehour

Reference

O. surinamensis (R),(Z,Z)-3,6-dodecadien-11-olide(II).(Z,Z)-3,6-dodecadienolide (III).(R),(Z,Z)-5,8-tetradecadien-13-olide (IV).

(R)-(-)-1-octen-3-ol.

Up toaround 50pga (total II+ III + IV;on oats).

Up toaround 0.8ng (after 4wks fromeclosion; onoats).

Pierce et al,1985; Pierceet al, 1989.

C. ferrugineus (E,E)-4,8-dimethyl-4,8-decadien-10-olide (V); (32,11S)-3-dodecen-11-olide (I); (Z)-5-tetradecen-13-olide (VII); (Z,Z)-3,6-dodecadien-11-olide (II); (Z,Z)-5,8-tetradecadien-13-olide (IV).

Wong et al,1983;Oehlschlageret al, 1987.

S. granarius (2S,3R)-1-ethylpropyl-2-methyl-3-hydroxypentanoate

Phillips et al,1989.

R. dominica (S)-(+)-1-methylbutyl (E)-2-methyl-2-pentenoate (dominicalure1); (S)-(+)-1-methylbutyl (E)-2,4-dimethyl-2-pentenoate(dominicalure 2).

Williams et al,1981.

aup to 100 pg per male beetle hour: here, the value is assumed to be halved for a mixed-sex population

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Table 2. Putative pheromones of primary pest mitesSpecies Major components Reference

A. siro perillen; decane; undecane; tridecane; 2-hydroxy-6-methyl benzaldehyde; citral (neraland geranial)?

Curtis et al, 1981;Bryning(unpublished);Tuma et al, 1990.

L. destructor tridecane; citral (neral and geranial)? Tuma et al, 1990.

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Table 3. Volatiles related to insect infestation of sorghum (Seitz and Sauer, 1996)Species Infestation level,

insects/kgaNon-grain volatiledetected

Levels of volatilerelative tograin volatilesb

O. surinamensis 5000 none -

C. ferrugineus 300 macrolide (V)macrolide (I)additional macrolide

mediumvery minorminor

R. dominica 30 2-pentanoldominicalure 1dominicalure 2apparent homologue ofdominicalure 1

minormajormajormedium

aIncludes insects in all stages of development.bArea of gas chromatogram peak relative to peaks arising from normal grain volatiles.

Table 4. Fungal volatiles identified in inoculated cereal cultures by different authors

Cereal:Fungal Volatile Maize Barley Wheat

1-Butanol c2-Butanol c, d

3-Methyl-1-butanol a b c, d1-Pentanol a b

1-Hexanol a c2-Octen-1-ol c

1-Octanol c3-Octanol a c

1-Octen-3-ol a bPhenyl ethanol c

2-Ethyl-5-methyl-phenol bHexanal a

2-(2-Furyl) pentanal bBenzaldehyde c3-Octanone c

2-Hydroxy-3-butanone aNonanone c

2-Methyl-acetophenone bButyl acetate cAmyl acetate cOctyl acetate c2-Methylfuran d

2-(1-Pentyl)furan b3-Methyl anisole b

aRichard-Molard et al (1976); bWilkins & Scholl (1989); cKaminski et al (1987); d Borjesson et al (1989).

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Table 5. Rate of volatile metabolite production from six fungal species grown on wheat. Adapted fromBorjesson et al (1992)

Production of metabolite on wheat from fungi, ng/ha:Volatile P. brevi-

compactumP. glabarum P. roque-

fortiA. flavus A. versi-

colorA. candidus

Acetone 240002-Propanol 2983-Methylfuran 4.8 26 12 30 27 32Nitromethane 9.42-Methyl-1-propanol

10 0.67 83 13 2.9 9.3

3-Pentanone 1.7 322-Methyl-1-butanol

12 1.4 8 3.8 3.6

1-Penten-3-ol 2.6 4.3Octadiene 6.1 2.3 3.82-Butanone 28 22Dimethylbenzene 7.5 2.9 1.3Ethylbenzene 0.83 0.6Limonene 0.2 0.47 2.1 1.73-Octanone 121-Octen-3-ol 3.2Monoterpene 1 14Sesquiterpene 1 7Sesquiterpene 2 15Thujopsene 0.96 1.5 0.62

a production rate is for 400 g of grain inoculated with a 10 ml suspension of spores(104 spores per ml)

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35

ANNEX 2 Report on Cranfield University mycolological work for the project

1. Irradiation of grain for experiments

Wheat grain 20 kg from the 2000 harvest was provided by SRI for irradiation and distribution to CSL York andother partners. Initial moisture content was 12.3% and had a water activity of 0.713 at 25oC. Grain wassubdivided into 500 g samples and placed in polyethylene bags and sealed. The 20 kg of grain was sent to acontract company (Isotron, Swindon, U.K.) for irradiation at 12 kGry using a gamma radiation source. Thegrain was subsequently checked to ensure that it was free of mould contaminants, but with retained germinativecapacity. The grain was used to construct a water absorption curve to accurately modify the water availability todifferent treatment conditions (Figure 1). Grain with retained germinative capacity was successfully achievedusing this treatment and provided to CSL York for inoculation with mites.

2. Mycofloral examination of samples inoculated with mites and tested using the GASP systems.

The natural grain, and grain containing various amounts of mites were supplied by SRI and CSL York forexamination of fungal loads to ensure that interference from moulds could be determined where necessary.

The method involved the serial dilution method with plating of serial dilutions onto both malt extract agar andmalt 10% salt agar to obtain information of overall populations of contaminating moulds. Samples wereexamine in different batches as they were received from SRI after measurements with GASP had been carriedout.

Table 1a and 1b shows that the natural grain contained the normal range of fungal contaminants one wouldexpect. The mean population of about 3.3 x 106 CFUs g-1 is a level which can be expected in freshly harvestedgrain. Overall, the populations of spoilage moulds was relatively low.

Overall 26 samples had some fungal contamination with 60 samples examined having none. Table 2a and 2bshow the samples from mite experiments with irradiated grain which had mould contamination, particularly byPenicillium spp. and occasionally yeasts. This could partially be due to microbial contaminants of the foodsource on which the mites are multiplied prior to infecting of the grain treatments.

Table 3 shows that there were a number of samples which remained completely free of mould regardless oftreatment moisture content or time of incubation. It is worthwhile noting that the final series of samplesexamined with metal oxide sensor arrays (188-221) contained no mould contamination. Thus the resultsobtained with these samples where good differentiation was obtained did not have any interfering volatilesbeing produced by mould contaminants.

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Table 1a. Natural grain plated on MEA Volume plated =0.01 ml; dilution=10-3)

Species/samples NG1 NG2 NG3 NG4 NG5 NG6 NG7 NG8 TotalAcremonium 4.4 17.5 11.5Alternaria 2.5 2 1.5Asp. Ochraceus 5Aurobacidium 1 2 1 1Cladosporium 17 3 4 9.5 21 6.5 7.5 9.5Fusarium spp 3.5 0.5Gliocladium 0.5Mucor 2.5 0.5 0.5Penicillium spp. 1 1.5V. lecanii 6.5 3.5 3.5Verticillium 0.5W. sebi 4yeast (pink) 1 2.5 0.5 4.5yeast (white) 8 3 4 9.5 22.5 14 30.5 12otherTotal populations 34 17 13 28.9 54 40.5 52.5 28Mean population 33.4875Population permilligram 3400 1700 1300 2890 5400 4050 5250 2800Mean Pop. permilligram 3348

Table 1b. Natural grain plated on MS

Species/samples NG1 NG2 NG3 NG4 NG5 NG6 NG7 NG8 TotalAcremonium 0.5 2.5Asp. ochraceus 3.5Cladosporium 5 1.4 5 2 4Fusarium 3Penicillium spp 2W. sebi 2Other 6.5total population 12 6.9 8 0 2 2.5 2 4Mean pop. 4.675Pop. Per milligram 1200 690 800 0 200 250 200 400Mean pop. Permilligram 467

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Table 2a. Irradiated samples plated onto Malt extract agar

Sample\SpeciesA.restrictus

A.ochraceus Eurotium

Penicillium

Yeast(white)

Totalpopulations persample

Pop. Pergram

74 1.5 0.5 2 20000076 3.5 2 5.5 55000087 8 8 80000090 0.5 0.5 5000093 7 7 70000094 0.5 0.5 5000095 0.5 1 1.5 15000096 1 0.5 1.5 15000097 56 56 5600000

115 0.2 0.2 20000116 0.2 0.2 20000117 0.17 0.17 17000118 0.08 0.08 8000119 0.18 0.18 18000120 0.2 0.2 20000127 0.19 0.19 19000128 0.2 0.2 20000129 0.2 0.2 20000130 0.18 0.18 18000132 0.19 0.19 19000139 0.19 0.19 19000140 0.16 0.16 16000141 0.2 0.2 20000142 0.07 0.07 7000143 0.2 0.2 20000144 0.2 0.2 20000

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Table 2b. Irradiated samples plated on Malt 10% saltagar.

sample\speciesA.ochraceus

Penicillium

totalpopulation pop. Per gram

76 1.5 0.5 2 200000115 0.2 0.2 20000116 0.2 0.2 20000117 0.1 0.1 10000118 0.06 0.06 6000119 0.13 0.13 13000120 0.2 0.2 20000127 0.18 0.18 18000128 0.19 0.19 19000129 0.2 0.2 20000130 0.15 0.15 15000132 0.15 0.15 15000133 0.18 0.18 18000140 0.15 0.15 15000141 0.2 0.2 20000142 0.05 0.05 5000143 0.2 0.2 20000144 0.2 0.2 20000

Table 3. List of samples with no fungal growth001 to 072 88 109 188c

73 89 110 192c75 91 11 194c77 92 112 197c78 98 113 199c79 99 114 203c80 100 121 210(100)81 101 122 211(100)82 102 123 214(100)83 103 124 215(100)84 104 125 220(100)85 105 126 221(100)86 106 131

107 133108 134

135136137138

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Figure 1. Moisture content/water activity adsorption curve for irradiated wheat grain

10

15

20

25

30

35

40

0.7 0.8 0.9 1

Water activity

Mo

istu

re c

on

ten

t (%

)

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ANNEX 3 CSL Contribution to GASP final report (MAFF AR0601)

Chris Ridgway, CSL, 6/4/01

EXPERIMENTAL

General

Wheat used was unmilled, variety Riband, irradiated by Isotron, Swindon, U.K. at 12 kGry using a gammaradiation source. Wheat was used either at approximately 16% moisture content (mc) as received orconditioned to approximately 19% mc (CSL Standard Operating Procedure IREG number 006, 1990). Grainwas stored in sealed jars at 4oC for at least 1 week before use. Mites used were Acarus siro L, sex and ageundetermined. Insects used were adult Oryzaephilus surinamensis, known sex (both male and female), agedapproximately 0-2 week from eclosion.

Preparation and analysis of samples

Samples for analysisA summary of the samples analysed in each experiment performed is given in Table 1. For Experiment 1,twelve replicate 32 g samples at each infestation level of 0, 16 and 32 mites were prepared both for wheat atapproximately 16% mc and wheat at approximately 19% mc, giving a total of 72 separate samples of sixdifferent types. Mites were separated manually from their food of culture, counted and added without mixing tothe wheat in 55ml PET tubes. The tubes were then fitted with muslin covers secured by wire. The sampleswere then held in a controlled-environment room at 75% relative humidity and 20oC until being despatched(courier) for analysis by the GASP instrument (SRI). Samples were despatched approximately 0, 1, 2 and 4weeks after being prepared. At each of these times, 3 replicate samples of each sample type were despatched.

For Experiment 2, samples were prepared, held and despatched in the same way as in Experiment 1, butadding 0, 2 or 10 insects in place of mites. Here, the number of male and female insects added to each infestedsample was made equal.

For Experiment 3, samples were prepared as for Experiment 1, but with only 2 replicates per sampletype (12 samples total). Samples were held as above until being subjected to SPME headspace analysis (CSL).After approximately 1 week from preparation, one replicate of each sample type was analysed. The remainingsamples were analysed after approximately 3 weeks from preparation.

For Experiment 4, samples were prepared and analysed as for Experiment 3, but adding 0, 2 or 10insects in place of mites (as above).

For Experiments 5-8, replicate 25 g samples at each infestation level of 0 and 100 mites were preparedfor wheat at approximately 19% only, and held as above. For Experiment 5, the number of replicates was 18.Nine replicate samples of each sample type were despatched for analysis by the GASP instrument both atapproximately 3 weeks and at approximately 5 weeks from preparation. For Experiment 6, the number ofreplicates was 20 and all samples were despatched for analysis by the GASP instrument at approximately 4weeks from preparation. For Experiment 7, three replicates were prepared of each sample type and all sampleswere despatched for analysis by the GASP instrument/Tenax-tube headspace analysis (SRI) at approximately 4weeks from preparation. For Experiment 8, three replicates were prepared of each sample type and all sampleswere despatched for assessment by odour panel (SRI) at approximately 7 weeks from preparation.

Samples for counting by laboratory reference method

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For Experiments 1-4, 6 and 7, analytical samples (see above) were chilled to -10oC immediately after analysisand held at this temperature until analysed by the appropriate laboratory reference method. For Experiments 5and 8, however, replicates additional to those described above were prepared at the same time as the analyticalsamples for the purpose of estimating contaminant levels. Two such replicates of each sample type wereprepared for Experiment 5 and these were chilled and held at -10oC after 3 weeks from preparation. Similarly,for Experiment 8, two such replicates were prepared and these were chilled and held at -10oC after 7 weeksfrom preparation.

SPME headspace analysis of grain samples

Sampling methodA 75 µm carboxen/PDMS Supelco SPME portable field sampler was used. The SPME fibre was conditioned at270oC under helium for at least 30 min prior to sampling (spare GC injection port). Immediately beforeanalysis, exactly 7 g from the top portion of the grain sample was removed by gentle tipping. The samplevessel was then sealed with aTeflon lined septum (35-45 Duromer with 3mil teflon. (Supplied by SpecialitySilicone Products, product code SSP119IT-35D-SS) and the sample maintained at 40oC (heated water bath) for1 h. After this time, the freshly conditioned SPME fibre was inserted into the sample vessel, left for 30 minthen removed and immediately analyzed by GC-MS.

GC-MS methodGC-MS analysis was conducted on a Hewlett Packard 5890 series II gas chromatograph coupled to a VG Trio-1mass spectrometer. After sampling, the SPME fibre was immediately desorbed for 1 min at 270oC in splitlessmode (purge on after 1 min) onto a 50 m Chrompack CPSil19CB column (0.32 mm i.d., 1.2 µm film thickness).Helium was used as the carrier gas. The oven temperature was held at 30oC for 1 min rising at 5oC/min to130oC, then increased to 190oC at 2oC/min, then increased to 270oC at 10oC/min and finally held at thistemperature for 2 min. The initial head pressure was 5.3 psi and the gas chromatograph operated in constantflow mode. The mass spectrometer source and interface temperatures were 200oC and 275oC respectively. Themass spectrometer was operated in Electron Impact mode (EI+) at 70 eV and scanned once a second from m/z33-350 with no solvent delay.


Sampling methodGrain samples were scanned by the GASP instrument device following the normal procedure, but withsimultaneous Tenax-tube sampling of the sensor array exhaust. In order to overcome the extra resistance toairflow caused by the Tenax, an additional, laboratory vacuum pump was connected down stream of the GASPinstrument outlet flowmeter. This allowed the air-flow during sampling to be maintained at the standard 35ml/min. Sampling tubes (Chrompack) were packed with Tenax TA (100 mg), conditioned for 1 h at 250oCunder helium, capped and stored prior to use (24h maximum). The tube was connected to the sensor arrayexhaust outlet immediately prior to analysis the grain sample and left for the duration of the scan (3 min) beforeremoving, capping and chilling immediately (around 0oC). Chilled samples were transported overnight to CSLand further chilled to -35oC until analyzing by thermal desorption GC-MS.

All samples were held at 30oC for 15 min immediately before being scanned at 30oC. Two of the threereplicates containing mites were then re-analysed, this time vigorously shaking the sample by hand (approx. 30s) immediately before both holding and then analysis at 40oC.

GC-MS method

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Exposed Tenax tubes were desorbed onto the GC-MS using a Chrompack Thermal Cold Trapping (TCT)device. The precool temperature was kept at -1100C for 3 min and the samples then desorbed at 250oC for 10min. After this time, the cryotrap was heated from -110oC to 250oC and held at this temperature for 3 min. Thedesorption flow rate was set to 20 ml/min. The TCT head pressure was set to 10 psi and the same temperatureprogramme and mass spectrometer conditions used as with the SPME analysis. A measured aliquot of areference solution of undecanone in pentane (90.75 µg/ml) was injected into the sampling tube (outlet end toGC) immediately prior to analysis as an internal standard. Quantitative measurements were obtained asfollows:

Amount of component, ng = (peak area of component/peak area of undecanone) x (90.75/volume ofreference injected, in µl)

Amounts of volatiles obtained were used to calculate volatile headspace concentrations (ppm) based on theGASP instrument airflow and the sampling time, following standard methods. In order to confirm thatdesorption of sampled volatiles from the Tenax tube into the GC was quantitative, one of the tubes obtainedfrom the shaken, 40oC-heated mite-infested samples was desorbed twice. It was not possible to perform abreakthrough experiment, using a second (breakthrough) Tenax tube connected in series after the first(sampling) tube, to confirm that volatiles reaching the sampling tube were not passing through the Tenax andhence being underestimated. However, for the relatively high-boiling components of interest here, this will nothappen at the low air-flow rate and short sampling time used (Ventura et al, 1993 and references therein).


One additional 25 g grain sample (16% mc) containing 25 A. siro was prepared, together with one uninfestedcontrol sample. These were analysed by SPME as above, but only one day after adding the mites. Afteranalysing, each sample was shaken vigorously for 30 s and then immediately re-analysed. Here, samples weremaintained at 30oC for 30 min and then sampled with the SPME fibre for 60 min. GC conditions were asfollows: the oven temperature was held at 30oC for 1 min rising at 5oC/min to 270oC and finally at thistemperature for 10 min.

Laboratory reference method for estimating mite numbers

The wheat sample was tipped into a clean glass beaker (400 ml capacity), rinsing out the empty sample vesselinto the same beaker with 50% water/ethanol (100 ml). Water (150 ml) was added to the beaker, and the beakerand contents sonicated by ultrasonic bath for 10 min. The liquid was then decanted onto a gridded filter paper(12.5 cm diameter) held under suction in an Hartley funnel. The filter paper was then stained using approx.1%w/w 50% water/IMS methylene blue solution (5 ml) and examined under a stereoscopic microscope(approx. ×10-×15 magnification). The total number of A. siro which could be observed on the filter paper wasrecorded and the presence of any other mite/insect species noted.

Laboratory reference method for checking insect numbers

Grain samples were tipped out onto a white tray and the presence of adult O. surinamensis and other speciesrecorded.

RESULTS

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Numbers of mites/insects present in samples at time of analysis

Results from performing the laboratory reference method for A. siro or O. surinamensis on scanned samples aresummarised in Tables 2-5. Consistently low levels of tarsonimid mites were also found to be present in thewheat (around 17 tarsonimid mites/kg), together with a few field beetles (ground beetles, clover beetles androve beetles; around 4 adult insects/kg). However, these appeared quite desiccated and were almost certainlypresent in the pre-irradiated grain and killed during irradiation.

For the insect experiments, the number of adult insects present in the sample was not expected to changeover the 4 weeks from adding, as the life-cycle is likely to be longer than 28 days under the conditions inwhich samples were held. However, the results show that some insects were removed along with the 7 g grainwhich was removed immediately before analysis by the GASP instrument (Experiment 2).

Changes in headspace of grain samples with mite infestation (Experiment 3)

Using SPME headspace analysis, it was found that 3 weeks from adding the mites, mite presence wasassociated with the appearance in the chromatogram of either one (16% initial mc wheat) or both (19% initialmc wheat) of two minor peaks (Figures 1-2 and 3-4 respectively). The peak at retention time (tR)=31.5 min wasconfirmed as tridecane, both by comparison with library spectra and by comparison with the tR and spectrum oftridecane standard. The peak at tR=33.2 min was tentatively identified as 2-methoxy-6-methylbenzaldehyde,based on comparison with library spectra only. No other differences in the chromatograms were detected. At 1week from adding the mites, no such differences were observed (chromatograms not shown).

Interestingly, both here and in Experiment 4 (below), chromatograms from all samples at 19% initial mcgenerally possessed a number of additional/larger peaks compared to those from the 16% initial mc samples(for example, Figure 5). In particular, levels of ethanol were much higher for the 19% initial mc samples.


No differences were observed between chromatograms from the infested and control samples, either at 1 weekor 3 weeks from adding the insects.

Determination of mite-volatile concentrations reaching the GASP instrument sensor array, by Tenax-tube headspace analysis (Experiment 7)

Example chromatograms obtained from this experiment are given in Figures 6 and 7. It can be seen thatanalysis at 30oC and without first shaking the sample results in zero or negligible amounts of the mite-volatilestridecane and 2-hydroxy-6-methylbenzaldehyde reaching the GASP instrument sensor array (trace levels oftridecane were detected for both the control and unshaken mite-infested samples under these conditions, asshown in Figure 7, but this is thought to arise at least in part from an unavoidable low-level hydrocarbon bleedfrom the Tenax itself rather than from the sample). Analysis at 40oC, with shaking of the samples beforehand,results in surprisingly large amounts of tridecane and 2-hydroxy-6-methylbenzaldehyde reaching the sensorarray, especially when compared with other volatiles arising from the grain such as ethanol (Figure 6). Theknown mite-produced alarm pheromone citral (both isomers) was also detected (Figure 7). Repeat desorptionof one of the tubes from the shaken, 40OC-heated mite-infested samples did not show the presence of anyretained volatiles, confirming that the desorption method used was quantitative for the volatiles being studied.From these results, concentrations (ppm) of mite-volatiles reaching the sensor array during analysis of the mite-infested samples (shaken, 40OC) were calculated and are given in Table 6.

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Results from this additional experiment are given in Figure 8. It can be seen that 2-hydroxy-6-methylbenzaldehyde was only detected in the headspace of the shaken, mite-infested sample.

DISCUSSION


In general, mites multiplied more slowly than expected under the conditions in which the samples were held.This was especially the case in Experiments 5-7, with counted mite numbers after 3 or 4 weeks being close toor even below the number of mites added. However, in Experiments 6 and 7 some mites could possibly havebeen missed during counting as many would have been severely crushed and desiccated by the shaking/heatingprocedure used in analysing them. In Experiment 6, the average concentration of mites in the infested grainsamples when scanned by the GASP instrument was determined to be approximately 5,500 mites/kg grain.Even allowing for the possibility that it is an underestimate, this level of infestation is sufficiently low to be ofdirect relevance to the needs of the cereal trade.

Changes in headspace of grain samples with mite infestation

The results from the SPME headspace sampling experiment (Experiment 3) show that the presence of even lowconcentrations of A. siro does impart a detectable change in the volatile profile of wheat. The observedassociation of tridecane with infestation by A. siro is in agreement with previous work (Curtis et al, 1981).Interestingly, the volatile 2-hydroxy-6-methylbenzaldehyde has not previously been reported as beingassociated with the headspace of mite-infested wheat, but has been obtained by whole-body solvent extractionof A. siro (Curtis et al, 1981). To investigate this further, an additional experiment was undertaken todetermine the origin of the latter compound. Surprisingly, shaking of a sample containing just 25 A. siro in 25g wheat generated a small but definite chromatographic peak corresponding to 2-hydroxy-6-methylbenzaldehyde. This confirms that the compound, present within the mites themselves, is released whenthe mites are crushed.


The fact that no volatiles were observed to be associated with the presence of the insects, even at the ratherextreme concentrations of insects used, suggests that a method based on grain volatile profiling will not workfor the detection of O. surinamensis.


The results of Experiment 7 suggest that the GASP instrument detection of A. siro in wheat can be improvedimmensely by shaking the sample and heating and analysis at 40oC. However, it should be noted that for 2-hydroxy-6-methylbenzaldehyde to be released by shaking, it is probable that the mites must be intact (i.e. alive)beforehand. Therefore, shaking specifically for the detection of this compound may not be of such a benefit ifthe detection method is required to include the determination of dead mites also. On the other hand, however, it

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is potentially a very useful way of discriminating between the presence of live and dead mites (for example, byanalysis the grain sample both before and after shaking).

The presence of levels of tridecane as high as 2 ppm in the headspace from infested samples to whichthe GASP instrument sensors are exposed is very encouraging. This is especially so when considering that thevolatiles from the wheat itself occur at only similar or lower concentrations, such that tridecane is a, if not the,major constituent of the headspace of the mite-infested wheat. The 2 ppm tridecane was generated by aninfestation level of around only 2,000 mites/kg. Hence a device which could reliably detect this concentrationof tridecane (and/or the lower concentrations of 2-hydroxy-6-methylbenzaldehyde or citral also likely to bepresent) would have a sensitivity very close to that required by the cereal trade.

Citral (both isomers) is an alarm pheromone known to be released by several species of stored-productmites when disturbed or crushed (Kuwahara et al, 1980). Citral has been detected previously in grain infestedwith mixed populations of A. siro and two other mite species (Tuma et al, 1990).

REFERENCES

Curtis R F, Hobson-Frohock A and Fenwick G R (1981) Volatile compounds from the mite Acarus siro L. infood. Journal of Stored Products Research, 17, 197.

Kuwahara Y, Matsumoto K and Wada Y (1980) Pheromone study on acarid mites IV. Citral: composition andfunction as an alarm pheromone and its secretory gland in four species of acarid mites, Jap. J. Sanit. Zool.,31(2), 73-80.

Tuma D, Sinha R N, Muir W E and Abramson D (1990) Odor volatiles associated with mite-infested bin-storedwheat. Journal of Chemical Ecology, 16(3), 713.

Ventura K, Dostal M and Churacek J (1993) Retention characteristics of some volatile compounds on TenaxGR. Journal of Chromatography, 642, 379.

Table 1. Summary of samples prepared

Expt. No.samples

Experiment description Wheat type Contaminant type Sample age whenscanned

1 72 GASP instrument analysis of mite-infested grain over 4-weeks

16 and 19% initial mc; 32g/sample


0,1,3 and 4 weeksfrom adding mites

2 72 GASP instrument analysis of insect-infested grain over 4-weeks



0,1,3 and 4 weeksfrom adding insects

3 12 SPME headspace analysis of mite-infested grain




4 12 SPME headspace analysis of insect-infested grain



1 and 3 weeks fromadding insects

5 36 Modification of the GASP instrumentmethodology (a) + determination ofodour-panel response to mite-infestedwheat (a)

19% initial mc; 25g/sample



6 40 Modification of the GASP instrumentmethodology (b)




7 6 Determination of mite-volatileconcentrations to which the GASPinstrument sensor array is exposed




8 6 Determination of odour-panel responseto mite-infested wheat (b)




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Table 2. Mite numbers in samples at time of analysis, Experiment 1

Average no. A. siro found (/25 g; n=3):Initial wheat mc (%) No. A. siro added (/32g) Week 0 Week 1 Week 2 Week 416 0 0 0 0 016 16 3 4.7 5.7 1416 32 5 10 8.7 25.319 0 0 0 0.3 0.319 16 2.3 8.3 5.7 77.319 32 4.3 15 11.7 134.3

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Table 3. Insect numbers in samples at time of analysis, Experiment 2

Average no. O. surinamensis found (/25 g; n=3):Initial wheat mc (%) No. O. surinamensis

added (/32g)Week 0 Week 1 Week 2 Week 4

16 0 0 0 0 016 2 3.3 1.7 1.7 1.716 10 3.7 7 4.7 6.319 0 0 0 0 019 2 1.3 1.7 1.7 1.719 10 7 5 5.3 4

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Table 4. Mite numbers in samples at time of analysing, Experiment 3

Average no. A. siro found (/25 g; n=1):Initial wheat mc (%) No. A. siro added (/32g) Week 1 Week 316 0 0 016 16 - 1816 32 11 4219 0 0 019 16 5 12819 32 13 213

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49

Table 5. Mite numbers in samples at time of analysis, Experiments 5-8 (initial wheat mc=19% for all samples)

Average no. A. siro found (/25 g):Expt. No. A. siro added (/25g) Week 3 Week 4 Week 75 0 0 (n=2) - -

100 115 (n=2) - -6 0 - 0 (n=15) -

100 - 137 (n=15) -7 0 - 0 (n=3) -

100 - 43 (n=3) -8 0 - - 0 (n=2)

100 - - 546 (n=2)

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50

Table 6. Mite-volatile concentrations reaching the GASP instrument sensor array, as determined by Tenax-tubeanalysis, for sample at 40OC with shaking.

Volatile Concentration in sensor exhaust (ppm)tridecane 0.6-22-OH-6-Me-benzaldehyde 0.06-0.3citral (sum of both isomers) 0.03-0.07

30/1/5/130/2/190/10/270/2inj270 33-550 19-Dec-200016:07:4330/1/5/130/2/190/10/270/2inj270 33-550week3,controlgrain,16%,spme

0.000 5.000 10.000 15.000 20.000 25.000 30.000 35.000 40.000 45.000 50.000 55.0000

100

%

0

100

%

0

100

%

142 312 568

388

439

501

804578

592 771

664

1087

944

871 999

11301401

1164

13231253

19051455

18871482 2433

Scan EI+

1.50e5

GASP035

141

137

312 568

387

439

501

804577

771

591

650664

1130

1087

944

902 999

1401

1164

13021253

19051455

1887

1482

Scan EI+

1.50e5

GASP034

142

137

327 568

439

501

799577

664 678

804

11301087

944

871 1000

14011164

1294

14551905

1482 2434 3132

Scan EI+

1.50e5

GASP033 (a)

(b)

(c)

scan no.1887=tridecane


Figure 1. Example chromatograms from SPME headspace analysis of control/mite-infested grain (Experiment3) at 3 weeks from adding mites, 16% initial mc wheat; (a)=control wheat (0 added mites), (b)=16 added mitesper 32 g sample, (c)=32 added mites per 32 g sample.

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51


30.000 30.250 30.500 30.750 31.000 31.250 31.500 31.750 32.000 32.250 32.500 32.750 33.000 33.250 33.500 33.750 34.000 34.250 34.500 34.750 35.0000

100

%

0

100

%

0

100

%

1905

1887

1806 1839 187419821966

Scan EI+

1.02e5

GASP035

1905

1887

1799 19811965 1993

Scan EI+

1.02e5

GASP034

1905

180719811965

Scan EI+

1.02e5

GASP033 (a)

(b)

(c)




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0.000 5.000 10.000 15.000 20.000 25.000 30.000 35.000 40.000 45.000 50.000 55.0000

100

%

0

100

%

0

100

%

142 468

502

798

672

804

1130944

901

1113

1087

966

1887

14551164 1401

13221253 1481 19913133

Scan EI+

2.00e5

GASP032

142

137

468

502

798641

671

7031130

944

901

1087

966

1886

1455

11641401

1322 2433 3132

Scan EI+

2.00e5

GASP031

142

139

468

501

798

671

702

803 1131943

901

1087

965

999

19021455

14001164

1322

2431

3164

Scan EI+

2.00e5

GASP030

(a)

(b)

(c)


scan no.1887=tridecanescan no.1991=2-OH-6-Me-benzaldehyde

Figure 3. Example chromatograms from SPME headspace analysis of control/mite-infested grain (Experiment3) at 3 weeks from adding mites, 19% initial mc wheat; (a)=control wheat (0 added mites), (b)=16 added mitesper 32 g sample, (c)=32 added mites per 32 g sample.

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30.000 30.250 30.500 30.750 31.000 31.250 31.500 31.750 32.000 32.250 32.500 32.750 33.000 33.250 33.500 33.750 34.000 34.250 34.500 34.750 35.0000

100

%

0

100

%

0

100

%

18871905

199119811966

Scan EI+

1.60e5

GASP032

18861904

199219811964

Scan EI+

1.60e5

GASP031

1804 19801964

Scan EI+

1.60e5

GASP030

scan no. 1886=tridecanescan no. 1992=2-OH-6-Me-benzaldehyde

(a)

(b)

(c)scan no. 1887=tridecanescan no. 1991=2-OH-6-Me-benzaldehyde


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30/1/5/130/2/190/10/270/2inj270 33-550 19-Dec-200018:46:3430/1/5/130/2/190/10/270/2inj270 33-550week3,grain+32mites,16%,spme

0.000 1.000 2.000 3.000 4.000 5.000 6.000 7.000 8.000 9.000 10.000 11.000 12.000 13.000 14.000 15.000 16.000 17.000 18.0000

100

%

0

100

%

284

199

142

145

233

468

312

387327

349 437

567

798

577

591640

784

803

943

Scan EI+

3.00e6

GASP030

280

142

233

312

297

327

568

479388

804799

786

Scan EI+

3.00e6

GASP035

(a)

(b)

scan no.199=acetaldehydescan no.284=ethanolscan no.468=ethyl acetatescan no.640=acetic acid

Figure 5. Example chromatograms from SPME headspace analysis of control/mite-infested grain (Experiment3) at 3 weeks from adding mites: differences in chromatographic profile with initial mc of wheat (a)=controlwheat (16% initial mc), (b)=control wheat (19% initial mc)

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0.000 2.500 5.000 7.500 10.000 12.500 15.000 17.500 20.000 22.500 25.000 27.500 30.000 32.500 35.000 37.500 40.000 42.500 45.000 47.500 50.000rt0

100

%

0

100

%

0

100

%

204

1861948

279

212

641

542436 7807452057 2203

Scan EI+ TIC

3.50e7Scan

GASP050

203

185

281

2204622

Scan EI+ TIC

3.50e7Scan

GASP049

203

185

151

280

2203650

Scan EI+ TIC

3.50e7Scan

GASP048 (a)

(b)

(c)scan no.1948=tridecanescan no.2057=2-OH-6-Me-benzaldehyde(scan no.2203=internal reference)

Figure 6. Example chromatograms from determination of mite-volatile concentrations to which the GASPinstrument sensor array is exposed (Experiment 7); (a)=control wheat (0 added mites), (b)=100 added mites per25 g sample scanned at 30OC without shaking), (c)=100 added mites per 25 g sample scanned at 40OC withshaking (all samples analysed at 4 weeks from adding mites; all samples are 19% initial mc wheat).

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30.000 31.000 32.000 33.000 34.000 35.000 36.000 37.000 38.000 39.000 40.000 41.000 42.0000

100

%

0

100

%

0

100

%

1906

18571816 1881

1924

2057

1963

20252002

2203

2141

2103 2171

2265

2241

2285

248123512317 2376

Scan EI+

1.00e6

GASP050

2204

1946

190718581817 1883

1925 1964 2025 2172

2266

2286

23522479

Scan EI+

1.00e6

GASP049

2203

19451906

18571816 1881 1924 1963 20242171

2265

2234

2285

23502317 24802375

Scan EI+

1.00e6

GASP048

(a)

(b)

(c) scan no.2141=cis-citralscan no.2241=trans-citral


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30/1/5/270/10 inj280 33-550,462445 15-Nov-200017:59:2930/1/5/270/10 inj280 33-550,46244525gcontrol, spme, 1h sample, 30deg, unshaken

29.500 29.600 29.700 29.800 29.900 30.000 30.100 30.200 30.300 30.400 30.500 30.600 30.700 30.800 30.900 31.000 31.100 31.200 31.300 31.400 31.500rt0

100

%

0

100

%

0

100

%

0

100

%

18091800

17831770 1822 18581836 1849 1871 1879

Scan EI+ TIC

2.80e5Scan

GASP003

18091800

1782 18581835 1849 1870 1879

Scan EI+ TIC

2.80e5Scan

GASP002

18111801

17841771 18591837 1842 1851 1872 1881

Scan EI+ TIC

2.80e5Scan

GASP005

18101800

1770 1782 18581841 1850 18801871

Scan EI+ TIC

2.80e5Scan

GASP004

(a)

(b)

(c)

(d) scan no.1822=2-OH-6-Me-benzaldehyde

Figure 8. Investigation of the origin of the mite-volatile 2-hydroxy-6-methylbenzaldehyde; (a)=unshakencontrol wheat (0 added mites), (b) same sample as (a) after shaking, (c)=unshaken mite-infested wheat (25added mites per 25 g sample), (d) same sample as (c) after shaking (all samples analysed within 24 h fromadding mites; all samples are 16% initial mc wheat).

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ANNEX 4 Paper submitted to ISOEN’01ELECTRONIC NOSE DETECTION OF INVERTEBRATE CONTAMINANTS IN GRAIN

K.C. Persaud, P.D. Wareham, R.N. Hobson†, R.W. Sneath†, N. Magan‡, J. Chambers* and C. Ridgway*.

DIAS, UMIST, PO BOX 88, Manchester, M60 1QD, UK.†Silsoe Research Institute, Wrest Park, Silsoe, Bedford, MK45 4HS, UK.

‡Biotechnology Centre, Cranfield University, Silsoe, Bedford, MK45 4DT, UK.*Central Science Laboratory, Sand Hutton, York, YO41 1LZ, UK.

ABSTRACT

Invertebrate infestation of bulk storage grain can initiate spoilage processes detrimental to post-harvest quality. An analytical device capable of effective early detection of such infestationwould therefore prove invaluable to the grain industry. Results from the application ofelectronic nose technology to detection of invertebrate contaminants in grain are presented.Using a metal oxide semiconductor sensor array, detection of mite infestation in wheat grain wasclearly visible at run-time, with 90% to 95% classification accuracy achieved with laboratorytest samples.

INTRODUCTION

Invertebrate infestation of bulk-storage grain is often linked to proliferation of fungal infection causinglarge-scale spoilage, with invasion providing a transport mechanism for mould spores throughout the bulksample. Additionally, invertebrate infestation reduces the nutrient value of grain and leads to deposition ofallergenic components. A dedicated analytical instrument, based on electronic nose technology, has previouslybeen shown to be effective for early detection of fungal infection in bulk grain samples (1). Extension of thisinstrument to produce an early warning system for grain contamination from invertebrates would provide aninvaluable tool for effective management of post-harvest grain quality.

EXPERIMENTAL

The existing Grain Automated Sampling Prototype (GASP) instrument has been detailed previously (1).The system uses organic conducting polymer (OCP) sensor technology coupled to robust sample pre-conditioning and headspace sampling protocols. For the purposes of invertebrate detection, the system wasextended by integration of an array of metal oxide semiconductor (MOS) sensors for increased sensitivity tomarker volatiles. The sensor array configuration is shown generally by figure 1.

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Figure 1. Integration of MOS sensor array in existing GASP instrument.

The MOS sensor array comprises commercially available sensors configured in a header assembly, drivenby a custom heater control and data acquisition interface (2). The integrated measurement system wasevaluated using control and mite-infested wheat grain, with infestation levels representative of normal tradedetection and action thresholds.

RESULTS & DISCUSSION

Results from the MOS sensor array are presented here. Typical sensor response data corresponding tocontrol and mite-infested grain samples are shown in figure 2. The general profiles reflect the GASPmeasurement protocol (baseline measurement, followed by sample response measurement, followed by a seriesof wash cycles).

Figure 2. Typical MOS sensor array output obtained for (a) control and (b) infested grain samples.

OCP Sensor Array MOS Sensor Array

Sample Inlet

Sample Exhaust

Fungal Contamination Detection

Invertebrate Contamination

Detection

(32 Sensors) (8 Sensors)

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(b) Mite-infested Grain Response

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Projecttitle


MAFFproject code

AR0601

60

Direct comparison of the profiles suggests that an increased response rate (relative to other sensors) of asingle sensor (sensor 4) is indicative of mite infestation. This is further illustrated by figure 3.

Figure 3. Comparison of response rate of sensor 1 and sensor 4 for mite-infested grain profile shown in figure2b.

To evaluate this correlation, normalised sensor response was analysed by averaging over a 10 second period (asindicated in figure 3). Figure 4 details the analysis results for a set of 10 control and 10 mite-infested grainsamples.

Figure 4. Discrimination between control and mite-infested sample groups is visible when normalisedresponses of sensor 1 and sensor 4 are compared.

All samples comprising the control group are correctly discriminated (S1 response > S4 response). Themajority of mite-infested samples are also correctly discriminated (S4 response > S2 response), with theexception of two samples, with incorrect and borderline responses respectively.

Comparison of Normalised Sensor Response (S1 & S4) for Control and Mite-infested Grain Samples (40

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Sensor Response Rate Comparison

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Projecttitle


MAFFproject code

AR0601

61

Figure 5 details principal component analysis (PCA), applied to normalised responses of all sensors, for thesample groups shown in figure 4 and butanol standards.

Figure 5. PCA of normalised sensor responses (all sensors) for sample groups shown in figure 4.

Figure 5 suggests some cluster separation according to the defined sample groups, however slight overlap ofinfested and control groups produces a margin of uncertainty for classification, as previously indicated byfigure 4.

Anecdotal evidence surrounding human detection of mite infestation has suggested that physically rubbinginfested grain yields a distinctive odour. To investigate a possible effect, control and infested samples weresubjected to controlled shaking prior to measurement. Figures 6 and 7 detail repeat analysis for shakensamples.

Figure 6. Discrimination within the infested sample group is improved subsequent to sample shaking.

Comparison of Normalised Sensor Response (S1 & S4) for Unshaken and Shaken Mite-infested Grain Samples (40

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PCA (All Sensors) for Control and Mite-infested Grain Samples(40

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Projecttitle


MAFFproject code

AR0601

62

The effect of sample shaking has clearly yielded discrimination improvement within the infested samplegroup (figure 6). The previously incorrect and borderline classifications have been resolved, with a markedimprovement in sensor response separation visible over all samples. This is also reflected by PCA, showingclear cluster separation according to control and mite-infested sample groups (figure 7).

Figure 7. PCA analysis of control and mite-infested grain samples shaken prior to measurement.

CONCLUSION

Use of a MOS array within the GASP system for detection of mite contamination in grain samples hasproved effective for discrimination between laboratory test samples. Detection of infestation was clearlyvisible at run-time, with 90% and 95% classification accuracy directly achievable for unshaken and shakensamples respectively. Such results are encouraging, however, further system improvements and extensivetesting are required for development of a measurement system applicable to trade practice.

ACKNOWLEDGEMENTSThe authors would like to acknowledge the financial support provided by the Ministry of Agriculture, Fisheriesand Food (MAFF).

REFERENCES1. P. Evans, K.C. Persaud, A.S. McNeish, R.W. Sneath, R.N. Hobson and N. Magan, in Electronic Noses andOlfaction 2000, J.W. Gardner and K.C. Persaud, Editors, 211-216

2. P.D. Wareham, H.Chueh, K.C. Persaud and J.V. Hatfield in Electronic Noses and Olfaction 2000, J.W.Gardner and K.C. Persaud, Editors, 197-200

KEYWORDS: Electronic nose, grain, mite, metal oxide semiconductor, sensor array.

PCA (All Sensors) for Control and Mite-infested Grain Samples(40

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Projecttitle


MAFFproject code

AR0601

63

ANNEX 5Poster submitted to ISOEN’01

Comparison of Normalised Sensor Response (S1 & S4) for Unshaken and Shaken Mite Infested Grain Samples (40 oC)

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Comparison of Normalised Sensor Response (S1 & S4) for Control and Mite Infested Grain Samples (40 oC, Unshaken)

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A i m .The aim of this project is to develop an electronicnose for detection of invertebrate contaminationin bulk grain. Invertebrate infestation of bulk-storagegrain is often l inked to proliferation of fungal infectioncausing large-scale spoi lage, with invasion acting asa transport mechanism for mould spores throughoutthe bulk sample. Additionally, invertebrate infestationreduces the nutrient value of grain and leads todeposit ion of al lergenic components. A dedicatedanalyt ical instrument, based on electronic nosetechnology, has previously been shown to beeffective for early detection of fungal infection in bulkgrain samples [1]. Extension of this instrument toproduce an early warning system for graincontaminat ion from invertebrates would provide aninvaluable tool for effective management of post-harvest grain qual i ty.

R eferences.

[1] P. Evans, K.C. Persaud, A.S. McNeish, R.W. Sneath, R.N.Hobson and N. Magan in Electronic Noses and Olfact ion 2000,Eds. J.W. Gardner and K.C Persaud, IOP Pub. 211-216.[2] P.D. Wareham, H. Chueh, K.C. Persaud and J.V. Hatf ie ld inElectronic Noses and Olfaction 2000, Eds. J.W. Gardner and K.CPersaud, IOP Pub. 197-200.

E lectronic N ose D etection of InvertebrateC ontaminants in G rain.

K.C. Persaud, P.D. Wareham , R.N. Hobson† , R.W. Sneath †, N. Magan ‡ , J. Chambers * , and C.Ridgway* .

Department of Instrumentat ion & Analyt ical Science UMIST, PO BOX 88, Manchester, M60 1QD, UK. †Si lsoe ResearchInsti tute, Wrest Park,

Si lsoe, Bedford, MK45 4HS, UK. ‡Biotechnology Centre, Cranf ield Universi ty, Si lsoe, Bedford, MK45 4DT, UK.*Central Science Laboratory, Sand Hutton, York, YO41 1LZ, UK.

R esults & D iscussion.

The exist ing Grain Automated Sampling Prototype(GASP) instrument has been detai led previously [1].The system uses organic conduct ing polymer (OCP)sensor technology coupled to robust sample pre-condit ioning and headspace sampling protocols. Forthe purposes of invertebrate detection, the systemwas extended by integrat ion of metal oxidesemiconductor (MOS) sensor technology forincreased sensitivity to likely marker volatiles (figure1 ) .

Figure 1.Integration ofMOS sensortechnology inex is t ing GASPinstrument.

A cknowledgements.

The authors would l ike to acknowledge the financialsupport provided by the Ministry of Agriculture,Fisher ies and Food.

To evaluate this correlation, normalised sensorresponse was analysed over a 10-point average(figure 3). Figure 4 details the analysis results for aset of 10 control and 10 mite-infested grain samples.

C onclusion.

Use of a MOS array within the GASP system fordetect ion of mite contamination in grain samples hasproved effective for discrimination between laboratorytest samples. Detection of infestation was clearlyvisible at run-t ime, with 90% and 95% classif icationaccuracy directly achievable for unshaken andshaken samples respect ively. Such results areencouraging, however, further system improvementsand extensive testing are required for development ofa measurement system appl icable to trade pract ice.

Figure 2. Typical MOS sensor array output obtained forcontrol and infested grain samples.

Figure 4 . Discriminationbetween control andmite-infested samplegroups is visible whennormal ised responses ofsensor 1 and sensor 4are compared.

Figure 6 . Repeat analysis for control and mite infested grainsamples shaken pr ior to measurement.

Typical sensor response data corresponding tocontrol and mite- infested grain samples are shown infigure 2. The general profi les reflect the GASPmeasurement protocol (basel ine measurement,fol lowed by sample response measurement, fol lowedby a ser ies of wash cycles). Direct comparison ofprof i les suggest that an increased response rate(relative to other sensors) of a single sensor (sensor4, l ight blue) could be indicative of mite infestation(figure 3).

Figure 5. P C A o fnormal ised sensorresponses (al l sensors)for sample groupsshown in f igure 4.

The MOS sensor array comprises commercial lyavai lable sensors in a header assembly, driven by acustom heater control and data acquisit ion interface[2]. The integrated system was evaluated usingcontrol and mite-infested wheat grain, at levelsrepresentative of normal trade detection and actionthresholds. The results for the MOS sensor array arepresented here.

The effect of sample shaking has clearly yieldeddiscrimination improvement within the infested samplegroup (f igure 6a). The previously incorrect andborderl ine classif ications have been resolved, with amarked improvement in separation visible over al lsamples. This is also reflected by PCA, showingclear separation according to control and mite-infested sample groups ( f igure 6b).

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(a) Control-grainresponse.

(b) Mi te-infestedgrainresponse.

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Figure 3. Comparison ofresponse rate of sensor4 to sensor 1 for mite-infested grain profileshown in f igure 2b.

All samples comprising the control group are correctlydiscriminated (S1 response > S4 response). Themajority of mite-infested samples are also correctlydiscr iminated (S4 response > S2 response), with theexception of two samples, with incorrect andborderline responses respectively. Figure 5 detailsprincipal component analysis (PCA), appl ied tonormalised responses of all sensors, for the samplegroups shown in f igure 4.

Figure 5 suggests some separation according to thedef ined sample groups, however sl ight overlap ofinfested and control groups produces a margin ofuncertainty for classif ication, as previously indicatedby f igure 4 .

Anecdotal evidence surrounding human detection ofmite infestation has suggested that crushing infestedgrain yields a dist inct ive odour. To invest igate apossible effect, control and infested samples weresubjected to control led shaking prior to measurement.Figure 6 details repeat analysis for shaken samples.

(a) Discr iminat ionwithin the infestedsample group isimproved subsequentto sample shaking.

(b) Discr iminat ionimprovement is alsoreflected by PCA ofnormal ised sensorresponses (allsensors) withcomplete samplegroup separat ion.

OCP Sensor Array MOS Sensor Array

Sample Inlet Sample Exhaust

Fungal Contamination Detection

Invertebrate Contamination

Detection

(32 Sensors) (8 Sensors)

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Projecttitle


MAFFproject code

AR0601

CSG 15 (1/00) 64

ministry of agriculture fisheries and food csg 15...

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