DON Occurrence in Grains:
A North American Perspective
ABSTRACT
In agricultural commodities, the occurrence of deoxynivalenol (DON) has been reported all
over the world, with levels varying among grain types and years of production. The grain supply
chain, including growers, buyers, and end users, have effectively managed DON with strategies
to control this issue systematically. The safety of consumers is ensured through use of these management strategies. This is observed in this review of the North American systems. This article
describes the occurrence and management of DON in North America, which is accomplished
by 1) a review of the toxicological effects of DON; 2) a review of publically available data and
introduction of new information regarding the occurrence of DON in wheat, maize, and barley
in North America, including variability due to growing regions, grain varieties, and year of
production; 3) an overview of industry practices to reduce DON contamination from field
through milling when necessary; 4) a review of how all in the value chain, including growers,
buyers, and end users, have effectively managed DON for more than 20 years; 5) a description
of current maximum limits associated with DON; and 6) the economic impact of any potential
changes in international regulations. This article focuses on wheat, maize, and barley grown in
Canada and the USA, as these two countries are the major exporters of these grains in North
America (1).
AUTHORS
Andreia Bianchini, The Food
Processing Center, Food Science and
Technology Department, University of
Nebraska – Lincoln, NE, USA
Richard Horsley, Department of Plant
Sciences, North Dakota State
University, ND, USA
Maia M. Jack, CPGglobal, LLC, USA
Brent Kobielush, General Mills, MN,
USA
Dojin Ryu, Bi-State School of Food
Science, University of Idaho/Washington
State University, ID, USA
Sheryl Tittlemier, Grain Research
Laboratory, Canadian Grain
Commission, Winnipeg, MB, Canada
William W. Wilson, Department of
Agribusiness and Applied Economics,
North Dakota State University, ND, USA
Hamed K. Abbas, USDA-ARS, NBCL,
Stoneville, MS, USA
Susan Abel, Food & Consumer
Products of Canada, Toronto, ON,
Canada
Gordon Harrison, Canadian National
Millers’ Association, Ottawa, ON,
Canada
http://dx.doi.org/10.1094/CFW-60-1-0032
©2015 AACC International, Inc.
32 / JANUARY–FEBRUARY 2015, VOL. 60, NO. 1
J. David Miller, Department of
Chemistry, Carleton University,
Ottawa, ON, Canada
W. Thomas Shier, Department of
Medicinal Chemistry, University of
Minnesota, MN, USA
Glen Weaver, Ardent Mills, Omaha,
NE, USA
PUBLIC REVIEWERS
Dave Katzke, General Mills, MN, USA
Dirk E. Maier, Kansas State University,
Grain Science & Industry, Manhattan,
KS, USA
Jim Pestka, Food Science and Human
Nutrition/Microbiology & Molecular
Genetics, Michigan State University,
East Lansing MI, USA
LIAISONS
Benjamin Boroughs, NAMA Liaison,
Director of Regulatory and Technical
Affairs
Anne R. Bridges, AACCI Liaison,
Director of Technical Resources
Introduction
Fungi associated with production and
storage of grains in North America include the genera Fusarium, Penicillium,
and Aspergillus. Mycotoxins are secondary metabolites of these filamentous fungi that can cause illness in humans and
animals through absorption, ingestion,
or inhalation (2). Since grains, in general,
provide an ideal substratum (medium)
for mold growth and mycotoxin production, close attention must be paid to
their food and feed safety. Additionally,
grains and grain-based products represent one of the major sources of carbohydrates for humans and livestock (3);
therefore, their safety is of primary concern.
The prevalence of mycotoxins in grains
is usually associated with the occurrence
of the causal organisms and related causal
factors, such as temperature and moisture,
in both the field and in storage (2,3). Deoxynivalenol, also referred to as DON or
vomitoxin, is one of a broad category of
mycotoxins known as trichothecenes.
DON is produced mainly by F. graminearum and F. culmorum, especially in
grains. Production of DON by F. pseudograminearum has also been reported in
warmer climates, although with less frequency than the major producers (2).
F. graminearum is an important plant
pathogen that causes Fusarium head
blight (FHB) in wheat and barley and ear
rot in maize. This leads to DON contamination of these crops during crop growth,
prior to harvest. DON is found globally in
these crops, as well as in rye, oats, and
rice (4–6).
To minimize human exposure to DON
via the consumption of contaminated
grain-based foods, regulatory organizations have established advisory levels,
guidelines, and regulations for various
commodities and foods. In North America, the US-FDA has imposed a restriction of 1 mg/kg on processed grains (7).
Health Canada has set regulations of
2 mg/kg in uncleaned soft wheat for use
in nonstaple foods and 1 mg/kg in uncleaned soft wheat for use in baby foods;
however, these regulations are currently
under review.
Toxicity and Deoxynivalenol (DON)
DON was isolated from moldy barley
by Japanese scientists in 1973 and redescribed as “vomitoxin” by USDA researchers in the same year (8–12). Since then,
toxicologists have sought to understand
the acute and chronic effects that may be
associated with the ingestion of DON.
The principal health risks of DON are
associated with acute dietary exposure,
which is caused by intake of large amounts
of DON within a short time frame. Shortly after ingestion of heavily contaminated
grains, DON causes vomiting and feed
refusal in animals, especially swine, and
causes gastroenteritis with vomiting in
humans (13–15). To date there is no evidence of occurrence of adverse human
health outcomes in North America associated with acute dietary intake of DON.
The chronic effects of dietary intake of
DON include weight gain suppression,
anorexia, and altered nutritional efficiency
(16). It has also been shown to adversely
affect immune systems (17). With any
toxicological risk assessment, it is important to understand the absorption, distribution, metabolism, and elimination of a
given toxin or toxicant (18). Unlike other
toxins, such as dioxin and other fat-soluble
compounds, DON is water soluble, which
allows it to be rapidly cleared in vivo. In
rodents and swine, which are frequently
used to study the adverse effects of DON
(9), this toxin and its metabolites are absorbed and excreted quite rapidly (8). Specifically, studies have shown that 25% and
64% of radiolabeled, orally administered
doses of DON and known metabolites in
rats were detected within 96 hr in urine
and feces, respectively (8,19). Subsequent
analyses of the tissues in these rats showed
that no radioactivity was retained in the
tissues after 96 hr (8,19). Similarly, in pigs
DON is rapidly excreted, with a plasma
half-life of 3.9 hr and no significant retention in the tissues (8,19–23).
Acute exposure to DON is most notably
characterized by emesis (8,9). A few outbreaks of grossly contaminated grain in
Japan and Korea (1940s–1960s) (24), China
(1984–1991) (25), and India (1988) (26)
have been described, with the symptoms of
the disease being typical of illnesses associated with DON exposure. However, current
global regulations, better crop management
techniques, improved resistance to FHB,
and the advancement of milling practices
have considerably reduced the number of
acute incidences of DON-related illnesses.
Additionally, animal studies have shown
that DON most notably exerts its effects
when exposure occurs in single or multiple bolus doses (9). The latter does not
represent a likely scenario for the vast
majority of the global population today
who can readily access minimally contaminated sorted and cleaned grains that
very rarely result in acute incidences.
In contrast, as previously mentioned,
high chronic exposure has been shown to
cause growth retardation, alter immune
function, and interfere with reproduction and development (8,9). In 2001, the
Joint Food and Agriculture Organization/
World Health Organization (FAO/WHO)
Expert Committee on Food Additives
(JECFA) proposed a provisional maximum tolerable daily intake (PMTDI) for
DON of 1 µg/kg body weight (bw) based
on the growth effects associated with DON
exposure (8,27,28). In the following decade, investigations into the mechanisms
of the effect of DON on weight gain were
pursued and understood (8,9,29–32). In
2010, JECFA extended the PMTDI to apply to both DON and its acetylated derivatives and concluded that mean estimates of national exposure to DON were
below the PMTDI of 1 µg/kg bw (8,27,28).
Likewise, recent national assessments determined that exposures to DON were
below levels of concern. Based on these
collective assessments, the current global
limits on DON are not only protective
from a chronic ingestion standpoint, but
affirm that a level of 1 mg/kg on semiprocessed grains is safe, and levels proposed
for unprocessed raw grain would have no
benefit from a public health safety perspective, as described further below.
Although DON has been associated with
a number of acute (8,9,13,25) and chronic
(8,9) health events, the likelihood of such
occasions remains relatively rare. In the
USA, for instance, advisory levels for grain
containing DON have been in place since
1982 (7). In fact, in 1993, an outbreak of
DON in wheat led to the elimination of a
previously held limit of 2 mg/kg on unprocessed raw wheat and wheat by-products. After this incident the US-FDA decided to rely on purchasing and cleaning
practices to significantly reduce DON
levels to the 1 mg/kg maximum for finished wheat products, including the following: flour, germ, and bran (7). Since
then, the US-FDA continues to recognize
an advisory limit of 1 mg/kg on finished
food products containing wheat and wheat
by-products. A level that remains protective for the USA population and USA export markets. The same is true for advisory levels on finished grain established
by regulatory agencies elsewhere.
DON Occurrence in North America
The body of available research indicates
that acceptably low DON levels in unprocessed grain products can be achieved in
exports and shipments for domestic use in
most crop years. These levels are achieved
through the aggregation of grain stocks
and blending that occurs along the supply
chain, monitoring of DON levels in deliveries of grain shipments to processors, and
a variety of grain sorting and cleaning
technologies available to processors. The
North American grain industry’s experience suggests that adoption of unduly
Fig. 1. Schematic of the North American grain-handling supply chain.
CEREAL FOODS WORLD / 33
restrictive maximum limits for DON in
unprocessed grains could actually hinder,
rather than assist in, the management of
DON levels in foods and feeds, while contributing to significantly higher costs to
the entire supply chain.
Wheat. Due to its importance as a foodstuff and as an exported grain, the bulk of
DON monitoring and surveillance data
for grains pertains to wheat. DON is observed in wheat at various stages of the
North American grain-handling chain, a
general schematic of which is shown in
Figure 1.
Wheat quality, including the occurrence of DON, is closely monitored
throughout the North American grainhandling chain. For example, at the early
to middle stages of the handling chain,
DON is determined in soft and hard
wheat delivered to USA wheat milling
facilities by truck or railcar. In Figure 2,
data from more than 42,100 samples
representing wheat harvested throughout
12 consecutive seasons (2003–2014) from
various production areas in the USA and
shipped to USA milling facilities are
summarized. Among the samples analyzed, 81.1% were below the limit of quan-
titation (LOQ) of the methods used
(0.3–0.5 mg/kg).
To obtain each of the samples represented in Figure 2, the sampling process
suggested by the USDA Grain Inspection,
Packers and Stockyards Administration
(GIPSA) for drawing a representative
sample from a lot of grain was followed.
Toxin levels were determined by enzymelinked immunoassay (ELISA). The method of choice (manufacturer and test type)
varied from one milling facility to another; however, all of them used GIPSAapproved methods (e.g., Neogen 2/3,
5/5, Q+) with LOQ varying from 0.3 to
0.5 mg/kg. In this data set, reported values below the limit of detection (LOD)
of the method used were assigned a numerical value of “zero” to calculate average values. For those reported values that
were below the LOQ but above the LOD,
a numerical value of LOQ/2 was assigned
to calculate average values. This data set
was used to produce Figures 2, 3, 7, 13,
and 14.
The annual average levels of DON
found in USA wheat delivered to milling
facilities were low and clustered around
0.5 mg/kg. However, as illustrated by the
Fig. 2. Annual average deoxynivalenol (DON) concentrations in wheat across all USA growing regions and classes delivered to milling facilities from the 2003 through 2014 crop years (n = 42,131).
Whiskers represent one standard deviation for the DON detected in each year. “Estimated Tonnes”
lists the amount of wheat represented by the samples analyzed each year.
Fig. 3. Levels of deoxynivalenol (DON), at the processor level, in soft and hard wheat harvested in
the Midwestern and Northeastern regions of the USA from the 2003 through 2014 seasons. Whiskers represent one standard deviation for the DON detected in each year. “Estimated Tonnes” lists
the amount of wheat represented by the samples analyzed each year.
34 / JANUARY–FEBRUARY 2015, VOL. 60, NO. 1
standard deviations in Figure 2, DON
concentrations in individual samples in a
given year do vary and can exceed 2 mg/kg.
For example, in 2014 the average level of
DON was 0.85 mg/kg, and the levels of
DON measured in individual samples
varied from LOD to 20.0 mg/kg. This
variation can be seen more clearly in Figure 3, where DON levels at the processor
level in soft and hard wheat harvested in
the Midwestern and Northeastern regions
of the USA from the 2003 to 2014 seasons
are shown in more detail. Depending on
the year and region, up to 14.3% of hard
wheat samples showed levels of DON
above 2 mg/kg, while up to 62% of soft
wheat samples showed levels that high.
Overall, during the period surveyed 1.7%
of the hard wheat samples analyzed had
levels of DON above 2 mg/kg, while more
than 30% of the soft wheat samples had
levels of DON that exceeded 2 mg/kg.
These variations are discussed further
later in this article.
The occurrence of DON in wheat taken
at earlier stages in the handling chain has
also been observed in Canadian wheat
(Fig. 4) and durum (Fig. 5). DON was
measured in 72% and 68% of wheat and
durum samples, respectively, taken on
farm and in 58% and 79% of wheat and
durum samples, respectively, taken from
primary elevator stocks before final
blending of grain to meet quality specifications was performed. At later stages of
the handling chain, <50% of wheat and
durum samples contained quantifiable
concentrations of DON. There were some
instances of high concentrations of DON
(i.e., >5 mg/kg) observed in individual
Canadian samples, as with USA samples
(Figs. 2 and 3). These instances occurred
in samples taken from on farm, primary
elevator stocks, or elevator loadings but
not at later stages in the grain-handling
chain. The average DON concentrations
in exported Canadian wheat and durum
were both <1 mg/kg.
The data incorporated into Figure 4
represents almost 13 million tonnes of
wheat at the farm stage and more than
15 million tonnes exported at the end of
the handling chain from 2009 through
2014, which encompasses years with
higher and lower incidences of FHB (33).
The data used to build Figure 4 included
samples from primary elevator stock
(n = 3,281), elevator loading (n = 572),
and terminal stock (n = 323) stages that
were analyzed using ELISA or quantitative lateral flow test methods, with an
LOD of 0.5 mg/kg. A small number of
on-farm samples (n = 16) were analyzed
using ELISA with an LOD of 0.25 mg/kg;
the remaining samples (n = 29,254) were
analyzed using ELISA with an LOD of
0.5 mg/kg. Shipments were analyzed
using ELISA (n = 130; LOD of 0.5 mg/kg)
and gas chromatography–mass spectrometry (n = 499; LOQ of 0.05 mg/kg) (34).
The data presented in Figure 5 represent durum analyzed in 2010 through
2014, mostly using ELISA or quantitative
lateral flow test methods with an LOD
of 0.5 mg/kg to evaluate samples at the
farm (n = 2,297), primary elevator stock
(n = 120), elevator loading (n = 554),
terminal stock (n = 496), and shipment
(n = 407) stages. Some on-farm samples
(n = 53) were analyzed using an ELISA
with an LOD of 0.25 mg/kg. In addition,
some shipment samples (n = 68) were analyzed using gas chromatography–mass
spectrometry (LOQ of 0.05 mg/kg) (34).
It is very difficult to directly compare
the degree of DON occurrence in North
American grains based on reports of
DON in grains grown in other grainproducing regions, as different sampling
schemes, sample preparation techniques,
sample types, analytical methods, and
production years all affect the concentrations of DON observed. Unfortunately, these details regarding samples, their
provenance, and methods of analysis are
often not provided in the scientific literature or are not provided in enough detail.
However, in general, average reported
concentrations for DON in wheat, maize,
and barley grown in North America are
similar to those reported for these grains
grown in other regions.
A broad compilation of data on the
global occurrence of DON in grains is
provided in Figure 6 (35–67). In this figure the average values for reported DON
concentrations in different commodities
throughout the world are presented, as
reported by more than 30 scientific papers published in the literature. These
reports included samples from more than
30 countries in different regions of the
world, such as Africa, the Americas,
Asia, the Middle East, Australia, and
Europe. The work in these reports analyzed samples mostly described as “field
samples” or recently harvested grain, with
a small percentage of the samples being
described as “commercial samples.” The
majority of the studies also indicated that
the sampling followed an opportunistic
approach, with very few being part of a
comprehensive monitoring program for
DON in grains. This may result in data
Fig. 4. Deoxynivalenol (DON) occurrence in Canadian wheat along the grain-handling chain.
Amount of grain represented for Terminal Elevator Stocks is not available.
Fig. 5. Deoxynivalenol (DON) occurrence in Canadian durum along the grain-handling chain.
Amount of grain represented for Terminal Stocks is not available.
Fig. 6. Reported occurrence of deoxynivalenol (DON) in various cereal grains grown around the
world (35–67).
CEREAL FOODS WORLD / 35
being presented that are not truly representative of the occurrence of DON in
grain from a particular region or time
period. Nonetheless, even though the
method of analysis varied from study to
study and included both rapid screening
and comprehensive instrumental techniques such as ELISA and liquid chromatography–tandem mass spectrometry, with
LODs varying from 0.01 to 180 µg/kg,
the averages presented in Figure 6 illustrate that, among the commodities described, the levels of DON reported are
similar. This applies for the different
areas of the world, with the exception of
some reports of high levels of DON in
wheat in Africa. Wheat samples from
Africa reported in this figure were collected in Morocco, Tunisia, and Kenya
and reported in three independent studies (40,44,67). Overall, 856 wheat samples
were collected in these three countries,
and most of the contamination seemed
to be associated with samples from Tunisia (average DON levels of 17.9 mg/kg).
More information regarding the occurrence of DON in the Republic of South
Africa is presented in Box 1. The differences among regions and grains are very
typical of mycotoxin occurrence, as it
varies based on the use of Good Agricultural Practices (GAPs), grain type and
cultivar grown, toxigenicity of species
and fungal strains associated with the
crop, and weather (temperature and precipitation).
Effects of Growing Seasons, Regions,
and Years
The presence of DON in wheat is governed by a number of factors that can
vary among growing years and regions.
These factors include environmental
growing conditions such as temperature
and precipitation, wheat type and cultivar
grown, as well as the species and chemotype (subpopulation) of F. graminearum
infecting the grain.
Figure 2 illustrates how DON can vary
among growing years. Since wheat-growing regions are large in Canada and the
USA, there can also be considerable variation in the presence of DON within growing regions. The annual average DON
concentrations in wheat across all USA
growing regions and classes delivered to
milling facilities peaked at 0.85 mg/kg in
2014 and was at its lowest at 0.27 mg/kg
in 2008. The effect of harvest year is further illustrated by Figure 3, where levels
of DON in wheat, based on the data set
provided by milling facilities in the USA,
are reported for two growing regions
(Midwest and Northeast) and two wheat
classes (soft and hard) for different years
(2003–2014). As noted by the bars in the
chart, the Northeast is more prone to
variation from year to year, regardless of
the type of wheat grown, while the Midwest seems to show more variation for
certain classes. Because mycotoxin production by molds is driven by intrinsic
and extrinsic factors, the environmental
conditions encountered by the grain in
the field have a great impact on the mycotoxin levels detected in the grain. Among
the intrinsic factors is mold species (or
strains/chemotypes), while the extrinsic
factors include temperature, water activity, nutrient availability, and chemical
agents (68). As a result, it is not uncommon to observe DON levels in grain varying greatly from year to year. Higher levels of DON in wheat are usually associated with excessively wet periods close to
the flowering stage, which is 6–8 weeks
prior to harvest.
Another example of such variation in
DON levels with harvesting year is illustrated by the data presented by Martínez
Box 1 – Deoxynivalenol Incidence in Africa
In developing nations with many low- to middle-income and high-density populations, grains represent a primary food source.
If not controlled properly, grains are predisposed to contamination by several fungi that can produce toxins: for instance, deoxynivalenol (DON). Figure 1 in this box shows overall DON levels in maize and wheat as reported in a survey conducted in the
Republic of South Africa (RSA) by the Southern African Grain Laboratory (SAGL) from 2009 to 2014. Five harvesting seasons
were evaluated, including 36 grain production regions (Fig. 2). Altogether these provinces account for an approximate production
of 1.85 million tonnes/season for wheat and 9.5 million tonnes/season for maize. Every growing season, SAGL randomly selects
wheat and maize samples for mycotoxin analysis that represent different growing regions as well as different classes and grades.
For the period described here, mycotoxin analysis was performed using a validated multimycotoxin screening method (UPLCMS/MS). The highest incidence of DON in maize was reported in a sample from the 2009–2010 growing season at
1.8 mg/kg; the highest incidence reported in wheat was in a sample from the 2012–2013 growing season at 0.4 mg/kg.
Acknowledgments: Information reported is courtesy of the Maize Trust and the Winter Cereal Trust (African industry
organizations) via SAGL.
Fig. 1. Mean annual DON incidence (whiskers indicate standard deviation) in maize and wheat in the RSA.
36 / JANUARY–FEBRUARY 2015, VOL. 60, NO. 1
Fig. 2. RSA crop production regions.
et al. (50). Data collected throughout
two harvesting seasons (2012–2013 and
2013–2014) in the Pampas region of
Argentina showed that in some years
DON levels were higher than others, on
average by 99.7%. Researchers have attributed the differences to weather-related
events (Box 2).
Variation in DON content in Canadian
wheat shipments also occurs from year to
year (69). Variation in DON concentrations in durum and wheat among years
appears to be related to the quality of the
grain in the shipments, with higher DON
concentrations seen in grain downgraded
due to Fusarium damage. This work also
reinforces the theory that annual variation in DON content occurs throughout
the Americas.
These variations observed among years
may be exacerbated or more difficult to
predict due to climate change. A shift in
environmental conditions could alter Fusarium populations. According to a re-
Box 2 – Deoxynivalenol Incidence in Argentinian Wheat
The sporadic nature of Fusarium head blight and other diseases caused by Fusarium spp. affect different commodities throughout
the world, and efforts have been made to reduce the presence of the causative agents. Such is the case for Argentina, where empirical forecasting models have been evaluated to estimate the spatial distribution of F. graminearum, a deoxynivalenol (DON)
producing mold. These models predict the incidence of the disease based on environmental conditions such as maximum and
minimum temperature, precipitation, and relative humidity. While validating the models in the Pampas region of Argentina, two
harvesting periods were evaluated, including several wheat cultivars. The models were very accurate and correlated well with the
mold incidence and levels of DON detected in the samples (Figs. 1–4). However, one interesting point to highlight from this study
was a large decrease, on average (99.72%), in the levels of DON from 2012–2013 to 2013–2014, with no interventions applied by
the researchers. Even though predictive models and other good agricultural practices have an impact on the quality of harvested
grain, one cannot disregard many environmental factors unaccounted for that may impact DON levels. Research on the performance of the models was performed at the Agricultural Experimental Station Oliveros and the National Institute of Agricultural
Technology in Argentina.
Fig. 1. DON incidence in the 2012–2013 harvest (Lat –32.55, Long –64.32).
Fig. 2. Spatial distribution obtained by the Agricultural
Experimental Station model for Fusarium incidence in
the 2012–2013 harvest.
Fig. 3. DON incidence in the 2013–2014 harvest (Lat –32.55, Long –64.32).
Fig. 4. Spatial distribution obtained by the Agricultural
Experimental Station model for Fusarium incidence in
the 2013–2014 harvest.
CEREAL FOODS WORLD / 37
view prepared by Wu et al. (70), the Fusarium populations in North America have
changed greatly in a period of 10 years.
Historically, the 15-ADON chemotype of
F. graminearum has been predominant in
North America and 3-ADON in South
America and Europe. However, the Fusarium populations in North America have
been changing. For example in North Dakota, the 3-ADON chemotype comprised
about 3% of Fusarium on wheat prior to
2002 and up to 44% of isolates collected
in 2008. These population shifts may
impact the levels of DON found in the
grain at harvest, since greenhouse studies
have shown that 3-ADON isolates produce higher levels of DON in FHB-susceptible and -resistant wheat varieties than
do 15-ADON isolates (71). In addition,
shifting environmental conditions could
alter insect populations and impact fungal
infection and mycotoxin production.
Fig. 7. Average deoxynivalenol (DON) concentrations at the processor level in soft and hard
wheat harvested in different regions of the USA from the 2003 through 2014 harvest seasons.
Averages represent 2,818 soft wheat samples and 39,313 hard wheat samples.
Fig. 8. Average deoxynivalenol (DON) concentrations in Canada western red spring wheat grown
in various crop regions of the Canadian Prairies.
38 / JANUARY–FEBRUARY 2015, VOL. 60, NO. 1
The effect of growing region, which is
mostly associated with the climatic conditions of a region, is clearly illustrated in
Figures 7 and 8. The map in Figure 7 is
based on data gathered from milling facilities in the USA. In general, the samples
were collected and analyzed using GIPSAapproved methods. The map in Figure 8
is based on samples collected from the
Canadian Prairies from 2008 through
2013 as part of the Canadian Grain
Commission’s Harvest Sample Program.
The Canadian samples were analyzed
using gas chromatography–mass spectrometry according to the method of
Tittlemier et al. (69).
The maps in Figures 7 and 8 illustrate
the variation in DON occurrence in wheat
from different growing regions in North
America. In the USA, soft wheat from the
Midwestern, Northeastern, and Southern
regions had higher levels of DON than hard
wheat from the same regions (P < 0.05),
with hard wheat representing 65% and
soft wheat 19% of total USA wheat production during the period surveyed
(2003–2014). Among soft wheat samples,
the highest levels of DON were found in
the Midwestern and Northeastern regions (P < 0.05), with levels, on average,
2–3 times higher in those regions than
the levels observed in the Southern part
of the country. When hard wheat samples
were compared, the Northeastern region
showed the highest levels, the Midwestern
and Southern regions showed similar levels
of DON, and the Western region showed
the lowest levels of DON (P < 0.05). For
this analysis, the means and standard deviations for each wheat class/region subset
were calculated and compared pairwise
using t-test statistics.
In western Canada, higher average
DON concentrations have been observed
in hard red spring (HRS) wheat grown in
the eastern prairies of Manitoba (Fig. 8)
compared with HRS wheat grown in western Saskatchewan and Alberta. These regional differences are driven by environmental factors such as temperature and
precipitation that predominate around the
time of anthesis (and thus affect Fusarium
infection), as well as the geographical distribution of DON-producing Fusarium
species. According to Cowger et al. (72)
and Cowger and Arellano (73), DON levels, percentage of Fusarium-infected kernels, percentage of Fusarium-damaged
kernels, and FHB symptoms at harvestripeness increased with an increasing number of wet days following anthesis. Canadian surveys have shown that the main
DON producer, F. graminearum, is present at higher levels in wheat from the eastern prairies, whereas other species such as
F. poae and F. avenaceum are more important in the western prairies (74).
Barley. Limited information exists
about levels of DON in North American
barley. In one study, Schwarz et al. (75)
collected barley samples at harvest throughout all barley-growing regions of North
Dakota and Minnesota. The samples used
in their survey were part of regional crop
surveys and covered the period from 1993
until 2003. Samples were cleaned using
a Carter Day Dockage Tester (Seedburo
Equipment Co.), but no further processing or grading was done prior to DON
analysis. The levels of DON observed in
the samples are summarized in Table 1.
The average DON levels detected in the
samples varied from 0.5 to 10.3 mg/kg.
In most of the surveyed years as least
one-third of the samples had levels in
excess of 3 mg/kg, with some years showing as much as 59% of the samples with
those levels of contamination. Variation
from year to year in DON levels and incidence is evident and illustrates once again
the volatility of the natural occurrence of
such toxins.
Data on the occurrence of DON in
samples of Canadian barley are presented in Figure 9. These samples were analyzed in 2009 through 2014, mainly using ELISA or quantitative lateral flow
test methods, with LOD of 0.5 mg/kg, to
analyze samples at the farm level (n =
2,237), primary elevator stock (n = 118),
and shipment (n = 14) stages. One onfarm sample was analyzed using ELISA
with an LOD of 0.25 mg/kg. In addition,
some shipment samples (n = 26) were
analyzed using gas chromatography–mass
spectrometry (LOQ of 0.05 mg/kg) (69).
The mean DON concentration for on-farm
samples was 0.7 mg/kg, which is within the
range of means reported for comparable
harvest samples presented in Table 1.
Maize. Data on the occurrence of DON
in North American maize are presented
in Table 2. The reports described in the
table used different sampling strategies
and methodologies to determine the level
of contamination. For example, in the USA
maize report on export data (76) a proportionate stratified sampling scheme was
used to ensure samples taken for analysis
were representative of USA yellow maize
exports, the samples were prepared for
analysis according to the GIPSA DON
handbook, and an ELISA test kit (GIPSA
approved) with an LOD of 0.3 mg/kg was
used. The Canadian maize export data
(69) were based on random sampling of
shipment loads and gas chromatography–
mass spectrometry analysis with an LOQ
of 0.05 mg/kg. The Canadian field data
(76–80) were obtained through random
sampling of 10 consecutive ears at 2 locations per maize hybrid grown within a
field. Another fundamental difference
among the reports is the sampling stage.
For example, the data relating to USA
and Canadian exports are from samples
taken at the end of the grain-handling
chain (after the grain has been blended
and cleaned), whereas the Ontario field
samples were taken at the beginning of
the handling chain. This lack of consistency with regard to the sampling point
stage in the grain-handling chain, test
methods used for DON analysis, and data
reporting format preclude direct compari-
son of the results from the various studies.
Nonetheless, the occurrence of DON in
maize cannot be ignored, and the results
summarized in Table 2 provide an indication of DON contamination observed
over the past 4 years in maize samples
from the beginning and end of the grainhandling chain. Based on this data, the
majority of DON in USA- and Canadiangrown maize is present at concentrations
lower than 2 mg/kg, with a small number
of instances where DON concentrations
exceeded 2 mg/kg. Additionally, as seen
in the Ontario field data in Table 2, the
proportion of these higher concentrations
will vary from year to year.
Management of DON in Wheat, Barley,
and Other Small Grains
The North American grain supply chain,
which includes growers, grain buyers, and
Table 1. Levels of deoxynivalenol (DON) in barley samples harvested in Minnesota and North
Dakota (adapted, with permission of the American Society of Brewing Chemists, from Schwarz
et al. [75])
Fig. 9. Deoxynivalenol (DON) occurrence in Canadian barley along the grain-handling chain.
LOQ = limit of quantitation; LOD = limit of detection.
CEREAL FOODS WORLD / 39
end users, has developed and refined management practices and tools to control
FHB and DON with the benefit of three
decades of modern experience in production, handling, and processing. These
practices are effective in safeguarding the
health of consumers.
Results from monitoring and surveillance activities indicate that acceptably
low DON levels in unprocessed grain
products can be achieved in exports and
shipments for domestic use in most crop
years following current advisory levels
and guidelines for DON. These levels are
achieved through the aggregation and
blending of grain stocks that occurs along
the supply chain, monitoring of DON
levels in deliveries of grain shipments to
processors, and a variety of grain sorting
and cleaning technologies and methods
that are available to processors.
All participants in the grain value chain
in Canada and the USA (Fig. 1) effectively
manage DON levels in wheat and other
grains. Coordinated research across years
and dozens of locations by scientists in both
countries ensures that research occurs in
all market classes of wheat and barley and
for growers in all at-risk growing areas (81).
The research also ensures that the recommendations made to growers are evidencebased. Growers (producers) use an integrated approach to reduce the likelihood
of DON in wheat and barley that includes
sowing resistant cultivars, use of fungicides, choice of previous crop, method of
tillage, and disease forecasting (82–88). In
maize, management of Gibberella ear rot
with similar cultural practices has had a
limited effect in reducing disease development and mycotoxin accumulation (89).
However, maize hybrids do vary in their
resistance to infection, and growers are
encouraged to compare these differences
when choosing a hybrid to plant (90).
Following the severe epidemic of FHB
in wheat and barley in Canada and the
USA in 1993, breeding for reduced DON
became a higher priority (91). The use of
disease screening nurseries and collaborative regional testing of advanced breeding
lines and cultivars became routine and
still continues today. Since the early 2000s,
wheat and barley breeders have been successful in releasing cultivars with improved
FHB resistance and reduced DON accumulation to replace susceptible cultivars
(92–101). FHB severity and/or DON accumulation in the improved cultivars has
been reduced by more than 50% compared
with the susceptible checks (controls),
and growers have been growing the new
cultivars. For example, in the HRS wheat
growing areas of Minnesota, North Dakota, and South Dakota in the USA, the
frequency of FHB-susceptible HRS culti-
Table 2. Reported occurrences of deoxynivalenol (DON) in North American maize (69,76–80)
40 / JANUARY–FEBRUARY 2015, VOL. 60, NO. 1
vars sown decreased from 76% in 1999 to
21% in 2011 (102). The sources of resistance in the improved cultivars includes
exotic sources such as Sumai #3 from
China and native resistance already
present in existing breeding germplasm
(103,104). The incorporation of quantitative trait loci (QTL) conferring FHB resistance by wheat breeding programs in
Canada and the USA, including the QTL
FHB1 from Sumai #3, has been enhanced
through marker-assisted selection (105).
Appropriate crop rotation to reduce
DON accumulation is a requirement that
is well-understood by grain growers in
high-risk areas (86). Additionally, combining improved cultivars with fungicides
and optimal spray technology at flowering
provides the best management practice
for reducing the risk of DON in wheat
and barley, as demonstrated by Wegulo
et al. (84) (Fig. 10) and others (106–108).
Fungicides with proven effectiveness
in reducing DON accumulation include
tebuconazole (Folicur), prothioconazole
(Proline), metconazole (Caramba), and
a combination of prothioconazole and
tebuconazole (Prosaro) (109). In a metaanalysis of more than 100 uniform fungicide trials conducted on wheat, Paul
et al. (110) found metconazole reduced
DON accumulation by 50% compared to
the check (control), followed by tebuconazole (40%) and prothioconazole (32%)
(Fig. 11).
Biological control agents are alternatives to synthetic fungicides. These agents
may provide growers with an additional
option for crop protection when the allowable window for applying synthetic
fungicides has passed (111,112) or for
organic production. Organisms that have
been tested include the bacteria Bacillus
amyloliquefaciens, B. subtilus, and Lysobacter enzymogenes and the yeasts Cryptococcus nodaensis and C. flavescens (81).
Taegro (113) is a strain of B. subtilis that is
marketed as a biological control agent.
In uniform fungicide trials conducted
by the U.S. Wheat and Barley Scab Initiative (USWBSI), none of the biological control agents by themselves has been as
efficacious as synthetic fungicides in reducing DON (77). Growers, crop consultants, extension educators, and others in
the value chain can access information on
best management practices and resistant
cultivars online at Scab Smart Management (114)
Important tools for alerting growers
and others in the grain value chain of
areas at risk for DON accumulation in-
clude web-based disease-forecasting tools
that utilize hundreds of automated weather stations located across Canada and the
USA (82,115–117). The system used in
Ontario, Manitoba, and Saskatchewan in
Canada, Weather Central (118), is based
on research at the University of Guelph
(82,115). A number of forecasting models
are available in the USA; for example, the
Fusarium Risk Assessment Tool (119),
which was developed using USDA-ARS
funds, and other forecasting models can
be accessed through the USWBSI website
(120). Both the Canadian and USA forecasting systems are widely used in the
spring and summer in all regions as an
indicator of FHB likelihood. Each of the
forecasting websites differ slightly, but in
general, users can go to the websites and
enter information such as their location,
the market class of wheat they are producing, the relative resistance of the cultivar
they are growing, the date, and the number of hours out they want to forecast
potential risk. Based on the information
provided, the websites will return maps of
the specified region indicating the potential risk of infection. The USWBSI also
developed and maintains the FHB Alert
System, which sends an e-mail or text message to subscribers in the USA to warn
them that conditions in their region are
favorable for FHB development. All of the
forecasting tools and the FHB Alert System warn participants in the grain value
chain about regions with potentially unacceptable levels of DON, growers of the
need for timely applications of fungicides,
and grain buyers to develop strategies
before harvest to manage potential problems. This is the first phase of determining the potential risk of unacceptable
DON levels by producers, procurers, and
processors and has a large impact on the
sampling plan and management of crop
segregation. In years and regions with a
high risk of DON, surveillance includes
sampling of individual fields before harvest to ensure unacceptable grain is kept
out of the food chain.
Large processors and end users have
staff or consultants who monitor the
expected condition of the crop to avoid
sourcing grain from areas with FHB. The
overall strategy in North America for
managing grain contamination by F.
graminearum and DON is illustrated in
Figure 12.
The challenge of sourcing acceptable
grain is impacted by the year-to-year variations in DON levels in different sourcing
areas and even by how different cultivars
within a market class respond to the disease. The North American grain-handling
chain (Fig. 1) generally moves grain in
bulk from individual farms to primary
elevators, where grain from a number of
individual farms is accepted for delivery
and combined. Grain from primary elevators is then moved via rail and/or domestic shipping to terminal elevators, where it
is combined with grain from other primary elevators. This results in a large volume of grain originating from a variety of
locations that should meet the quality and
safety specifications of end users. At each
step in the value chain, processors test
truck and/or railcar loads for DON levels
to further segregate the grain or to reject a
load and have it sent back to the supplier.
Steps are taken by processers to ensure
that DON concentrations are below USFDA advisory levels or Health Canada
guidelines.
Another challenge in procuring grain
each crop year is that processors and other
end users have limitations on the number
and size of bins they have available for
segregating incoming grain. Thus, it is
critical that procurers determine the risk
for unacceptable DON levels or other
end-use quality traits in the origination
Fig. 10. Fungicide efficacy for Fusarium head blight (FHB) index, deoxynivalenol (DON), Fusariumdamaged kernels (FDK), and yield in moderately resistant and susceptible wheat cultivars. Within
each variable, least significance difference (LSD) values were calculated at P = 0.05. (Adapted, with
permission of The American Phytopathological Society, from Wegulo et al. [84].)
Fig. 11. Efficacy of various fungicides for reducing Fusarium head blight (FHB) in the field and
suppressing deoxynivalenol (DON) content in harvested grain, expressed as percent control compared with untreated wheat. FHB = Fusarium head blight index; DON = deoxynivalenol; TEBU =
tebuconazole; PROP = propiconazole; PROT = prothioconazole; TEBU + PROT = tebuconazole plus
prothioconazole; METC = metconazole. (Adapted, with permission of The American Phytopathological Society, from McMullen et al. [81].)
CEREAL FOODS WORLD / 41
areas for the different grains they wish to
procure. After this is completed, the processor can create the blend that will meet
the customers’ requirements. The ranking
of components of the grain blend design
is based on 1) food safety; 2) functional
requirement; and 3) consideration of processing performance.
Another consideration is whether the
processor is using grain from the export
Fig. 12. Overall strategy for managing deoxynivalenol (DON) in grains.
Fig. 13. Levels of deoxynivalenol (DON) detected at the processor level in wheat samples from
the Northeastern, Midwestern, Western, and Southern regions of the USA from 2003 through
2014 (n = 42,131). Samples include soft and hard wheat varieties. “Estimated Tonnes” lists the
amount of wheat represented by the samples analyzed each year.
Fig. 14. Annual average deoxynivalenol (DON) concentrations in exported soft wheat sublots
from the USA. Values in parentheses indicate the number of sublot samples analyzed each year.
42 / JANUARY–FEBRUARY 2015, VOL. 60, NO. 1
system or local origins. Elaborate systems are in place to assure consistency
of grade, including minimizing DON levels in grains that are exported. Processors
within Canada and the USA receive grain
shipments originating from farms, primary elevators, and terminal elevators;
thus, the domestic processor often has
much more variation to deal with than a
processor procuring grain through the
export channel. Having a target for finished products is more appropriate to assure food safety compliance than targeting unprocessed raw grain with a fixed
level when DON distributions are not
known.
The relationships between FHB, FDK,
and DON in grains are complex (121) but
understood to result from both the plant
response to the pathogen (122) and strain
variation (123,124). Nonetheless, harvest
surveys have demonstrated that DON in
wheat can be managed by minimizing the
amount of FDK present in grain and using FDK as a grading factor (69). Growers
can reduce FDK in the harvested grain by
adjusting airflow settings on their combines (125).
In addition to the blending that occurs
along the Canadian and USA value chains,
cleaning often occurs at larger primary
and terminal elevators. Grain can be
cleaned using a variety of techniques,
such as optical sorting, sieving, and gravity tables. These handling steps can decrease the level of FDK and, thereby, DON
levels in a volume of grain (126).
The ability to handle large volumes of
grain of varying quality and meet desired
specifications increases along the grainhandling chain. Figure 4 illustrates how
higher concentrations (i.e., >2 mg/kg) of
DON in wheat occurred at earlier stages
in the grain-handling chain, such as on
farm or at primary elevators, but not further along the grain-handling chain. The
fraction of wheat samples containing DON
at concentrations >2 mg/kg decreased
from 19% on farm to 0.5% in shipments
from terminal elevators when analyzed in
nontargeted monitoring and surveillance
programs (i.e., where the sampling scheme
was not biased). A decrease in the occurrence of DON concentrations along the
handling chain similar to that described
for wheat was observed for Canadian durum and barley and is illustrated in Figures 5 and 9, respectively.
Processors at intermediate stages of the
grain-handling chain can be more limited
in their ability to manage DON in deliveries coming directly from farms or primary
elevators. Figure 13 shows the incidence
and levels of DON reaching USA milling
facilities from 2003 through 2014 and represents more than 1.2 million tonnes of
wheat. (Figures 13 and 14 use the same
data set as was used for Figures 2 and 3.)
The DON levels shown in Figure 13
follow a distribution, with the majority of
the samples showing levels of contamination below the LOQ of the method. Two
LOQs (0.3 and 0.5 mg/kg) are reported in
the figure because different milling facilities used different ELISA methods to evaluate the samples. Among the samples that
showed quantifiable amounts of DON,
3.1% had levels that exceeded 2 mg/kg. In
Canada, data from a small targeted survey
run from June 2011 through October 2013
showed that up to 9% of wheat grown in
eastern Canada and delivered to milling
facilities contained DON at concentrations ≥2.0 mg/kg (127). This is within the
range of 1–10% of samples containing
DON at concentrations ≥2.0 mg/kg noted
by USA wheat processors (Fig. 13).
Information regarding the levels of
DON in USA wheat destined for export
can be found in the U.S. Wheat Associates
Crop Quality Reports (128). U.S. Wheat
Associates provides annual reports on the
quality of the different classes of wheat
grown in the USA. Different USDA-ARS
and USDA-GIPSA laboratories and other
government institutions provide the data
used in these reports. A historical data set
made available by U.S. Wheat Associates
provides information on DON levels in
samples of hard (n = 6,278), soft (n =
1,869), and durum (n = 718) wheat directed to exporting from 1997 through
2013.
This data set shows that, as discussed
previously, the levels of DON in USA
wheat being exported are maintained,
through management, on average below
2.0 mg/kg. However, some years and/or
wheat classes are more challenging to
manage than others. For example, DON
levels in samples representing shipment
sublots of hard wheat for export have been
reported as being below 1.0 mg/kg on
average, with levels of up to 8.10 mg/kg
found in individual samples in 2001. For
durum wheat, averages also were below
1.0 mg/kg over the last 10 years, with
maximum levels of 4.6 mg/kg being detected in 2003 in samples representing
export sublots. For soft wheat directed to
export, averages historically have been
well below 1.5 mg/kg (Fig. 14); however,
levels of up to 5.9 mg/kg (in 2003) were
detected in samples representing sublots
of wheat leaving the USA as exports. Based
on the data from the USA, as for Canada,
in general as grain moves through the
handling chain to export the average reported levels for DON are reduced, even
more so for soft wheat than for hard
wheat in the last 10 years.
Effect of Processing on DON Content
in Wheat and Other Grains
Wheat Milling. Harvested grains are
converted into flour and other fractions
for human consumption or further manufacturing. Processing consists of cleaning
(including sorting) and milling (Fig. 15).
The sorting step removes any impurities,
such as straw and dust, but can also be
used to remove broken or mold-damaged
grains. This selection or separation step is
performed based on the physical parameters of the kernels, such as shape, size,
specific gravity, relative density, and color.
Fusarium-infected grains become shriveled and lighter than healthy grains (126).
Some studies observed that selection and
separation based on gravity was effective
in removing heavily infected grains with
high concentrations of DON from healthy
grains (126,130). Nevertheless, this management approach has two potential problems: 1) many Fusarium-infected grains,
which may contain high levels of DON,
can be physically indistinguishable from
healthy grains and not removed by some
sorting methods; and 2) FHB level is not
always correlated with the concentration
of DON in the grains when secondary
Fusarium infection occurs (131).
Cleaning can also be used to remove
infected grains. Nowicki et al. (132)
reported that scouring was effective in
reducing the level of DON by 22% because the toxin was unevenly distributed
on the surface of grains; Fusarium was
also removed from the surface of grains.
According to Abbas et al. (133) the preparation cleaning step in the milling process reduced the concentration of DON
by 6–19% in infected wheat grains, with
cleaning efficiency depending on the
initial condition of the grain and the
extent of the contamination (Table 3).
More recently, Lancova et al. (140) observed that the effective removal of
screenings and the outer layers of bran
from the surface of grains during cleaning steps reduced the concentration of
DON by 48%.
The international wheat milling industry has carried out several DON reduction trials in wheat mills over the last
5 years. These normally have shown the
need to both mechanically clean and to
pass the wheat through an optical sorter
Fig. 15. Wheat cleaning and milling process diagram. Cleaning steps in green boxes indicate
where reduction of deoxynivalenol (DON) typically occurs (129). * Wheat “Red Dog” consists of
the offal from the “tail of the mill” together with some fine particles of wheat bran, germ, and
flour. This product must be obtained in the usual process of commercial milling and must contain
not more than 4% crude fiber.
CEREAL FOODS WORLD / 43
to maximize reduction of DON levels.
They showed typical reductions from
3 mg/kg in wheat to about 1 mg/kg at the
output of the optical sorter placed after
mechanical cleaning, although there was
some variability depending on the incoming grain (personal communication).
Mechanical cleaning normally consists of
a combination of a classifier, gravity separation, and aspiration, sometimes also using a scourer.
The optical sorter, which is not standard
in all mills, normally uses a light sort in
the visible region and a light sort in the
short-wave infrared (SWIR) region. The
largest reduction (relative) is normally
seen with the use of the SWIR region of
the sorter. Typically the optical sorter will
remove between 2 and 5% of the product
stream to achieve these reductions. In
smaller mills, some reduction can be
achieved using only a visible light sort
with a blue filter. In this case, reductions
of 25% of the DON level or more have
been achieved using a standard optical
sorter as found in the cleaning section of
a modern mill in Europe or the USA (personal communication). Optical sorting is a
potential option for mills to use to manage high or variable DON levels in wheat
and other grains; however, it is a significant investment for a mill.
During the milling process some grains
are polished, removing most of the bran
and germ and leaving the endosperm,
followed by the reduction of the endosperm to a uniform particle size of flour.
This process involves a sequence of breaking (stage 1), reducing (stage 2), and separating steps. In stage 1 the grains are
passed through a set of rough or corrugated break rolls rotating at different speeds.
Table 3. Effect of cleaning on removal of deoxynivalenol (DON) from grain (131,133–141)
44 / JANUARY–FEBRUARY 2015, VOL. 60, NO. 1
Break rolls do not crush the grains but
shear them open, separating the bran
from endosperm. The sheared grains are
sieved into three main components: bran,
germ, and endosperm. In stage 2, the endosperm particles are channeled to a set
of smooth reduction rolls for final milling
into white flour. This separation of the
bran from the endosperm can significantly reduce DON levels, since most
mycotoxins tend to be concentrated in
the bran (outer layer) and germ fractions
(Table 4).
In the case of the wheat milling process
(Fig. 15), separation involves passing the
grain through 2–3 break rolls and 3–5 reduction rolls, each followed by sieving.
This results in five fractions: white flour,
wheat germ, wheat feed (red dog), wheat
shorts, and wheat bran. According to several researchers, when milling wheat or
maize mycotoxins tend to be concentrated
in the germ and bran fractions (133,141–
145). Similar to other mycotoxins, DON
is a heat-stable compound (155) and may
not be destroyed during most food processing operations, including milling (156).
Therefore, the best way to reduce DON is
to separate the highly contaminated kernels from the bulk during the preparation
steps and subsequent sieving steps.
Research has shown that the white flour
has approximately half the level of DON
found in the cleaned wheat, while the bran
can have levels two or more times greater
than the initial whole wheat (133,150).
According to the research of Tanaka et al.
(150), the flour fraction of barley contained 3.2% of the DON, while the bran
fraction contained 96.8% of the DON
found in the whole grain. In the case of
wheat, the bran contained 81.6% of the
DON. Milling wheat and barley is effective in removing the DON contained in
the outer layers of the kernels. It should
also be noted that significant improvements have been made in modern mills
to decrease DON in the flour fraction
(Fig. 16).
There have been varying reports of reduction of DON levels using peeling or
debranning of wheat. The assumption is
that the mycotoxin is in the bran layer on
the surface of the grain. Some trials have
shown DON reductions of up to 50% after debranning, but it has also been suggested that reductions will be lower when
the whole grain has been affected by fungal attack. DON may also be distributed
throughout the milling fractions independent of wheat variety (131,133–136,140,
157,158).
Dry Milling of Maize (Corn). With
wheat, the milling process does not reduce the total amount of DON but rather
converts the wheat into fractions, segregating the DON in lower value fractions
while the high-value fraction, white flour,
is relatively low in the toxin. Maize goes
through a different milling process (159).
After cleaning, maize kernels are soaked
twice in water, then passed through a
degerminator and dried again. The degermed maize is then sifted and either
placed on gravity tables for production of
germ and coarse grits or rolled to make
flour or fine grits. During the milling process, the DON segregates heavily into the
bran, screenings, germ, and germ meal
fractions, leaving the grits and flour fractions with 5–10% of the DON level contained in the bran (160). Most products
for human consumption are prepared
from flour and grits. Therefore, it is possible to reduce DON in human foods
during the milling process. Similar to
wheat milling, these results suggest the
milling process does not remove DON
but redistributes it. This explains the consistent tendency for DON to segregate into
milling fractions used for animal feed and
out of fractions used for human foods;
thus, it makes much more sense to regulate milled products than unprocessed
raw grain.
Oat Milling. When oats are milled, they
undergo a dehulling process to remove the
husk from the grain before kilning (heat
treatment to inactivate lipase). Most of the
DON in oats is concentrated in the hull,
so dehulling oats results in a reduction in
the level of DON compared to the initial
grain. This is evidenced by the oat flakes
produced by the milling process, which
contain 5–10% of the DON present in the
oats before milling (161).
Risk Management Measures for DON
Maximum levels (MLs), which are the
maximum concentrations of a specific
substance recommended to be legally permitted in a specific commodity, provide
dietary guidance for consumers. MLs are
not necessary for all contaminants in all
foods. Establishing an ML for a given
contaminant in a certain food would be
necessary only if and when the contaminant may be found in amounts that result
in significant adverse public health impacts.
In this case, the ML would afford adequate
assurances of safety. The main criterion is
that the contaminant is a significant contributor to total dietary exposure for consumers. Therefore, determination of MLs
for DON across multiple grains must satisfy the “significant contributor to total
dietary exposure for consumers” criterion
and provide health benefits. Setting levels
for DON in an unprocessed raw commodity that is not typically consumed in that
form and that contributes minimally to
dietary exposure from the finished food
product (after processing) may not significantly change health outcomes. De-
termination of MLs for DON across
multiple grains must afford adequate
health protections in bad climactic years,
provide additional health benefits at a
reasonably achievable level, and be practically achievable so that trade disruptions
do not occur.
Emesis is the critical effect in DON
acute food toxicity. The acute reference
dose (ARfD) of 8 µg/kg bw/day of DON
Table 4. Effect of milling on removal and distribution of deoxynivalenol (DON) from grain (126,
131–138,140,146–154)
Fig. 16. Deoxynivalenol (DON) distribution (%) in milled wheat fractions (total DON amount in
cleaned grains = 100%). (Derived from data presented in Tables 3 and 4.)
CEREAL FOODS WORLD / 45
used in international standards was established by the 72nd JECFA in 2010 (162).
This ARfD is used in the derivation of
proposed MLs that would adequately protect health (163). JECFA reported that
“dietary exposures to DON up to 50 µg/kg
bw/day are not likely to induce emesis”
(162). This suggests that JECFA has established an ARfD that affords at least a fivefold margin of safety.
The 2006 WHO Global Environment
Monitoring System/Food Contamination
Monitoring and Assessment Programme
(GEMS/Food) identified food consump-
tion patterns for 13 regional clusters (164).
The regions likely to contribute most to
DON exposure from different grains for
the global population are represented by
clusters B and E (Table 5). Using this information, the proposed MLs for unprocessed raw wheat, maize, and barley were
calculated. Based on the predicted consumption of unprocessed raw grains, the
calculated MLs that would adequately protect health based on worst-case scenario
assumptions were 43, 4, and 11 mg/kg for
wheat, maize, and barley, respectively
(details provided in Tables 5 and 7). The
Table 5. Grain consumption rates (g/day) derived from the 2006 WHO Global Environment
Monitoring System (GEMS) cluster diets
Table 6. Grain consumption rates (g/day) derived from the 2012 WHO Global Environment
Monitoring System (GEMS) cluster diets
Table 7. Comparison between corrected maximum levels (MLs) from 2006 WHO Global
Environment Monitoring System/Food Contamination Monitoring and Assessment Programme
(GEMS/Food) consumption data, 2012 WHO GEMS/Food consumption data, and proposed MLs
in the Codex Committee on Contaminants in Foods (CX/CF) 12/6/9 (166)
46 / JANUARY–FEBRUARY 2015, VOL. 60, NO. 1
unprocessed raw grain consumption assumptions removed contributions from
primarily flour.
The WHO GEMS/Food cluster diets
were updated in 2012 (165). The 2012 update employed a new approach to assess
diets and consumption patterns, reorganizing the regional dietary consumption
patterns into 17 clusters (Table 6). MLs for
consumption of unprocessed raw wheat,
maize, and barley that adequately protect
health can be recalculated using the new
GEMS database information. These are
based on worst-case scenario assumptions
(removing contributions primarily from
flour). Based on the predicted consumption of unprocessed raw grains, calculated
MLs were 21, 19, and 9 mg/kg for wheat,
maize, and barley, respectively (details provided in Tables 6 and 7).
In summary, understanding the differences in consumption patterns across regional clusters of different unprocessed
raw grains intended for sale and for direct
human consumption is necessary to determine appropriate MLs for these grains.
It is assumed that these grains will not
undergo further processing. Additionally, contributions from different grains
(durum wheat, soft wheat, maize, and
barley), whether unprocessed raw, semiprocessed, or processed, to the overall
consumption of grain-based products
should be tallied. This would allow for an
accurate assessment of appropriate MLs
for various grains at each stage of the harvesting and milling continuum. Furthermore, MLs proposed should correspond
to the point at which the grains are analyzed and sampled for DON. This would
ensure consistency of the reporting basis
between MLs and the occurrence data.
The point of sampling and analysis varies
from country to country. For example, in
the United Kingdom the sampling is a
mixture of point-of-sale data and harvest
data. To compare data and provide consensus on appropriate MLs, the international
community must first attain consensus on
stages of the harvesting and milling continuum at which sampling and analysis
should be done.
Method for Estimating Intake of
Unprocessed Raw Grains
Total grain consumption is not an appropriate substitute for unprocessed raw
grain consumption when used to establish
an ML for DON in unprocessed raw grains
intended for direct human consumption.
This assumption can result in an overestimation of the actual unprocessed raw
grains consumed and would generate an
unrealistically low ML that would not
provide additional public health benefits.
To eliminate the inherent uncertainties
associated with the GEMS/Food data relative to the amount of unprocessed raw
grains actually consumed globally, it may
be prudent to seek actual unprocessed
raw grain (specifically durum wheat, soft
wheat, maize, and barley) consumption
data from impacted nations to serve as
the basis for the proposed ML. Risk management decisions should be based on the
most appropriate data when specifying
proposed mitigation measures for DON
contamination of unprocessed raw grains
intended for direct human consumption.
It is an internationally accepted principle that MLs for DON in unprocessed
raw grain should be set at levels that are as
low as reasonably achievable (167) and
that MLs should be adequately protective
of health, yet also practically achievable so
trade disruptions do not occur or are minimized to the extent possible.
Aggregate Impact of DON on North
American Food Grains
The long-term prospective impacts of
imposing limits or further regulations
regarding DON would affect growers,
millers, food processors, traders, handlers, and ultimately consumers. Currently the USA domestic industry conforms to advisory limits. Other countries
have limits on unprocessed raw and/or
processed grains. Proposals have been
made that would change these limits to be
more restrictive, particularly for unprocessed raw grains. If adopted, this would
impact the entire value chain, which
could result in escalated costs, reduced
exports, expanded use of wheat as feed
within North America, increased testing
and segregation costs, and growers inevitably further switching away from wheat
and other affected grains in regions that
are vulnerable to or at higher risk for excessive DON levels.
The presence of DON has major implications for the entire supply chain of affected grains, including both for domestic
processors of grain-based products and
for exporters and importers. The presence
of FHB in North America and the resultant incidence of DON raise costs and
risks for growers, inducing them to use
more costly management practices and/or
shift to other crops. In addition, it raises
the cost of developing new cultivars, since
all lines of germplasm must be screened
for Fusarium resistance regardless of other
traits being pursued. The presence of
DON also reduces the quantity of vulnerable crops produced, raises production
costs, and increases premiums for wheat
and other grains at risk for DON contamination. This leads to higher overall
costs and risks and more complicated logistics for domestic processors and importers, and, finally, it raises the costs of
breeding. All of these effects would be
exacerbated by proposals to measure and
limit DON on unprocessed raw materials
instead of products.
Earlier studies by Johnson et al. (168)
and Nganje et al. (169–171) have estimated the value of economic losses due to
DON to the USA industry. Johnson et al.
(168) estimated production and price effects for HRS wheat, durum, and soft red
winter (SRW) wheat from 1993 to 1997.
They estimated relationships for yield as
a function of rainfall, temperature, and
trend. To proportion losses due to FHB
and determine yields without FHB, they
utilized the difference between the forecasted yields and actucal yields, together
with expert opinion. Acreage adjustments
were included to compensate for higher
acreage abandonment in FHB outbreaks.
Price effects were evaluated as the production shortfall impact on market prices and
the effect of crop quality premiums and discounts. The economic impact of production losses ranged from 3.6 million tonnes
in 1993 to a low of 1.7 million tonnes in
1996. Price effects due to production shortfalls resulted in higher prices than would
have occurred without FHB outbreaks.
Combining the two effects reduced the
total impact of FHB. The largest production effect occurred in 1993; however, when
considering both price and production
effects, the largest losses occurred for all
classes in 1995, due mostly to the large
negative price effects on SRW wheat. For
HRS wheat, the year with the largest loss
was 1994 at $245 million.
Nganje et al. (169) updated the results
from Johnson et al. (168) to cover the years
1998–2000 and expanded the analysis to
include malting barley. Nganje et al. (169,
170) used generated losses attributable to
FHB to estimate direct and secondary
yield losses that were then utilized within
an input-output model of the economy to
project direct and secondary economic impacts on the larger economy. Direct economic losses in the USA were estimated
at $870 million from 1998 to 2000.
More recent estimates of outbreaks
have tended to focus on yield losses and
the extent of coverage of FHB outbreaks.
Cowger and Sutton (172) estimated the
impacts of the 2003 SRW wheat outbreak.
They interviewed researchers, extension
specialists, extension agents, millers, and
growers in the southeastern USA for opinions on the 2003 infestations. Lilleboe
(173,174) summarized the effects of FHB
in 2010 and 2011 across states and crops
for the USA. McMullen et al. (81) summarized past studies on the economic
estimates of FHB outbreaks and the degree and location of FHB outbreaks by
class of wheat since 1991.
Grower Risks and Responses to
the Incidence of FHB
One of the fundamental impacts of FHB
on growers is that it increases risks, raises
costs, and ultimately increases the propensity for growers to switch to other crops
with less risk and/or an increase in the
risk premiums for growing these crops.
FHB Risks
There are two notable risks related to
FHB for growers. One is the incidence of
FHB during production, which reduces
yields and damages kernels, potentially to
the point of being unmerchantable. Some
crops are more susceptible to Fusarium
infection and DON production due to
factors such as variety, growing regions,
and weather variations from year to year.
Soft wheat varieties, especially soft white
winter (SWW) wheat, when grown in
temperate regions like eastern and midwestern areas of the USA and eastern
Canada are vulnerable to DON production. This is a result of the higher frequent
rainfall coupled with warm temperatures
that are typical for these areas, in addition
to the emerging growth of other crops
(i.e., maize) in these regions. This corroborates discussions presented in previous sections concerning regional vulnerability to DON production throughout
North America and elsewhere. While published data for maize are more limited for
North America, the presence of DON has
been demonstrated. Variability in occurrence of FHB also is seen from year to year.
For example, in 1996 the SWW wheat crop
in Ontario and the eastern USA was dramatically affected by FHB, cutting yields
by a third, with much of the crop unusable for human consumption. HRS wheat
and durum crops were severely impacted
in 1993, followed by several other years,
including 1998–2010 and 2014 (81).
The other critical risk related to FHB is
price discounts, or more specifically, postharvest price discounts. These discounts
CEREAL FOODS WORLD / 47
are encountered in numerous forms. The
most common current forms are simply
rejecting the product, reclassifying it to a
lower grade/class, or applying price dis-
counts. The former two have obvious, although random, price adjustments. Table 8
shows discounts that were applied in 2014
for Fusarium-damaged kernels (FDK or
Table 8. Example of wheat discounts for Fusarium-damaged wheat kernels (FDK) at a representative
primary elevator in North Dakota
Fig. 17. Area planted to selected crops in North Dakota. (Source: USDA-NASS [179])
Fig. 18. Area planted to selected crops in Canada. (Sources: USDA-FAS [180] and Agriculture and
Agri-Food Canada [181], various years)
48 / JANUARY–FEBRUARY 2015, VOL. 60, NO. 1
scab) for a representative country elevator
in North Dakota for HRS wheat. At the
time these discounts were applied, wheat
prices were $6/bu ($220/tonne). As an
example, a discount of $1 is about 17% of
the price of the crop or a loss of $40/acre
($99/ha), which is sufficient to shift plantings to other crops.
Currently, it is common to either test a
sample of the grain analytically at internal
labs, send it to a grain inspection service
for a certified test, or require growers to
provide a certificate of a test result prior
to unloading the grain. Similar procedures are used at export elevators. The
presence of FDK results in financial
losses to growers due to the penalties or
reclassifications of wheat lots, as shown in
Table 8. If the levels exceed grading standards or contractual obligations, excessive
FDK levels can rise to the point of a total
crop loss for a grower.
Farm Management Practices and Costs
As described earlier, growers now have
a number of farm management practices
that can be adopted with the goal of mitigating some of the risks of DON. These
include, but are not limited to, crop choices,
choices among improved varieties regarding DON resistance, agronomic practices
including crop rotation, application of
fungicides, etc. Farm management practices to control DON were analyzed recently by McGee et al. (175) and are presented in Figure 12. As discussed earlier,
fungicides are particularly important and,
in response to the 1996 crop failure, were
registered in Canada for mitigating FHB
in soft wheat starting in 1999. In addition,
varying forecasting tools now exist. DONcast is one modeling tool that has been
available to growers in Ontario since 2000;
other similar models are available in Canada (118) and the USA production regions
(119,176,177).
To understand the quantitative impacts
of these on farm management decisions,
Wilson and Dahl (178) quantified the riskiness of alternative grains in North Dakota.
These include not only price risks but also
risks related to yield, quality rejection, and
post-harvest quality discounts. These results illustrate the riskiness of HRS and
durum wheat relative to competing crops.
Switching to Competing Less Risky
Crops
DON has resulted in growers shifting
production to less risky crops/crop rotations. Changes in cropping patterns have
been influenced by many factors, includ-
ing government farm program changes;
the rising importance of ethanol; increased
demand for maize, soybeans, and canola;
increased profitability of alternative crops;
etc. Increased risk of FHB occurrence may
also impact a grower’s decision concerning which crop to cultivate, as illustrated
in Figure 17 for North Dakota and Figure 18 for Canada. In North Dakota HRS
acres have declined from about nearly
10 million acres (ma) (4.1 million hectares), to about 6 ma (2.4 million hectares);
durum has decreased from 2.5 ma to less
than 1 ma; and malting barley acres have
fallen similarly. Similar changes have also
occurred in Canada for all wheat, decreasing from 30 ma (12.3 million hectares) to
20 ma (8.2 million hectares), mostly switching to canola which is less risky and more
profitable.
Regardless of the cause, it is a fact that
grains that are vulnerable to Fusarium are
more risky than the alternatives, and this
provides a motivation to shift to less risky
crops. Or, similarly, in order to retain the
same area planted with these crops, risk
premiums have to increase for these crops
relative to competing ones, which has indeed been seen during this period.
Ali and Vocke (182) analyzed the impact of DON on planting decisions by
growers since the 1990s. The degree of
disease incidence may be increasing due
to larger maize plantings and the switch
toward minimum or reduced tillage practices, which increase host presence for
DON development when environmental
conditions are favorable. Similarly, much
of the durum and malting barley production has shifted out of eastern, central,
and northeastern counties in North Dakota into more western counties in North
Dakota and eastern counties in Montana.
Growers have many options available to
them when planning crop rotation programs. Should the risks associated with
growing a specific crop exceed the return,
growers could cease to plant those crops.
Soft wheat varieties, in particular, and
dry-milled maize for food use are currently at some risk, leading processors to
haul grain greater distances at greater cost
to meet their manufacturing requirements.
This means significantly added costs for
consumers.
effectively manages its impact. However,
these adaptations have a cost, do not eliminate DON completely, and have the effect
of reducing the product stream.
As grain moves along the supply chain
(Fig. 1), its quality is improved by the application of several management strategies, including segregation, blending, and
cleaning (183–185). These strategies allow
not only for the improvement of the quality of the grain, but also its safety by managing the presence of DON. This management, including the monitoring of
grain for DON along the handling chain,
requires resources for proper sampling,
analytical testing, and interpretation of
test results. These activities add time, as
well as cost, to the handling of grain.
At the mill level (or point of first processing), the incidence of DON is also managed. The most effective way (Fig. 15) is
to remove Fusarium-damaged kernels from
the unprocessed raw grain during the initial sorting and cleaning steps prior to
milling. Cleaning and scouring of wheat
prior to milling reduces DON content,
and the milling industry also uses optical
sorters that can effectively reduce DON
content.
Further processors of grains such as
mills and food manufacturers specify
thresholds for DON as a primary means
of ensuring finished goods as consumed
will meet the <1 mg/kg advisory level set
by the US-FDA. DON level mitigation
can be achieved through careful selection
of lots of grain; blending, cleaning, and
sorting; removal of the husk, hull, and bran
layers; and dilution with other ingredients
in a processed food. DON levels are not
reduced through washing or cooking.
Processors such as bakers or breakfast
cereal manufacturers have few tools available to reduce DON levels. This is particularly problematic for products that
contain whole grain and whose primary
component is a grain such as soft wheat.
Whole grain crackers and cereals are examples of products for which ingredient
dilution and bran removal are not available options. For these processors, the
primary tool available is the inclusion of
DON limits in contractual agreements.
For primarily whole grain products to be
sold in Canada or the USA, contracts limit DON to <1 mg/kg. For products destined for Europe, contracts will often set
the thresholds for DON at 0.5 mg/kg. To
illustrate, a list of countries and their contract limits on DON in wheat is provided
in Table 9. It is clear from this list, that
importers can effectively limit their DON
Table 9. Contract limits on deoxynivalenol (DON) (vomitoxin) specifications (Source: U.S. Wheat
Associates)
Supply Chain Impacts: Current
Practices
The supply chain for these grains was
described earlier. It is important to note
that the supply chain has adapted to the
incidence of DON and efficiently and
CEREAL FOODS WORLD / 49
content through maximum specifications.
It is worth mentioning, however, that some
grain suppliers are reluctant to contract
based on DON levels given that analytical
tests add cost and delivery delays. Some
handlers have been slow to adopt quantitative DON testing.
Some further processors of grains, especially small- and medium-sized enterprises,
that have less leverage at the grower level
maintain that a ML set on grains could
enhance market pressures for growers to
expand the use of tools such as fungicides. Others argue that sufficient safeguards are already in place, which is evidenced by targeted surveys of foods at the
retail level that show a very high compliance level for achieving DON levels of
<1 mg/kg in the finished food. Both parties agree, however, that setting any limit
for DON on unprocessed raw grain would
be highly problematic for North America
given the vastly different agronomic practices from those in Europe, such as farm
size, transport, and storage, in addition to
differences in climate and farm support
payments.
Prospective Impacts of Establishing
International MLs for DON in
Unprocessed Raw Grain on Supply
Chain and Marketing Practices
Currently, MLs in the USA are applied
on semiprocessed grains. However, some
countries would like MLs to be applied
to unprocessed raw grains, which could
detect affected grain prior to entering the
primary elevators. The latter would be
more costly and restrictive.
There are different points in the supply
chain (Fig. 1) at which MLs could be applied, including at the farm, at the point
of entry into the marketing system (i.e.,
the primary elevator), at terminals, at the
points of first processing, or on finished
products. Due to the density of transactions and costs of executing such a program, it would seem most practical that
these regulations or standards would be
evaluated at mills. This is a point with
fewer locations and would likely be the
most cost-effective. For these reasons, the
direct impacts of establishing MLs on DON
would be on domestic mills, while there
would be indirect impacts on growers and
exports and imports (discussed below).
In response to this proposed regulation,
domestic mills would be impacted most
directly, although an increase in cost
would impact other sectors in the supply
chain as well. Mills and first processors
would have to change their strategies.
50 / JANUARY–FEBRUARY 2015, VOL. 60, NO. 1
Mills would seek to purchase wheat with
greater assurance of conformance to the
MLs and/or add preprocessing functions
to assure meeting MLs for DON. This
could include a number of strategies:
sourcing wheat from production regions
that typically experience lower incidence
of Fusarium and lower DON levels (where
possible); imposing stricter limits on
wheat and/or larger discounts for excessive DON; requiring more extensive
cleaning prior to shipment from the elevator; and segregation, testing, and cleaning
at the mill to assure ML conformance.
Ultimately, this would add costs to both
purchasing and processing. These added
costs would vary through time and geographically. In-mill costs of cleaning,
scouring, added storage, etc. would also
vary through time but, nevertheless,
would be a real added cost to the milling
sector. Since such MLs currently are not
applied to unprocessed raw grains, major
processors have not yet quantified the
costs associated with such proposed regulations. To do so would require detailed
simulation modeling of these functions
and risks. Ultimately, these costs would
vary by location and be determined by
logistics and the mill’s capability for segregation and cleaning.
As previously discussed, growers currently seek to control DON through crop
rotation strategies, adoption of improved
cultivars, and use of fungicides and optimal spray technology at flowering. Tighter MLs on DON would have the following
impacts: more intensive management,
including variety selection and fungicide
use, all of which will add costs; larger discounts for excessive DON; and greater
risk for wheat and other crops grown with
excessive DON, leading to a shift to other
crops with less risk or greater returns.
These impacts would vary geographically
and through time. It is important to note
that as the risk associated with wheat
production increases and concurrently
competing crops become more viable
and profitable there would be a move
away from production of wheat and
other affected crops in the USA, Canada,
and elsewhere. This likely would reduce
supplies and increase prices to all consumers.
Importers of grains, at least from North
America, also have tools available for controlling DON content. In concept these
are similar to those of domestic mills and
include primarily contract limits for DON
content. Additionally, these can include
targeting locations, ports, and suppliers
that have the ability to reduce DON content in years when it is problematic. This
is most commonly accomplished by targeting origins and cleaning at the country
and export elevator (183,184) prior to
shipment, ultimately to meet specification limits set by importers. It is clear from
these strategies, that importers can effectively limit their DON content through
contract limits. Of course, tighter controls
would accrue greater costs due to testing
and potential rejections. Meeting these
specifications could impact the available
supply of wheat.
Finally, importers would also be impacted indirectly. If stricter MLs are imposed, the strategy of domestic mills in
grain-exporting countries would change
and could reduce (slightly) the available
supply of DON-compliant wheat to the
export market. For this reason, there
would be a minor component of crops
with unacceptable (even if precautionary)
DON levels that would be channeled elsewhere in the market system. This would
include the export market or markets for
nonfood uses. For importers, this could
increase the risks of receiving shipments
containing DON at unacceptable concentrations and, as a result, would require
more scrutiny of contract limits and price
differentials. The response would be to
increase the intensity of cleaning and targeting of origins for grain prior to exporting, which also would affect costs.
Final Remarks
In agricultural commodities, the occurrence of DON has been reported all over
the world, with levels varying among grain
types and years of production. The grain
supply chain, including growers, buyers,
and end users, has effectively managed
DON with strategies to control this issue
systematically. The safety of consumers is
ensured with use of these management
strategies.
Based on the information reviewed and
introduced in this report, the occurrence
of DON in North America does not appear to be different than that reported
around the world. Sporadically, levels of
DON in grains (wheat, maize, and barley)
can be much higher than usual in certain
years due to more severe Fusarium infection. Cool and wet conditions during
specific developmental stages of grains
(e.g., wheat flowering) promote Fusarium
infection, although wet conditions at harvest can lead to secondary Fusarium infection and DON production as well.
Other factors influencing the levels of
DON in agricultural crops include the
growing region and its climate, in addition to wheat class.
As discussed in the report, management of FHB and consequently DON in
grains is a complex problem with numerous component methods available.
Each method, such as crop rotation, tillage, cultivar resistance, fungicides, biological control agents, and optimized
spray technologies, provides some benefit, but using multiple approaches is the
most efficient way for growers to manage
this problem.
As far as the levels of DON found at
different stages of the grain-handling
chain, the data presented suggest that as
grain moves along the chain, its quality is
improved by the application of management strategies such as blending, cleaning, and selecting. These strategies allow
not only for the improvement of the quality of the grain, but also its safety, by managing the presence of DON. Indeed, numerous studies with the major grains,
including wheat, maize, and oats, have
shown that DON in whole grains is mainly redistributed during processing into the
bran and germ fractions rather than the
endosperm. The flour fraction (from the
endosperm) destined for human consumption typically contains DON levels
that are 10–20 times lower than those
observed in the bran or germ fractions,
which are mostly used for animal feed.
The technology or equipment used in the
mill affects the recovery and segregation
of DON in each fraction. Therefore, it
would be plausible to adopt different
standards or regulatory limits for different milled fractions of grains instead of
applying a single level for the whole grain.
That is, if action levels are to be endorsed,
they should be endorsed for 1) flour and
other milling fractions intended for direct
human consumption; and 2) bran, germ,
and other fractions intended for feeding
to various animal populations.
MLs should be adequately protective of
health yet also practically achievable so
that trade disruptions do not occur. Since
unprocessed raw grains are not typically
consumed in that form and contribute
minimally to dietary exposure from the
finished food product (after processing),
setting MLs for unprocessed raw grain
would not significantly change health outcomes.
In the grain supply chain, current practices for managing risks of excessive DON
content in grain include 1) targeting locations with less incidence of DON; 2) in-
cluding contract limits and discounts for
excessive DON; 3) segregating wheat in
storage; 4) selectively testing and/or cleaning to assure contract performance; and
5) where appropriate, use of cleaning and/
or scouring to remove kernels with excessive DON content. Through these processes, North American domestic mills
effectively and efficiently control the incidence of excessive DON in their products.
Any additional restrictions would increase
costs and risks to mills not only in North
America but also globally.
More restrictive interventions on DON
content would have numerous impacts. It
is important to note that there would be
increased costs and risks related to executing any further restrictions. A more
strict management, including the monitoring of grain along the handling chain
for DON, would require resources for
proper sampling and analytical testing,
lead to an increase in risks to growers,
and cause changes at the processor level
that also would impact grain to be exported. All of these effects would add
costs to the grain-handling chain. Additionally, improvements in management
of DON at the farm, elevator, and processor levels have shown that any regulatory
limits would more efficiently safeguard
public health if applied to the finished
product rather than to unprocessed raw
grains.
Acknowledgments
Juan Carlos Batista (SENASA, Argentina);
Benedict Deefholts (Buhler Sortex Limited,
UK); Wiana Louw (SAGL, Southern African
Grain Laboratory NPC, South Africa); Rodrigo
Mendoza (University of Nebraska – Lincoln,
NE, USA); Donald Mennel (Mennel Milling
Company, Fostoria, OH, USA); National Grain
and Feed Association (Washington, DC, USA);
Terry Nelsen (AACCI Statistician, USA);
North American Export Grain Association
(Washington, DC, USA); North American
Millers Association; Lauren Robin (FDA/
CFSAN, USA); Luis Eduardo Sabillon (University of Nebraska – Lincoln, NE, USA); Paul
Schwarz (North Dakota State University, ND,
USA); U.S. Grains Council (Washington, DC,
USA); U.S. Wheat Associates (Arlington, VA,
USA); Felicia Wu (Michigan State University,
MI, USA).
Data were provided by Viterra Inc., Pioneer
Grain Company Operations, and Richardson
International Corporate Quality Assurance
and Food Safety.
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