J Sci Food Agric 1998, 78, 343È348

Use of Digital Aroma Technology and SPMEto Compare Volatile CompoundsGC-MS

Produced by Bacteria Isolated from ProcessedPoultry*

Judy W Arnold¤ and Samuel D Senter

United States Department of Agriculture, Richard B Russell Agricultural Research Center, PO Box 5677,Athens, Georgia 30604, USA

(Received 2 March 1998 ; accepted 10 March 1998)

Abstract : Digital aroma technology, solid-phase micro-extraction (SPME) andgas chromatographic mass spectral (GC-MS) analysis of the headspace volatileorganic compounds were used to compare bacterial species important for foodsafety and common to bioÐlms in the poultry processing environment. Theinstrument for digital aroma technology, called the electronic nose, measuredchanges in resistance of polymer sensors caused by volatile gases from the head-space of samples. Graphical output by the Sammon mapping technique produc-ed patterns of di†erences or similarities among the samples. ArtiÐcial neuralnetwork software was used to model groups of samples and classify subsequentunknowns. Compounds isolated from the headspace of sealed cultures usingpolydimethylsiloxane SPME Ðbres and identiÐed by GC-MS analyses were pre-dominantly alcohols and indole. These qualitative proÐles were repetitive for spe-ciÐc organisms in relation to purity and repeatability of the cultures, di†ered byspecies and were used as objective standards to compare the graphical outputs ofthe electronic nose. 1998 Society of Chemical Industry.(

J Sci Food Agric 78, 343È348 (1998)

Key words : bioÐlms ; poultry ; bacteria ; aroma; electronic nose ; SPME; GC-MS

INTRODUCTION

Digital aroma technology, or the electronic nose, hasbeen developed in recent years as a quality assurancetool to detect odours in food and Ñavour industries.Intended to mimic biological olfactory functions ofhuman sensory panels, it functions by rapidly adsorbingand desorbing volatiles at the surfaces of sensors,causing changes in measured electrical resistance. Whileanalytical techniques, such as gas chromatography(GC), separate headspace gases from samples into peakscorresponding to individual compounds, the electronicnose integrates measurements of the total headspace

* This article is a US Government work, and, as such, is inthe public domain in the United States of America. Referenceto a company name or product does not imply endorsementby the US Department of Agriculture.¤ To whom correspondence should be addressed.

volatile organic compounds (VOCs) as they cross anarray of sensors (Hodgins and Simmonds 1995). Rapidreversibility of the volatile to sensor binding processallows samples to be run in rapid succession. In earlymodels, sensor arrays usually were connected tonumerical modules for statistical analysis, ie semicon-ductor gas sensors responded to the aromas, patternrecognition analysis di†erentiated the resulting datamatrices and cluster analysis was used to classify thesamples (Aishima 1991 ; Newman 1991 ; Persaud 1991).A system for odour classiÐcation that was introducedlater included a sensor array, statistical analysis moduleand an artiÐcial neural network. The network classiÐedand stored the statistical data, then used the informa-tion to match subsequent unknown samples with pre-viously encountered samples (Dodd et al 1991 ; Shurmerand Gardner 1992 ; Davide et al 1994 ; Hines andGardner 1994).

3431998 Society of Chemical Industry. J Sci Food Agric 0022È5142/98/$17.50. Printed in Great Britain(

344 J W Arnold, S D Senter

Historically, qualitative assessment of spoilage poten-tial for foods and the by-products of spoilage has beenmade by human panelists (Dalgaard 1995) who are pre-sented serial dilutions of air samples for olfactory mea-surements (Hobbs et al 1995). Quantitativecharacterisation was then made with model substratesand measurement of speciÐc VOCs by analytical pro-cedures that characterise the aromas or odours. Exam-ples are the isolation and identiÐcation by GC massspectroscopy (GC-MS) of key VOCs that contribute tothe odour of stewed beef (Guth and Grosch 1994) andthe analyses that chemically proÐled the major odourcompounds of pig and chicken livestock wastes (Hobbset al 1995). In the latter study, an electronic nose wasused to discriminate odours through sensor responsepatterns. Pattern recognition by the electronic nose alsohas been used to determine food quality and di†eren-tiate between raw food materials such as meat, grainsand types of cheese (Pisanelli et al 1994 ; Brewer andVega 1995 ; Jonsson et al 1997 ; Muir et al 1997) and topredict storage time and quality of ground beef(Winquist et al 1993). Analysis of vapours produced bymicroorganisms involved in sausage fermentation indi-cated that the method could be used to assess contami-nation of food products (Rossi et al 1995).

The purpose of the present work was to evaluate thespeciÐcity, sensitivity and reproducibility of the elec-tronic nose when used to characterise and proÐle head-space VOCs from bacterial cultures isolated frombroiler carcasses and grown on deÐned media. Thespecies chosen were representative of potential patho-gens commonly found in bioÐlms from the food pro-cessing environment. The inÑuence of parameters forbacterial growth, such as medium, temperature andphase of growth were considered and related to changes

in the concentration of VOCs as determined objectivelyby solid-phase micro-extraction (SPME) GC-MSanalyses.

EXPERIMENTAL

Sample preparation

The source and names of bacterial species used in thisstudy are shown in Table 1. Field isolates were obtainedfrom whole carcases collected from a commercialbroiler processing plant after the New York rinse. Eachcarcass was rinsed with 100 ml phosphate-bu†eredsaline. Aliquots of the rinse were diluted with trypticasesoy broth (TSB) in duplicate tenfold series, 1 ml of eachplated on plate count agar (PCA) and the plates incu-bated for 18 h at 37¡C. Isolates were selected for identi-Ðcation after multiple passages on PCA. For long-termmaintenance, aliquots of bacterial cultures were storedat [30¡C in TSB containing 5% glycerol. To resusci-tate, an aliquot was thawed and 200 ll was added to10 ml TSB, then incubated at 35¡C for 18 h, unlessotherwise stated. Sensitivity tests of the instrumentswere performed on tenfold dilution series of 18-h cul-tures, using TSB, phosphate-bu†ered saline (PBS) orwater as the diluent in separate experiments.

Sample analysis by digital aroma technology

A 5-ml aliquot of the incubated culture was transferredto a 750-ml capacity, single-use, disposable pouch,which was then Ðlled with air that had been Ðlteredthrough indicating Drierite, (WA Hammond Drierite

TABLE 1Bacterial species used in cultures to evaluate head space volatile organic com-

pounds by the electronic nose and gas chromatography mass spectral analysis

Species Source % ConÐdencea Cells ml~1 b

Salmonella enteritidis ATCCc 99 2É91 ] 108Escherichia coli ATCC 99 2É66 ] 108L isteria monocytogenes ATCC 99 1É08 ] 108Klebsiella pneumoniae Field isolated 96 3É66 ] 108Enterobacter cloacae Field isolate 99 4É99 ] 108Pseudomonas aeruginosa Field isolate 99 4É99 ] 108Acinetobacter calcoaceticus Field isolate 99 3É53 ] 108

a Level of conÐdence for identiÐcation of experimental cultures, performed on aVitek instrument (bioMerieux, Inc, Hazelwood, MO, USA).b Samples incubated in trypticase soy broth 18 h at 35¡C prior to testing. Eachconcentration shown was the mean of four experiments.c American Type Culture Collection (ATCC), Rockville, MD, USA. IdentiÐcationof experimental cultures were veriÐed by Vitek.d The method for selecting and maintaining Ðeld isolates is described in theExperimental section.

Comparison of volatile compounds produced by bacteria from poultry 345

Co, Xenia, OH, USA). Pouches were stored in a 35¡Cconditioning cabinet for 5 min for temperature equili-bration and then sampled with the AromaScannerbench-top instrument (Foss Food Technology Corp,Eden Prairie, MN, USA). Temperature and humiditywere monitored during sampling, and the relativehumidity of sample headspace and reference air werecontrolled to 16% to allow consistent headspace gener-ation. Between samples, the vapours from a wash bottlecontaining approximately 20 ml of a 2% butanol solu-tion were sampled for 10 s as a sample line wash. Acontrol of TSB was run as the Ðrst and last sample eachday.

Data analysis for digital aroma technology

The combined responses from the sensors were used bythe AromaScanner software to generate a pattern char-acteristic of the controlled headspace from each sample.The patterns were displayed as line graphs or histo-grams and stored in databases for later comparison.Multiple discriminant analysis reduced the data foreach species into two dimensions viewed in a singleplot. The patterns, or proÐle data, were analysed bycluster analysis (Sammon mapping), and then plotted asa map. The axis of each map was in units of EuclideanDistance (ED) (Persaud 1992), which is a measure ofdi†erences between samples : the greater the ED, thegreater the di†erence. An ArtiÐcial Neural Network(ANN) classiÐed and retained the data for comparisonwith subsequent unknowns. Succeeding samples wereclassiÐed by reference to the database of previouslyencountered patterns, and correlation was displayed asa percentage conÐdence level.

SPME extraction, GC analysis of headspace volatiles

For each species evaluated, two culture tubes(150] 16 mm), each containing 10 ml TSB, were inocu-lated with 200 ll of the speciÐc culture and incubatedfor 18 h at 35¡C. Two control tubes of TSB were pre-pared and incubated similarly. After incubation, ali-quants from one tube were added to the second to bringthe depth of the culture to 110 mm, which resulted inconsistent headspace volume among samples. Thoroughmixing was succeeded by capping with a 20-mm siliconesepta, which was covered with ParaÐlm to assure ade-quate sealing. The tubes were then placed in a 37¡Cwater-bath for 30 min before sampling for headspaceVOC equilibration.

A 100-lm polydimethylsiloxane (PDMS), manuallyoperated SPME Ðbre and holder system (Supelco Inc,Belfonte, PA, USA) was used for headspace sampling.These Ðbres are a recent innovation that have been usedfor the extraction of VOC from the headspace of suchdiverse biological materials as Ñavour volatiles from

fruit beverages (Penton 1996), forensic and pharma-ceutical samples (Mindrup 1995), volatiles from soiland water samples (Schumacher 1997), organic com-pounds from environmental samples (Zhang and Paw-liszyn 1993) and the volatile compounds from humanbreath (Grote and Pawliszyn 1997). The PDMS Ðbrewas inserted through the spectrum of the sample tubeand allowed to equilibrate with the headspace volatilesfor 30 min. The Ðbre was then retracted into the barrelof the syringe and immediately inserted into the injectorof the GC for 1 min desorption of the entrapped VOCs.

Chromatographic Ñame ionization detection (GC-FID) analyses of the VOCs were performed with aPerkin-Elmer Autosystem XL gas chromatograph(Perkin-Elmer, Norwalk, CT, USA) that was equippedwith a 60 m ] 0É25 mm (id), 0É25-lm Ðlm thickness andDB-1 column (J & W ScientiÐc, Folson, CA, USA).Helium was the carrier gas at 30 psig, which resulted ina linear velocity of 30 cm s~1 with the column at 40¡C.Chromatograph operating conditions were as follows :initial oven temperature 40¡C with no hold time, thenprogrammed to 275¡C at 8¡C min~1 and held for5 min ; injector temperature 250¡C; detector tem-perature 310¡C. The injector was held in the splitlessmode for 1 min after insertion of the Ðbre ; the purgewas then automatically engaged.

GC-MS analyses

Qualitative analysis of the extracted volatiles was per-formed with a Finnigan MAT GCQ mass spectrometer(Finnegan, San Jose, CA, USA) operated in theelectron-ionisation (EI) mode. Electron energy was70 eV, multiplier voltage 1100 V, source temperature200¡C and transfer line 240¡C. Spectral data wasacquired over a mass range of 28È200 amu at a scanrate of 0É6 s scan~1. Chromatographic conditions forthe interfaced GC were as follows : column60 m ] 0É25 cm (id), 0É25-lm Ðlm thickness DB-1 (J &W ScientiÐc) using He carrier gas at 28 cm s~1 linearvelocity at 40¡C; oven temperature initially 40¡C with1 min hold, then programmed to 275¡C at 8¡C min~1and held for 5 min ; injector temperature 225¡C. TheSPME absorption and desorption time was the same asin the preceding chromatographic conditions, with theinjector (0É75-mm liner) operated in the splitless modefor 1 min, then in the purge mode for the remainder ofthe run.

RESULTS

Detection

Analysis of the VOCs in the headspace of samplestested by digital aroma technology detected the pres-ence of each of the bacterial species tested : Salmonella

346 J W Arnold, S D Senter

Fig 1. Mapping of the response patterns generated by theelectronic nose for bacterial species. Samples were incubatedin TSB, 18 h, 35¡C prior to testing. Each point represents thedata taken from separate experiments performed on nine dif-ferent days : Salmonella enteritidis ; Escherichia coli ;(=) (…)

Enterobacter cloacae ; Pseudomonas aeruginosa. For(>) (@)each sample, the Sammon mapping technique reduced theresponses from the 32 sensors to a single data point and com-

pared the points by non-linear dimensional analysis.

Fig 2. Comparative gas chromatograms of volatile organiccompounds (VOCs) from the headspace of Escherichia coliand Pseudomonas aeruginosa cultures using polydimethylsilox-ane (PDMS), solid-phase micro-extraction (SPME) Ðbres(Supelco Inc, Bellfonte, PA, USA) for extraction and concen-tration. B refers to the VOCs isolated from the culture broth,and the numerals refer to the identiÐed bacteria VOCs listed

in Table 2.

enteritidis, Escherichia coli, L isteria monocytogenes,Klebsiella pneumoniae, Enterobacter cloacae, Pseudo-monas aeruginosa and Acinetobacter calcoaceticus(Table 1). After data was collected for multiple samplesof each species tested, the electronic nose was able todistinguish each of the cultured species from each otherin subsequent analysis. Responses to the di†erentsamples and mapped data are shown in Fig 1. Di†er-ences or similarities between the bacterial species areshown by the relative spatial separation of the datapoint clusters.

Stability

Sample response patterns were reproducible over time.A database, generated for each species, contained pat-terns from samples tested on each of nine di†erent days(Fig 1). The responses to the sensors of each specieswere stable over the course of the experiment. Multipleclasses or descriptor levels of bacterial odour proÐleswere processed and retained by the ANN for compari-son of new samples with previously encounteredsamples.

Sensitivity

The sensitivity and discriminating ability of the ANNincreased as more data points were collected for thestandard samples. Sensitivity of the system was furthertested by a dilution experiment in which the bacterialcultures were diluted in a tenfold series of TSB, PBSand water. When data from the samples shown in Fig 1were used to train the ANN and diluted samples werecompared, recognition was achieved.

Chromatographic analyses

Gas chromatograms of the VOCs isolated from theheadspace of E coli and P aeruginosa are presented inFig 2 and represent the diversity in the headspaceVOCs isolated from cultures of the eight speciesexposed to the PDMS Ðbres. Compounds identiÐedfrom the isolates are presented in Table 2 as area per-centage of the chromatograms with threshold level ofthe PE-Nelson Turbochrom-4 integration system(PerkinÈElmer) set at 500 lV s~1. IdentiÐed com-pounds were predominantly alcohols, with ethanolbeing the major constituent in all species except P aeru-ginosa and A calcoaceticus. In these species, componentscharacteristic of the other species were absent except forP aeruginosa, which produced only 3-methyl-1-butanoland phenethyl alcohol in measurable quantities. Speciesproducing the greater number of compounds, predomi-nantly alcohols, were S enteritidis, E coli, K pneumoniaeand E cloacae. L isteria monocytogenes was distinguished

Comparison of volatile compounds produced by bacteria from poultry 347

TABLE 2Volatile organic compound isolatesa from the headspace of bacterial cultures from processed poultry by

polydimethylsiloxane, solid-phase micro-extraction (comparative areas of the chromatograms)

Peak RT b Compound Bacteria speciesc and percent aread

SE EsC L M KP EnC PA AC

1 3 : 76 Ethanol 47É9 25É7 12É6 63É9 40É82 4 : 20 1-Propanol 2É6 2É7 1É8 0É83 4 : 98 3-Methyl butanal 4É64 6 : 07 3-Methyl-1-butanol 3É0 0É5 0É3 4É8 12É9 1É65 12 : 92 Octanol 1É6 2É6 1É3 1É26 13 : 68 Phenethyl alcohol 1É3 3É27 16 : 89 9-Decene-1-ol 0É6 0É7 0É8 0É78 17 : 10 Decanol 3É6 10É6 0É4 6É3 6É19 17 : 22 Indole 41É2

10 20 : 84 Dodecanol 3É2 1É9 1É7 3É9 5É211 23 : 87 cis-7-Tetradecene-1-ol 2É2 0É6 0É7 2É212 24 : 17 Tetradecanol 2É7 0É5 2É4 2É6

a IdentiÐcation by comparison of mass spectra and chromatographic retention times with authenic stan-dards.b Retention time of the individual compounds identiÐed.c SE, Salmonella enteritidis ; EsC, Escherichia coli ; LM, L isteria monocytogenes ; KP, Klebsiella pneumon-iae ; EnC, Enterobacter cloacae ; PA, Pseudomonas aeruginosa ; AC, Acinetobacter calcoaceticus bio ani-tratus.d Percentage area of the chromatogram.

by the production of 3-methyl butanal and E coli by theproduction of indole. Extractable volatiles from theheadspace of TSB were predominantly pyrazine deriv-atives and benzaldehyde.

DISCUSSION

Because traditional human evaluation of odour is verysubjective, digital aroma technology should lend itselfwell to the development of a system based on objectivemeasurements. The use of human odour panels toevaluate and control the quality of raw materials forspoilage, or bacterial contamination of Ðnished pro-ducts, is labour-intensive, time-consuming, expensive,prone to errors and can be hazardous to human health.Objective odour measurement for improving qualitycontrol from raw material to Ðnished product couldprovide real-time detection of process problems. Earlydetection and measurement of hazardous or contami-nated samples would have cost-saving beneÐts for rawmaterial quality control, new product development andÐnal product standardisation. Digital aroma technologycan alleviate these concerns.

Results showed that digital aroma technology wassufficiently sensitive to measure the volatiles in theheadspace of bacterial samples, and the method wasreproducible within the limits of the analyses. Changesin sensor resistance generated data to cluster and groupsamples. The array of sensors had di†ering degrees of

selectivity towards di†erent volatile compounds, as evi-denced by the GC-MS analyses where substantial diver-sity was observed by species. Samples were processedrapidly, and data was output in graphical form andstored to later compare and classify succeeding samples.The sensitivity and discriminating ability of the instru-ment was improved as more data points were collectedand further processed. Neural network algorithms per-formed real-time recognition ; conÐdence levels werereported for subsequent data validation.

It was not the intention of this work to discover newVOCs produced by known species of bacteria in a foodprocessing environment, but to detect and proÐle head-space VOCs by a new analytical technique (the elec-tronic nose) and conÐrm observed di†erences by a newisolation technique (SPME) and standard analyticalprocedures (GC-MS). Selectivity of the PDMS Ðbresused was a limiting factor in the extraction of thesevolatiles for GC-MS analyses ; however, the availabilityof di†erent Ðbres has been improved since the com-pletion of this study and may o†er an improvedapproach to this type of analysis. These experimentssuggest that digital aroma technology may have poten-tial for studying the VOCs of bacteria. However, thearoma technology system needs further development toimprove reproducibility and sensitivity and to reducethe time required for the experimental work and datahandling.

The preceding results acknowledge di†erences in theheadspace VOCs that constitute the complex odours

348 J W Arnold, S D Senter

generated by bacteria and shows that a sensory studyon the basis of digital aroma technology, static head-space analysis with SPME GC-MS analysis is a prom-ising approach to detect the key compounds andbacterial species implicated in food spoilage and isimportant for food safety.

ACKNOWLEDGEMENTS

The authors wish to thank T Breedlove, P Mason andK Tate for technical assistance.

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