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Journal of Stored Products Research 36 (2000) 319±340
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Review

Volatiles as an indicator of fungal activity and
di€erentiation between species, and the potential
use of electronic nose technology for early detection
of grain spoilage
N. Magan a,*, P. Evans b
a

Applied Mycology Group, Cran®eld Biotechnology Centre, Cran®eld University, Cran®eld, Bedford MK43 0AL, UK
b
Department of Instrumentation and Analytical Science, Faraday Building, UMIST, PO BOX 88, Sackville Street,
Manchester M60 1QD, UK
Accepted 10 November 1999

Abstract
There is signi®cant interest in methods for the early detection of quality changes in cereal grains. The
development of electronic nose technology in recent years has stimulated interest in the use of

characteristic volatiles and odours as a rapid, early indication of deterioration in grain quality. This
review details the current status of this area of research. The range of volatiles produced by spoilage
fungi in vitro and on grain are described, and the key volatile groups indicative of spoilage are
identi®ed. The relationship between current grain quality descriptors and the general classes of o€odours as de®ned in the literature, e.g. sour, musty, are not very accurate and the possible correlation
between these for wheat, maize and other cereals, and volatiles are detailed. Examples of di€erentiation
of spoilage moulds and between grain types using an electronic nose instrument are described. The
potential for rapid and remote grain classi®cation and future prospects for the use of such technology as
a major descriptor of quality are discussed. 7 2000 Elsevier Science Ltd. All rights reserved.
Keywords: Fungi; Stored grain; Volatiles; Electronic nose technology; Odour detection

* Corresponding author. Tel.: +44-01234-750111; fax: +44-01234-750907.
E-mail address: N.Magan@Cran®eld.ac.uk (N. Magan).
0022-474X/00/$ - see front matter 7 2000 Elsevier Science Ltd. All rights reserved.
PII: S 0 0 2 2 - 4 7 4 X ( 9 9 ) 0 0 0 5 7 - 0

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N. Magan, P. Evans / Journal of Stored Products Research 36 (2000) 319±340
Contents
1.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 320

2.

Fungal volatiles. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321

3.

Volatiles in naturally contaminated grain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 326

4.

Volatiles as taxonomic markers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328

5.

Descriptors of odour quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328
5.1. Classi®cation of o€-odours in cereals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329

6.

Grain classi®cation using electronic noses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333

7.

Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 336

8.

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337

Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 338

1. Introduction
Combine harvesting of both temperate and tropical cereals is most ecient when the ripened
grain is slightly moist. Subsequent drying to safe moisture contents (e.g. for wheat this is 14%
0 0.70 water activity) is essential to prevent initiation of fungal activity which can result in
heating of the stored grain, and ultimately end in spontaneous heating and complete loss of the

grain. The activity of spoilage fungi can also result in the production of mycotoxins by certain
genera, which prevents such moulded grain from being used for either animal or human
consumption. Thus it is very important to detect fungal deterioration in stored cereal grains at
an early stage. This would facilitate and improve existing management of grain stores. It would
also allow remedial measures to be more e€ectively implemented, allowing signi®cant losses
and grain downgrading to be avoided.
Many rapid methods for the detection of fungal spoilage in grain have been examined. These
include quantifying the e€ects of degradation on grain components, changes in fungal enzyme
activity, respiratory activity of moulds, changes in chemical components, particularly of chitin,
ergosterol and ATP, of moulds during growth in grain, immuno¯uorescence, DNA and
immunoassays, electrochemical methods and very recently, photoacoustic FTIR methods
(Tothill et al., 1992; Magan, 1993; Gordon et al., 1998). However, some of these at best
correlate poorly with fungal growth or biomass in colonised grain. Many of these techniques
are also time-consuming, expensive or not sensitive enough for the early detection of fungal
activity. A speci®c biochemical marker with adequate reproducibility to detect early spoilage
would help prevent major losses as a result of moulding of stored grain by fungi due to poor
storage management.
Fungi commonly produce volatile compounds as they start colonising nutrient-rich

N. Magan, P. Evans / Journal of Stored Products Research 36 (2000) 319±340

321

substrates such as grain. In the 1970s Kaminski et al. (1972, 1974, 1975) demonstrated that
spoilage fungi produced volatiles, which were characteristic and di€erent from those produced
by bacteria or the seeds themselves. Indeed, in this period several studies suggested that the
monitoring of the appearance of volatiles might be a good early indicator of quality loss and
mycotoxin formation in grain (Stawicki et al., 1973; Richard-Molard et al., 1976; Abramson et
al., 1980).
The primary objective of this review is to examine some of the key studies carried out on the
use of volatiles as an indicator of the potential for spoilage. To this end it will consider a
number of areas: (a) the range of fungal volatiles produced by spoilage fungi; (b) the presence
of volatiles in naturally contaminated grain as an early indicator of spoilage; (c) the possible
relationship between odour discriminators and volatiles produced by spoilage fungi on grain;
(d) early detection of the activity of spoilage moulds in grain substrates; and (e) the potential
for using electronic nose technology for detection of spoilage of grain. This review will not
extensively cover the analytical methods used to quantify volatile production by spoilage fungi.

2. Fungal volatiles
Linton and Wright (1993) reviewed the possible reasons for the production of fungal

volatiles. Production of a volatile may be a way of removing inhibitory intermediates from the
metabolism under unfavourable conditions. They also suggested that volatiles might have
inhibitory e€ects on other fungi and act as self-regulators of growth and development. For
example, in Geotrichum candidum Link, volatiles were found to in¯uence all stages of growth,
while those of Trichoderma harzianum Rifai have been demonstrated to inhibit the
mycotoxigenic Fusarium moniliforme Sheldon, a common coloniser of maize. Ecologically, the
situation can become more complex as certain fungal volatiles also attract insects (Hedlund et
al., 1995).
Most of the early work on the detection of volatiles was done using gas chromatography
(GC) and mass spectrometry (MS). For GC analysis most workers have used a polar
stationary phase for the separation of the fungal alcohols, aldehydes, ketones and esters.
Kaminski et al. (1985, 1987) also developed a spectrophotometric method for the accurate
quanti®cation of volatile carbonyl compounds.
A range of in vitro studies have been carried out to determine the types of volatiles
produced by grain spoilage fungi. These have often included growing individual fungi on
cereal-based substrates and the use of GC or GC±MS to quantify the key volatile compounds
produced. Volatiles arising from growth of pure cultures on sterile wheat, maize, barley and
whole wheat bread have been described. A range of classes of volatile compounds including
alcohols, carbonyls and hydrocarbons have been identi®ed. The major volatile compounds
found were 3-methyl-1-butanol, 1-octen-3-ol and other 8-carbon ketones and alcohols. Table 1

summarises some of the major volatiles produced by spoilage fungal species and the substrates
on which they were cultured. This covers the whole range of key spoilage fungi, including
Aspergillus, Penicillium, Eurotium, Alternaria and Fusarium species, and includes a number of
mycotoxigenic species. The di€erence in the metabolites found by di€erent authors may
partially be due to the di€erence in the nutrient substrate used for the cultivation of the

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N. Magan, P. Evans / Journal of Stored Products Research 36 (2000) 319±340

Table 1
Volatile compounds found in cultures of fungi grown on di€erent grain and cereal substratesa
Volatiles

Grain medium

Fungal species

Reference

Alcohols
Ethanol

Wheat

BorjessoÈn et al. (1989)

1-Butanol

Wheat/maize

2-Methyl-1-propanol

Wheat

1-Pentanol
2-Methyl-1-butanol
3-Methyl-1-butanol

Barley

Wheat
Wheat

E.amstelodami, Asp.¯avus, Fus.culmorum,
Pen.cyclopium
Asp.¯avus, Asp.parasiticus,
Pen.chrysogenum, Alt. spp
Asp.¯avus, E.amstelodami, Pen.verrucosum,
Fus.culmorum
Pen.viridicatum
E.amstelodami
Asp.¯avus, Asp.niger, Asp.ochraceus,
Asp.oryzae, Asp.parasiticus, Asp.nidulans,
Pen.chrysogenum, Pen.citrinum,
Pen.funiculosum, Pen.raistricki,
Pen.viridicatum, Alt. spp, Cephalosporium
spp, Fus.spp.
Asp. ¯avus
Alt.alternata, E.repens, Asp.¯avus,
Asp.versicolor, Pen.chrysogenum,

Pen.cyclopium, Fus.moniliforme,
Fus.semitectum
Asp.¯avus, Pen.cyclopium
Pen.aurantiogriseum, Pen.verrucosum,
Pen.viridicatum, Pen.coprophilum
Asp.¯avus, Asp.parasiticus,
Pen.chrysogenum, Alt. spp.
Asp.¯avus, Asp.niger, Asp.ochraceus,
Asp.oryzae, Asp.parasiticus, Asp.nidulans,
Pen.chrysogenum, Pen.citrinum, Pen.
viridicatum, Cephalosporium sp.
Asp.¯avus, Asp.ochraceus, Asp.oryzae,
Asp.parasiticus, Asp.nidulans, Pen.
chrysogenum, Pen.citrinum,
Pen.funiculosum Pen.raistricki,
Pen.viridicatum Alt. spp., Cephalosporium
spp., Fus. spp.
Pen.roquefortii, Asp.¯avus, Asp.niger

Tuma et al. (1989)

Whole wheat
bread
Wheat

Wheat
Barley
Corn
3-Octanol

Wheat

1-Octen-3-ol

Wheat

Whole wheat
bread
Wheat

Barley
Maize

Alt.alternata, E.repens, Asp.¯avus,
Asp.versicolor, Pen.chrysogenum,
Pen.cyclopium
Pen.aurantiogriseum, Pen.verrucosum,
Pen.viridicatum
Asp. ¯avus, Asp. parasiticus, Pen.
chrysogenum, Alt.spp

Wasowicz (1988)
BorjessoÈn et al. (1989)
Wilkins and Scholl (1989)
BorjessoÈn et al. (1989)
Kaminski et al. (1972, 1974)

Harris et al. (1986)

BorjessoÈn et al. (1989)
Wilkins and Scholl (1989)
Wasowicz (1988)
Kaminski et al. (1972, 1974)

Kaminski et al. (1972, 1974)

Harris et al. (1986)
Tuma et al. (1989)

Wilkins and Scholl (1989)
Wasowicz (1988)

N. Magan, P. Evans / Journal of Stored Products Research 36 (2000) 319±340
2-Octan-1-ol

Wheat

1,5-Octadien-3-ol

Whole wheat
bread
Wheat/maize

Hexanol
Octanol

Whole wheat
bread

Carbonyls
Acetaldehyde

Wheat/maize

2-Pentane
3-Octanone

Wheat
Wheat

Nonanal
2-Methyloacetophenone
Hydrocarbons
Dimethyl benzene

Whole wheat
bread
Wheat
Whole wheat
bread
Barley

Whole wheat
bread
Trimethyl hexane
Whole wheat
bread
2, 4-Dimethyl hexane Wheat
Styrene
Barley
Naphthalene
Miscellaneous
Ethyl acetate
2-Methyl-furan
2-(1-Pentyl)-furan

Wheat
Wheat
Barley

2-(2-Furyl)-pentanal

Barley

2-Ethyl-5-methylphenol
3-Methyl-anisole
Monoterpenes
2-Methyl-isoborneol

Barley

Damascenone

Whole wheat

Barley
Wheat
Whole wheat
bread
Whole wheat
bread

Asp.¯avus, Asp.ochraceus, Asp.oryzae,
Asp.parasiticus, Asp.nidulans,
Pen.chrysogenum, Pen.raistricki,
Pen.viridicatum Alt. Spp., Cephalosporium
spp, Fus. spp
Pen.roquefortii
Asp.¯avus, Asp.parasiticus,
Pen.chrysogenum, Alt. spp
Asp.¯avus, Asp.niger

323

Kaminski et al. (1972, 1974)

Harris et al. (1986)
Wasowicz (1988)
Harris et al. (1986)

Wasowicz (1988)

Asp.¯avus, Asp.parasiticus,
Pen.chrysogenum, Alt. spp
E.amstelodami
Asp.¯avus, Asp.ochraceus, Asp.oryzae,
Asp.parasiticus, Asp.nidulans,
Pen.chrysogenum Pen.citrinum,
Pen.funiculum Pen.raistricki,
Pen.viridicatum, Alt. spp., Cephalosporium
spp, Fus. spp
Pen.roquefortii, Asp.¯avus, Asp.niger

Wasowicz (1988)

E.repens, Pen.cyclopium
Asp.¯avus, Asp.niger

Tuma et al. (1989)
Harris et al. (1986)

Pen.coprophilum

Wilkins and Scholl (1989)

Asp.¯avus, Asp.niger

Harris et al. (1986)

Pen.roquefortii

Harris et al. (1986)

Fus.culmorum
Pen.aurantiogriseum, Pen.verrucosum,
Pen.viridicatum, Pen.coprophilum
Asp.niger

BorjessoÈn et al. (1989)
Wilkins and Scholl (1989)

Fus.culmorum
E.amstelodami, Asp.¯avus, Pen.cyclopium
Pen.aurantiogriseum, Pen.verrucosum,
Pen.viridicatum, Pen.coprophilum
Pen.aurantiogriseum, Pen.verrucosum,
Pen.viridicatum, Pen.coprophilum
Pen.aurantiogriseum, Pen.verrucosum,
Pen.viridicatum, Pen.coprophilum
Pen.aurantiogriseum, Pen.coprophilum
Fus.culmorum
Pen.roquefortii

BorjessoÈn et al. (1989)
BorjessoÈn et al. (1989)
Wilkins and Scholl (1989)

Wilkins and Scholl (1989)
BorjessoÈn et al. (1989)
Harris et al. (1986)

Pen.roquefortii

Harris et al. (1986)

BorjessoÈn et al. (1989)
Kaminski et al. (1972, 1974)

Harris et al. (1986)

Wilkins and Scholl (1989)
Wilkins and Scholl (1989)

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N. Magan, P. Evans / Journal of Stored Products Research 36 (2000) 319±340

species. One other important fact of note was that in many cases the water availability of the
substrate was not accurately controlled, or measured. This could have a signi®cant impact on
and modify the importance of individual volatile compounds produced by a speci®c species on
a temperate or tropical cereal.
Both temperature and culture age can also have an e€ect on volatile production, e.g.
Kaminski et al. (1972, 1974) found that in di€erent cultures of fungi grown on autoclaved
wheat meal at 26±288C for 5 days, volatile alcohols represented 79±96% of the total volatiles.
The alcohol, 1-octen-3-ol was found to be predominant (35±93%). BorjessoÈn et al. (1989)
found that alcohols, particularly ethanol, constituted 80% of the total volatile concentration in
spoilage fungi, with the exception of the xerophilic species Eurotium amstelodami Mangin
where about 50% were alcohols. Subsequent detailed studies by BorjessoÈn et al. (1990, 1992)
found that there were di€erences in the fungal volatiles produced by grain fungi (Penicillium
spp, Aspergillus ¯avus Link, A. versicolor (Vuill)Tiraboschi and A. candidus Link) on agar and
on moist temperate cereals over a 14 day incubation period using GC. Interestingly, there was
less of a di€erence between grain substrate type and age of cultures than between species. They
found that over 80% of the volatiles were alcohols, except in the case of Eurotium
amstelodami. In grain cultures ethanol accounted for more than 90% of the total alcohols
produced. They also found that with the ubiquitous Penicillium species, P. aurantiogriseum
Dierckx, the production of the 8-carbon alcohols, 2-methyl-1-propanol and 3-methyl-1-butanol
was higher in grain than in agar cultures. Other studies (Sinha et al., 1988; Tuma et al., 1989)
revealed 3-methyl-1-butanol and 1-octen-3-ol to be predominant along with the ketone, 3octanone. Since then other alcohols such as 3-octanol have been identi®ed (Nilsson et al.,
1996). More recently, Pasanen et al. (1996) have suggested that volatile organic compounds,
particularly ketones, may also be useful markers of the activity of mycotoxigenic species such
as Fusarium sporotrichoides Sherbako€ and Penicillium verrucosum Dierckx. This suggests that
patterns of volatile production could also be a powerful tool for the rapid and early detection
of the activity of mycotoxigenic species. Wilkins and Scholl (1989) identi®ed volatiles from
Penicillium spp grown on irradiated barley (20±25% moisture content (m.c.)) for 7 days. Of the
compounds identi®ed from P. aurantiogriseum, P. verrucosum and P. viridicatum Westl., 3methyl-1-butanol, styrene and 1-octen-3-ol were predominant.
The main esters found are acetates, which include ethyl acetate, isobutyl acetate and
isopentyl acetate (Larsen and Frisvad, 1995). They also identi®ed aromatic ethers such as 1methoxy-3-methylbenzene. Besides esters, pyrazines such as methoxy pyrazines (Larsen and
Frisvad, 1994), sulphurous compounds such as dimethyl disulphide (BorjessoÈn et al., 1993) and
a number of mono- and sesqui-terpenes are produced. BorjessoÈn et al. (1989, 1990) also
identi®ed heterocyclic compounds such as 3-methylfuran.
Harris et al. (1986) cultured fungi on whole wheat bread (70 g in a 1 litre round bottom
¯ask) and found that P. roquefortii Thom. produced 2-methyisoborneol (75 ppb) and
damascenone (310 ppb). Kaminski and Wasowicz (1991) found that volatiles produced by A.
parasiticus Speare, A. ¯avus, P. chrysogenum Thom. and an Alternaria sp. grown on wheat and
maize meal at 308C for 72 h reached more than 60 ppm compared to the trace amounts found
in control, uninoculated samples. However, in most of these studies the impact of storage
water availability and temperature were not investigated. Table 2 summarises information from

N. Magan, P. Evans / Journal of Stored Products Research 36 (2000) 319±340

325

Table 2
Fungal volatiles identi®ed in inoculated cereal cultures by di€erent authorsa
Fungal volatile
1-Butanol
2-Butanol
3-Methyl-1-butanol
1-Pentanol
1-Hexanol
2-Octen-1-ol
1-Octanol
3-Octanol
1-Octen-3-ol
Phenyl ethanol
2-Ethyl-5-methyl-phenol
Hexanal
2-(2-Furyl) pentanal
Benzaldehyde
3-Octanone
2-Hydroxy-3-butanone
Nonanone
2-Methyl-acetophenone
Butyl acetate
Amyl acetate
Octyl acetate
2-Methylfuran
2-(1-Pentyl)furan
3-Methyl anisole

Maize

a
a
a

a
a

Cereal barley

b
b

Wheat
c
c, d
c, d
c
c
c
c

b
c
b

a
b
c
c
a
c
b
c
c
c
d
b
b

a

Key: a, Richard-Molard et al. (1976); b, Wilkins and Scholl (1989); c, Kaminski
et al. (1987); d, BorjessoÈn et al. (1989).

the literature concerning the main fungal volatiles produced in inoculated grain cultures on
maize, barley and wheat available.
The metabolic pathway leading to the formation of volatiles gives important clues to the
relationship between various groups of volatiles, non-volatiles and mycotoxins (Fig. 1).
Ethanol is produced under anaerobic conditions. Alcohols are derived from amino acids via
the Ehrlich pathway. 1-octen-3-ol and other eight and ten carbon compounds are synthesised
by oxidation of linoleic acid (acetate±fatty acids±alcohol pathway). The breakdown of lipids
through fungal lipase activity results in free fatty acids. These are oxidised to b-keto acids,
which are subsequently decarboxylated to methyl ketones. The corresponding secondary
alcohols are formed by the reduction of methyl ketones. Lactones are produced from g-keto
acids. Enzyme catalysed reactions between alcohols and acyl-CoA compounds result in the
formation of esters. Pyrazines are thought to be synthesised by the condensation reaction
between acetoin and ammonia. The dimethylsulphide is produced from methionine. The
mevalonic acid pathway gives rise to a variety of terpenes such as geosmin and 2methylisoborneol.

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N. Magan, P. Evans / Journal of Stored Products Research 36 (2000) 319±340

Fig. 1. The pathways involved in the production of di€erent secondary metabolites.

3. Volatiles in naturally contaminated grain
A number of studies have identi®ed the background odours produced by di€erent cereal
types and cultivars. These have shown that a wide range of volatiles including alcohols, esters,
aldehydes, ketones, alkanes, alkenes, furans, lactams, phenols, pyrazines, and pyrroles are
produced by wheat, maize and rice grains (Kaminski and Wasowicz, 1991). However, few
studies have examined the detailed accumulation of volatiles produced during fungal
colonisation of cereal grain.
For example, Richard-Molard et al. (1976) followed the accumulation of fungal volatiles: 1octen-3-ol, 3-octanone, 3-octanol, 3-methyl-1-butanol, in airtight stored maize at di€erent
temperatures in France. They found a sequential increase in the quantities of these volatiles
produced with storage time. In naturally ventilated wheat, barley and oats in Canada,
Abramson et al. (1980) identi®ed 1-octanol, 3-octanone and 3-methyl-1-butanol in moist grain
(21% m.c.) in farm granaries over a 20-week storage period. They found a 10±15 times
increase in volatiles by the seventh week of storage, with levels decreasing by the sixteenth
week. They also found that 1-octanol was predominant, comprising 51±81% of the total
volatiles. The highest concentrations of fungal volatiles were found in oats, but the widest
range of volatiles occurred in barley. In another study Abramson et al. (1983) compared
volatiles produced in barley grain stored at 16 and 20% m.c. for 66 weeks. The maximum was

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N. Magan, P. Evans / Journal of Stored Products Research 36 (2000) 319±340

produced in the sixth week of storage, with signi®cantly higher levels of volatiles produced in
the higher m.c. barley. The key volatiles were 3-methyl-1-butanol, 3-octanone, 1-octanol and
1-octen-3-ol.
Similar studies by Sinha et al. (1988) and Tuma et al. (1989) of wheat stored at a range of
m.c.s' (15.5±25%) in unventilated and ventilated storage bins demonstrated that regardless of
season, volatiles could be detected and correlated with fungal growth and activity in the stored
grain. The highest levels of 3-methyl-1-butanol occurred in the 25% m.c. wheat and correlated
signi®cantly with total counts of bacteria, Penicillium spp and Fusarium spp. At 20% m.c. there
was also correlation with the Eurotium glaucus group of species, which are important in
initiating spoilage. In non-ventilated bins 1-octen-3-ol production was correlated with
Penicillium spp in wheat at both 20 and 25% m.c. Interestingly, higher levels of volatiles were
present in seed with a low viability suggesting that volatiles could be a very good early
indicator of loss of seed viability and spoilage in stored grain. However, very little information
is available on the correlation between fungal volatiles, quality loss and mycotoxin formation
as an early indicator in storage. Pasanen et al. (1996) demonstrated some relationship between
fungal volatiles and mycotoxins. They cultivated Fusarium sporotrichoides on straw, wheat and
oat grains and found that on both grain types, a similar composition of volatiles were
produced. Equal amounts of terpenes and ketones, and to a minor extent alcohols were
produced. Interestingly, large amounts of trichothecene mycotoxins were also synthesised.
These are synthesised via the terpenoid route, the same pathway used for the production of
terpenes. They therefore suggested that the production of large amounts of ketones was due to
the high lipid content of grain. Furthermore they showed that there were di€erences in the
volatile composition between toxigenic and non-toxigenic strains of Penicillium verrucosum.
The isolate that synthesised ochratoxins showed an accelerated production of ketones
compared to the non-toxigenic isolate. Ochratoxins are derived from polyketides and
phenylalanines. Thus, similarity between the polyketides and fatty acid pathways may result in
increased production of ketones in the mycotoxinogenic isolate.
Attempts have also been made to relate fungal volatile production in di€erent grain types to
total fungal populations (colony forming units, cfu) (Wasowicz, 1988). They monitored 100 g
samples of wheat and maize of 17% m.c. stored for up to 70 days in 1 litre containers using
direct gas chromatography. Fungal cfus increased from 102 to 106, and 103 to 107 gÿ1
respectively. At 21% m.c. they increased to 8  108 and 8  1010 gÿ1 wheat and maize
Table 3
Mean speci®c and total fungal volatiles in wheat and maize grain of di€erent moisture contents (m.c.) after 28 days
storage (adapted from Kaminiski and Wasowicz, 1991)
Volatiles (ppm)
Grain treatments

Total volatiles

3-octanone

1-octen-3-ol

Wheat grain Ð 17% m.c.
Wheat grain Ð 21% m.c.
Maize grain Ð 17% m.c.
Maize grain Ð 25% m.c.

15.0
27.5
30.0
125.0

4.5
3.5
7.5
25.0

< 0.25
1.4
0.4
4.8

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N. Magan, P. Evans / Journal of Stored Products Research 36 (2000) 319±340

respectively. The temporal changes in total and dominant volatiles in these two grain types are
shown in Table 3. It was notable that there were di€erences between the volatiles produced in
wheat and maize. This could partially be a result of the di€erence in starchy and lipid/sugar
rich grains.
Some studies have also been carried out to try to correlate the volatile concentrations found
in sound cereals and those found in musty/sour cereals with total cfus and other methods of
quantifying mould presence. Wasowicz (1988) showed that in sound and musty wheat grain the
volatiles present were qualitatively the same. However, some volatiles present in musty wheat
grain were not detected in sound grain, and some also occur in signi®cantly higher
concentrations in musty grain. They found that 2-methylisoborneol and geosmin, mainly
produced by actinomycete species were mainly responsible for the musty odour found, with
amounts of 3-octanone, 1-octen-3-ol, 3-octanol, and 1-octanol also present in high
concentrations. These studies all point to the potential for using fungal volatiles as an early
indication of grain quality during storage.

4. Volatiles as taxonomic markers
Studies on a range of fungal species revealed that speci®c volatiles such as 3-methylfuran are
produced in similar amounts regardless of the fungal species and grain substrate used
(BorjessoÈn et al., 1992). However, other volatile compounds, especially terpenes, were both
species- and strain-speci®c (Larsen and Frisvad, 1995; Nilsson et al. 1996; BorjessoÈn et al.,
1989, 1993; Larsen, 1997) e.g. Aspergillus species produced thujopsene, which was absent from
the Penicillium cultures. Aspergillus candidus produced a monoterpene not found in the other
fungi examined, suggesting that monoterpene pro®les could be used to di€erentiate between
fungi. Volatile pro®les can be used rather than individual volatile compounds to classify fungi
at a species level, as a combination of volatiles is often unique to each species (Larsen and
Frisvad, 1994; Larsen, 1997; Wilkins et al., 1997; Korpi et al., 1998). Larsen (1997) was able to
classify Penicillium species within 2 days after inoculation and in a mixed culture of P.
roquefortii and P. commune Thom. in a ratio of 1000:1, with identi®cation after 3 days. Larsen
and Frisvad (1995) were also able to use these patterns to reclassify similar groups of
Penicillium spp into separate clusters based on the production of geosmin. Since it is clear that
there are a range of characteristic volatile odours produced by fungi when colonising grain the
question is whether there is any relationship between these patterns and the odour descriptors
actually used in the grain trade, particularly in the USA.

5. Descriptors of odour quality
The determination of odorous o€-taints in cereal crops has largely been an inde®nite science
with ill-de®ned parameters. The factors de®ning the o€-taints commonly encountered for four
cereals, corn (Zea mays L.), sorghum (Sorghum bicolour (L.) Moench), soybean (Glycine max
L.) and wheat (Triticum aestivum L., T. compactum Host. and T. durum Desf.), are reviewed
along with the methods currently in use for investigating them.

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329

5.1. Classi®cation of o€-odours in cereals
In Europe the grading of grain is covered by ISO 605:1991 (E) 1991. It states that odour
should be determined as soon as possible after sampling but de®nes no parameters other than
the fact that grain possessing a foreign odour should be rejected. If no odour is detected the
sample is sealed and retested after 24 h. After this stage sub-samples of ca 5 g may be taken,
ground and then heated to no more than 608C before re-evaluating the odour. Further
examinations for foreign odours may be carried out during or after grinding.
In the United States an inspector determines the odour of cereal grains. Detection of any
taint in the grain odour immediately reduces the grading of the grain to the lowest possible,
namely, that of sample grain. This obviously has a serious e€ect on the economic value of the
crop. The outcome of a grading may however be subject to an appeals process. A review of the
current Grain Inspection Handbook (USDA, 1990) reveals that whilst odour classi®cation is
described, little is known about the volatiles giving rise to the o€-taints. Numerous sources of
possible taint cause are listed in the handbook. For example the following categories are
quoted:
Heat damage

``May arise from a variety of situations and can be a reason for downgrading
the grain without odour analysis. Instances of its occurrence stem from:
(i) grain stored with too high a ®eld moisture content;
(ii) moisture migration due to convective air currents in storage;
(iii) localised infestations of grain insects''.

Germ damage
Sprout damage
Mould damage
Scab damage

These situations all favour mould development and reduce the nutritional
value of the grain. Drier damage is less severe and given the classi®cation of
`damaged by heat' but may also lead to o€-taints.
``Results only in colouration of oils from the grain''.
``May ultimately lead to the presence of moulds''.
``Can occur in the ®eld or in storage''.
``Arises from ®eld damage by Fusarium sp. and usually has mould in the germ
of the seed. May also include vomitoxin (deoxynivalenol) which can lead to
poisoning problems''.

The grain may be inspected for odour at three stages of the quality sampling process; (i)
when sampling the whole of the lot (ii) before removal of foreign material and broken seed or
(iii) after removal of foreign material and broken cereal. In all cases the same standard applies
to the sample. Two samples are taken, a working sample and a ®le sample that may be
referred to in any subsequent appeals. The following guidelines constitute the de®nitions of o€taint available to an inspector for the four grains considered in this report.
(a) Corn (250 g sample)
Three odour classi®cation categories are described in the USDA grain handbook with these
further subdivided into speci®c types of taint (see Table 4).

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Table 4
Odour classi®cation for corn samples (USDA, 1990)
Odour classi®cation examples
Sour

Musty

COFOa

Boot
Fermenting
Insect (acrid)
Pigpen

Ground
Insect
Mouldy

Animal hides
Decaying animal and vegetable matter
Fertiliser
Fumigant
Insecticide
Oil products
Skunk
Smoke
Strong weed

a

COFO: Commercially O€ensive Foreign Odours (de®ned as odours foreign to grain that render it un®t for normal commercial usage).

(b) Sorghum (30 g sample)
As per Table 4 except that Smut and Garlic odours are covered by a separate exclusion
based upon a visual inspection to determine the level of smut or garlic bulblets present. A
separate classi®cation of Garlicky or Smutty Sorghum is de®ned in these instances.
(c) Soybean (125 g sample)
As per Table 4 except that smoke is also a category in the Sour de®nition. This application
of smoke is only valid under sour for canola, ¯axseed, soybean and sun¯ower.
(d) Wheat (50 g sample)
As per Table 4 except that the Smut and Garlic odour de®nitions used for Sorghum also
apply for wheat samples. Smutty and Garlicky Wheat classi®cations may be used in these
instances.
For all types of grain, fumigant and insecticide odours are liable for special consideration.
The sample is aerated and retested over a 4-h period and the sample reclassi®ed if the odour
dissipates within that period. Marginal outcomes require a consensus decision between
inspectors. In the ®nal report, grain failing for odour classi®cation is graded only as musty,
sour or commercially o€ensive foreign odours (COFO). Kansas State University grain grading
standards (Hermann and Kuhl, 1997) apply the following criteria:
Musty:
Sour:
COFO:

may be subdivided into mould and insect. This classi®cation typically applies when
certain grain boring insects or mould are present;
may arise from insect infestation of fermenting mouldy grain;
from petroleum products or from mis- or overuse of fumigants.

Relating the o€-taint responsible for the rejection of grain samples to speci®c volatile species
has been a dicult problem that to date remains unsolved. Weinberg (1986) found no

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relationship between the chemical composition measured by GC±MS and the perceived
odour.
BorjessoÈn et al. (1992) studied the volatiles evolved by six fungal species on grains (see
Table 5). Three Penicillium sp. were chosen along with three Aspergillus spp. All six produced
unique pro®les by GC±MS analysis. Whilst several shared numerous common volatiles all six
had characteristic metabolic products, the most signi®cant example being P. brevicompactum
Dierckx which produced acetone at an astonishing rate. The relationship between accumulated
CO2 evolution and fungal growth was found to be signi®cant. The correlation between
ergosterol and volatile production was also signi®cant but the correlation between colony
forming units (cfu) and volatile metabolites was less strong.
Smith et al. (1994) presented the best attempt yet to de®ne the vocabulary used to describe
odours associated with grain (Table 6). A set of reference odours descriptive of/or alluding to
the grain descriptor is provided for thirty-one de®ned terms. Five non-speci®c descriptors still
remain and were the most commonly applied when the system was evaluated against 400 grain
samples (105 wheat, 116 corn, 75 soybean and 104 sorghum).
Descriptors often associated with the same broad category were found to be distinctly
di€erent from each other, e.g., over-ripe fermented fruit and sweaty socks are di€erent but
both may be described as being sour. Another example is the case of an odour not being
Table 5
Rate of volatile metabolite production from six fungal species grown on wheat (adapted from BorjessoÈn et al.
(1992))
Production of metabolite (ng/ha) on wheat from fungi
Volatile

P. brevi compactum

P. glabrum

P. roque fortii

A. ¯avus

A. versi color

A. candidus

Acetone
2-Propanol
3-Methylfuran
Nitromethane
2-Methyl-1-propanol
3-Pentanone
2-Methyl-1-butanol
1-Penten-3-ol
Octadiene
2-Butanone
Dimethylbenzene
Ethylbenzene
Limonene
3-Octanone
1-Octen-3-ol
Monoterpene 1
Sesquiterpene 1
Sesquiterpene 2
Thujopsene

24,000
298
4.8

26

12

27

32

10
1.7
12

0.67
32
1.4

83

30
9.4
13

2.9

9.3

3.8

3.6
4.3

a

8
2.6

28

6.1
22

2.3

3.8
7.5

0.2
12
3.2

0.47

2.1

2.9
0.83
1.7

1.3
0.6

14
7
15
0.96

1.5

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

0.62

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N. Magan, P. Evans / Journal of Stored Products Research 36 (2000) 319±340

Table 6
Correlation between odour classi®cation systems and volatile metabolites from fungi on graina
Grain
odour
class
(USDA)

Odour
descriptor
(USDA)

Surrogate vapour(s)
(Smith et al., 1994)

Characteristic volatile(s)
(Seitz et al., 1998)

Volatile
from
fungi

Sour

Sour

Tincture of civet,
Hershey's Special Dark,
mildly sweet chocolate bar,
Blackberry WONF
(]3RA654)
Red Star dry yeast
Choline chloride

Styrene

Styrene

Ethyl acetate
Methyl butanoate
Ethyl butanoate
Methyl pentanoate,
Methyl-3-methylbutanoate
Ethyl pentanoate,
Ethyl hexanoate
2-Pentanol,

Ethyl acetate

Musty

Insect

Hydratophobic aldehyde
(C-7),
fresh latex paint

Sesquiterpene,
1-Pentadecene,
Musty

Musty

Isocyclocitral,
Isopropyl-quinoline
Hydratophobic
aldehyde (C-7),
2-ethyl-1-hexanal,
3-octanol, Geosmin,
Fresh peanut shells

Anisole
1-Octen-3-ol

Nitromethane
1,2 Dimethyl-benzene

COFO

Smoke

Carvacrol

(Naphthalene)
4-Ethenyl-1-methoxybenzene,
1-Ethyl-4-methoxybenzene,
Geosmin 1-Chloro-4methoxybenzene,
(Methylene chloride),
(Chloroform)
(para-Dichlorobenzene)
2-Methylbenzofuran

1-Penten-3-ol,
1-Pentanol,
Nonanal,
Hexanol
Sesquiterpenes

3-Methylanisole

2-Octen-1-ol,
1,5-Octadien-3-ol,
Nonanal
Nitromethane
Dimethyl-benzene
Ethyl benzene
Naphthalene

2-Methylfuran,
3-Methylfuran,
2-(1-Pentyl),
furan

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COFO

Fumigant

Naphthalene

COFO

Weed

2-Isobutyl-thiazole

Benzofuran, 1H-Indene,
2-Ethyl pyridine,
2-Ethyl-3,5-dimethylpyrazine,
O,O,S-Trimethylphosphorodithioc acid
O,O,O-Trimethylphosphorodithioc acid
?-Bergamotene

Naphthalene

a

Bracketed volatiles in column four are tentative identi®cations. Volatiles in column ®ve are fungal volatiles identical to/or associated with those in columns three and four.

distinct enough to categorise precisely, being given a description of musty which could include
`damp basement', `earthy humus', `mouldy' or `mushroom', all separate de®nitions. The terms
de®ned are not exhaustive but encompass the commonest o€-odour sources encountered.

6. Grain classi®cation using electronic noses
In recent years there has been signi®cant research interest in the development of electronic
nose technology for food, agricultural and environmental applications (Gardner and Bartlett,
1994; Bartlett et al., 1997). Whilst not truly mimicking the natural olfactory system, electronic
noses borrow from the mechanism of natural olfaction. A range of general non-speci®c sensors
is exposed to a vapour and the pattern of response generated by all of the sensors is used to
characterise the odour. However, it must be stressed that the sensors do not exactly reproduce
the sensations encountered by the human nose. Consequently, noses must be trained or
calibrated against known odours in order to correlate them against human perceptions of
odour.
Typically an electronic nose consists of three elements: a sensor array which is exposed to
the volatiles, conversion of the sensor signals to a readable format, and software analysis of the
data to produce characteristic outputs related to the odour encountered. The output from the
sensor array may be interpreted via a variety of methods such as pattern recognition
algorithms, principal component analysis, discriminant function analysis, cluster analysis and
arti®cial neural networks to discriminate between samples. The data obtained from the sensor
array are comparative and generally not quantitative or qualitative in any way.
A variety of sensors are available for use in electronic nose systems. The most common types
encountered are metal oxide or conducting polymer based. Conducting polymers o€er the
advantage that they are able to respond rapidly and reversibly at ambient temperatures. They
are non-speci®c but can be highly sensitive, responding to a range of di€erent compounds. The
conductivity of the polymer changes when molecules are absorbed at the sensor surface. The
sensors respond strongly to the presence of alcohols, ketones, fatty acids and esters, but have
reduced responses to fully oxidised species such as CO2, NO2, and H2O.
Two types of studies have been carried out with electronic nose technology. Firstly, attempts
have been made to di€erentiate between spoilage fungi, based on their in vitro volatile

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production patterns, and secondly, studies have been carried out to try and distinguish between
di€erent grain samples and correlate the output with more traditional mould enumeration
techniques. Recently, in vitro studies on a milled wheat-based medium showed that it was
possible to distinguish between germinating spores of di€erent xerophilic grain and food
spoilage fungi within 48 h, prior to visible growth (Fig. 2, Keshri et al., 1998). The volatile
pro®les obtained from replicate plates were compared for six di€erent fungi using a 14 surface
response sensor array system. Butanol and agar blanks were used as controls. By using
discriminant function analysis (DFA) it was possible to di€erentiate between ®ve di€erent
species but not between some related Eurotium spp, based on the volatile pro®les.
Initial studies with a range of di€erent unmoulded dry grain types by examining the volatile
odours produced by dry grains placed in 9 cm Petri plates in approx. 750 ml bags using the
same electronic nose system suggested that it was possible to distinguish between some types,
using DFA, but that there was some overlap between rape seed and barley (Fig. 3; G. Keshri
and N. Magan, unpublished data, 1998). Some detailed studies have been carried out on grain
samples where accurate correlations have been made with traditional methods of analysing
grain contamination (Pisanelli et al., 1994, BorjessoÈn et al., 1996; Jonsson et al., 1997). The
UMIST group has previously successfully discriminated between good and bad samples of
wheat, with an unknown taint (Pisanelli et al., 1994) using a 20 element array of sensors using
conducting polymer technology and a neural network discrimination architecture.
Recently, BorjessoÈn and Olsson (1998) have examined the correlation between the ergosterol
and mycotoxin content of 40 barley samples of which approximately two thirds possessed some

Fig. 2. Discriminant function analysis of the di€erentiation of di€erent mould species, based on volatile pro®les
after growth for 48 h at 258C on a 2% wheat agar medium using an electronic nose apparatus (from Keshri et al.,
1998). Sampling of the head space odours was carried out above a 2% wheat meal agar medium containing
germinating spores in a 9 cm Petri plate placed in a 750 ml volume sealed polyethylene bag containing ®ltered air
using a 14 conducting polymer sensor array system.

N. Magan, P. Evans / Journal of Stored Products Research 36 (2000) 319±340

335

kind of o€-odour. An array of 10 MOSFET sensors (metal oxide semiconductor ®eld e€ect
transistors), 6 MOS sensors (metal oxide semiconductor (Taguchi type) sensors and a CO2
sensor were used. Samplers of approx. 33 g were used at 508C. A correlation with ochratoxin
content was achieved when 1977 harvested barley only was used, as well as with
deoxynevalenol content. Samples from grain harvested in di€erent years caused diculties with
correlations. Ergosterol was much easier to estimate, with a 0.75 correlation coecient
achieved when using partial squares to analyse the data.
A sensory array device based upon electrochemical sensors developed by Stetter et al. (1993)
was evaluated using samples previously evaluated by quali®ed USDA grain inspectors. The
array could be trained to classify the odours from the samples correctly 83% of the time using
a neural network simulation. The sampling protocol was quite complex and required preconcentration of volatile fractions from heated samples before measurements were taken.
BorjessoÈn et al. (1996) used metal oxide semiconductor ®eld e€ect transistor sensors
(MOSFET), SnO2 semiconductors and infrared detectors (to measure CO2 production in
samples) to evaluate mould activity in grain. They examined a range of normal, mouldy/musty,
acid/sour, and burnt samples (235 samples) of wheat, barley and oats and compared this with

Fig. 3. Discriminant function analyses of di€erent dry grains based on analyses of the head space above 25 gm
samples of dry grain in 9 cm Petri plates in a polyethylene bag containing ®ltered air using a 14 conducting polymer
sensor array system at 258C (G. Keshri and N. Magan, unpublished data, 1998).

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the two classes (good, bad) used by grain inspectors. They found that the electronic nose
correctly classi®ed 75% of samples when using the four classes, and 90% with the two-class
system, i.e. good or bad only.
Jonsson et al. (1997) described the use of an electronic nose to di€erentiate between various
samples of oats, barley and rye quality. The general categories used were based on the Swedish
Board of Agriculture classi®cations which are summarised as normal; musty; mouldy; acid;
sour; burnt; or foreign and the intensities as weak, pronounced or strong (Statute Book, 1991).
Samples of wheat with varying levels of ergosterol and fungal and bacterial cfus were also
evaluated. Good correlations between the electronic nose system and inspectors were found for
mouldy, weakly and strongly musty oats. Reasonable correlations were also found when oats,
barley and rye were presented as good/musty mixtures leading to the conclusion that a basis
for describing odour intensity was achievable. There were also some correlations between
volatile patterns and quantitative measures of fungal growth as measured by the biochemical
marker ergosterol, and the total fungal cfu counts with the arti®cial neural network predicted
values.

7. Discussion
The key to e€ective utilisation of the new technology such as electronic noses is the
capability for early and rapid detection of mould activity to enable remedial measures to be
taken, and to be able to e€ectively distinguish between good and poor quality grain.
Correlations with existing criteria used for discriminating grades are also essential. Trials
carried out by one electronic nose company (Osmotec plc) with grain graded by USDA
inspectors displayed broad correlation with the descriptors available, but signi®cant variations,
particularly within the musty grade (Dr A. S. McNeish, Osmetec plc, personal communication
1999). An important factor to consider when using an electronic nose system is that generally
its sensitivity spectrum is di€erent from the human nose. Thus an electronic nose will not
identify odours using identical criteria to a human panel. It can be seen from Table 5 that
broad correlations exist between o€-odour classes and the presence of speci®c fungal infections.
The odours described by Smith et al. (1994) are intended purely as reference odours. They are
examples of the kind of smell encountered when classifying grain rather than actual
components of the grain odour itself.
The majority of fungi produce volatiles that are identi®ed with musty odours in grain. The
dominant class of compound in this category is the C-8 alcohols. The primary odour expected
for musty grain would therefore be associated with a mushroom-like smell (the C-8 alcohols)
with subtle taints of other associated compounds such as aromatics and lower molecular
weight alcohols. Whilst Seitz et al. (1998) identi®ed esters as sour descriptor components, only
ethyl acetate was found in other studies of fungal infection of grains.
Potential may exist using electronic nose technology for the early detection of insect odours.
However, they are less easily replicated than fungal ones. Insect odours currently occur in two
categories (sour and musty by the USDA de®nition) which is unsatisfactory. The source and
type of odours de®ning these categories need investigation and at least one de®nition needs to
be reclassi®ed. Some interference can occur from fumigant/insecticide/fertiliser odours that are

N. Magan, P. Evans / Journal of Stored Products Research 36 (2000) 319±340

337

often used during the harvesting and storage of grain. Therefore, grain treated with these
common chemicals can easily be evaluated. This category (within COFO) should consequently
be de®ned easily.
In trying to apply an electronic nose to the problem of classifying o€-odours in grain a
consistent standard is required. The broad categories o€ered by the USDA system are
applicable but the sub-gradings need re®ning, those within the musty category particularly so,
since ``mouldy'' is a broad sub-section with a range of potential causes. The ``insect'' category
is best retained in one category only (musty) unless the description in sour is rede®ned with
another term or speci®c type of insect infestation.
Descriptive surrogates are available that represent most of the sub-categories (Smith et al.,
1994) which should facilitate better correlation between electronic nose measurements and the
grading of inspectors. However, these surrogates are not truly representative of the odours
encountered. Better surrogates are required based upon the actual volatiles encountered. At
present the USDA grading system does not contravene any of the other systems used. The
Swedish system separates mouldy from musty, and adds an acid category, which could be
placed in the COFO category. Similarly, the de®nitions of Seitz et al. (1998) are classes and
sub-classes of the USDA system. No classi®cation is o€ered in the ISO/BSI European
standard.

8. Conclusions
This review has shown that a wide variety of volatiles are produced by fungi, either in vitro
or when growing on agricultural grain substrates. Potential exists for distinguishing between
species of fungi based on characteristic volatile patterns, which may be important when key
spoilage fungi may be responsible for the production of harmful mycotoxins. It may be
possible to use electronic nose systems to try and distinguish between grain colonised by
mycotoxigenic and non-mycotoxigenic species, and this area needs further investigation.
Generally, bacteria are not a problem in intermediate moisture content stored cereals, and
thus more detailed focusing is required on fungi, particularly xerophilic and xerotolerant
species known to in