127 / 166
Estimation of a wheat kernel’s contribution to gluten
content in pure oats
As mentioned, gluten-containing kernels of wheat, bar-
ley and rye are the predominant source of gluten con-
tamination in oats (Thompson, 2004; Hernando
et al.
,
2008; Thompson
et al.
, 2010; Koerner
et al.
, 2011). If
not effectively mitigated, these kernel contaminants
will survive the oatmeal production process intact
(possibly being cut) and ultimately appear in a serving
as indistinguishable flakes, consumed unknowingly by
GF conscious consumers.
Using wheat as an example, we have estimated the
gluten contribution from a single kernel in a typical
serving size of 40 g of otherwise pure oats (Table 2).
This is based on ‘literature reported’ wheat protein
content (2015 Crop Quality Report by US Wheat
Associates,
http://www.uswheat.org/cropQuality)and
wheat gluten content (Shewry, 2009). We found that
for the six predominant North American wheat vari-
eties, a single wheat kernel will bring on average 65
–
129 mg kg
1
of gluten to 40 g of pure oats.
This estimation suggests that gluten kernel contami-
nants, including a cut or broken kernel, can lead to
noncompliance at a serving size level, thereby posing a
risk to GF oatmeal consumers.
Sampling implications in assessment of kernel-based
gluten contamination
The binary-like circumstance of gluten outcomes cre-
ates a sampling context similar to a pass/fail one. A
serving fails when a gluten kernel or part of one exists
in a serving, leading to noncompliance relative to glu-
ten regulatory thresholds (e.g.
>
20 ppm by FDA), and
passes when one does not. ‘Attribute’-based sampling
caters to binary type outcomes like this (Taylor, 1992).
This type of sampling is in contrast to ‘variable
sampling’, which assumes a few samples can provide
information about the others around them. A key pre-
requisite for variable sampling therefore is the ability
to pick a sample that is ‘representative’ of the rest
(Taylor, 1992). The kind of distribution uncovered in
this survey (Fig. 1) complicates doing so however, as
randomly selecting some servings for analysis may not
adequately provide a representative inference on the
rest.
To investigate this, a sampling simulation was con-
ducted where 10 000 samples of five, ten, twenty-five
and fifty servings each were generated by randomly ‘se-
lecting’ outcomes from the distribution of the 965 out-
comes from the survey. Doing so, it was found that the
probability of all servings selected being found compli-
ant was 0.92, 0.84, 0.64 and 0.41 for samples of five, ten,
twenty-five and fifty servings, respectively. So, with fifty
servings evaluated for instance, about 40% of the time
one will not get an indication of a compliance problem,
getting all compliant outcomes. This probability
increases when fewer servings are evaluated. So, with an
underlying noncompliance rate of about one in fifty-
seven servings, with
~
1 in 161 being more than four
times the regulatory maximum, sampling quantities in
this range can fail to detect (with high confidence) inher-
ent process and lot acceptance incapability. This is
believed due to underlying statistical inferences that are
being relied upon, which are undermined by the binary
type distribution which kernel-based gluten contamina-
tion has been shown to cause.
Table 3 expands on this, showing the probability of
selecting a contaminated serving in one to fifty tries
for various rates of contamination present. This table
is built on binomial distribution probabilities for pass/
fail type outcomes (i.e. attribute-based sampling) and
further shows how noncompliance can go undetected
for a time when modest sampling efforts are employed.
When nonconformance rates are as high as one in ten
servings, examination of five servings under this sce-
nario provides less than a 50/50 chance of randomly
selecting a serving that contains a gluten kernel.
Attribute-based sampling guidelines
Sampling required to avoid this risk is also shown in
Table 3. In the right most column are sample sizes
Table 2
Estimated gluten in 40 g of oats containing a kernel of North American varieties of wheat
Hard Red
Winter
Hard Red
Spring
Soft Red
Winter
Soft
White
Northern
Durum
Desert
Durum
Thousand kernel weight (g)*
29.1
30.4
32.6
35.3
39.2
48
Weight/kernel (g)
0.0291
0.0304
0.0326
0.0353
0.0392
0.048
% Protein*
12.7
14.1
10
10
13.5
13.4
% Gluten level in protein
†
80
80
80
80
80
80
Gluten content in 40 g of oats containing
1 wheat kernel (ppm)
74
86
65
71
106
129
*
Five year average values reported in 2015 Crop Quality Report by US Wheat Associates,
http://www.uswheat.org/cropQuality.†
Shewry (2009).
©
2016 PepsiCo, Inc. International Journal of Food Science & Technology published
by John Wiley & Sons, Ltd. on behalf of Institute of Food Science and Technology
International Journal of Food Science and Technology 2016
Kernel-based gluten binary-like outcomes
R. D. Fritz and Y. Chen
5