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COMPREHENSIVE REVIEWS IN FOOD SCIENCE AND FOOD SAFETY
Residues of glyphosate in food and dietary exposure
John L. Vicini Pamela K. Jensen Bruce M. Young John T. Swarthout
Regulatory Sciences, Bayer Crop Science,
Chesterfield, Missouri, USA
Correspondence
John L. Vicini, Regulatory Sciences, Bayer
Crop Science, Chesterfield Parkway
West,Chesterf ield, MO , USA.
Email: john.vicini@bayer.com
Abstract
Glyphosate is the active ingredient in Roundup R
brand nonselective herbicides,
and residue testing for food has been conducted as part of the normal regulatory
processes. Additional testing has been conducted by university researchers and
nongovernmental agencies. Presence of residues needs to be put into the context
of safety standards. Furthermore, to appropriately interpret residue data, ana-
lytical assays must be validated for each food sample matrix. Regulatory agency
surveys indicate that % of glyphosate residues in food are below the European
maximum residue limits (MRLs) or U.S. Environmental Protection Agency tol-
erances. These data support the conclusion that overall residues are not elevated
above MRLs/tolerances due to agricultural practices or usage on genetically mod-
ified (GM) crops. However, it is important to understand that MRLs and toler-
ances are limits for legal pesticide usage. MRLs only provide health informa-
tion when the sum of MRLs of all foods is compared to limits established by
toxicology studies, such as the acceptable daily intake (ADI). Conclusions from
dietary modeling that use actual food residues, or MRLs themselves, combined
with consumption data indicate that dietary exposures to glyphosate are within
established safe limits. Measurements of glyphosate in urine can also be used to
estimate ingested glyphosate exposure, and studies indicate that exposure is <%
of the current European ADI for glyphosate, which is . mg glyphosate/kg body
weight. Conclusions of risk assessments, based on dietary modeling or urine
data, are that exposures to glyphosate from food are well below the amount that
can be ingested daily over a lifetime with a reasonable certainty of no harm.
KEYWORDS
Analytical chemistry, Glyphosate, Pesticide exposure, Risk assessment, Urinary pesticide
1 INTRODUCTION
Modern agricultural practices provide farmers with tools to
maximize the production of food for a growing world pop-
ulation. Herbicidal pesticides help farmers grow more food
on less land by protecting crops from weeds competing for
essential nutrients, water, and sunlight. Oerke () con-
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cluded that % of potential crop losses were attributable
to weeds.
Glyphosate is a herbicide that is a phosphonomethyl
derivative of the amino acid glycine (Figure ). Glyphosate
inhibits Class I -enolpyruvylshikimate--phosphate syn-
thase (EPSPS), an enzyme in the shikimate pathway that
is required for de novo synthesis of aromatic amino acids
5226 wileyonlinelibrary.com/journal/crf Compr Rev Food Sci Food Saf. ;:–.
G .. . 5227
FIGURE 1 Glyphosate chemical structure and microbial degradation pathways in soil. Abbreviations: AMPA, aminomethylphosphonic
acid; GOX, glyphosate oxidoreductase. Adapted from Duke () and Giesy et al. ()
in plants. Because these amino acids are needed for syn-
thesis of proteins and lignin in all eukaryotic plants (Tzin
& Galili, ), glyphosate is a broad spectrum herbicide.
Cells from humans and animals do not have this pathway,
which is why phenylalanine, tryptophan, and tyrosine are
essential amino acids that need to be supplied in diets for
mammals and birds (Giesy et al., ). Glyphosate has
global regulatory approvals for its use as a nonselective her-
bicide in agriculture, mostly preplanting, as well as around
roadways and railroads.
Transgenic varieties of corn, soybeans, canola, and sugar
beets were made tolerant to glyphosate by the insertion of
a gene that encodes for a Class II microbial EPSPS that
is not inhibited by glyphosate. This variant was discov-
ered from the CP strain of Agrobacterium tumefaciens that
was isolated from wastewater at a glyphosate manufactur-
ing facility (Barry et al., ). Aminomethylphosphonic
acid (AMPA) is a major microbial degradation product of
glyphosate (Figure ) but AMPA does not compete with
the EPSPS substrate phosphoenolpyruvic acid for enzyme
binding (Duke et al., ; Reddy et al., ). In rats and
humans, metabolism of absorbed glyphosate has not been
shown to occur (BfR, ; Niemann et al., ).
Development of glyphosate tolerant (GT) crops required
multiple global regulatory agencies to authorize the cul-
tivation of the GT seed along with additional approvals
for the application of glyphosate over-the-top on GT crops.
Glyphosate is considered by these regulatory agencies to
be safe when used according to each specific label use.
More specifically, regulatory agencies have concluded that
glyphosate does not pose a cancer risk when used accord-
ing to the label. Recently, one organization, that lacks reg-
ulatory oversight, listed glyphosate as a “probable carcino-
gen” (IARC, ); however, multiple regulatory agencies
and competent authorities have assessed that listing and all
of these reviews concluded that glyphosate is not a carcino-
gen. Assessments by these regulatory agencies and compe-
tent authorities about the carcinogenicity of glyphosate are
listed in Table S.
Global regulatory authorities ensure food safety by
establishing realistic levels of human exposure to a given
pesticide that enable calculating exposure levels that
5228 G .. .
provide a “reasonable certainty of no harm” for the con-
sumer (Winter et al., ). However, the increased pub-
lic awareness of what is in food has resulted in a surge
in reports on residues of glyphosate, not only in peer-
reviewed scientific journals but also in nonscientific media
articles and stories posted to nonrefereed social media
sites. A literature search was conducted on topics related
to glyphosate, including residues, from the last years of
publications following EFSA guidelines (EFSA, ). Rel-
evant literature identified for this search for all of these
topics is available (GRG, ). Additional papers were
identified by checking references from these sources for
additional manuscripts and government reports that were
not identified by the original search. In order to provide a
robust discussion of the scientific findings and limitations
for a representative, albeit not fully comprehensive, set of
reports, articles were selected that () applied specifically
to food that is commonly consumed, () for field experi-
ments that appeared to follow product labels, and () pro-
vided some evidence of type of the method for quantify-
ing residues. A second search was conducted using the
terms “Glyphosate” or “Glifosato” from to using
Buzzsumo, which searches media content on the internet
across popular social media. This search generated ,
hits. The public impact of the media reports is remarkable
and, therefore, necessitates some inclusion in this review,
when related to reports of glyphosate detection in food.
Many of these media reports have interest-grabbing head-
lines about the detection of pesticide residues, but do not
provide interpretable data, or when they do, the values are
rarely provided in a context to help understand if these
residues could result in a consumer health issue. More-
over, laypeople typically lack formal training in the sci-
entific principles underlying dose–response relationships
and, consequently, often regard the detection of a chemical
as synonymous with that presence being unsafe (Siegrist &
Bearth, ).
The media reports and misunderstandings of dose–
response principles have created an expectation or desire
that food and beverages should have zero residues. The
people that consumers look to for food safety advice (e.g.,
health care professionals, nutritionists, and dietitians)
should have scientifically balanced information needed to
discuss the topics of residues. However, current training
curricula for these professions have limited, if any, course-
work on relevant topics. For instance, medical students
receive little training on issues of environmental chemical
exposure (Temte & McCall, ). As a start, it is impor-
tant to convey that detectable residues, including naturally
occurring toxicants, are in many foods regardless of agri-
culture practice, including both organic and conventional
agriculture, and that the presence of residues does not
directly equate with harm (Winter et al., ). A next step
is to provide the necessary context around what a reported
detection means in terms of current safety guidelines. The
science-based risk assessment of residues relies on the
reporting of accurate concentrations of residues of interest
in commodities/foods and comparison of these values to a
regulatory-derived safety standard. The maximum residue
limits (MRLs) are derived from regulatory studies of
residues obtained when pesticides are applied according to
the proposed label to agricultural products following good
agricultural practices (European Commision, b;Win-
ter et al., ). These data are used to statistically deter-
mine the legal limits for residues when individual crops
are grown in adherence to a regulatory agency’s approved
product label. By themselves, they are not a safety stan-
dard, per se. Crops with residues that are less than the MRL
would be considered safe, assuming all other crops treated
with the same pesticide had residues that are at or below
the MRL; however, a crop that experiences an exceedance
of the MRL is not by definition unsafe. One way to provide
the proper context regarding dietary residues and potential
risk is by comparing the sum of these residues for all crops
to health-based guidance values, such as the acceptable
daily intake (ADI). The ADI is a health-based guidance
value (Herrman & Younes, ) that, according to the
Chemicals Regulation Directorate (), is the amount
of a pesticide that can be ingested over a lifetime with-
out appreciable risk. In the United States, an equivalent
health-based guidance is the reference dose (RfD) and tol-
erances are the legal limits for residues in crops. The most
recent EU ADI for glyphosate (. mg glyphosate/kg body
weight) is used throughout this review in calculations,
partly because it is a more conservative value than the RfD
used by the U.S. Environmental Protection Agency (EPA)
( mg/kg).
Advancements in analytical chemistry technology have
contributed to increased reports of detection of pesticide
residues because increasingly sensitive detection meth-
ods have resulted in many assays now accurately measur-
ing pesticides in parts per billion (ppb, µg/L, or µg/kg).
As a result, it is becoming increasingly more likely that
residues, that were previously too low to measure, will
be detected. Comparing the sum of residue concentra-
tions of foods in the diet to health-based guidance enables
an assessment of potential health impacts. Moreover,
the increasing availability of assay methods that require
less complicated and less expensive instrumentation has
increased the reporting of residue detects. However, like all
analytical methods, these less complicated assays must be
validated for the sample matrix being assayed. If the valida-
tion is lacking, this results in the reporting of residue values
that are not quantifiable or are reported in the absence of
the laboratory-derived limits of detection. Risk assessment
involves a comparison between the ADI or RfD, derived
G .. . 5229
from animal studies, and estimated exposure of the pesti-
cide from all sources. The objectives of this review are to:
() review the assays available for measuring glyphosate in
food, water, beverages, and urine; () review reports of test-
ing glyphosate in food or urine, and convert these values to
estimates of exposure; and () put these exposure estimates
into context by comparing them to health-based guidance
values used to assess risk.
2GLYPHOSATE ASSAYS
There are many different types of analytical technologies
that can and have been used to detect glyphosate and its
metabolite AMPA. Both molecules are highly polar and
ionic and have extremely limited solubility in organic sol-
vents, which makes their analysis more difficult than most
pesticides on the market today. As a result, glyphosate
and AMPA are not typically included in multiresidue pes-
ticide monitoring methods. A review by Koskinen et al.
() on methods for analysis of glyphosate and AMPA
in crops, water, and soil published between and
highlights the vast combinations of derivatization, separa-
tion, and detection techniques that have been attempted
over the years. The majority of published methods were
based on liquid chromatography with fluorescence detec-
tion (LC-FLD) or liquid chromatography coupled to mass
spectrometry (LC-MS/MS). However, in recent years, an
ELISA (enzyme-linked immunosorbent assay) kit has been
used increasingly for glyphosate analysis. Thus, this review
will focus on discussion of these three techniques and their
advantages and disadvantages for glyphosate analysis.
2.1 Liquid chromatography with
fluorescence detection
LC-FLD methods were developed before mass spectrom-
eters became common in analytical labs. While these
methods have drawbacks, as discussed below, they cur-
rently provide a reasonable alternative for labs without
access to more sophisticated LC-MS/MS equipment. Since
glyphosate and AMPA do not have a chromophore group,
typical LC detectors cannot be used for residue analysis
without first derivatizing the analytes. Although several
derivatization reagents have been tried (Arkan & Molnár-
Perl, ), the most commonly used are o-phthalaldehyde
(OPA) and -fluorenyl methoxycarbonyl chloride (FMOC-
Cl), both of which result in products that can be detected
using fluorescence. Since any compound in the sample
having a primary amine will be derivatized, the result-
ing chromatograms can have many peaks. Therefore, the
only means for identifying glyphosate and AMPA is by
comparison of the retention time to that of pure refer-
ence standards. This lack of specificity due to the occur-
rence of many peaks makes the analysis more susceptible
to matrix interferences, which can result in mistaken iden-
tification (false positives) or overestimation in quantitation
from coeluting matrix components. For this reason, com-
plex matrices, such as food and feed commodities, require
extensive sample cleanup and concentration steps prior to
analysis to reduce matrix interferences and to obtain the
desired method sensitivity. This makes these methods very
tedious and labor-intensive and limit the number of sam-
ples that can be analyzed in a day.
The method developed by Cowell et al. ()isan
example of a method that requires extensive cleanup
to obtain reliable detection at a limit of quantitation
(LOQ) of . ppm (mg/kg) for crop matrices using OPA
derivatization. A majority of LC-FLD methods, however,
have favored the use of precolumn derivatization using
FMOC-Cl (Druart et al., ; Fitri et al., ; Hogen-
doorn et al., ; Kaczyński & Lozowicka, ;LeBot
et al., ; Nedelkoska & Low, ;Wangetal.,).
Although these methods use less extensive sample cleanup
compared to OPA, they require careful optimization of
the derivatization reaction conditions to minimize matrix
effects. An advantage of FMOC-Cl methods is that the
derivatives of glyphosate and AMPA become less polar,
making them more readily separated using traditional
reverse phase columns and thus easier to implement in
most labs. This simpler chromatography is one reason why
FMOC-Cl derivatization is also used in several LC-MS/MS-
based methods, such as for analysis of milk and nutritional
ingredients (Ehling & Reddy, ), crops (Bernal et al.,
; Goscinny et al., ), and various foods (Liao et al.,
; Thompson et al., ).
2.2 Liquid chromatography coupled to
mass spectrometry
In general, complicated, multistep derivatization and
cleanup procedures are not desirable as they are time-
intensive and often more prone to errors. The intro-
duction of LC-MS/MS provided the ability to analyze
glyphosate and AMPA without derivatization and reduced
the degree of cleanup required. Several LC-MS/MS direct
analysis methods have been developed for different matri-
ces, including various crops (Botero-Coy et al., ;
Chamkasem & Harmon, ; Kaczyński & Lozowicka,
; Marek & Koskinen, ; Martins-Júnior et al., ),
food matrices (Chamkasem & Vargo, ; Chen et al.,
;Jensenetal.,; Nagatomi et al., ;Steinborn
et al., ; Zoller et al., ), and urine (Jensen et al.,
). LC-MS/MS provides added selectivity over LC-FLD
5230 G .. .
by using mass measurement for identification in addition
to retention time comparison to reference standards. The
increased specificity provided by MS/MS detection results
in greater sensitivity and accuracy, compared to LC-FLD
methods. The ability to use stable-isotope-labeled (e.g.,
C) analogs of glyphosate and AMPA as internal standards
adds another degree of confidence in confirming the ana-
lyte identity as well as improving accuracy and precision.
For these reasons, LC-MS/MS methods are typically pre-
ferred for analysis of glyphosate and AMPA.
2.3 Enzyme-linked immunosorbent
assay-based methods
ELISA has increasingly been used in the last years as
a simple and quick method for glyphosate analysis and
a commercial kit is available (Abraxis, now owned by
Eurofins Scientific, Luxembourg). Early application of the
ELISA was aimed at development, optimization, and val-
idation for analysis of glyphosate in water samples (Clegg
et al., ; Rubio et al., ) and was primarily intended
as a rapid screening tool, where any positive results would
be confirmed by a more quantitative method, such as
LC-MS/MS (Byer et al., ; Lee et al., ). Used in
this manner, ELISA can be a useful and effective tool,
especially for analysis of water samples where interfer-
ences from matrix components are limited. However,
since there are no sample clean-up or separation steps
involved in the ELISA, it is easy to see how application
to more complex matrices could present issues in accurate
quantitation.
According to the ELISA kit’s instructions, calibration
standards are prepared in water and the resulting stan-
dard curve is used to extrapolate the concentration of
glyphosate in the sample. This assay uses an indirect
competitive ELISA technique, which means glyphosate in
the sample competes with a glyphosate-enzyme conjugate
for antibody binding sites. Therefore, the intensity of the
absorbance signal generated by the enzyme reaction prod-
uct is inversely proportional to the amount of glyphosate
that is present in the test sample. Because the assay uses
indirect detection, components present in more complex
matrices, like milk, may interfere with multiple aspects
of the ELISA, including the glyphosate-enzyme conjugate
binding to the antibody, that would result in a decrease in
the amount of enzyme product generated. The resulting
lower absorbance signal would then be interpreted incor-
rectly as the presence of glyphosate in the sample. Even
with - or -fold dilution of samples prior to anal-
ysis, macroconstituents, such as sugars and lipids, could
still have an impact on the assay. Preparing the calibration
standards in the matrix being analyzed is an easy step that
could help correct for these matrix effects (Schmidt & Alar-
con, ; Singh et al., ), yet none of the reports cited
in this review using this ELISA have indicated using this
approach.
Even in the relatively simple matrices of surface and
ground water, some researchers found the assay tended to
overestimate glyphosate concentrations or generate false
positives (Byer et al., ; Mörtl et al., ), possibly
due to interferences from a range of components in sam-
ples, such as metal ions, organic matter, or high acid con-
tent. Unfortunately, the glyphosate ELISA is often applied
to complex matrices without validating performance in
the target matrix, such as with reports on breakfast foods
(ANH-USA, ; John & Liu, ), beer and wine (Cook,
; Fagan, ), and breast milk (Honeycutt et al., ).
In other studies, which used the ELISA to analyze human
and animal tissue samples (Krüger et al., ) or honey,
corn, and soy product samples (Rubio et al., ), reported
results included recovery tests in the matrices being ana-
lyzed, but did not evaluate potential matrix effects on the
limit of detection (LOD) or generation of false positives.
The glyphosate immunoassay approach has also been
extended to other formats, such as fluorescence covalent
microbead immunosorbent assays (FCMIA) (Biagini et al.,
) and immunostrip tests (Eurofins Abraxis, Warmin-
ster, PA). The FCMIA method, validated in water and urine
(Biagini et al., ), offers a promising way to analyze for
multiple pesticides simultaneously, but no similar valida-
tion has been published for the glyphosate immunostrip
tests
2.4 Assay validation
Assay validation is a requisite step no matter the type of
analytical method used. The method should be assessed
for its ability to generate accurate and reproducible data
at the glyphosate concentrations being measured and for
the sample matrix being analyzed. Method validation is a
rigorous approach in which several key parameters that
define the capabilities and limitations of the method are
evaluated. Validation criteria include defining the lin-
ear range, LOD, LOQ, specificity, accuracy, and precision.
Detailed discussion of each of these parameters and how
they are applied and evaluated under varying analytical
scenarios can be found elsewhere (Hill & Reynolds, ;
SANTE, ). The focus of this discussion of studies that
used the ELISA is on how particular aspects of these
parameters can impact confidence in the reliability and
accuracy of the glyphosate data produced.
Estimation of accuracy and precision are central com-
ponents of defining a method’s capabilities and are deter-
mined using spike and recovery experiments. A spiked
G .. . 5231
concentration at or near the LOQ (FAO/WHO, a)
should be tested to ensure assay accuracy since it is rea-
sonable to expect that these low levels of analyte are most
affected by interference from matrix components. When
glyphosate assays are conducted without examining the
accuracy of the ELISA in the relevant matrix (Cook, ;
Honeycuttetal.,; John & Liu, )orbyusingcon-
centrations spiked at much higher levels than the LOQ
(Krüger et al., ), the reported data cannot be accurately
interpreted.
Critical to reporting assay values at the low range is prop-
erly establishing the LOD and LOQ of the method used.
There are multiple techniques for determining LOD and
LOQ (Bernal, ;Corley,), but simply defined, the
LOD is the smallest concentration of analyte in a sam-
ple that can be reliably differentiated from the background
(e.g., blank sample), whereas the LOQ is the smallest con-
centration that provides a quantitative result with suit-
able accuracy and precision. It is not sufficient to define
the LOD and/or LOQ simply based on the lowest con-
centration in a standard curve, as this practice does not
account for the effects of matrix components and thus
does not reflect the true capability of the method. Instead,
the LOD and LOQ are specific to the matrix being ana-
lyzed and must be determined experimentally through the
use of blank matrix samples. Analysis of blank samples
is also important in demonstrating the specificity of the
method. If blank samples are not included, it is hard to
know if the glyphosate detected is real or a possible artifact
caused by components from the matrix or other reagents
that are interfering with the assay (ANH-USA, ; Cook,
; Honeycutt et al., ; John & Liu, ). Confirm-
ing results with a secondary method can be a useful tool
for verifying the presence (or not) of glyphosate in the
sample. Simply comparing results between two methods
should not, however, be the primary basis for determining
a method is valid, as was done by Krüger et al. () when
comparing an ELISA assay to GC-MS/MS, as this does not
verify the LOD/LOQ, accuracy, precision, or matrix effects
of the method being used.
2.5 Use of reported data
Pesticide residue reports should include clear descriptions
about the quality of the method being used since this infor-
mation is critical to evaluating the reliability of the data.
No analytical method is perfect or universally applicable
to all sample types, so it is important to know details of the
method used and to what extent, if any, the method was
validated for its stated purpose.
When interpreting data, treatment of values around the
LOD and LOQ can be a source of error or confusion. By
definition, values below the LOD are not reliably distin-
guished from background noise and thus often are better
reported as “not detected” or “<LOD.” Results above the
LOD but below LOQ, are by definition, not quantitative
and, therefore, are inconsistent with being mathematically
analyzed. If included in the report, regulatory agencies sug-
gest that they be regarded as qualitative results, often desig-
nated as <LOQ (EPA, ;SANTE,), and their treat-
ment in any statistical analysis be clearly stated and not be
included as its numeric value. Various resources (Corley,
;EFSA,;EPA,) provide guidance on how to
handle values below LOD or LOQ when performing calcu-
lations.
Using a method that has not been properly validated
may be suitable for qualitative assessments of the data,
such as comparing the frequency of detects between differ-
ent sample groups. However, if the data are being used to
make further calculations, statistical comparisons, or for
use in a risk assessment, then it is critical that there is
confidence in the numerical results. Studies that provide
the information needed to determine whether the method
was validated according to generally accepted standards
(FAO, ; Hill & Reynolds, ), including determi-
nation of LOD and LOQ, and if samples were analyzed
using appropriate quality control measures (FAO/WHO,
a;FDA,a) can be more reliably used in risk
assessments.
2.6 Summary about glyphosate assays
All methods have their pros and cons and a summary of
the relative merits of the three method types discussed is
summarized in Table . For instance, LC-MS/MS methods
to detect glyphosate and AMPA residues offer the most
sensitivity, specificity, and reliability across a wide variety
of complex matrices but are more expensive and require
greater expertise than other methods. Although the ELISA,
when compared to LC-MS/MS and LC-FLD, is quicker and
less expensive for analysis of glyphosate, reports to date
using this method to quantify glyphosate in complex matri-
ces have typically provided, as summarized below in this
review, little to no supporting validation data that allow the
results to be interpretable and repeatable by other scien-
tists (ANH-USA, ;Byeretal.,; Cook, ; Fagan,
; Honeycutt et al., ; John & Liu, ;Krüger
et al., ; Mörtl et al., ; Rubio et al., ). Regard-
less of technique, to interpret data, knowledge of the capa-
bilities and limitations of the method used are needed.
Thus, when reading about reports of glyphosate residues
where the data are presented without inclusion or refer-
ence to method details, validation details, or appropriate
validation of assay capabilities (e.g., LOQ, accuracy, and
5232 G .. .
TABLE 1 Relative differences in selected characteristics of types of assays used to quantify glyphosate in different matricesa
Sample matrix LC-MS/MSbLC-FLD ELISA
LOD/LOQ Water +++
Corn/soy + +++ ++
Milk + +++ ++
Urine +++
Accuracy Water +++ +++ +++
Corn/soy +++ +++ ++
Milk +++ +++ +
Urine +++ +++ ++
Specificity (lack of false positives) Water +++ +++ ++
Corn/soy +++ ++ +
Milk +++ ++ +
Urine +++ +++ +
Difficulty/time (incl. sample prep) Water + + +
Corn/soy ++ +++ +
Milk ++ +++ +
Urine + + +
Cost NA +++ ++ +
aRelative comparison of assay types and not of specific assays used in studies cited in this paper.
bRanking: +Low; ++ Medium; +++ High.
Abbreviations: ELISA, enzyme-linked immunosorbent assay; LC-FLD, liquid chromatography with fluorescence detection; LC-MS/MS, liquid chromatography
coupled to mass spectrometry.
specificity) in the relevant matrix, the results should be
regarded cautiously.
3RAW AGRICULTURAL
COMMODITIES
Global regulatory authorities, such as the U.S. FDA, U.S.
EPA, and the European Food Safety Authority (EFSA),
have required extensive data both prior to, and often after,
commercialization of pesticides, such as glyphosate. The
goal of monitoring food for pesticide residues by regula-
tory agencies is to ensure the public that pesticide appli-
cators are following approved label instructions and that
residues are not at unexpectedly high amounts (Winter
et al., ).TheU.S.FDAandEFSAcompileyearlymon-
itoring reports of pesticides using validated assays that are
capable of measuring multiple pesticide residues in a sin-
gle analysis. Access to comprehensive data from these sur-
veys is important to understand the average concentra-
tions, validation limits of the assays, and percent of the
samples that have detectable residue levels.
A new glyphosate assay, separate from the multiresidue
method, was developed and was first used with samples
from the survey in the EU (EFSA, ). In the United
States, an assay exclusively for measuring glyphosate was
first used for market surveys in samples obtained in
for a limited number of foods (FDA, b). A total of
, samples are tested and are reported in Tables –,
and >% of these had values that were less than the
MRL. The limited numbers of samples that had glyphosate
greater than the MRL suggest that there was a high degree
of compliance in use of glyphosate in the production of
these crops.
The paucity of peer-reviewed reports of glyphosate
residues in cultivated crops might be due to the complexity
of obtaining samples with adequate knowledge of specific
crop cultivation practices. Data from cultivation studies are
variable, especially when the variability of environmental
effects are not captured by a limited number of trial sites
(Fleming et al., ). Instead, it is easier, and more com-
mon, to do market surveys of the foods that consumers pur-
chase, recognizing that these will likely be blended com-
modity crops with various cultivation practices.
3.1 Soybean
Other than the surveys conducted by regulatory agen-
cies (Tables –) or residue studies submitted to regula-
tors, there are only two academic studies that measured
glyphosate residues in commodity crops and both are
with soybeans (Arregui et al., ; Bøhn et al., ).
Arregui et al. () conducted a study in Argentina at five
G .. . 5233
TABLE 2 Selected examples of market survey of unprocessed food items for detectable glyphosate in Europea
Commodity # Samples
# Detects
(%)
# Detects
>Tol . (%)
Min
Detect
(mg/kg)
Max Detect
(mg/kg)
Avg. Detect
(mg/kg)
Min LOQb
(mg/kg)
Max LOQ
(mg/kg)
EU
Tolerance
(mg/kg)
Small grains
Barley (%) . . . . .
Buckwheat and
other pseudo-
cereals
(%) (%) . . . . . .
Lentils (dried) (%) (.%) . . . .
Oat (%) . . . . .
Rye (%) . . . .
Wheat , (%) . . . . .
Animal-derived commodities
Animal fat (all) – – – . . None
Eggs – – – . . None
Milk (all) – – – . . .
Row crop commodities
Maize/corn – – – . .
Sweet corn – – – . .
Rapeseed/canola
– – – . .
Soybeans (%) . . . . .
Other commodities
Honey (%) (%) . . . . . .
aData sources: (EFSA, ,,).
bMultiple LOQs are reported by different countries in the survey; therefore, minimum and maximum LOQs are provided.
TABLE 3 Combined results for glyphosate in samples of corn, soybean, milk, and eggs in the United States (FDA and USDA)a
Commodity Source # Samples
# Detects
(%)
# Detects
>U.S.
Tol . (%)
Min
Detect
(mg/kg)
Max
Detect
(mg/kg)
Avg.
Detect
(mg/kg)
LOQ
(mg/kg)
U.S.
Tolerance
(mg/kg)
Soybean grains USDA
(%)
. . . .
Soybean grains FDA
(%)
.b . .
Corn (maize) FDA
(%)
.
b. . .
Milk FDA – – – . NTc
Eggs FDA – – – . .
aData Sources:(FDA, b,;USDA,).
bFDA designates residue levels detected above the LOD but below the LOQ as “trace.”
cNo tolerance for milk in the U.S. Codex and EU has MRL =. mg/kg.
farms over three growing periods. Glyphosate was mea-
sured using extraction and high performance liquid chro-
matography (HPLC) analysis with an LOD =. mg/kg.
Glyphosate was reported in soybeans at ., ., and
. mg/kg for two, two, and three applications, respec-
tively. AMPA values were lower (not detectable, . and
. mg/kg, respectively) than glyphosate concentrations.
The authors concluded that concentrations of glyphosate
and AMPA were greater when sprayings were applied later
in the growing season, near flowering.
Bøhn et al. () compared concentrations of
glyphosate between organic, conventional, and GT
5234 G .. .
TABLE 4 Summary offoods tested for glyphosate by CFIA in Canada and just needs a space separating of and foodsa
Program Food type
#Samples
tested
%Sampleswith
glyphosate
residues detected
%Sampleswith
glyphosate
residues above
MRLs
National Chemical Residue
Monitoring Programa
Fresh fruits and vegetables .% %
Processed fruits and vegetables .% %
Targeted SurveysaGrain products .% .%
Juice and other beverages .% .%
Bean/pea/lentil products .% .%
Soy products .% %
Children’s Food ProjectaInfant cereal .% %
Infant food .% %
Tot al .% .%
Kolakowski et al. () Other grains .% .%
Corn and corn products .% %
Pulses and pulse products .% .%
Wheat and wheat products .% %
Barley and barley products .% %
Oats and oat products .% %
Soy and soy products .% %
Dairy and/or meat % %
Fresh or processed fruits and
vegetables
.% .%
Infant foods .% %
Manufactured foods .% %
Tot al .% .%
aData Sources: (CFIA, ).
Abbreviation: MRL, maximum residue limit.
soybeans. Samples were collected during one growing
season from individual fields in Iowa. The samples
were analyzed by a commercial lab but information on
the type of assay and the LOD/LOQ was not provided.
The authors reported for the genetically modified soybean
samples that the average concentrations of glyphosate and
AMPA were . (range =.–.) mg/kg and . (.–)
mg/kg, respectively. There were no residues of glyphosate
or AMPA in the conventional or organic soybean samples.
The glyphosate residues from both studies (Arregui
et al., ; Bøhn et al., ) are less than the current
European MRL and U.S. Tolerances for glyphosate in soy-
beans ( mg/kg)and are within the values reported by
EFSA in multiple years of market basket surveys (Table ).
Soybeans have been tested using validated analytical
methods in surveys conducted by several regulatory agen-
cies from around the world. Glyphosate was detectable on
Current residue definition for glyphosate in soybeans is glyphosate only
in the EU, and the sum of glyphosate and N-acetlyglyphosate, expressed
as glyphosate, in the United States.
soybeans in % of the samples collected in the surveys con-
ducted by EFSA (EFSA, ,,)(Table). Other
commodity grains that are approved for import as GT crops
into Europe (corn and rapeseed) did not have detectable
glyphosate (Table ). The U.S. EPA survey specifically
tested crops due to public interest in GT corn and soybeans
and there were no residues greater than the tolerances
established by the EPA (FDA, b,). Glyphosate was
detected in % of soybean samples for the years of testing
(Table ). The USDA Pesticide Data Program (USDA, )
also conducts pesticide testing of foods related to infants
and they tested soybean samples grown in Missouri
from to . Glyphosate was detected in % of the
samples and the average amount of glyphosate was .
mg/kg, with a maximum of . mg/kg. The EPA estab-
lished tolerance for glyphosate on soybeans is mg/kg. A
survey conducted by regulators in Canada tested sam-
ples of fresh or frozen soybeans and found one sample with
glyphosate at a level less than the MRL; however, there is
no indication as to whether any of these samples were con-
ventional or GT varieties (Kolakowski et al., ).
G .. . 5235
3.2 Corn (maize)
Glyphosate residues in corn have not been quantified in
regulatory surveys conducted by EFSA and CFIA. Detec-
tion of glyphosate occurred in % of samples from the
surveys conducted in the United States where GT corn is
grown (FDA, b,); however, the average detectable
amount was . mg/kg, which is times less than the
EPA tolerance.
3.3 Other crops
In addition to the glyphosate residue levels summarized
above for two major crops, soybean and maize, residue lev-
els are available for other crops, including fruits, vegeta-
bles, and other grains, including regulatory agency surveys
(EFSA, ,,; Kolakowski et al., ; Zoller
et al., ). An early government agency report about ana-
lyzing foods for glyphosate was conducted on samples col-
lected in and in Germany (Scherbaum et al.,
). Information about the assay method or LOD and
LOQ is not provided. They analyzed grain samples (not
including corn) reported that two samples (millet and rye
crispbread) had detectable residues, both of which were
below the MRL. In general, fruits and vegetables had the
lowest detections of glyphosate compared to other food cat-
egories, and if detected, values were far less than the MRLs.
The crops with the highest percentages of detections were
lentils, beans, and wheat. Lentils had the most detections
(value >LOQ) in the European surveys, with glyphosate
detected in % of samples with .% exceeding the MRL.
Exceedances for buckwheat and honey are calculated from
MRLs that are not derived by field data but instead from
the LODs of the assays, which result in a significantly lower
MRL. For instance, the field-derived tolerance for cereals
in the United States is mg/kg compared to the assay-
derived value in the EU, which is . mg/kg. In Canada
(Kolakowski et al., ), glyphosate was most prevalent
in wheat, pulses, barley, and oat products and was of low
prevalence in fresh fruits, vegetables, and soy products. In
general, glyphosate was less prevalent in organic food than
conventional.
3.4 Animal products (milk, meat, and
eggs)
Animal products, with the exception of kidney and liver
due to their physiological functions, are not expected to
contain meaningful residues of glyphosate when animals
are fed crops cultivated with glyphosate at labeled appli-
cation rates. This is because glyphosate has a high water
solubility (. g/L), a low octanol-water partition con-
stant (log POW =−.), and is rapidly excreted via the kid-
ney (BfR, ; Bus, ). Three reports warrant detailed
review because they generated considerable online dis-
cussion (Honeycutt et al., ; John & Liu, ;Samsel
& Seneff, ). The first, an internet report, was about
human milk, but it is reported here because the physiology
of milk synthesis is similar across mammals and because
milk is a considerable source of nutrients for infants, chil-
dren, and neonatal mammalian animals. That report said
that glyphosate was found in three samples of human milk
(Honeycutt et al., ) based on the ELISA kit that was
not validated for a complex matrix like milk. A subsequent
study demonstrated that glyphosate was not detected in
human milk (McGuire et al., ) and it was accompa-
nied by a report (Jensen et al., ) of a validated assay that
was significantly more precise for milk than the assay used
by Honeycutt et al. ()(LOD=. vs. µg/L), respec-
tively. In order to not confuse whether their subjects actu-
ally had been exposed to glyphosate, McGuire et al. also
confirmed that nearly all of their subjects were exposed
to glyphosate at the time that milk samples were collected
by sampling urine and milk from each subject simultane-
ously. Subsequent reports have confirmed that glyphosate
is not detectable in human and bovine milk (EFSA, ;
Ehling & Reddy, ;FDA,b; NZ Ministry for Pri-
mary Industries, ; Steinborn et al., ; von Soosten
et al., ; Zoller et al., ). Ehling and Reddy ()
also demonstrated that glyphosate and AMPA were not
detected in bovine whole milk powder.
John and Liu () used the same ELISA kit to test
several foods, including locally purchased milk and beef.
Glyphosate was detected in organic milk, conventional
milk, beef, and fish at . µg/L, . µg/kg, . µg/kg,
and . µg/kg, respectively. The absence of data on
ELISA validation in this report (John & Liu, )for
these varied and complex samples makes the results from
this study difficult to interpret. Although this report has
only marginal information on how the analyzed samples
were collected, the reported data are also inconsistent with
results reported by other studies with meat, milk, and
egg samples in which validated assays and more complete
information on sample collection conditions are reported
(EFSA, ;FDA,b). Lastly, it is noteworthy that the
ELISA kit has been shown to generate false positives in
milk (Bus, ; Chamkasem & Vargo, ; McGuire et al.,
).
The third report that needs detailed review relative
to the topic of glyphosate in meat or other animal tis-
sues is by Samsel and Seneff (). This report was
apparently based on their interpretation of metabolism
studies that utilized radiolabeled glyphosate. They specu-
lated that glyphosate was synthetically incorporated into
5236 G .. .
proteins and suggested that it is “hidden” in pro-
tein molecules resulting in numerous maladies. For the
hypothesis presented by Samsel and Seneff ()tobe
consistent with the mechanism through which mam-
malian cells synthesize proteins, glyphosate would need
to substitute for glycine. However, it has been shown by
Antoniou et al. () that glyphosate does not substi-
tute for glycine in metabolically active mammalian cells.
Perhaps, the speculative interpretation of the metabolism
study results by Samsel and Seneff () comes from their
interpretation of a study (EPA, )inwhichasmall
percentage of the C-radiolabel was measured in bone
and muscle fractions. However, detections of C in these
samples were not molecularly characterized to confirm
the author’s speculations. Additionally, given the very low
detected levels of C-radiolabel and the timeframe, the
data most likely are the result of transient binding of C-
glyphosate to calcium in the bone as glyphosate is known
to weakly bind minerals, like calcium (Williams et al.,
). This is not an indication that glyphosate was incor-
porated into a protein.
Glyphosate has not been found in milk, eggs, or fish
from seven regulatory agency surveys, all of which used
validated assays (EFSA, ,,;FDA,b,;
Kolakowski et al., ; Zoller et al., ). One excep-
tion for the lack of glyphosate in animal products is that
glyphosate was above the LOQ in three samples of sausage
or meat loaf in the study of Zoller et al. (), but there was
no information about whether these samples were %
meat or if they contained plant-based fillers.
3.5 Summary about raw agricultural
commodities
Regulatory surveys are an important tool to ensure post-
marketing phytosantitary vigilance and play an important
role in regulatory risk assessment. Since approved pesti-
cide labels establish the legal limits that prevent unac-
ceptably high residue levels (Winter et al., ), these
survey studies monitor foods for pesticide residues to
assess whether pesticide applicators are following the label
requirements. In the vast majority of commodity analy-
ses, the observed residue levels are below the legal thresh-
old suggesting that most farmers are not exceeding prod-
uct label rates and that most harvested crops are legal for
trade (EFSA, ,,;FDA,b,). Assays
conducted as part of the regulatory agency surveys are vali-
dated in order to reliably and accurately measure the target
analyte(s), given the variety and complexity of the many
raw agricultural commodities included in these surveys.
The MRL is the highest level of a pesticide residue that
is legally tolerated in or on food or feed when pesticides
are applied correctly. The MRL is based on residue levels
obtained in supervised field trials under GLP where the
product is applied according to the proposed label instruc-
tions. Prior to formally setting the MRL, it is subject to a
risk assessment in which it is compared along with other
exposures with health-based guidance values. The ongo-
ing surveys of glyphosate residues beginning with sam-
ples collected in (EFSA, ) and most recently with
samples from (EFSA, ) suggest a high degree
of compliance and provide no indication that residues
have exceeded regulatory levels. Residue studies by non-
regulatory agency investigators are helpful additional data
beyond findings of regulatory agencies; however, the pes-
ticide data need to be collected with detailed, validated
methodology that generate reliable results.
4PROCESSED FOODS
This section reviews foods that are derived from products
that were derived from crops sprayed with glyphosate dur-
ing cultivation. Although it might be reasonable to expect
glyphosate residues in processed foods to reflect the lev-
els in their raw agricultural commodities, the washing and
removal of the outer coating of grains during food process-
ing would be expected to reduce residues. Isolation of por-
tions of foods/feeds that contain glyphosate, such as hulls,
or by drying might increase the residue concentration.
4.1 Soy products
Most soybeans are not consumed directly by people,
instead they undergo various processes to produce differ-
ent soy fractions, such as soy protein concentrate or iso-
lated soy protein. Rubio et al. () used the ELISA kit to
test soy fractions and they reported that the assay was vali-
dated for each matrix, but details of the validation informa-
tion were not provided. Also, the reported LOQ for several
substances is the same as the LOQ reported for qualitative
measurement of glyphosate in water according to the kit
instructions, suggesting that the LOD was not established
independently for the matrices tested. Glyphosate was
detected in eight out of (%) soy sauce samples. Con-
centrations were greater than the method LOQ ( µg/L)
with a range between and µg/L and a mean of
µg/L. They also claim that glyphosate was not detectable
in soy milk or tofu (Rubio et al., ). Rodrigues and de
Souza () tested brands of soy-based infant formulas
in Brazil using a validated HPLC method with a stated LOQ
=. mg/kg. Multiple samples of these infant formulas
were tested from to and they found that of the
brands consistently had no detectable concentrations
G .. . 5237
of glyphosate. The eight brands that tested positive were
further assessed according to the degree in which the
ingredients from soybeans were processed. Three brands
were made from minimally processed soybean extract and
had, on average, . mg/kg of glyphosate. The other five
brands were made from the more highly processed soy pro-
tein isolate and had, on average, . mg/kg of glyphosate.
It is reasonable to expect that soy protein isolate would
have lower amounts of glyphosate compared to soybean
extract since significant amounts of glyphosate should be
removed during the additional water-based processes to
produce soy protein isolate.
4.2 Breakfast cereal
A report of breakfast foods was issued by the Alliance for
Natural Health (ANH-USA, ) in which a variety of
products, including grain-based foods, coffee creamer, and
eggs were tested for the presence of glyphosate residue.
Despite the variety of matrices, all testing was done with
the Abraxis ELISA kit and it appears that most foods were
tested assuming the kit-sensitivity of µg/L, but it is
unclear whether this value was used as an LOD or LOQ.
Likewise, the authors report that glyphosate was detectable
in eggs, both conventional and organic, and in “organic
coffee creamer.” The eggs and organic coffee creamer had
reported concentrations of glyphosate > µg/L, results
that are not consistent with other reports, including regu-
latory market basket surveys using validated methods, that
were unable to detect glyphosate in milk or eggs (EFSA,
,;FDA,). All of the other breakfast products
that were reported as positive for glyphosate in the ANH-
USA report contained wheat or oatmeal. A Swiss agency
survey also tested breakfast cereals and of samples had
glyphosate residues that were above the LOQ (Zoller et al.,
).
4.3 Infant foods
Regulatory agencies tested foods that were categorized as
infant food. In a survey conducted in Canada (CFIA, ),
there were samples classified this way and con-
tained quantifiable glyphosate, none of which was more
than the MRL (Table ).
The Infant Total Diet Study (iTDS) conducted in France
(ANSES, ) surveyed dietary ingredients specifically
intended for infants. Modeling intake of infants is critical
because total food consumed per unit of body weight is
usually greater for children (<-year old) than for adults,
and because children and infants typically consume a
smaller variety of food types. This study tested sub-
stances from foods prepared as consumed. Glyphosate was
detected in both of the two tested breakfast cereal samples.
The Australian and New Zealand Regulatory Author-
ity purchased replicate samples of food items that were
analyzed for many agricultural chemicals. Some chem-
icals, including glyphosate, were tested in a subsample
of the foods that were targeted as suspected of being
likely sources of exposure to agricultural chemical residues
(FSANZ, ). Among the subsample of foods tested for
glyphosate residue were rice-based, breakfast cereal and
mixed infant cereal. For both foods, the percentages of
detects (values >limit of reporting) were % and mean
concentrations of residues were . mg/kg. Other reg-
ulatory agencies did not detect glyphosate in baby food
(Zoller et al., ) nor in milk-based infant formula
(Kolakowski et al., ); however, these are difficult to
compare because they could contain different ingredients
and source of grains, and processing methods could have
an impact on residues.
4.4 Ice cream and sugar
The Organic Consumers Association reported an anal-
ysis of glyphosate in various flavors of Ben & Jerry’s
(Unilever, South Burlington, VT) premium (high-fat) ice
cream (OCA, ). The LOD and LOQ were reported to
be . and . µg/L, respectively, but no other informa-
tion about validation was provided, including the assay
method. All flavors except one had detectable amounts
of glyphosate, but concentrations of glyphosate were not
reported. Cream and skim milk are principle ingredi-
ents in ice cream and as discussed above milk has con-
sistently been shown not to contain detectable amounts
of glyphosate (EFSA, ; Ehling & Reddy, ;FDA,
b; NZ Ministry for Primary Industries, ;Steinborn
et al., ; von Soosten et al., ; Zoller et al., ).
The Canadian survey (Kolakowski et al., ) also tested
samples of plain yogurt and plain custard and did not
detect glyphosate. Furthermore, the milk fat levels, that are
higher in premium ice creams compared to other lower fat
brands, would make it even less likely that the milk ingre-
dient would be the source of glyphosate since glyphosate
is not lipophilic (Bus, ; Shelver et al., ). Vanilla
ice cream is the simplest of the recipes that tested pos-
itive. Besides milk, the only other ingredients currently
listed for Ben & Jerry’s vanilla ice cream are sugar, egg
yolk, water, guar gum, vanilla extract, vanilla bean, and
carrageenan. None of these ingredients are expected to
contain glyphosate. Even sugar derived from either sug-
arcane or GT sugar beets would not be predicted to con-
tain glyphosate, due to the water solubility of glyphosate
(Williams et al., ) that would reduce residues
5238 G .. .
during the water-based processing to crystallize food-grade
sugar. A recent study used LC-MS/MS and determined
that, although glyphosate residues are found in GT sugar
beets, due to the water processing steps for crystalizing
sugar, this herbicide is not detectable in the final product
(Barker & Dayan, ).
Combining the lack of information on the analytical
method used to measure glyphosate levels with the lack of
any ingredients in this premium ice cream product being a
plausible source of glyphosate residue, the scientific valid-
ity of this report is questionable.
4.5 Honey and sugary syrup
There are several reports about glyphosate in honey and
presumably the glyphosate would be from honey bees for-
aging for nectar from plants exposed to glyphosate. These
reports vary in where samples were collected and assays
utilized. The ELISA method was used to test honey for
glyphosate without any modification or validation of the
assay (Rubio et al., ). The authors reported that of
honey samples had quantifiable amounts of glyphosate
(range of – µg/kg). The highest reported value of
µg/kg from this nonvalidated assay would exceed the
EU MRL for honey, which is µg/kg (European Commi-
sion, a), while the U.S. EPA does not have a tolerance
for honey (CFR, ). They also tested pancake and corn
syrup and said that glyphosate was not detectable in these
highly processed sugar-based items.
FDA scientists developed an LC-MS/MS assay to detect
glyphosate in honey (Chamkasem & Vargo, ). The val-
idated assay had an LOQ = µg/kg, and of sam-
ples bought from a local market had glyphosate >LOQ.
Of these, the median concentration of glyphosate was
µg/kg with a range of – µg/kg.
Glyphosate was measured in honey from hives on the
island of Kaua‘I, Hawaii in five “batches” (Berg et al.,
). The different collections were as follows: () two
hive samples in fall, ; () hive samples during
the summer of ; () hive samples in fall, ;
() retail samples in winter, ; and () three retail
samples in fall, . All analyses were done using the
ELISA through three different labs depending on the
batch. The authors state that samples were tested with
both the ELISA and an LC-MS/MS method; however, no
validation information is provided. They reported that
glyphosate was quantifiable in .% of samples, which
are not independent samples, and the mean value was
. µg/L.
An assay was developed and reported by Pareja et al.
() using ion chromatography coupled to Q-Orbitrap
MS. Assay validation information is reported with an
LOQof.µg/g. They reported that the assay had a
medium matrix effect. Sixteen samples of honey taken
from hives, and commercial samples from South Amer-
ica and Europe, were tested and % of the samples
had detectable concentrations of glyphosate. Half of the
honey samples with detectable glyphosate had concen-
trations greater than the European MRL of µg/kg.
Concentrations of glyphosate in the detectable samples
were not reported, and AMPA was not detected in any
sample.
Another study using derivatization prior to solid phase
extraction coupled to LC-MS/MS was used to analyze
randomly selected honey samples from those submitted
to the lab (Thompson et al., ). There was no indica-
tion as to whether all of these were independent samples.
Validation information was provided, and glyphosate was
detectable above the LOQ of µg/kg in of the samples.
The greatest concentration of glyphosate was . µg/kg
and they indicated that there were no samples with both
glyphosate and AMPA greater than the LOQ. They provide
a scatter plot of both analytes, and the ratio of glyphosate
to AMPA appeared to vary anywhere from approximately
/ to /. There is no explanation for why these would
vary to this extent. The source of all AMPA is not necessar-
ily derived as a metabolite of glyphosate as another source
may be from degradation of phosphonates used as deter-
gents (Botta et al., ).
Honey was tested in two regulatory agency surveys
and had detectable glyphosate in % of samples (EFSA,
,,), which is much less than detections
in other studies. LOQs reported by the different coun-
tries that tested these honey samples ranged from .
to . mg/kg. Whereas, in the Swiss survey, honey had
detectable glyphosate in of samples (LOQ =.
mg/kg) and with a mean concentration of . mg/kg
(Zoller et al., ). None of the honey samples had
detectable amounts of AMPA and honey samples had
glyphosate values greater than the LOQ for AMPA, sug-
gesting that for these samples, if AMPA was present, it
would not be greater than the concentration of glyphosate.
This is inconsistent with the data of Thompson et al.
(), in which many of the samples had more
AMPA than glyphosate. One noteworthy aspect of the
publication of Zoller et al. () is that individual LOQs
are provided for each food category and for each of the
glyphosate and AMPA assays. Therefore, it is meaning-
ful that this validated study showed that the concentra-
tion of AMPA was never greater than % of the value for
glyphosate when both glyphosate and AMPA were greater
than or equal to their respective LOQs. This is in con-
trast to other studies that did not report validation, and
occasionally reported AMPA levels that were greater than
glyphosate.
G .. . 5239
4.6 Beer and wine
The Munich Environmental Institute (Guttenberger &
Bear, ) tested German beers using the ELISA kit
method. The reported LOD is . µg/L, a multiple of
the LOD reported by the kit manufacturer for analy-
sis of glyphosate in water. However, Guttenberger and
Bear () do not include assay validation data that
compare the assay performance between water and beer
samples, and yet beer includes alcohol and other con-
stituents that would reasonably be expected to affect
ELISA methods. They indicated that all samples had
detectable glyphosate with a value ranging from . to
. µg/L. In , this same group conducted a new round
of beer testing, which was reported in the media, but a pub-
lished report is currently not available online. The German
Federal Institute for Risk Assessment (BfR, ) issued a
statement about these results in which they indicate that
detection of glyphosate in beer is not unexpected. Based on
these values, the BfR concluded that, regarding glyphosate,
an adult would be able to drink L of beer per day with
a reasonable expectation of safety.
The California Public Research Group (Cook, )
reported concentrations of glyphosate in five brands of
beer and brands of wine. However, interpretation of
the results in this report is difficult for two reasons. First,
the report is unclear about the assay method employed,
because it cites an LC-MS/MS assay method but then gives
detailed steps for using the ELISA method. Additionally,
independent of which assay was actually used, there was
no validation or LOD/LOQ reported. They reported that
of tested beers and wine had detectable glyphosate.
For nonorganic wine, values ranged from . to . µg/L.
Nonorganic beers ranged from . to . µg/L. Two brands
of beer and two brands of wine labeled as organic were
tested and one beer and both wine samples were reported
to have glyphosate at ., ., and . µg/L, respectively.
Considering that grapes are almost exclusively the whole-
food ingredient used in many wines, it is reasonable to
conclude that grapes would be the source of glyphosate in
wine but because grapes are sensitive to glyphosate they
are not sprayed directly. But glyphosate is used between
the rows of vineyards because it is not taken up into the
vines through the roots. It would have to enter plants pre-
dominantly by droplets that get onto the leaves through
overspray. Also, it would have to be in an amount that is
low and does not kill the plant. Therefore, for glyphosate
residues to be present in grapes used to make wine, they
would be expected to be very low. Even though grapes are
not sprayed directly, there is an MRL for wine grapes in
the EU, which is µg/kg. The most common grains used
for making beer are barley, wheat, maize (corn), and rice,
all of which are crops that can be sprayed with glyphosate
preplanting and corn is the only one of these available as
GT.
In the Swiss food survey that reported values from a val-
idated assay, beer had detectable amounts of glyphosate in
only of samples (median value was <. µg/kg) but
glyphosate was detectable in % of wine samples (.
µg/kg). AMPA was not detectable in any beer sample and
was detectable in of the wine samples.
Notwithstanding the questions about the validity of
the analytical methods and the agronomic source of
glyphosate residues, it is reasonable to conclude that
glyphosate has been detected in beer and wine samples,
and residues on grains used for beer or grapes for wine are
the probable sources.
4.7 Enteral formula
A website (Seneff, ) reported testing of samples
from a single batch of a commercial enteral formula using
the ELISA kit at a commercial lab with a stated LOD
= µg/L. As stated previously, this value is provided
by the kit for water analysis and there was apparently
no validation reported for this lab and sample matrix.
Although the samples came from the same batch, of the
samples had detectable glyphosate (ranged from to
µg/L).
4.8 Summary about reports on
processed food
The presence of pesticide residues in foods is regulated by
global authorities to ensure food safety by establishing real-
istic levels of human exposure. Therefore, while reports of
the detection of glyphosate residues in certain processed
foods can be predicted, as long as the levels are below
the established legal limits, food safety is ensured. How-
ever, interpreting reported values can be difficult when
assays are not validated or there is an unstated applica-
tion of an appropriate LOD. However, if assuming these
reported values for glyphosate are accurate, most values do
not approach the MRL. Regulatory Agency surveys have
tested many of these same, or similar, processed foods
and provide more reliable information. One food item
that seems worthy of additional consideration is honey,
for which a disproportionate number of samples seem to
approach, or exceed, the MRL. More detailed studies with
validated assays would help address the current high vari-
ability in glyphosate residue levels from the many reports
with honey summarized above, since some of the variabil-
ity might be due to the rapid decline in glyphosate in nectar
over time (Thompson et al., ).
5240 G .. .
5 RISK ASSESSMENTS
One key goal for regulatory authorities is ensuring food
safety by modeling realistic levels of human exposure to
a given pesticide that provide a “reasonable certainty of
no harm” for the consumer (Winter et al., ). Given
that different approaches to exposure modeling exist (see
below for examples), after experimental data have estab-
lished an upper boundary for the level of a given chem-
ical (e.g., pesticides like glyphosate) that might result in
an adverse effect, regulatory authorities integrate into their
health risk assessment the concept of an “uncertainty fac-
tor” (Herrman & Younes, ). The desire to use uncer-
tainty factors is founded on the expectation that reduc-
ing the potential for exposure by an appropriate “factor”
(for the ADI for glyphosate, the uncertainty factor is ),
will yield the required “reasonable certainty of no harm”
from exposure to the given chemical for the majority
of the population, including vulnerable subgroups. How-
ever, consumers have typically looked to health care pro-
fessionals, nutritionists, and dietitians for their views on
whether these regulatory processes ensure the safety of
foods from agricultural use of pesticides (both conven-
tional and organic). As mentioned above, the current train-
ing curricula for the professions that consumers look to
for guidance have limited, if any, coursework on relevant
topics, so it is critical to have these professionals become
well-informed on how residues relate to overall food con-
sumption and safety (Sanborn et al., ; Temte & McCall,
). One key concept critical to an understanding of
how regulatory processes ensure food safety is the empir-
ical data for pesticide residues that are used by regula-
tory authorities to establish MRLs and tolerances related
to the legal application of the pesticide in agriculture.
Importantly, a single residue measurement is insufficient
to conclude safety (or imply lack of safety) since a sin-
gle residue level is only a part of this larger assessment.
Notably, since , the Environmental Working Group has
annually released reports on pesticide residues in fruits
and vegetables (EWG, ). These reports rank fruits and
vegetables for the presence of residues but they do not pro-
vide consumption estimates in comparison to the amounts
that are determined to be safe by regulatory agencies. Win-
ter and Katz () responded to this report by calculat-
ing from these same data that all exposures were less than
% of the RfD and most were <.% of the RfD. This
illustrates the importance of an assay needed to quantify
residue accurately. To be meaningful to discussions of food
safety, it is critical that reports of “detections” of a residue
are put into the context of consumption and toxicity. This
section will review published risk assessments that com-
pare dietary exposure of glyphosate to the ADI and these
studies are summarized in Table .
5.1 EFSA assessment
As part of EFSA’s most recent report on pesticides in
food, dietary assessments of glyphosate were conducted
(EFSA, ). EFSA conducted a short-term dietary assess-
ment for glyphosate that examined the impact of eat-
ing large portions of unprocessed foods that contain the
highest reported residues. They concluded that this type
of high-intake, short-term dietary exposure to glyphosate
would not be expected to be of concern for consumer
health. The chronic risk assessment is meant to predict
lifetime exposure. EFSA used two approaches for how
they dealt with concentrations of glyphosate in a food
that were <LOQ: () a more conservative approach in
which the concentration of glyphosate was set to the
LOQ; and () a less conservative approach in which con-
centrations of glyphosate were set to zero. Using these
approaches, they calculated that chronic exposure to
glyphosate based on assumptions of these models ranged
between .% and .% of the ADI. Even though these
values excluded residues in drinking water, this expo-
sure is over two orders of magnitude below the ADI and
it provides a reasonable certainty that there would be
no-harm.
5.2 EPA assessment
EPA () conducted a highly conservative dietary risk
assessment that assumed residues of all commodities are
at the tolerance, % of a commodity is treated, and the
default processing factors from the Dietary Exposure Eval-
uation Model (DEEM Version .) were used. Residue
amounts at the tolerance level for each food are multiplied
by the daily intake of that food, and these are summed
to get the estimated residue intake. For the U.S. general
population, the conservative estimated intake was .
mg/kg/day, which is % of the U.S. RfD of . mg/kg/day.
The same conservative level of intake would be % of the
EU ADI.
5.3 Swiss study
In the Swiss study (Zoller et al., ), dietary exposure
was calculated and the authors considered that this was
done conservatively by choosing food consumption values
that overestimate actual daily average consumption. They
compared individual food categories using median or max-
imum residue values. If median residues were used, they
concluded that individual food categories were less than
.% of the ADI/ARfD. The ARfD (acute reference dose),
established by the EU, is the amount of a substance that
G .. . 5241
TABLE 5 Modeling for chronic dietary consumption of glyphosate
References Residue Processing <LOD
Food consumption
source
ADI or
RfD(mg/kg/day)
Exposure (%
ADI or RfD)
EPA () % of crop treated and all food
at tolerance amounts
Default processing factors N/A Daily food intakes from
DEEM
%
EFSA () From residue testing Assumes residue =..%
From residue testing Assumes residue =
LOD
. .%
FSANZ () Mean concentrations from
testing
Prepared ready-to-eat Assumes residue = – Australian
National Nutrition and
Physical Activity Survey
. <%
Zoller et al. () Median residues from testing . .%
Max residues from testing . <%
FAO/WHO ( ) Median residues from supervised
trials
Median residues from supervised
trials for processed foods
GEMS .%a
Stephenson and
Harris ()
All foods at EU MRL Uses commodity residues (i.e.,
sugar beet for table sugar)
UK toddler . .%
EU MRL or median residues
from supervised trials
Uses commodity residues (i.e.,
sugar beet for table sugar)
UK toddler . .%
EU MRL or median residues
from supervised trials or
monitoring residues
Processing factors Irish adult . .%
Actual residues (barley residues
matched to commodity
intakes)
Processing factors Irish adult . .%
From testing, unmeasured
residues =
Processing factors Assumes residue = Dutch adult . .%
From testing, unmeasured
residues =MRL
Processing factors If <LOR residue =
LOR
Dutch adult . .%
aValue represents the median of the GEMS Cluster Diets (G–G); range across all cluster diets is .–.% of ADI.
Abbreviations: ADI, acceptable daily intake; LOD, limit of detection; LOR, limit of reporting; RfD, reference dose.
5242 G .. .
can be consumed in a single meal or over a -h period
without appreciable health risk. If maximum values were
used, all food categories were <%. They concluded that
these residues for any food category were not a cause for a
health concern.
5.4 Australia Total Diet Study
The Australia Total Diet Study (FSANZ, )estimates
the exposure of the general Australian population to agri-
cultural chemicals, including glyphosate. This modeling
used the following conditions: () food samples were pre-
pared ready-to-eat; () mean concentrations of glyphosate
in samples were used; () concentrations of glyphosate
in food items that were <LOR (limit of resolution) were
assumed to be zero; and () food consumption data
were used from the to Australian National
Nutrition and Physical Activity Survey. For dietary expo-
sures to glyphosate, they determined that the estimated
mean and th percentile exposures were .–.
µg/kg BW/day and .–. µg/kg BW/day for all age
groups years and above, respectively. These values for
all age groups were <% of the Australian ADI, which is
. mg/kg.
5.5 Joint FAO/WHO Meeting on
Pesticide Residues
The Joint FAO/WHO Meeting on Pesticide Residues
(JMPR) (FAO/WHO, ) considered acute and long-term
dietary exposures to glyphosate. The JMPR concluded
that an ARfD for glyphosate was not necessary and this
meeting likewise concluded that the acute dietary expo-
sure to residues of glyphosate is unlikely to present a public
health concern.
For the long-term assessment, the median residues
from standardized trials (STMR), or the STMR for pro-
cessed foods were used, and intakes were calculated for
regional cluster diets defined by the Global Environment
Monitoring System (GEMS) (WHO, ). These calcula-
tions assume an ADI of mg/kg of body weight and the
daily intake of glyphosate was estimated to range between
.% and .% of the ADI (median =.%).
5.6 Deterministic and probabilistic
modeling
Modeling of acute exposure to a chemical, like glyphosate,
typically follows one of two approaches: deterministic or
probabilistic. Deterministic approaches establish an expo-
sure for a single consumer from a single high-residue food
with a high-level of consumption (.th percentile), while
probabilistic approaches (i.e., Monte Carlo Risk Assess-
ment model) establish a distribution of acute exposures
for different populations from all sources of the chemi-
cal. Both deterministic and probabilistic approaches were
used to model exposure to glyphosate in the EU (Stephen-
son et al., ). The deterministic method used either the
highest residue value or median residue for a commod-
ity, or when not available, the MRL. Using this conserva-
tive method, the majority of foods had glyphosate levels
<% of the ARfD. Moreover, foods with glyphosate levels
predicted to be above % typically were raw agricultural
commodities that are subsequently cooked or processed
in a way that often results in a lower residue (Barker &
Dayan, ; Kolakowski et al., ; Stephenson et al.,
; Williams et al., ). By comparison, probabilis-
tic modeling of exposure to glyphosate was done for the
Dutch adult and child based on empirical monitoring data
collected between and in the UK (Stephenson
et al., ). Probabilistic exposure models account for vari-
ations in consumption patterns and variations in residue
concentrations in order to estimate optimistic and pes-
simistic exposure scenarios according to EFSA guidance
(EFSA Panel on PPR, ). Using these assumptions and
scenarios, all individuals had exposures to glyphosate of
<% of the ARfD. They concluded that acute dietary expo-
sure to glyphosate is unlikely to represent a concern.
Probabilistic exposure models account for variations in
consumption patterns and variations in residue concentra-
tions in order to estimate optimistic and pessimistic expo-
sure scenarios according to EFSA guidance (EFSA Panel
on PPR, ). Using these assumptions and scenarios,
all individuals had exposures to glyphosate of <% of
the ARfD. They concluded that acute dietary exposure to
glyphosate is unlikely to represent a concern.
Similar deterministic and probabilistic approaches were
taken to model chronic exposures to glyphosate (Stephen-
son & Harris, ). The worst-case deterministic model
was the theoretical maximum daily intake (TMDI). The
TMDI approach combines the average daily regional con-
sumption levels with the MRL for each commodity and
sums these intakes for all commodities. It indicated that
the maximum exposure was approximately .% of the EU
ADI (. mg/kg BW/day). As in other models, foods that
accounted for much of the glyphosate intake are known
to overestimate realistic exposures, such as glyphosate
residue levels in whole sugar beets instead of refined sugar;
and, milk and cream that have not been shown in mar-
ket surveys to contain detectable glyphosate. These com-
modities accounted for % of the glyphosate consumption
derived by using the TMDI approach. In refined chronic
dietary models that used processing factors and STMR
G .. . 5243
values or actual residues, the exposure is progressively
reduced to .% of the ADI (Table ).
Probabilistic modeling was also performed using EFSA
guidance on chronic dietary exposure. When there were no
monitoring data or unmeasured residues in animal com-
modities, the pessimistic scenario used MRL values, while
the optimistic scenario used a zero. Treatment of residues
less than the LOR was set at the LOR for the pessimistic
scenario and set to a zero for the optimistic scenario. Using
this approach, the .th percentile exposures for adults
were determined by the pessimistic and optimistic scenar-
ios to be .% and .% of the ADI, respectively. For
the children aged – years old, exposures were .% and
.% of the ADI, respectively.
One report analyzed estimated maternal exposure to
glyphosate using two different approaches (McQueen,
Callan, & Hinwood, ). One approach measured
glyphosate in composited aliquots of food consumed for
a -h period and the weight of this food that each
subject consumed. This was done for each of preg-
nant women in Australia and the assay used was an
LC-MS/MS method with an LOD and LOQ of . and
. mg/kg, respectively. They calculated that the aver-
age dietary consumption of glyphosate +AMPA was .%
of the Australian ADI (. mg/kg/day). For the second
approach, pregnant women were used and exposure
to glyphosate +AMPA was determined by recording for
h weight and type of food consumed. These amounts
were multiplied by the MRL for each of the food types.
Using this approach, mean dietary exposure was % of
the ADI. Similar to modeling studies cited above, regard-
less of the calculation used (actual residues vs. MRL),
both approaches resulted in estimates that were at the
low end of the ADI and the method using actual residues
was times less than the MRL method (McQueen et al.,
).
5.7 ANSES Infant Total Diet Study and
risk assessment
A study evaluated the impact of chemicals, including
glyphosate, in the diets of infants less than years old
(Hulin et al., ). The conclusion of the study was that
the ADI for glyphosate was not exceeded for this popu-
lation and, using the most conservative assumptions, the
th percentile consumption was .% of the ADI. This
conclusion was based on an older ADI for glyphosate of
. mg/kg BW for the EU that was later increased to
the current . mg/kg BW, suggesting that the difference
between modeled intake and the current ADI is now
greater.
5.8 Summary about risk assessments
Unlike the warnings from the Environmental Working
Group released annually to consumers about produce that
cites detection of residues, risk assessments conducted by
regulatory authorities put these residue measurements in
context by using dietary models that estimate a daily intake
that can then be compared to previously established daily
exposure thresholds that have a reasonable certainty of no
harm. Although risk assessments for glyphosate follow this
general approach, each uses various assumptions to test
the robustness of their conclusions. The dietary modeling
for risk assessments for chronic consumption of glyphosate
and some of their assumptions are summarized in Table .
The six published assessments, five being conducted by
regulatory authorities, all reach a conclusion that, regard-
less of the assumptions being used, exposure of people to
glyphosate is less than the ADI, which includes infants,
children, and adults. These results are important since it
has been suggested that the use of glyphosate has intensi-
fied as a result of increased use in recent years due to the
adoption of Roundup Ready crops (Benbrook, ), creat-
ing a perception that exposure is unexpectedly too high.
The results from these assessments by regulatory agen-
cies would indicate that exposure to glyphosate is within
amounts that are considered to cause no harm.
6 ESTIMATING DIETARY EXPOSURE
FROM URINE
6.1 Metabolism of glyphosate and
presence in urine
The prior sections summarize studies that directly mea-
sured glyphosate residue in a variety of sources, includ-
ing a number of raw and processed foods, which are
then used to model dietary exposure and compare these
results to regulatory thresholds that ensure public safety.
However, exposure to glyphosate can also be assessed by
measuring the levels of metabolic excretion of ingested
glyphosate. Approximately % of ingested glyphosate in
mammals is absorbed from the gastrointestinal tract into
the circulatory system (Niemann et al., ). The half-lives
for an oral dose were approximately h for the αphase
(distribution) and βphase (elimination), which indicates
rapid clearance and poor absorption (FAO/WHO, b;
Williams et al., ). Virtually, no absorbed glyphosate is
metabolized, and it is cleared from the body by the kid-
neys (Niemann et al., ). Consequently, the presence
of glyphosate in urine is not unusual, and detection of
glyphosate in urine that is within the ranges observed with
5244 G .. .
typical exposures is not indicative of a health risk. Instead,
glyphosate in urine reflects absorption and excretion lev-
els that regulatory agencies have reviewed extensively and
concluded is safe (BfR, ). Elevated glyphosate con-
centrations can occur when urine volume is reduced for
various physiological reasons independent of exposure to
glyphosate. Elevated levels of urinary glyphosate can also
result from rare instances of high exposure to glyphosate,
such as is documented in the Farm Family Exposure Study
(Acquavella et al., ). Moreover, AMPA is often
detected in urine, but since glyphosate is virtually not
metabolized within the body itself, AMPA in urine is
most likely the result of absorption of ingested AMPA,
not metabolism of absorbed glyphosate (Niemann et al.,
). Possible sources of AMPA are from consumption of
foods from crops that have metabolized glyphosate (Reddy
et al., ) and/or from detergents from a variety of
sources that are known to contain AMPA (Botta et al.,
).
As a result of the known characteristics of absorption,
metabolism, lack of bioaccumulation, and excretion of
glyphosate described above, total glyphosate ingestion can
be estimated reliably by knowing the glyphosate concen-
tration in urine. Comparing the estimated level of exposure
to glyphosate from studies measuring urinary glyphosate
levels, with the ADI for glyphosate is informative about
safety.
For an adult human with a urine output of L/day,
the formula to estimate glyphosate ingestion in µg/kg/
day is:
Glyphosate Ingestion (𝜇g∕kg∕day)
=C
urine∗Vurine ∗0.20−1∗BW−1
where Curine is concentration of glyphosate in urine
(µg/ml) and Vurine is daily output of urine (ml/day). This
section assumes kg for an average body weight for this
calculation based on Niemann et al. ().
This formula uses the reasonable assumption that
ingestion is the primary route of exposure to glyphosate
when tested individuals have not recently sprayed with
glyphosate. If so, this formula provides an estimate of total
glyphosate and does not rely on subjects estimating, often
with low precision (IOM, ), their consumptions of dif-
ferent types of food or water and measuring, or estimat-
ing, glyphosate in these potential sources. Exposures of
glyphosate as a percentage of the ADI or RfD estimated by
this method can be compared to the exposures discussed
in Section of this paper as a way to determine if values
from these two distinct methods corroborate one another
(Tables and ).
6.2 Exposure estimated from urine
.. Publications in journals
Niemann et al. () provide a comprehensive discussion
of using urine to determine exposure and put it into context
by comparing it to health-based guidance. They reviewed
seven reports of studies in which samples of urine from
human subjects were collected and analyzed (Acquavella
et al., ; Curwin et al., b; Honeycutt et al., ;
Hoppe, ;Krügeretal.,; Markard, ; Mesnage
et al., ). However, it should be noted that Niemann
et al. () cite an unpublished report by Markard (),
and apparently a subset of the data of Markard overlaps
with the data reported by Conrad et al. (). Further
complicating an effective review of these seven papers, two
(Krüger et al., ; Mesnage et al., ) are in predatory
journals, one is a nonpeer-reviewed laboratory report
(Hoppe, ) and one is from an internet site that is also
not peer-reviewed (Honeycutt et al., ). The two publi-
cations in predatory journals might not have gone through
a rigorous scientific peer review (Beall, ). As noted
by Acquavella et al. (), studies that do not complete
peer-review (such as in the popular press or posted to the
internet) are more likely to lack basic information about
demographics and selection of subjects, sample handling
procedures, and basic assay validation information critical
to scientific interpretation of the results. Fortunately,
there are several studies with reliable residue testing that
provide concentrations of glyphosate in urine that enable
comparison of the ranges of dietary exposure estimates,
thereby avoiding the potential for error from those that
lack validation. Studies that report urinary glyphosate are
described below and are summarized in Table .
InthestudybyCurwinetal.(b), urine samples from
farm and nonfarm households in Iowa were measured
by immunoassay that used the Abraxis anti-glyphosate
antibody with a reported LOD of . µg/L (Biagini
et al., ). Urinary concentrations greater than the LOD
were detectable in –% of six groups (farm/nonfarm X
father/mother/children). Mean glyphosate concentrations
for the different groups ranged from . to . µg/L and
urinary levels of glyphosate were unaffected by farm ver-
sus nonfarm individuals. In a follow-up publication (Cur-
win et al., a), daily exposure to glyphosate for the sam-
ples from these same children was normalized by urinary
creatinine, instead of estimated daily urine volume. The
glyphosate exposures for both farm and nonfarm groups
ranged from . to . µg/kg/day, and the authors con-
cluded that the overall dose estimates did not exceed either
the acute or chronic RfD for glyphosate. Hoppe ()
examined urine samples from Europeans. The data
G .. . 5245
TABLE 6 Glyphosate concentrations in urine samples (maximum values) and calculated estimates of ingestion, compared to acceptable daily intake (ADI) or reference dose (RfD)a
Author, year
Analytical method (reported
LOD and LOQ)
Maximum reported
urine value (µg/L)
Calculated
glyphosate
ingestiona(µg/kg)
% of U.S. reference
dose (RfD, 1.0
mg/kg/day)
% of EU acceptable daily
intake (ADI, 0.5
mg/kg/day)
Brändli and Reinacher () NR . . . .
Connolly et al. ()LC/MS-MS (. µg/L, NR) . . . .
Conrad et al. () GC/MS-MS (NR, . µg/L) . . . .
Curwin et al. (a) Child (nonfarm)
Child (farm)
FCMIA (. µg/L, NR) .
.
.b
.b
.
.
.
.
Curwin et al. (b)
Adult
Child (nonfarm)
Child (farm)
FCMIA (. µg/L, NR) .
.
.
.b
.b
.
.
.
.
.
.
Fagan et al. ()
Adult
Child
LCMS (. µg/L, . µg/L) .
.
.
.c
.
.
.
.
Honeycutt et al. ()ELISA.
µg/L, NR) . . . .
Hoppe ()GC/MS-MS (NR, . µg/L) . . . .
Jayasumana et al. () ELISA (. µg/L, NR) . . .
John and Liu () ELISA (. µg/L, NR) . . . .
Knudsen et al. ()
Adult
Child
ELISA (. µg/L, NR) .
.
.
.c
.
.
.
.
Krüger et al. ()ELISA (NR, NR), GC/MS (NR,
NR)
. . .
Krüger et al. (a) ELISA (. µg/L, NR) . . . .
Krüger et al. (b) ELISA (. µg/L, NR) . . . .
Markard () GC/MS (NR, . µg/L) . . . .
McGuire et al. () LC/MS (. µg/L, . µg/L) . . . .
Mesnage et al. ()
Child
HPLC/MS ( µg/L, µg/L) . .c. .
Mills et al. ()HPLC/MS (. µg/L, NR) . . . .
Parvez et al. () LC/MS-MS (. µg/L, . µg/L) . . . .
Rendon-von Osten and Dzul-Caamal
()
ELISA (. µg/L, NR) . . . .
Sauvage () ELISA (NR, NR) . . . .
(Continues)
5246 G .. .
TABLE 6 (Continued)
Author, year
Analytical method (reported
LOD and LOQ)
Maximum reported
urine value (µg/L)
Calculated
glyphosate
ingestiona(µg/kg)
% of U.S. reference
dose (RfD, 1.0
mg/kg/day)
% of EU acceptable daily
intake (ADI, 0.5
mg/kg/day)
Sierra-Diaz et al. ()
Child
HPLC/MS (NR, NR) .d,e .f. .
Soukup et al. ()LC/MS-MS (. µg/L, . µg/L) . ND ND .f
Trasande et al. ()
Child
LC/MS (. µg/L, . µg/L) .c.c. .
aData are for adults unless noted otherwise. Glyphosate ingestion (µg/kg/day) =Curine *V
urine *.
– *BW
–.Where,C
urine is concentration of glyphosate in urine (µg/ml), Vurine is daily output of urine (ml/day).
Calculation is based on a -kg adult.
Exposure, calculated as a % of RfD and % of ADI, is all calculated using this formula and the max (when available) concentration of glyphosate in urine to enable direct comparisons between studies.
bGlyphosate ingestion calculation is based on a median value of .-kg child (farm) and median value of .-kg child (nonfarm) as reported (Curwin et al., a).
cGlyphosate ingestion calculation assumes a -kg child.
dMean value.
eValue for child calculated based on reported average child weight of kg.
fThis calculation uses actual body weights and -h urine volumes for each subject.
Abbreviations: AOEL, acceptable operator exposure level; ELISA, enzyme-linked immunosorbent assay; FCMIA, fluorescence covalent microbead immunoassay; G, glyphosate; GC, gas chromatography; HPLC, high-
performance liquid chromatography; LC, liquid chromatography; LOD, limit of detection; MS, mass spectrometry; MS/MS, tandem mass spectrometry; ND, not determined; NR, not reported.
were not peer-reviewed but were supplied to the BfR. The
analytical procedure was conducted by a GC-MS/MS with
an LOQ =. µg/L. They indicated that % and % of
samples had concentrations of glyphosate and AMPA in
urine that were >LOD, respectively. Average and maxi-
mum concentrations were . and . µg/L for glyphosate
and . and . µg/L for AMPA. The AMPA/glyphosate
ratios were highly variable, and the authors suggested this
might have been due to variable dietary exposures to other
sources of AMPA, which is known to occur (Botta et al.,
).
Details of one report (Honeycutt et al., )wereonly
provided on an internet site with insufficient information
validating the methodology to qualify the data to be sci-
entifically interpretable. Individuals provided samples for
analysis using the commercial ELISA kit that was not val-
idated for urine. Minimal information describing sample
collection was included in this online report (e.g., age, gen-
der, weight, and zip code). Instead of determining an LOD
for this matrix, samples were diluted with water -fold
andanLODof.µg/L was assumed, which was times
the LOD for water provided by the ELISA kit’s instruc-
tions. Thirteen of samples of urine had glyphosate val-
ues that were greater than this nonverified LOD, and of
the detectable samples, the range was . µg/L (-year-
old male) to . µg/L (-year-old female). Comparing this
highest urinary glyphosate value to a health endpoint rep-
resents .% of the EU ADI. This calculation is described
in Table .
McGuire et al. () tested urine of lactating mothers
in two states, Idaho and Washington. Samples were tested
using an LC-MS/MS assay (Jensen et al., ) validated
for measuring glyphosate in urine samples with an LOD
and LOQ of . and . µg/L, respectively. Samples were
collected from subjects and glyphosate was detectable
in and quantifiable in of them. The highest concen-
tration of glyphosate was . µg/L and the mean urinary
concentration was . µg/L, considerably less than con-
centrations reported by Honeycutt et al. (). Based on
their highest reported glyphosate concentration in urine
using a validated assay, these experimental subjects were
exposed to .% of the ADI for glyphosate.
Krüger et al. () reported results for glyphosate in
urine using an ELISA that did not have validation infor-
mation. Although the authors reported that the ELISA
results correlated with another method, this is insufficient,
by itself, to validate an assay. The authors did not pro-
vide actual values for glyphosate in human urine, but by
extrapolation from a figure in the publication, it appears
that the greatest glyphosate concentration was approxi-
mately µg/L. The authors claimed that healthy humans
had significantly less glyphosate in their urine than chron-
ically diseased humans. They did not provide demographic
G .. . 5247
information or criteria to define the healthy and unhealthy
groups. Furthermore, the error bars around the mean
glyphosate concentrations in urine from the health and
chronically diseased individuals overlapped considerably,
albeit the authors report a difference at p<. between
these groups.
Sri Lankan agricultural nephropathy is a kidney dis-
ease that is most prevalent among agricultural workers
in Sri Lanka and there is no clear etiology. Jayasumana
et al. () compared urine samples of patients diagnosed
with this disease to two control groups that were non-
patients from endemic and nonendemic areas. Concen-
trations of glyphosate in urine of the clinically ill group
ranged from . to > µg/L and adjusting for creatinine
resulted in greater concentrations of glyphosate in urine
samples of these patients than either of the control groups.
Renal disease is known to reduce urine volume. Accord-
ingly, the urinary concentration of a biomarker depends
on the excretion rate and the urinary flow rate. Oliguria
has been shown to increase concentrations of biomarkers
and absolute concentrations may be misleading because
of the difference in flow rates. Likewise, creatinine nor-
malization in the setting of renal disease may be mislead-
ing because of variability in the urinary creatinine excre-
tion rate (Waikar et al., ). Therefore, elevated concen-
trations of glyphosate could be an artifact, unrelated to
dietary exposure since -h exposure requires a reasonable
estimate or actual measurement of urine volume. Never-
theless, dietary exposures to glyphosate would be .% of
the ADI, when using the same calculations described in
Table .
The German Federal Environmental Agency conducted
an unpublished study of glyphosate levels in human urine
that was reported by Niemann et al. ().A-hurine
sample was collected in and from male and
female students from to years. The subjects lived
in Greifswald, Germany and samples were analyzed by gas
chromatography with an LOQ of . µg/L. Glyphosate was
detectable in of the samples. Data were not shown
but the authors indicated that in compared to
the values for glyphosate were slightly higher, but val-
ues for AMPA declined. The maximum concentration for
glyphosate was of . µg/L, which corresponds to .%
of the ADI. A subsequent manuscript (Conrad et al., )
apparently shares data with the Markard study. This retro-
spective study used -h urine samples from human sub-
jects who were – years old, and samples were col-
lected yearly from through from Greifswald.
Samples were analyzed randomly from males and
females in each year. Glyphosate was measured by a vali-
dated GC-MS/MS method with a reported LOQ of . µg/L
and .% of the samples had concentrations of glyphosate
greater than the LOQ. This report suggests that concentra-
tions of glyphosate in urine increased from to
and declined after . The maximum detected urinary
glyphosate was . µg/L and was from . This value
represents .% of the ADI.
Urine of Danish mothers and of their children were
tested for glyphosate using the Abraxis ELISA kit (Knud-
sen et al., ), albeit this assay is not validated for urine
samples. They reported that glyphosate was detectable in
all samples and that values ranged from . to . µg/L
and . to . µg/L for mothers and children, respectively.
Some values at the lower end of these ranges are below the
Abraxis LOD for glyphosate in water samples provided in
the instructions. However, even if the highest reported val-
ues are assumed to be accurate, these would represent a
total exposure to glyphosate that are .% and .% of the
ADI, for the mothers and children, respectively.
Eighty-four subsistence farmers and fishermen in Mex-
ico had urine tested for glyphosate using the ELISA kit.
Based on their supplemental data, % of urine samples
had a mean concentration of glyphosate of . µg/L, and
the maximum value was from a farmer with . µg/L
(Rendon-von Osten & Dzul-Caamal, ). From this high-
est concentration of glyphosate in the urine, an exposure of
.% of the ADI can be calculated.
One report used an HPLC-MS assay, but without report-
ing validation details, to test urine samples for glyphosate
from a total of men and women (Mills et al., ).
These subjects had samples collected in – and
again in –. The average age of subjects at the time
of the later sampling period was years. The number of
detects and the mean values were elevated between
and and and , which the authors attributed
to increased use of glyphosate. The upper % confidence
intervals for urinary glyphosate from the earlier and later
periods were . and . µg/L, respectively. This appar-
ent doubling of concentrations using the high-ends of the
confidence intervals could seem like a significant change
in exposure; however, exposures as a percent of the ADI
would have changed from .% to .% of the ADI,
resulting in both values having a >-fold reasonable
expectation of safety.
Urine samples from pregnant women, – years old,
in Indiana were tested for glyphosate (Parvez et al., ).
Two samples were collected during gestation, but results
were reported only for the samples collected during gesta-
tion weeks –. The assay used a validated LC-MS/MS
method. They reported that % of these women had
glyphosate in their urine above the LOD of . µg/L and
the average concentration was . µg/L. There was no
correlation between urinary glyphosate and growth mea-
surements of the baby. They reported that gestation length
was shorter for mothers with higher concentrations of
glyphosate in urine, but the change was approximately
5248 G .. .
days. Given the small sample size, wide age range, com-
plications arising from two premature deliveries, errors in
establishing time of conception, and mean values within
normal ranges, the significance of this association is equiv-
ocal. Based on the urine values, the woman with the high-
est exposure would have been at .% of the ADI.
Urine samples were collected from college students
from one class in Erie, PA and analyzed for glyphosate
using the ELISA kit (John & Liu, ), which was not
validated. The LOD of the assay was given as . µg/L,
although most reports employing this assay used a dilu-
tion that resulted in an unverified LOD of . µg/L. They
reported that one subject had a urinary glyphosate value
that was less than the LOD, and that concentrations of
glyphosate in urine ranged from . to . µg/L. Using
the highest value, this subject would have had an exposure
of .% of the ADI.
A small pilot study of glyphosate in the urine of Irish
adults was conducted in June (Connolly et al., ).
Most of these subjects reported using glyphosate-based
products at home but none used them as part of their occu-
pation. A validated LC-MS/MS method was used with a
reported LOD =. µg/L. Samples were normalized for cre-
atinine. Glyphosate was not detectable in % of the sam-
ples. Median and maximum concentrations in the sam-
ples that had detectable amounts of glyphosate were .
and . µg/L, respectively. Based on this highest value, this
person would have been exposed to .% of the EU ADI.
A study was conducted in Mexico with children who
ranged in age from to years (Sierra-Diaz et al., ).
They used an HPLC-MS/MS assay, but the manuscript
is missing information about validation, LOD, and LOQ.
They claim that glyphosate was detected in % and %
of test subjects from two different communities and the
mean concentrations of glyphosate in urine were . and
. µg/L, respectively. The authors indicated that in one
of these communities, children are known to apply pes-
ticides, but the authors did not indicate if any of these
subjects had sprayed glyphosate prior to sampling urine.
Assuming that glyphosate in urine was due to ingestion
and that the children weighed kg, this highest urinary
concentration of glyphosate would result in an exposure
that was .% of the ADI.
Trasande et al. () conducted a study in which urine
samples from three groups of children were collected
and tested for glyphosate using an LC-MS/MS assay that
lacks necessary validation information. Glyphosate was
detectable in %, .%, and .% of the infant/children
subjects in the following age categories: < days; –
months old; and – years old, respectively. The mean
detectable urinary glyphosate concentration was .
µg/L, and concentrations ranged from . to . µg/L.
Their highest exposure would be .% of the glyphosate
ADI. Their analysis did not find an association between
log-transformed glyphosate concentrations and any of
three biomarkers of kidney injury (albuminuria, neu-
trophil gelatinase-associated lipocalin, and Kidney Injury
Marker-).
In one study published recently, -h urine samples
were collected from adults for analysis of glyphosate
(Soukup et al., ). Samples were analyzed using an
LC-MS/MS method that was modified from the procedure
reported by Jensen et al. () with their own validation.
Study subjects were recruited to be healthy, not pregnant
or lactating, and not taking medications. For these sub-
jects, .% did not have detectable glyphosate or AMPA.
Glyphosate exposures as a percent of the ADI were calcu-
lated for each study subject using their own body weight
and -h urine excretion. Therefore, unlike other studies,
there was no need to use assumptions for body weight or
volume of urine. Otherwise, they had the same assump-
tions, as used throughout the calculations in this paper:
() that % of ingested glyphosate is absorbed; () that
glyphosate is poorly metabolized; and () that glyphosate
is rapidly eliminated via urine, showing no potential for
bioaccumulation. The maximum glyphosate exposure was
. µg/kg BW and, using the actual body weights, they cal-
culated that this person’s exposure represented .% of the
ADI. This study also used -h dietary recalls and did rank-
order correlations to estimate food sources of glyphosate
and AMPA. This was done based solely on the amount
of food consumed and not measured glyphosate content
of the food. Nevertheless, they found that consumption
of pulses and mushrooms was correlated with glyphosate
and AMPA in urine, respectively. Absorbed glyphosate is
not metabolized in the body, suggesting that ingestion of
AMPA per se, not glyphosate, was responsible for uri-
nary AMPA. The authors conjectured that mushrooms can
get exposure to glyphosate from cereal straw and manure,
which by microbial degradation is converted to AMPA, but
amount of AMPA in the mushrooms was not known.
A study tested glyphosate in urine samples, using a vali-
dated MS method, from people prior-to and after switch-
ing between conventional and strictly organic diets (Fagan
et al., ). The greatest concentrations for the children
and adults prior to switching diets were . and . µg/L,
which correspond to .% and .% of the EU ADI. The
study reported that the switch to organic diets resulted
in a rapid decrease in urinary glyphosate, which is not
unexpected as it confirms the short half-life of absorbed
glyphosate, which was discussed previously.
The studies reported above use different assays, different
diets, and different demographics of test subjects. In spite
of these various conditions, they all result in exposures that
are low, and in a narrow range, for glyphosate as a percent-
age of its ADI (.–.%).
G .. . 5249
.. Media reports
Although media reports of data are not typically included
in scientific reviews, several media reports about urinary
glyphosate have generated noteworthy public attention
necessitating a scholarly discussion of their scientific
elements. Many of these media reports lack details that
handicap accurate interpretation of the results, such as
some or all of the following: () no information about
sample collection, storage, or processing; () no infor-
mation about subjects; () no information about assay or
its validation; () no information about an LOD/LOQ or
how it was used in the presentation of the data; and ()
results often indicated that all, or nearly all samples, were
positive for residues, which is inconsistent with reports
using validated assays and use of an LOD. Some reports
did indicate that they used the ELISA commercial kit, but
no reports include data showing validation of this method
for urine. In spite of these deficiencies, results in these
reports can be scrutinized to determine if they provide
information that would be pertinent to understanding the
safety of glyphosate exposure within a specific region or
population.
An article was published in a communication medium
for a nonprofit foundation about testing glyphosate in
the urine of nonagricultural workers in Berlin (Brändli &
Reinacher, ). This article indicated that all samples
had detectable concentrations of glyphosate, and that they
ranged from . to µg/L. However, information about
their analytical methods used for these data was inten-
tionally withheld from inclusion in this publication with a
claim that the data about their method would be published
within the year, which did not appear to have occurred.
Their highest urinary glyphosate represents .% of the
ADI.
A report that was the subject of numerous media reports
was by the Heinrich Böll Foundation (Krüger et al., b)
that analyzed urine samples. This is the largest num-
ber of samples analyzed for this purpose but the Abraxis
ELISA kit was utilized, a method lacking validation in
urine. Nonetheless, the authors claimed that .% of Ger-
mans were “contaminated” and % had “urine levels more
than five times the legal limit of drinking water.” How-
ever, the legal limit for glyphosate in water is not a point
of reference directly relevant to a health standard. Their
highest value was .% of the ADI, and due to the exten-
sive media coverage of this report, the German Federal
Institute for Risk Assessment put out a statement stat-
ing that for children, the residues in urine are within the
expected range and without any expected adverse health
effects (BfR, ).
Urine of EU Ministers was sampled and tested for
glyphosate, using the Abraxis ELISA for which the report
did not provide any information about assay validation
(Krüger et al., a). Creatinine was used to correct for
differences in water consumption; however, creatinine is
related to muscle mass, which necessitates body weight
measurements to be useful. The authors reported that all
of their subjects had detectable concentrations of uri-
nary glyphosate, with concentrations ranging from . to
. µg/L. The report did not include LOD or LOQ val-
ues for the assay, complicating the interpretability of these
reported values. If their maximum value is used, this
would result in the exposure for this individual with
the highest concentration of glyphosate equal to .%
of the ADI, which is well within acceptable exposure
levels.
A report was published in French media about
farmers providing urine samples for testing of glyphosate
(Sauvage, ). Apparently, the ELISA was run by two
labs and results were compared to the results of an LC-
MS/MS assay, run by a third lab, but it is not clear if this was
done for all samples. There is no information about LODs
for the assays, or if they were even used it in summariz-
ing the results. They did conclude that the ELISA always
detected higher concentrations than the LC method. The
highest detectable urinary glyphosate was . µg/L from a
sample tested by ELISA. It is noteworthy that this value
was described as alarming, but it represents .% of the
ADI.
6.3 Summary about concentrations of
glyphosate in urine
The absorption and excretion of glyphosate allows for a
reasonably accurate way to calculate the transient inges-
tion of glyphosate without having to make assumptions
about what a person consumed, the concentrations of
glyphosate in each consumed type of food, the daily
consumption of individual foods, and the concentration of
glyphosate in water and the amount of water consumed.
Therefore, urinary glyphosate measurements allow for
an estimate of glyphosate ingestion that can be compared
to the ADI. These studies, and the comparison to the
ADI, are presented in Table and Figure . Although
the Abraxis ELISA for glyphosate is not validated for
urine samples, these data suggest that urinary glyphosate
concentrations appear to be slightly greater when assayed
using the ELISA as compared to the more precise and
often well-validated LC-MS/MS assays. This could simply
be due to the LOD of the ELISA being greater than for
the LC-MS/MS, but it is not always clear how the LOD
was applied when summarizing results generated by the
ELISA. Regardless of the assay used, exposures of individ-
uals are less than .% of the ADI with the greatest dietary
5250 G .. .
FIGURE 2 Estimate of glyphosate exposure for adults as a percentage of the EU acceptable daily intake (%ADI) derived from the
maximum concentrations obtained from each cited study. Urine was tested using an ELISA method, a mass spec (MS) method, or a method
that was not reported (NR). None of the studies that used the ELISA provide detailed validation, whereas more detailed validation
information are available for the MS assays.
exposure to glyphosate determined using the questionable
ELISA assay. The studies by Jayasumana et al. (),
Rendon-von Osten and Dzul-Caamal (), and Curwin
et al. (b) do not clearly distinguish between occupa-
tional/farm exposure and dietary exposure. All remaining
studies have glyphosate exposures that are <% of the ADI.
Calculating glyphosate exposure from concentrations in
urine indicates that the concentrations in reports sum-
marized in this review paper result in exposures that are
substantially below the ADI (Figure ). As mentioned
previously, an ADI is an estimate of the amount of a
substance in food and drinking water, expressed on a
body weight basis, that can be ingested over a lifetime
without appreciable health risk (Chemicals Regulation
Directorate, ). Exposure of humans to glyphosate
was reviewed recently by Gillezeau et al. () and they
concluded that mean concentrations of glyphosate in
urine are typically <µg/L, but they did not compare this
concentration to a safety standard. It is noteworthy that
they also had a concern about the sensitivity of the ELISA
and the difficulty of combining data or comparing across
studies due to differences in the LOD/LOQ. Using their
value ( µg/L) would result in an estimated ingestion of
.% of the ADI, an amount that is over two orders of
magnitude below the ADI, and therefore presumed to be
safe.
7DISCUSSION
Calculating dietary consumption of glyphosate can be
done using two disparate methods. In the first method,
residues are measured in individual food items and these
are summed based on consumption data for the foods that
people eat. This approach requires answering several ques-
tions to make reasonable assumptions used in the model-
ing such as: () what residue value for a food is used; () is
the food processed or cooked; () what residue value is used
when an analyte’s concentration is <LOD; () are mean,
median, or th percentile values used for consumption;
and () what and how much do people eat? In the second
approach, for a pesticide like glyphosate with the knowl-
edge of absorption from the gut, lack of metabolism, and
elimination from the body, sampling of urine is an accurate
way to calculate ingestion and exposure within the body
(Acquavella et al., ; Niemann et al., ). Regardless
of which of the two methods is used, these values need to
be compared to a safety standard, such as the ADI or RfD,
which are regulatory-derived safety standards. Results of
determining exposure to glyphosate by dietary modeling
or urinary glyphosate are presented in Table ,Table,
and Figure . Modeling allows different scenarios using
estimates of consumption and data derived from market
surveys, whereas urine is a surrogate for estimating actual
G .. . 5251
dietary exposure to glyphosate. The results from these two
methods are in relatively close agreement. Dietary esti-
mates range from .% to % depending on assumptions.
An especially critical assumption used is the residue levels
that are used. Urinary glyphosate estimates of exposure are
.%–.% of the ADI, which do not require an assump-
tion about residue on individual foods.
In spite of that, testing and publishing about glyphosate
residues, whether in peer-reviewed journals, by
internet postings or in the news media, has become
somewhat common in the last decade. Unfortunately,
many of the popular press reports are accompanied by
value-judgment words like “high” or “contaminate,” or
they make scientifically inappropriate comparisons to
other standards (i.e., concentrations in urine vs. regulatory
defined residue levels for drinking water). Furthermore,
some of these reports imply that glyphosate residues were
not known to exist previously in a given food or in urine,
and, therefore the findings are regarded as novel. Recent
publications, such as Winter and Jara (), Winter et al.
(), and Reeves et al. (), have attempted to provide
more information about the process for risk assessment
of pesticides conducted by regulatory agencies. Moreover,
timely communications from regulatory agencies, such
as BfR responding to reports of residues in food, German
beer, or urine (BfR, ,), provide helpful informa-
tion from what should be a trustworthy source in the face
of widespread social media communications about food
and agriculture (Ryan et al., ).
One statistic that is often encountered in publications
that also might generate concern by consumers is reports of
increased trends over time of usage of a pesticide, either by
expanded adoption or as the result of new technology, such
as herbicide-tolerant crops (Benbrook, ). These statis-
tics intimate that pesticide use has exceeded safe levels
established by the original regulatory assessments. In one
residue study, the authors suggested that it appeared that
MRL values were adjusted due to actual observed increases
andnotbasedontoxicity(Bøhnetal.,). This is pre-
cisely how MRLs are derived. It is important to highlight
that alterations in the use of a previously approved pesti-
cide, such as usage of glyphosate on newly approved GT
crops, require new residue data to be submitted from the
pesticide registrant(s) prior to regulatory approval. These
new residue data are reviewed by regulators in order to
ensure that the previous ADI or RfD is not exceeded. Addi-
tionally, MRLs or tolerances are derived from empirical
data of real-world conditions and, once established, MRLs
represent for any crop the agricultural practice that results
in the highest residue. EPA () stated in their guidance
that pesticide use patterns, such as changes in the pre-
harvest interval and/or postharvest treatment, are likely
to require residue studies, and potentially another peti-
tion for a new tolerance. Expanded usage of a pesticide
might change, but by conservatively assuming that %
of a crop will use the agricultural practice with the high-
est residue, exposure remaining below the ADI is not sub-
ject to changes in commercial adoption. If a new exposure
resulted in the sum of all exposures exceeding the ADI,
there would need to be a restriction in some use. More-
over, since regulatory authorities use data collected prior
to authorization of cultivation or import of the crop, com-
bined with periodic testing to ensure that tolerances are
not being exceeded, these media reports of residues do not
necessarily provide unexpected data. When properly con-
ducted, independent, peer-reviewed studies are published,
they can be a corroboration of the accuracy of previously
reported regulatory residue studies.
Putting pesticide residues into context by converting
these values to percentages of the EFSA- or EPA-derived
ADI or RfD helps one understand the margin of safety, but
many consumers want food that is free of synthetic pesti-
cides (Krystallis & Chryssohoidis, ). According to Cur-
rie (), many believe that with improved assays, a con-
centration of zero might be detected, but that is scientifi-
cally not feasible.
More than ever, as in other areas of science, trans-
parency on residues of pesticides and their assessment by
global regulatory authorities entrusted by the public to
ensure food safety is needed to address complex scientific
information (OECD, ). The scientific publication pro-
cess that requires peer-review of the data and conclusions
has largely provided the basis for science-based regulatory
assessments for the past century (Codex, ) . Although
peer-review is not a foolproof process, it is a process with
the intent of ensuring that results and conclusions from
published studies are based on well-conducted and doc-
umented scientific experiments. This is in sharp contrast
to the essentially unreviewed environment of media and
online publications. Adequacy of peer review is increas-
ingly more confusing with predatory journals and elec-
tronic publishing (Kelly et al., ). Since the public lacks
training to help them distinguish information from peer-
reviewed journals and science-based regulatory authorities
from information they see in media reports and predatory
journals, this review has included results on glyphosate
residues from both sources to provide them with a single-
point reference for an informed discussion of this subject.
8CONCLUSIONS
It has been observed that the perception of risk is greater
with consumers when: () it cannot be detected; () it
is not well understood; and () the belief is that the
science is not known (Ropiek, ). Global regulatory
5252 G .. .
authorities have spent the past decades establishing review
practices designed to define, as much as scientifically pos-
sible, the data required to establish the parameters needed
to define the known science needed for a safe food supply,
and what needs to be detected and understood to ensure
that such safety requirements are met. However, it is clear
that more is needed to demystify these regulatory processes
established to ensure their safety. In this review, glyphosate
residue data from both regulatory authorities and reports
from many groups, both peer-reviewed and in the media,
have been summarized. To generalize this large amount
of information, glyphosate residue data show that dietary
residue exposure is well below established ADIs.
ACKNOWLEDGMENTS
The authors wish to thank Kevin Glenn, Christophe
Gustin, and Kristian Kather for their guidance and
constructive review. The authors are all employ-
ees of Bayer Crop Science, a major manufacturer of
glyphosate.
AUTHOR CONTRIBUTIONS
J. Vicini coordinated the overall process and drafted the
manuscript, except for the assay portion that was drafted
by P. Jensen. J. Swarthout was responsible for calculations
and interpretation of urine values. B. Young was respon-
sible for collecting and interpreting data from residue
reports from regulatory agencies.
ORCID
John L. Vicini https://orcid.org/---
Pamela K. Jensen https://orcid.org/---
Bruce M. Young https://orcid.org/---
John T. Swarthout https://orcid.org/---
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SUPPORTING INFORMATION
Additional supporting information may be found online
in the Supporting Information section at the end of the
article.
How to cite this article: Vicini JL, Jensen PK,
Young BM, & Swarthout JT. Residues of glyphosate
in food and dietary exposure. Compr Rev Food Sci
Food Saf.;20:–.
https://doi.org/./-.
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