Trends in Food Science & Technology 19 (2008) 383e389

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* Corresponding author.

0924-2244/$ - see front matter � 2008 Elsevier Ltd. All rights reserved.doi:10.1016/j.tifs.2008.01.007

The significance of

low impact odorants

in global odour

perception

Danielle Ryan*, Paul D.

Prenzler, Anthony J. Saliba and

Geoffrey R. ScollaryNational Wine and Grape Industry Centre, School of

Wine and Food Sciences, Charles Sturt University,

Locked Bag 588, Wagga Wagga, New South Wales

2678, Australia (Tel.: D61 2 69334382; fax: D61 2

69332737; e-mail: dryan@csu.edu.au)

Low impact odorants are generally considered unimportant in

aroma perception; however, recent evidence establishes the

significance of these compounds in global odour perception.

We hypothesise that the perception of high impact odorants

is modified by sub- and peri-threshold odorants, even those

with low odour activity. In order to fully evaluate the impor-

tance of low impact odorants, and better understand the

complexities of global odour perception, a new multidisciplin-

ary approach is needed incorporating chemical, sensory and

neurological model studies.

IntroductionGeneral approaches of identifying ‘important’ or high

impact odorants are based on odour activity values(OAV). Gas chromatography-olfactory (GC-O) may facili-tate the process of determining OAVs, and elucidation ofthe most odour-active compounds are generally achievedusing GC-O aroma extract dilution analysis (AEDA), whichis a dilution to threshold approach that measures odourpotency via the maximum dilution of an extract that anodour is perceived in (Delahunty, Eyres, & Dufour,2006). Odorants with low OAVs, or low impact odorants(ie typical values� 1) are generally considered to be

unimportant to global sensory perception. However, recon-stituted model mixtures are often lacking when comparedto the original odorant mixtures. This may be partlyattributed to the fact that the GC-O technique considersthe impact of isolated aroma compounds in the extract,‘‘overlooking their joint effects in the original food product.Consequently, GC-O should be considered an essential butpartial procedure’’ (Lorrain et al., 2006). In light of theseaforementioned limitations, combined with recent evi-dence, we hypothesise that compounds with low OAVshave the potential to play a critical role in the global odourcharacterisation of a sample. Further, we present evidencethat compounds with relatively low OAVs may act assignificant impact odorants (Escudero et al., 2004). Whatis needed is a new multidisciplinary approach in tacklingglobal odour characterisation. In this review, wine is usedas the subject model to support our hypothesis, althoughother foods and beverages are discussed where relevant.

Reconstructed mixtures do not alwaysequate to the original mixture

Most literature regarding the aromatic profile of variouswines as determined by GC-O have shown that the vastmajority of wine volatiles have little to no odour activity,and that specific aromatic profiles may be explained by rel-atively few odorant compounds (Escudero, Campo, Farina,Cacho, & Ferreira, 2007). Atanasova, Thomas-Danguin,Chabanet et al. (2005) have hypothesized that ‘‘huge’’ aro-matic bouquet differences in wines may in fact arise due todifferences in concentration levels and proportions of thesame odorants in wine mixtures. Nevertheless, perceptualinteractions between volatile compounds combined ina mixture are difficult to predict both in wine and syntheticmodels (Atanasova, Thomas-Danguin, Chabanet et al.,2005), and reconstituted model mixtures of odorants donot always equate to the original mixture. In fact, Bult,Schifferstein, Roozen, Voragen, and Kroeze (2001) have in-troduced the term ‘reconstruction discrepancy’ to describethe phenomenon that the perceived smell of GC-O recon-structed mixtures differ from that of the original aroma ofthe whole sample, despite the fact that concentrations ofthe key odorants are identical in both mixtures. It is feasiblethen that reconstruction discrepancy could arise from sub-threshold components which cannot be detected at theolfactory sniff port.

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Omission tests are commonly used to establish thesensory importance of a component or family of componentsin a reconstituted mixture (Escudero et al., 2004). Comple-mentary to this, addition tests can be performed onsynthetic bases or real matrices (Escudero et al., 2004).Reiners and Grosch iterate that the only way to verify ifodorants identified in a sample contribute to flavour is viareconstitution tests (Reiners & Grosch, 1998). As such,they used reconstitution tests in addition to omission teststo determine potent odorants of Italian (I), Spanish (S) andMoroccan (M) extra virgin olive oils. Odorants weredetermined by AEDA using GC-O. Potent odorants (definedas those showing a flavour dilution factor� 8 in at least oneof the three oil samples, and an OAV> 5 based on eithernasal or retronasal odour values) were then dissolved in a re-fined plant oil in their corresponding concentrations found inthe three olive oils to represent the model oils I0, S0 and M0.Additional model oils I1eI9, S1eS5 and M1eM9 wereprepared as per I0, S0 and M0 with the omission of one orseveral compounds with the same odour quality. Compari-son of the original oils with I0, S0 and M0 showed M0 tobe most similar to its respective original oil based onretronasal evaluation scoring 2.8 (� 0.4) on a similarity scaleof 0 (no similarity) to 3 (identical with the original), with I0and S0 scoring 2.5 (� 0.3) and 2.5 (� 0.4), respectively.Such discrepancies may be attributed to the presence oflow impact odorants since only odorants with OAVs> 5were considered significant to oil flavour and aroma, andincluded in the model mixtures.

Odorants in a mixture should interact in a predictableand straightforward way (Olsson)

According to Olsson, the perceived intensity and qualityof a mixture can be predicted from the perceived intensityof its components presented separately (Olsson, 1994), andthat odour interaction reduces to a set of simple rules thatare consistent across levels of intensity and combinationsof odorants (Olsson, 1998). Such research suggests that ifboth odorants in a mixture have approximately equalunmixed intensities, both will be perceived in the mixture,and the quality of the mixture should be intermediatebetween the qualities of its unmixed components.

Evidence contrary to the predictive model existsEven in simple binary mixtures, qualitative and

quantitative odour perception is not straightforward, andevidence contrary to Olsson’s predictive modelexists (Atanasova, Thomas-Danguin, Chabanet et al.,2005; Atanasova, Thomas-Danguin, Langlois et al.,2005; Atanasova, Thomas-Danguin, Langlois, Nicklaus,& Etievant, 2004; Cain, Schiet, Olsson, & Dewijk,1995). Atanasova, Thomas-Danguin, Chabanet et al.(2005) investigated the qualitative perceptual interactionof three binary mixtures of wine odorants including iso-amyl acetate (fruity note)/whisky lactone (woody note);ethyl butyrate (fruity note)/whisky lactone (woody

note); ethyl butyrate (fruity note)/guaiacol (woody note).Results showed the qualitative dominance of the woodynote in the three fruityewoody binary mixtures when theperceived intensities of each unmixed compound wereequal. The authors developed their own linear logisticmodel to account for this phenomenon, since the Olssonpredictive model, by its very construction, could not ac-count for the woody quality dominance of iso-intense com-ponents. Quantitative results for the same three binarymixtures at supra-threshold levels showed quantitativeperceptual interactions were non-level independent, non-symmetrical, and reached the compromise level of hypo-addition (Atanasova et al., 2004). For the latter, compromisewas generally reached when mixtures contained a high pro-portion of woody odorant; however, this was not replicatedin mixtures with high proportions of fruity odorant. Assuch, woody notes had a higher hypo-additive effect suchthat the overall perceived intensity was less than the sumof the mixture components.

Modelling odour interactionIt is clear that strong evidence exists to refute Olsson’s

predictive model and other models that claim odour interac-tions can be reduced to a set of simple rules. Such modelsfail to account for odorant interactions. One model thatdoes attempt to account for interactions is the vector model(Berglund, Bergland, & Lindvall, 1973). However, thismodel assigns odorant interactions as a consistent summa-tion regardless of the compounds in question. The vectormodel has received little criticism and in fact remains oneof the best predictive models. One of the reasons whyBerglund et al.’s (1973) vector model and models like it(e.g. Patte & Laffort, 1979) have come under little criticismis that they do provide reasonable approximation of odourperception using simple mixtures. Perhaps a more appropri-ate explanation of their apparent lack of scrutinisation isthat these models fail honourably. Cain et al. (1995) pointout that the vector model lacks any theoretical base. It istrue that the model is a mathematical solution not basedon psychophysics for example. The advantage of the vectormodel approach is that there is little penalty when percep-tual changes do not accompany mixture changes, such aswhen a compound is increased in concentration withina solution but where human subjects fail to detect anychange in odour. Such facts are hardly an endorsement ofthese models because it follows that they do not completelyaccount for the opposite of suppression e hyper-additivity.The mathematical elegance of these approaches not with-standing, they offer a crude approximation of a broad rangeof complex mixtures.

The literal meaning of a model takes connotationsdepending on context and the field in which the term isused, but the general understanding of a model is a smallor incomplete replica of the real thing. In an attempt tomodel the real thing, it became popular in Perceptualmodelling research to embrace the underlying Physiology

385D. Ryan et al. / Trends in Food Science & Technology 19 (2008) 383e389

or Psychology, or even the combination of the two. Thisendeavour has clearly been limited by what is knownabout human odour perception, perhaps the least studiedof all human perceptual phenomenon. This is reflectedin the simplicity of Psychological models (e.g. Olsson,1994) that are based on a linear summation of the percep-tion of compounds added to a mixture. Derby, Ache, andKennel (1985) have used electrophysiological techniquesto demonstrate that two different odorants of moderate in-tensity may not sum to produce an intense mixture. Thisphenomenon is known as mixture suppression. Untilnow, the only explanation for mixture suppression hasbeen based on physiology and is best encapsulated bythe type of theory proposed by Laing (Stevens, 1957). La-ing proposed that compounds are differentially absorbedby the olfactory mucus and that this accounts for theirperception in a mixture. There is good psychophysical ev-idence that differential absorption, whatever the media-tion, is an important part of the Psychophysics of odourperception. Where a compound is perceived but to a lesserextent than a linear addition might suggest, saturation isa possible explanation. We ‘know’ that where subjectiveintensity of some stimuli increases in a linear fashion,the actual intensity grows exponentially (originally pro-posed by Stevens (1957)).

What has been discovered about human perception ofodours has largely been focused on intensity perception us-ing simple mixtures. Cain et al. (1995) propose the use ofquality as a metric to augment intensity perception. Thisapproach is limited twofold. Firstly, the assessment of qual-ity is subjective and influenced by many things that haveproven difficult to control. Quality is perceived throughcomparison of stimuli and is implicated with satisfaction(Oliver, 1997), such that different combinations of stimuliand idiosyncratic preferences will produce different results.Secondly, the notion of quality as a measure of odourinteraction within a mixture presupposes that all keycompounds are supra-threshold. That is, quality will onlyexplain interaction effects between compounds where thosecompounds can be perceived. While this is an assumptionwith little or no penalty for simple mixtures with fewcompounds, in complex mixtures such as wine and food,chemical reactions could render a compound sub-threshold.The presumption of perception limitation is in fact sharedwith all models reviewed above, except for the purelymathematical-based vector approach which makes no pre-supposition in terms of underlying theory. What ofcompounds that do not have a strong odour themselves,yet interact to produce an intense odour experience? Theauthors contend that no model currently exists that reliablyand accurately accounts for this phenomenon.

Reports highlight the importance of sub- andperi-threshold in perceived odour

Investigations by Atanasova, Thomas-Danguin, Langloiset al. (2005) using the same combinations (see above) of

binary mixtures showed that sub- and peri-threshold con-centrations of woody compounds modify the perceptionof supra-threshold fruity odour (Atanasova, Thomas-Danguin, Langlois et al., 2005). Such results illustratethat knowledge of the odour threshold of a volatile compo-nent in a food or beverage matrix may not sufficientlyindicate its impact on the whole aroma. Critically, percep-tual interactions of sub- and peri-threshold componentsmust be considered in order to ascertain the total odourintensity and quality of the particular matrix (Atanasova,Thomas-Danguin, Langlois et al., 2005).

The findings of Bult et al. (2001) relating to the impactof sub- and peri-threshold odorants on mixtures of appleodorants were not as clear cut as those of Atanasova,Thomas-Danguin, Langlois et al. (2005). The authorshypothesized that manipulating a mixture of odorants(MIX) by adding sub-threshold components will result ina mixture (MIXþ) that is more easily discriminated fromMIX than the sub-threshold components (BLANKþ) whichcan be discriminated from a blank stimulus (BLANK;water). Generally, addition of three sub- and peri-thresholdcomponents (MIXþ) did not significantly alter the aromaof the apple standard mixture containing eight odorants(MIX). However, when the level of concept refinementwas considered, subjects with highly refined stimulusconcepts (13 out of the 23 subjects) showed improveddiscrimination ability and could successfully differentiatethe apple standard mixture from that also containing thesub- and peri-threshold components.

Atanasova, Thomas-Danguin, Langlois et al. (2005)have attributed the different impacts of sub- and peri-threshold components on the global perception of mix-tures observed by themselves and by Bult et al. (2001)to the relatively high intensity level of the reconstructedapple aroma used (Bult et al., 2001) compared to the rel-atively low supra-threshold intensities of the fruity com-pounds used in their own investigations (Atanasova,Thomas-Danguin, Langlois et al., 2005). Furthermore,Bult et al. have used more complex mixtures as comparedto binary mixtures wherein sensory suppressive effectsmay occur. Such discrepancies highlight the need forcareful planning when dealing with sensory models inthat results gained are dependent upon experimental de-sign. This is a confounding difficulty inherent in sensoryanalysis.

The contribution of sub-threshold aroma constituents tothe global odour impression of a Chinese jasmine greentea infusion has been evaluated using sensory evaluation(Ito & Kubota, 2005). This research was motivated bythe apparent lack of work focussed on sub-threshold odourcompounds and their mutual interaction among foodflavour constituents. Recognition odour thresholds (ROT)of 14 individual odorants in aqueous solutions were deter-mined. Following this, 5% of each odorant was replacedby 4-hexanolide, and in all cases the concentration ofthe latter was below its ROT. Sensory evaluation showed

386 D. Ryan et al. / Trends in Food Science & Technology 19 (2008) 383e389

that the addition of 4-hexanolide caused the odour inten-sity of (E )-2-hexenyl hexanoate, (Z )-3-hexenol and indoleto increase from sub-threshold to supra-threshold levels,with odour descriptions of pungent, green and camphora-ceous, respectively. The structural homologues of (E )-2-hex-enyl hexanoate and (Z )-3-hexenol, namely (Z )-3-hexenylhexanoate and hexanol, respectively, were also investigated;however, no significant change in odour intensity wasapparent upon addition of 4-hexanolide. Based on theseresults, the authors concluded that there was no relation-ship between the functional groups of an odorant and itsmutual interaction with 4-hexanolide. Experiments werethen repeated in real jasmine tea infusions, and odour syn-ergism was apparent between each of the three odorantsand 4-hexanolide, all at sub-threshold concentrations,yielding enhanced sweet and astringent notes. Such resultsdemonstrate the existence and importance of a synergisticeffect between the sub-threshold aroma compounds in jas-mine tea infusion, and serve to highlight the significanceof sub-threshold or low impact odorants in the global sen-sory characterisation of food and beverage products.

Matrix impact on global odour perceptionAny model studies targeted at understanding the role of

low impact odorants in global odour perception must alsotake into account the matrix of the ‘‘real system’’ and tar-get the model accordingly. This is because matrix isknown to exert a significant effect on aroma profile(Buettner & Mestres, 2005); the physicoechemical prop-erties of the particular odorants combined with the chem-ical composition of the matrix and the formed matrixstructure can modify the concentration of the aroma com-pounds in the headspace (Bezman et al., 2003). For exam-ple, matrix effects were evident in the SPME (solid-phasemicroextraction) and static headspace quantitation ofmarker odorants in a buffer solution compared to thesame markers calibrated in a green tomato matrix. Gener-ally there was a higher retention of aroma by the tomatomatrix compared to the buffer, and only minor differenceswere observed between the SPME and static headspaceanalyses. Differing proportions of odorants in the head-space of the tomato and buffer matrices indicate that se-lected interactions of each odorant with the matrixcomponents determine odorant volatility, and that differ-ences cannot simply be explained by the inferior masstransfer of odorants from the green tomato matrix (Bez-man et al., 2003). Such results highlight the significantrole of the matrix in determining the overall profile ofodorants in the headspace.

Of particular relevance is the perceptual impact of ma-trix ethanol on the perception of wine flavour and aroma.Most recently, Le Berre, Atanasova, Langlois, Etievant,and Thomas-Danguin (2007), in an extension of their pre-vious research (ie Atanasova, Thomas-Danguin, Chabanetet al., 2005) sought to assess the physicoechemical andperceptual impact of ethanol on the volatility of woody

and fruity aromas. Woody (whiskey lactone) and fruity(isoamyl acetate) odours in aqueous and dilute ethanolsolutions were investigated. Physicoechemical resultsshowed both chemical and sensory interactions betweenthe three components, and reduced whiskey lactone vola-tility was observed in the presence of ethanol. This wasnot the case, however, for isoamyl acetate. Perceptually,a synergy effect of the woody on the fruity odour wasnoted in aqueous solutions, which disappeared in thepresence of ethanol. Contrary to this, woody odour wasmasked by the fruity odour in both aqueous and ethanolicsolutions, and significant ethanol odour masking by thefruity and woody odours was observed in the ethanolicsolutions. Collectively, such results show that perceptualinteractions of odorants can be affected by alcohol contentthrough modification of the chemical proportions ofodorants. As such, the importance of the ethanolic matrixcomposition in the perception of wine bouquet cannot beunderestimated.

Critically, evidence suggests that compounds withlow OAV play a key role in odour perception

Since 1963, it has been documented that sub-thresholdaddition or synergy can occur between volatile compoundssuch that sub-threshold volatiles which have no odourwhen assessed individually, may in fact contribute orpossess odour activity in mixtures (Day, Lillard, &Montgomery, 1963). More recently, Escudero et al.(2004) have reported that compounds with relatively lowOAVs can have an unexpectedly high effect on aroma.This study began as a ‘‘traditional’’ aroma analysis ofMaccabeo wine involving AEDA, followed by quantifica-tion of odour-active compounds, reconstitution, additionand omission tests. The authors report throughout thesensory analysis of reconstituted wines that the resultswere ‘‘disappointing’’; this was largely due to the factthat reconstitution C (containing all aroma compoundsquantified by AEDA) was found to be significantly differ-ent from the original wine, and addition tests yielded pos-itive results for only two odorants. Two compounds notincluded in the original quantitation and model analysesvis 4-mercapto-4-methylpentan-2-one and 2-methyl-3-furanthiol, were subsequently quantified and found to bepresent in quantities slightly above their threshold concen-trations. When added to the reconstituted wine (10 ng/Land 5 ng/L, respectively), the effect was pronounced. Inparticular, the authors report for 4-mercapto-4-methylpen-tan-2-one: ‘‘it is surprising how with an apparently lowvalue of aroma it can play such a predominant role inthe aroma of a mixture that contains tens of other aromaswith much greater potencies. It is also remarkable that thiscomponent affects the aroma of wine, but it cannot bedescribed as a proper impact component, because it doesnot communicate to the wine its primary aromatic charac-teristics (boxwood, mango), but gives the wine a citric andfruity note.’’ The authors conclude that ‘‘new tools, in

387D. Ryan et al. / Trends in Food Science & Technology 19 (2008) 383e389

addition to FDs and OAVs’’ are needed ‘‘for the evaluationof the potential importance of the individual odorants incomplex mixtures.’’

Even more surprising is a later report from the samegroup (Escudero et al., 2007) where the addition of com-pounds at or below their threshold level made a significantdifference to perceived aroma. In one case, dimethylsulfide was added to a dearomatized wine (at 10 mg/L,its threshold level), and although it could not be perceivedon its own, its presence with other added compoundsmade it possible to detect ‘‘complex sweet-fruity or greenolive notes.’’ In another test, isobutyl 2-methoxypyrazinewas added to a dearomatized wine at the level found inthe commercial wine and was detected as an ‘‘earthyaroma.’’ When added together with (Z )-3-hexenol and1-hexanol the sensory effect was more easily recognizedand a ‘‘pepper odour nuance (could) be recognized, which(suggested) that the three components may interact syner-gistically.’’ The two alcohols were added at concentrations(1-hexanol, 1.48 mg/L and (Z )-3-hexenol, 234 mg/L) wellbelow their threshold levels (1-hexanol 8.00 mg/L and(Z )-3-hexenol 400 mg/L (Guth, 1997).

Collectively, these results demonstrate that highimpact odorants do not necessarily guarantee an effecton wine aroma, and that compounds with relatively lowOAV may act as impact odorants. Significantly, low im-pact odorants may act to change the perception of otherodorants in a mixture, and may interact synergistically.Escudero et al. (2004) have concluded that the abilityof a particular compound to impact the aroma of wineis due to the ‘‘specificity of the aromatic note’’ of sucha compound. The fact that most compounds were foundto have no individual effect on wine aroma, despite con-centrations in excess of their odour thresholds with highOAV, implies that it is not the aroma of the individualcomponents which is perceived but rather the aroma ofthe mixture. The authors hypothesise that wine formssome kind of aromatic buffer towards a wide range ofaromas. This buffer, formulated through the presence ofhigh concentrations of ethanol, ethyl esters, volatilephenolics etc in wine, may only be broken by thepresence of an aroma with distinct aromatic propertiessuch as 4-methyl-4-mercaptopentan-2-one (Escuderoet al., 2004).

Therefore, the importance of low impact odorantsand matrix must be considered when determiningfood/beverage sensory profile

We hypothesise that the perception of high impactodorants is modified by sub- and peri-threshold odorants,even those with low OAVs. While the evidence we presentpoints to this new understanding gradually evolving, weknow of no fundamental, multidisciplinary studies of thetype proposed that are designed to test this hypothesis.We believe a new multidisciplinary approach is needed,

incorporating chemical, sensory and neurological modelstudies to evaluate global sensory perception. Critically,traditional AEDA and GC-O approaches must be ex-tended to incorporate model neurological studies.Ultimately, such approaches should be undertakenconcurrently.

Model neurological studiesElectroencephalograph (EEG) studies have been used in

assessing sensory preference ie for comparing sensory andbrain activity responses to flavour components (Patterson,Owen, Frank, Smith, & Cadusch, 2004); we believe thistechnology could be utilised to evaluate the role of lowimpact odorants on sensory perception. Patterson et al.(2004) aimed to link traditional sensory techniques withEEG (an electrophysiological technique), to furtherunderstand brain response to odour. This study wasdesigned to find possible differences in brain activity incohorts from two different cultural backgrounds (overseas‘‘OS’’ and Australian) when presented with differentodours. Four odour compounds were used in the study:p-cresol, 2-heptanone, methional, and dimethyltrisulfide(DMTS), which were ranked according to hedonic(emotional like/dislike) and strength response duringEEG recordings. While there were no significant differ-ences between cohorts for the subjective like/dislike andstrength responses, some significant differences in objec-tive EEG recordings were found. The most significantdifference was for p-cresol in the right frontal response.Similar trends were observed (but not statistically signifi-cant) for 2-heptanone in both right and left frontalresponse; and for DMTS in the left frontal response. Nosignificant differences or trends were found between thecohorts for methional. The authors concluded that ‘‘thedifferences.between the OS and Australian groups may(therefore) be consistent with the utilization of differentphysiological processes involved in the early sensoryresponse to the odours.’’ As different cohorts displaydifferent physiological responses to the same odour, it ispossible that a single subject may display different physi-ological response when presented with two odours e oneat threshold level. In any case, the methodology used byPatterson et al. (2004) may be used to explore thisphenomenon and simultaneously obtain both subjectiveand objective data on model odour compounds andmixtures.

Functional magnetic resonance imaging (fMRI) hasfound widespread application in various sensory researchinvestigations, and work continues to model olfaction andoptimise signal response in single odour stimulation, forexample in odorant-induced primary olfactory cortex(POC) signal changes in response to prolonged stimula-tion (Tabert et al., 2007). Significantly, however, fMRIand EEG techniques are complementary (Freeman,2004; Menon & Crottaz-Herbette, 2005); each method

388 D. Ryan et al. / Trends in Food Science & Technology 19 (2008) 383e389

has its strength where the other has limits. fMRI is a he-modynamic based method with a spatial resolution in therange of millimeters, whilst EEG has a time resolutionrange of milliseconds. EEG approaches thus offer goodtemporal resolution whilst fMRI achieves good spatialresolution (Mulert et al., 2004). Freeman (2004) suggeststhat simultaneously recorded, multichannel betaegammaEEG may assist in interpreting images derived byfMRI; this hypothesis has been realized in the work ofMulert et al. (2004) who have investigated auditory-evoked potential in nine human subjects simultaneouslyusing EEG and fMRI. Generally, due to technical andpractical challenges, EEG and fMRI data are acquiredin isolation in separate sessions. Simultaneous measure-ment requires special EEG hardware that can be usedinside the MRI without inducing artefacts or posingsafety risks to the subject. The results gained suggestsimultaneous EEG and fMRI permits improved under-standing of the spatiotemporal dynamics of brain activity(Mulert et al., 2004).

Recommendations and future directionsMounting evidence indicates the importance of low

impact odorants on global odour perception. The questionis, how do we ascertain the apparent synergistic effect oflow impact odorants, and how do we determine whichlow impact odorants have the capacity for synergism?By their very nature, low impact odorants may go

Fig. 1. Holistic odorant analysis incorporating GC-OeEEG. (i) Shows the potCompound B shows a very small ‘chemical response’, and would be referredresponse (conscious) may induce high brain activity. Compound C would alsoon brain activity may be negligible. (ii) Demonstrates hypothetical brain acti

and B, and the possible disparity in brain response that may ar

‘‘undetected’’ in traditional studies (e.g. GC-O), hencetheir importance may not be established. The task of sim-ply identifying such species, particularly in real systems/matrices, is challenging to say the least. A new approachis needed, and we propose that the significance of lowimpact odorants may be evaluated using neurologicalstudies to assess brain response during olfaction. Fig. 1proposes a ‘holistic’ approach incorporating traditionalGC-O (and GC-OeMS) analyses coupled with dynamicEEG monitoring (GC-OeEEG) for objectively monitoringsub-conscious response to low impact odorants. In thisapproach, the human sniffer would be fitted with EEGapparatus, and brain activity would be monitored duringthe GC-O run. We believe this approach would yieldvaluable information in identifying low impact odorantswith the potential for odorant synergism. Furthermore,this information would be the first step in ultimately un-derstanding if or how low impact odorants modify theperception of the high impact odorants in a global odor-ant mixture. Of course this GC-OeEEG approach wouldneed considerable optimisation using model binary mix-tures, however, its potential is considerable. Similarly, tra-ditional sensory studies could benefit through theincorporation of EEG/fMRI investigations to facilitatean improved and ‘objective’ understanding of neurologi-cal odour perception e to our knowledge there doesnot appear to be any fMRI studies where binary mixturesof odorants have been studied. Improved understanding of

ential neurological perception of three different odorants; A, B and C.to as a low impact odorant. However, its corresponding neurologicalbe classified as a low impact odorant; however, its subsequent impact

vity induced by sensory analyses of a binary mixture of Compounds Aise due to the contribution of the low impact odorant B.

389D. Ryan et al. / Trends in Food Science & Technology 19 (2008) 383e389

the chemical and neurological basis of odour perceptionwill facilitate the design of improved odour models whichshould ultimately yield a wealth of new information fora better appreciation of the complexities of global odourperception.

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