Critical Review
pubs.acs.org/est
Variability of Pesticide Dissipation Half-Lives in Plants
Peter Fantke*
Department of Management Engineering, Technical University of Denmark, Produktionstorvet 426, 2800 Kgs. Lyngby, Denmark
Ronnie Juraske
Institute of Environmental Engineering, Swiss Federal Institute of Technology, CH-8093 Zurich, Switzerland
S Supporting Information
*
ABSTRACT: Information on dissipation kinetics of pesticides in food crops
and other plants is a key aspect in current risk and impact assessment
practice. This is because human exposure to pesticides is predominantly
caused by residues in agricultural crops grown for human and animal
consumption. However, modeling dissipation of pesticides in plants is highly
uncertain and therefore strongly relies on experimental data. Unfortunately,
available information on pesticide dissipation in plants from experimental
studies only covers a small fraction of possible combinations of substances
authorized for use on food and fodder crops. Additionally, aspects and
processes influencing dissipation kinetics are still not fully understood.
Therefore, we systematically reviewed 811 scientific literature sources
providing 4513 dissipation half-lives of 346 pesticides measured in 183
plant species. We focused on the variability across substances, plant species
and harvested plant components and finally discuss different substance, plant and environmental aspects influencing pesticide
dissipation. Measured half-lives in harvested plant materials range from around 1 hour for pyrethrins in leaves of tomato and
pepper fruit to 918 days for pyriproxyfen in pepper fruits under cold storage conditions. Ninety-five percent of all half-lives fall
within the range between 0.6 and 29 days. Our results emphasize that future experiments are required to analyze pesticide−plant
species combinations that have so far not been covered and that are relevant for human exposure. In addition, prediction models
would help to assess all possible pesticide−plant species combinations in the context of comparative studies. The combination of
both would finally reduce uncertainty and improve assumptions in current risk and impact assessment practice.
1. INTRODUCTION
Assessing health risks and impacts from pesticide use helps to
provide support in the decision making process of regulatory
authorities and requires different input data, including
information regarding the dynamics of pesticides in the
plant−environment system.20 Within such assessments, information about the dissipation of pesticides from the target
plant species is crucial for calculating residual concentrations
found in plant components harvested for human or animal
consumption and, in addition, is one of the most uncertain
aspects in assessing the environmental fate of pesticides.21−23 In
this context, the term dissipation is defined as a composite of
processes describing volatilization, washoff, leaching, hydrolysis,
chemical and biological degradation, and other individual
processes reducing the amount of a pesticide in plants after
application,24,25 of which all are substance- and possibly plant
species-specific.26 Potential processes directly contributing to
pesticide dissipation in plants are shown in Figure 1. Since
currently no model exists that provides dissipation half-lives of
Since many decades, a wide range of chemical pesticides
contained in commercial plant protection product formulations
have been applied worldwide, with agriculture as the
predominating market.1,2 Benefits associated with the use of
pesticides are primarily reduced crop yield losses and improved
food quality.3−5 However, as they are inherently toxic to living
organisms, pesticides are likely to have negative impacts on
human health via exposure to residues in food and drinking
water, via occupational, by-stander, and residential exposure,
etc.,6−9 as well as on the environment by reaching nontarget
organisms via wind drift, leaching, runoff.10,11 The general
public is exposed to pesticides mainly through residues in
agricultural food crops.12−14 Hence, our society is increasingly
concerned about effects from a continuous low-level exposure
to pesticides found in food.15−17 As a consequence, assessing
dietary exposure to pesticide residues in food crops has become
a key step in the authorization and regulation of pesticides
based on a detailed risk assessment procedure required by
international pesticide regulations.18,19 In addition, dietary
exposure toward pesticides is considered an important aspect in
current health impact assessment.13,14
© 2013 American Chemical Society
Received:
Revised:
Accepted:
Published:
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August 30, 2012
March 7, 2013
March 7, 2013
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Environmental Science & Technology
Critical Review
conditions on pesticide dissipation. Finally, future research
directions with respect to both the assessment of pesticides and
experimental designs for measuring dissipation half-lives of
pesticides in plants are identified.
2. REVIEW OF MEASURED PESTICIDE DISSIPATION IN
PLANTS
2.1. Review Procedure. We conducted an extensive and
systematic literature review with respect to measured
dissipation half-lives of a wide range of pesticides applied to a
variety of plant species in experimental studies published
between 1956 and 2012. Data were primarily obtained from
systematic key word searches pertaining to quantitative metrics
of pesticide dissipation from plants (e.g., “persistence”, “halflife”, “dissipation”, “degradation”) in the databases of the
scientific press publishing international peer-reviewed journals
(e.g., Web of Science, Scopus, ACS Publications, Springer Link,
Wiley Online Library, CNKI). In all studies that were identified
as a result of the key word search, we also screened references
cited therein for further dissipation half-lives (hereafter also
referred to as data points). Altogether, we identified and
analyzed 796 peer-reviewed journal articles. In addition, we
analyzed 2 studies published in peer-reviewed conference
proceedings, 1 doctoral thesis, 2 master theses, 6 peer-reviewed
books or book sections, and 4 reports, of which 3 also were
peer-reviewed.
The first considered experiments on measuring residues and
dissipation half-lives of largely persistent pesticides (DDT,
aldrin, chlordane, etc.) in different food crops date back to the
1950s and were conducted by the working group of Francis
Gunther and Roger Blinn in Riverside, California.28−30 The
following 36 years between 1956 and 1992 show a slightly
increasing trend in publishing studies on pesticide dissipation
behavior in crops, but also in other plants, with less than four
studies on average per year (Figure 2).
Figure 1. Schematic representation of plant-environment interactions
with processes directly contributing to pesticide uptake or transport in
plants (half-filled arrows) and processes directly contributing to
pesticide dissipation from plants (filled arrows).
the numerous pesticides applied to a wide range of plant
species for use in more realistic risk and impact assessment,
half-life data are either obtained from experimental studies or
are simply not available. Even for the pesticide−plant species
combinations for which measured dissipation half-lives are
available or can be compiled from the peer-reviewed literature,
we are not aware of any data set consistently summarizing
information on pesticide dissipation in plants apart from a meta
study by Willis and McDowell (1987).27 This study reported
436 dissipation half-lives of 79 pesticides exclusively measured
on leaves of 53 plant species along with information about
study location, rainfall and temperature, if provided by the
original sources. However, the study of Willis and McDowell
dates back to 25 years ago and does not include the dissipation
of any pesticide in plant components primarily harvested for
human or animal consumption (fruits, tubers, etc.) and, in
addition, misses most pesticides currently authorized for use in
agriculture in various countries. Hence, a comprehensive data
compilation providing half-lives for the dissipation of the
various pesticides applied to or taken up by a certain range of
plant species and potentially even for specific harvested plant
components is required to improve current risk and impact
assessment practice.
In the present study, the variability of pesticide dissipation
half-lives in various harvested parts of a wide range of plant
species was systematically reviewed. Plant material in the
reviewed experimental studies was typically harvested and
sampled periodically after pesticide application with the first
sampling usually on the day of application. In some studies the
harvested material was stored and samples were extracted after
a certain time to account for storage conditions. Plant tissue
was either analyzed directly after sampling or kept frozen until
chemical analysis to avoid further degradation of pesticides. A
subsequent residue analysis usually included sample homogenization, extraction, concentration, cleanup, and finally
pesticide detection.
We focus on variability ranges of dissipation half-lives
between pesticide target classes (fungicides, insecticides,
herbicides, etc.), plant species classes (cereals, root crops,
trees, etc.), and plant components (leaf, fruit pulp and surface,
root, etc.). Furthermore, we discuss different models to fit
dissipation kinetics in plants as well as the influence of
substance properties, plant characteristics, and environmental
Figure 2. Trend of considered experimental studies (n = 811)
published per year between 1956 and 2012 that report on pesticide
dissipation in plants.
With time, this trend further increases with 20 published
studies per year between 1993 and 2006. An almost exponential
increase in publications reporting on the dissipation behavior of
pesticides in plants is seen just for the past 5 years between
2007 and 2012, where on average 65 studies are found per year,
with not all studies considered yet for 2012. This overall trend
goes well in line with the increasing concern of the general
public regarding pesticides that are found as residues in food
and other media15−17 yielding constant national and international regulatory amendments. However, of all considered
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Critical Review
Finally, repeated values of the same experimental study
reported by different literature sources were eliminated from
the set of compiled data points. All considered studies were
screened for additional, nonmandatory information with
respect to any aspect (temperature, light/shade conditions,
spatial variability, etc.) or physical (e.g., growth dilution),
chemical (e.g., photodecomposition), or biological (e.g.,
microbiological decomposition) process contributing to
pesticide dissipation in plants. Our interest in such information
is to gain knowledge that helps to explain some of the
variability of dissipation half-lives in plants between pesticides,
plant species, and sampled plant components. However, only
90 studies (11%) indicated any aspect or process influencing
reported pesticide dissipation kinetics. Other nonmandatory
information that we were interested in included experimental
study design (differences in pesticide application doses,
application times/seasons, locations, etc.) and conditions
(greenhouse cultivation, cold storage, etc.), as well as sample
properties (stage of plant samples, such as immature/mature,
possible sample pretreatment by, for example, washing, etc.). A
summary of the results of our review study is provided in Table
1.
studies, experiments conducted in China and India account for
around 67% with a trend of increasing importance. Whereas
before the year 2000, most of these studies were almost
exclusively published in national peer-reviewed journals of these
two countries, in the last 12 years, Chinese and Indian studies
have also been progressively being published in international
peer-reviewed journals released by the American Chemical
Society, Springer, Elsevier, and other major publishers. This is
consistent with the trend of the distribution of the global
population, to which China and India alone contribute with
more than one-third,31 as well as with the trend of global
economy, where China and India play a steadily increasing
role32 including the agricultural sector with its swelling demand
for pesticides in these countries.3
2.2. Considered Experimental Studies. Most of the
considered studies reported residual concentrations along with
dissipation rate constants kdiss (day−1) or corresponding halflives t1/2 (days) obtained from the relationship t1/2 = ln(2)/kdiss
for one or more pesticides applied to one or more plant species.
However, some studies exclusively reported a series of residual
pesticide concentrations C(t) (mg kg−1), that is, the mass of a
residual pesticide per mass of a harvested plant (component/
tissue) sample measured at different points in time after
substance application. In those cases, we assumed that kdiss is
proportional to C(t) and fitted measured pesticide residue data
to pseudo-first-order kinetics as recommended by, for example,
Gonzáles et al. (2001)33 and Boesten et al. (2006)34 according
to
C(t ) = C0 × exp( −kdiss × t )
Table 1. Review Study Summary of Pesticide Dissipation
Half-Lives in Plants
(1)
−1
where C0 (mg kg ) is the initial pesticide concentration in
plant (component/tissue) and t (days) is the time when the
plant sample was harvested. Rearranging eq 1 and solving for
kdiss yields
k
diss
ln[C0] − ln[C(t )]
=
t
(2)
from which we finally obtain t1/2 (see also Table 2). Data were
only considered, if the tested pesticides, plant species, and
sampled plant components (leaves, fruit pulp, straw, etc.) or
tissues (cuticular waxes, nectar) could be clearly identified and
either dissipation rate constants, dissipation half-lives, or a
series of measured residual concentrations were provided.
Required information of tested pesticides included the
Chemical Abstracts Service Registry Number (CAS-RN) and
the substance name according to the nomenclature of the
International Union of Pure and Applied Chemistry (IUPAC)
or a corresponding common name. For the sampled plant
species, the common name, the botanical name conforming to
the International Code of Nomenclature for algae, fungi, and
plants (ICN), and in case of cultivars, an additional
specification conforming to the International Code of
Nomenclature for Cultivated Plants (ICNCP) were required.
Furthermore, data from studies reporting dissipation rate
constants or half-lives were only considered, if the corresponding calculation methods (pseudo-first-order kinetics, nonlinear
kinetics, etc.) or alternatively if the applied fitting equations
were provided. In contrast, data from studies reporting residual
pesticide concentrations, but not dissipation rate constants or
half-lives, were only considered if the number of sampled times
after pesticide application was n ≥ 5 and the coefficient of
determination of the related linear fitting function was R2 ≥ 0.7.
review parameter
value
remarks
no. data points
4513
no. considered
studies
no. pesticides
811
88.9% reported, 11.1% calculated from reported
residues at different times after pesticide
application
>99% peer-reviewed literature
no. crop/other
plant species
no. plant
components
no. contributing
processes/
aspects
183
covering organic pesticides, inorganic pesticides,
and biological pesticides
covering target and nontarget species
33
including specific tissues, such as cuticular waxes
21
only rarely reported or discussed
346
3. CHARACTERISTICS OF DISSIPATION HALF-LIVES
3.1. Applied Models for Fitting Dissipation Kinetics.
Seven hundred nine studies directly reported dissipation rate
constants or half-lives. All these studies fitted measured
pesticide residue data in plants with nonlinear least-squares
regression analysis under the assumption of pseudo-first-order
kinetics. In addition, 17 studies also fitted their residue data
with calculation models describing zero-order kinetics,35,36 halforder kinetics,37 one-and-a-half-order, and second-order
kinetics,37−45 corresponding root functions of first-, one-anda-half-, and second-order kinetics,38−44,46 combined first + firstorder kinetics (biphasic or biexponential),37,46−52 or modified
first-order kinetics.53 All identified calculation models, corresponding residual pesticide concentration curves and related
half-lives t1/2 (day) are summarized in Table 2, where t1/2
corresponds to the time t, at which the residual pesticide
concentration C(t) equals half of the initial concentration C0.
Out of the 17 studies using additional calculation models,
however, only 6 studies reported significantly better fits with
non-first-order models for estimating dissipation curves of
cyfluthrin (green bean, pepper), deltamethrin and acrinathrin
(pepper), fenvalerate and τ-fluvalinate (pepper, zucchini),
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Table 2. Different Models to Fit Residual Pesticide Concentration Curves and Estimate Corresponding Dissipation Half-Lives
in Plants for Reported Dissipation Kinetics
residual concentration curvea
calculation model
dissipation half-lifea
C0
zero-order
C(t ) = C0 − kdiss × t
half-order
⎛
kdiss ×
C(t ) = ⎜ C0 −
2
⎝
first-order
C(t ) = C0 × exp(− kdiss × t )
t1/2 =
ln(2)
kdiss
one-and-a-half-order
⎛ 1
kdiss ×
+
C(t ) = ⎜⎜
2
⎝ C0
t1/2 =
2× 2 −2
C0 × kdiss
second-order
C(t ) =
t1/2 =
1
C0 × kdiss
root function first-order
C(t ) = C0 × exp(− kdiss ×
root function one-and-a-half-order
⎛ 1
kdiss ×
+
C(t ) = ⎜⎜
2
⎝ C0
root function second-order
C(t ) =
combined first + first-order (biphasic)
C(t ) = C0 × exp(− k1diss × t1) + C1 × exp(− k 2diss × t 2)
t1/2 =
t⎞
⎟
⎠
2
t1/2 =
t⎞
⎟⎟
⎠
−2
C0
1 + C0 × kdiss × t
1 + C0 × k
×
(2 −
2) ×
C0
kdiss
⎛ ln(2) ⎞2
t1/2 = ⎜ diss ⎟
⎝ k ⎠
t)
t⎞
⎟⎟
⎠
⎛ 2 × 2 − 2 ⎞2
⎟
t1/2 = ⎜⎜
diss ⎟
⎝ C0 × k ⎠
t
⎞2
⎛
1
⎟
t1/2 = ⎜⎜
diss ⎟
⎝ C0 × k ⎠
−2
C0
diss
2 × kdiss
numerical least-squares fitting required
C(t) = residual pesticide concentration (mg kg−1) at time t (day); C0, C1 = pesticide concentrations (mg kg−1) at t = 0 and t > 0, respectively; kdiss,
diss
−1
kdiss
1 , k2 = pesticide dissipation rate constants (day ); t1/2 = pesticide dissipation half-life (days).
a
bifenthrin (zucchini),41 thiacloprid (tomato),42 methamidophos (pepper),44 methomyl (eggplant),47 and tetraconazole
and difenoconazole (grape),48 as well as profenofos (cotton).53
For all other tested pesticide−plant species combinations in
these six studies, as well as for all studied combinations of the
remaining studies using different calculation models, the
variation of resulting half-lives between first-order approximations and other models was usually less than 50%. This is in
support of pesticide dissipation in plants generally following
first-order kinetics, although we might find some exceptions.
For future experimental studies, Table 2 will help to identify the
most suitable model for calculating half-lives according to the
observed dissipation kinetics.
3.2. General Characteristics of the Reviewed Data Set.
Pesticides. For the three major target classes, we collected 2973
data points for insecticides (66% of all considered data points),
1040 for fungicides (23%), and only 313 for herbicides (7%).
The small number for herbicides seems surprising, since
herbicides constitute the most important target class with
respect to quantity applied worldwide,1 and together with
insecticides, also with respect to the number of individual
substances per target class.54 The few data points, however,
might be the result of herbicides usually being applied at preemergence or early plant life stages to avoid damaging the
cultivated species itself. Hence, herbicides will have enough
time to dissipate below any measurable residue at harvest time.
In contrast, insecticides and fungicides are mostly applied
shortly before harvest or even postharvest,13 from which we
expect usually high residues at harvest time. We found
furthermore 97 data points for acaricides, 38 for plant growth
regulators, 8 for bactericides, 7 for molluscicides, 4 for
nematicides and 33 for which the target class was either not
specified or not unambiguous (use against different types of
pests), together accounting for 4% of all considered data points.
The chemical classes for which we gathered more than 100 data
points are organophosphates with 1138, pyrethroids with 527,
carbamates with 377, organochlorines with 272, triazoles with
247, neonicotinoids with 211, dithiocarbamates with 106, and
ureas other than sulfunylureas with 103 data points. Regarding
individual pesticides, we were able to collect 3 or more data
points from the same or different reviewed studies for 288
pesticides (83% of the full list of pesticides included in our data
set). For 45 pesticides (13%), we only found 2 data points and
for 13 pesticides (3.8%), we found only a single data point.
Most data points were reported for the insecticides endosulfan,
imidacloprid and methomyl with 135, 130, and 122 measured
or compiled half-lives, respectively. In contrast, we found only
three data points for the insecticide oxamyl, though this
substance is currently registered for use on potatoes, where
usually low residues are expected, but also for use on fruits and
fruiting vegetables,55 in which most pesticides show relatively
high residues.13,14 This is an example of the fact that many
experimental studies do not choose their test substances based
on the quantity applied or the importance for human and
animal consumption.
Plant Species and Harvested Components. Fruits and
vegetables are by far the main target crop classes of
experimental studies addressing pesticide dissipation with
1351 and 1198 reported data points, respectively. This is
because these are the crop classes where usually the highest
pesticide residues are expected and where harvested plant
components are consumed in high quantities and often
unprocessed.13,14 Fruits and vegetables are followed by cereals
with 625, leafy crops with 284, root crops with 259, forest trees
with 180, weeds with 178, ornamental plants with 144, and
herbs with 95 data points. The remaining 199 data points not
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for 43 combinations corresponding to only 2.9% of all
considered combinations.
Data Points. The 95% confidence interval of pesticide
dissipation half-lives in plants across all 4513 considered data
points for 1485 pesticide−plant species combinations ranges
from 0.6 to 28.7 days. The shortest half-lives between 0.02 and
0.04 days were observed for pyrethrins (plant-derived
insecticides) in leaves of tomato and pepper fruit, respectively.67 Half-lives of only 0.04 days were also reported for
some sulfonylurea herbicides, namely for triflusulfuron in sugar
beet leaves68 and for rimsulfuron in maize leaves.69 In contrast,
the longest half-lives were all observed for insecticides under
cold storage conditions, namely for pyriproxifen in pepper fruits
(518 to 918 days),70 for the metabolite fenthion sulfoxide in
grape fruits (256 to 267 days),71 and for buprofezin in pepper
fruits (245 to 260 days).70
3.3. Variability Across Pesticides, Plant Species, and
Plant Components. We analyzed the variability of pesticide
dissipation half-lives in plants at different aggregation levels,
namely for pesticide target classes, chemical classes, plant
classes and plant component classes (Figure 4). We separately
assessed fungicides, insecticides, and herbicides, whereas all
other target classes were aggregated into the class “other”
pesticides. Out of 114 different chemical classes, organophosphates, pyrethroids, carbamates, organochlorines, triazoles,
neonicotinoids, dithiocarbamates, and urea pesticides (excluding sulfonylureas) account for more than 66% of all considered
data points. Therefore, we also discuss these classes of synthetic
organic pesticides in more detail. Plant species and plant
components differ in composition and shape,13,22 and are
exposed to different processes, which also contributes to widely
varying pesticide dissipation half-lives measured in different
plant species and sampled components. Hence, we finally also
discuss the variability of pesticide dissipation in different plant
and component classes. Overall, Figure 4 illustrates that
between different target, chemical, and plant classes, the
variability shows a similar pattern, whereas some plant
components show either much lower (nectar, pollen) or higher
(surface waxes, tree bark) average dissipation half-lives
compared with other components. Details for each aggregation
level are discussed in the following.
Target Classes. Figure 5 contrasts the variability of all
considered data points for the different target classes.
Dissipation half-lives across all target classes show a very
similar variability pattern, which is in line with other studies
that compared pesticides across different target classes.27,61
Geometric means of reported fungicide dissipation half-lives
vary between 1.1 days for cycloheximide and 35 days for
imazalil, showing a variation of a factor 32 across pesticides
(Figure 5a). The corresponding 95% interval ranges from 1.5
and 17 days (variation by factor 11). Geometric means of
reported half-lives for insecticides show a variation of a factor
231 across substances (around 7 times higher than fungicides)
ranging from 0.3 days for biological pyrethrins and 0.6 days for
propoxur to 58 days for pyriproxifen (Figure 5b) with a 95%
confidence interval range between 0.8 and 23 days (variation by
factor 29). Herbicides show variability for geometric means of
reported half-lives of a factor 116 variation across substances
and half-lives ranging from 0.3 days for chlorsulfuron to 35 days
for dalapon (Figure 5c). The 95% confidence interval shows a
variation of a factor 26 between 0.6 and 16 days. Finally,
geometric means of all other reported pesticides not belonging
to one of the three aforementioned target classes vary between
assigned to one of the aforementioned crop classes mainly refer
to industrial crops like cotton and hops. Individual plant species
of highest interest for experimental studies are grape with 352,
tomato with 331, tea with 192, and apple with 179 data points.
Rice with 135, lettuce with 121, and potato with 60 data points
are the most important cereal, leafy and root crop/tuber
species, respectively. Plant components of concern are strongly
related to harvested parts edible for humans and animals. This
is reflected by the high number of 1927 and 1717 data points
obtained for leaf and fruit components, respectively (Figure 3).
Figure 3. Distribution of measured pesticide dissipation half-life data
points (n = 4513) between different sampled plant components
aggregated into classes surface, interior above-ground, interior belowground, and sampled whole plant.
However, many studies just harvested and homogenized the
whole plant (175 data points) or at least more than one plant
component (such as “straw” or “shoot” with 88 and 25 data
points, respectively). In these cases, it is impossible to identify
to which plant component some fraction of the total residual
pesticide concentration is associated. This is different, if more
than one plant component is harvested and analyzed as a
separate sample. However, different harvested plant components were sampled only for 213 pesticide−plant species
combinations (14.4% of all reported combinations), such as for
folpet in fruit and leaf of grape,56−58 pirimiphos-methyl on fruit
surface, in fruit and leaf of tomato,59−63 or parathion in peel,
fruit and leaf of orange.27,28,64−66 Out of these combinations,
information on dissipation kinetics of the same substance
applied to the same plant species must be carefully interpreted,
since it is often derived from distinct studies for the various
plant components and, hence, biased by study-specific
environmental conditions, sampling procedure, sample processing, plant life stage characteristics, and pesticide application
doses and times. Only where different plant components are
included in the same study, these additional sources of
measurement uncertainty can be excluded. In the abovementioned cases of folpet and grape, as well as pirimiphosmethyl and tomato, this reduces to one reference for each
pesticide−plant species combination that simultaneously
measured pesticide dissipation in different plant components,
namely Cabras et al. (2001)58 and Antonious and Snyder
(1994),60 respectively, whereas for parathion and orange no
study sampled more than one plant component. From the
perspective of the most important plant components sampled,
that is, leaf and fruit (see Figure 3), data points for both plant
components are available for only 80 pesticide−plant species
combinations, of which data were coming from the same study
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Figure 4. Box and whisker plots showing the variability of measured dissipation half-lives of pesticides in plants across different target, chemical,
plant, and plant component classes (without data points referring to cold storage conditions).
0.5 days for the acaricide chlordimeform and 55 days for the
metabolite fenthion sulfoxide with a variation of a factor 110
(Figure 5d) and with a 95% confidence interval range between
0.9 and 24 days (variation of a factor 27). Under field
conditions (excluding data points for greenhouse and cold
storage), fungicides and insecticides (including fenthion
sulfoxide, which is a metabolite of the insecticide fenthion)
show much less variability with geometric means of reported
dissipation half-lives varying from 1.1 to 19 days for fungicides
(variation of a factor 18) and from 0.3 to 28 days (variation of a
factor 110) for insecticides. Extreme values at the upper end are
either due to growing conditions (greenhouse) or postharvest
processing (cold storage), of which the latter is relevant only
for pesticides that are applied either shortly before harvest
(mostly insecticides) or postharvest (mostly fungicides).
Chemical Classes. Geometric means of reported dissipation
half-lives (with lower and upper 95% confidence interval limits
in parentheses) range from 3.2 days (0.8−10.6 days) for
carbamates and 3.3 days (1.1−5 days) for pyrethroids, 3.4 days
(3.1−9.3 days) for neonicotinoids, 3.5 days (0.9−22.8 days) for
organophosphates, 3.9 days (3−5 days) for dithiocarbamates,
and 4 days (1.9−27.8 days) for organochlorines to finally 5.1
days (2−12.8 days) for triazoles and 5.5 days (2−20 days) for
ureas. The highest variability was found for organophosphates
with a factor 75 between lowest and highest reported half-lives
of 0.7 and 55 days, followed by variability of a factor 24 and 20
for organochlorines and carbamates, respectively. Low varia-
bility of a factor 2 and 3, in contrast, was found for
dithiocarbamates and neonicotinoids, respectively. In addition,
we looked at nonsynthetic and inorganic chemicals. If we only
consider data points reported for biopesticides, that is,
pesticides that are not synthetic, but derived from animals,
plants, bacteria, or certain minerals, 95% of reported dissipation
half-lives would fall into the range of 0.4 to 20 days. In contrast,
if we only look at data points for inorganic pesticides, the 95%
confidence interval of dissipation half-lives ranges from 11 to 18
days.
Plant Species. Pesticide residues in fruits and vegetables are
reported to show a high level of variability.72 At least for
vegetables, we can confirm this trend, since we found more
than 3 orders of magnitude variability in geometric means of
reported dissipation half-lives for different pesticides. Vegetables are followed by cereals and root crops with a factor 594
and 430 of variability, respectively. In contrast, herbs and forest
trees only show variability of a factor less than 30. This
difference between crop classes might be partly attributable to
the variety in species characteristics, which is higher in the wide
range of cultivated vegetables than in natural herbs and trees.
95% confidence intervals of dissipation half-lives of substances
reported for the same crop class are in the range of 0.5−17 days
(cereals and vegetables), 1.5−31 days (forest trees), 1.7−29
days (fruit crops), 0.6−9.5 days (herbs), 0.9−13 days (leafy
crops, root crops and other crops), 0.7−27 days (ornamental
crops), and 0.6−23 days (weeds).
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Figure 5. Variability of measured dissipation half-lives of (a) 92 fungicides, (b) 152 insecticides, (c) 71 herbicides, and (d) 31 other pesticides in
plants with geometric mean, upper and lower 95% confidence interval limits, and number of measured data points for each pesticide.
Sampled Plant Components. Pesticide dissipation shows
the highest variability in plant leaves with a factor 156
difference between the lowest and highest geometric means
over half-lives reported per pesticide, which is partly due to the
large amount of reported data points in leaves (n = 1927). In
contrast, plant components with very few reported half-lives
only show variability of geometric means over reported data
points per pesticide of around a factor 1, such as for buds (n =
4), grains (n = 7), and waxes (n = 8). 95% confidence intervals
of half-lives per plant component range from 0.4 to 0.7 days for
pollen at the lower end and from 4.3 to 57 days for tree bark at
the upper end, thereby indicating a high variability between
plant components.
Individual Pesticides: Field Conditions. The shortest
geometric mean half-lives per pesticide (across data points
per substance) under field conditions are 0.25 days for the
insecticidal pyrethrins (n = 4) data points), 0.3 days for
herbicide chlorsulfuron (n = 2), and 0.5 days for acaricide
chlordimeform (n = 5). The longest geometric mean half-lives
per pesticide under field conditions are 35 days for herbicide
dalapon (n = 2), 28 days for insecticide tebufenozide (n = 26),
and 26 days for insecticide cadusafos (n = 4). Variability for
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multistep process including mainly oxidation, reduction,
hydrolysis, and conjugation reaction pathways.76 Metabolism
of pesticides in plants can be categorized into three phases with
oxidative, reductive, and hydrolytic mechanisms being characteristic for the initial phase, conjugative processes dominating
the second phase, and the third and final phase encompassing
the formation of secondary conjugates and bound residues.77 In
46 reviewed studies (5.7% of all studies), metabolic pathways
(mainly hydrolysis and oxidation, that is, chemical decomposition) were assessed along with identifying major and minor
metabolites.56,60,69−71,78−117 However, only 23 studies quantitatively reported how much the formation of metabolites
contributed to the overall dissipation of the parent compound,56,60,69,71,78−95 with a large variability between active
ingredients ranging from 2% for acephate that metabolized into
methamidophos in cucumbers82 to 89% for fenthion that
mainly transformed into fenthion sulfoxide in grapes.71 In
addition to chemical decomposition, microbial degradation may
also result in metabolites that are sometimes used by the
degrading organisms as an energy pool or growth substrate.118
However, enzymatic catalysis of pesticide degradation processes
by microorganisms in plants has rarely been characterized.114
Microbial degradation in plants has been assessed by six
reviewed studies,78,95,114,118−120 with reported contributions to
overall pesticide dissipation of up to 100% for different
pesticides in tomato fruits.120
Stereoselectivity of Chiral Pesticides. Around 30% of known
registered pesticides are chiral, that is, they exist as two or more
nonsuperimposible species (enantiomers) differing in direction
of rotation and three-dimensional arrangement, and usually
exhibit some degree of stereoselectivity (also known as
enantioselectivity) in their biodegradation rates or toxicity.121
However, only 15 reviewed studies (<2%) addressed chirality as
a substance property potentially influencing variability of
pesticide dissipation from plants.122−136 In 10 of these studies,
it was shown that enantioselective metabolism in plants varies
significantly between pesticides.122−131 Famoxadone, for
instance, showed no obvious stereoselectivity between the
(S)-(+)-enantiomer and (R)-(−)-enantiomer degradation
behavior on grape leaves resulting in almost identical halflives.129 In contrast, significant stereoselective metabolism was
reported for benalaxyl, where the (S)-(+)-enantiomer was
shown to degrade 9% to 304% faster than the (R)(−)-enantiomer in all tested plant species (tomato, tobacco,
bell pepper, and sugar beet).125 Only one study reported that
the (R)-(−)-enantiomer was more stable than the (S)(+)-enantiomer with 42% slower degradation for epoxiconazole
in grapes.127 Finally, 5 studies assessed the difference in
dissipation half-lives of isomers.132−136 Variation in half-lives
was shown to range between no significant difference in the
dissipation rate of four cypermethrin isomeric pairs in elm
bark134 and 100% difference between alpha- and betaendusulfan on surfaces of tea shoots.136
Other Chemical-Dependent Aspects. Aspects related to
ionization potential, polarity, ability to form chelates with metal
ions and more might also influence pesticide dissipation in
plants.10,11,26,27 However, none of these aspects was considered
qualitatively or even quantitatively in any of the reviewed
studies, except a single study speculating that the formation of
chelate complexes with copper ions might slow down the
dissipation of benalaxyl in tomato fruits.117
4.2. Plant-Related Aspects. Dilution by Plant Growth.
Growth dilution refers to the effect that with increasing weight
individual pesticides can be characterized by the ratio of 2.5th
percentile half-life divided by the 97.5th percentile half-life
(95% confidence interval limits) across all data points for each
substance. This variability ranges from a factor 1 (i.e., no
variability) usually for substances with not more than 2
reported data points from a single reference to a factor 505 for
the insecticide parathion-methyl with 46 reported data points
from 9 distinct references with different study conditions.
However, less than 2% of all considered substances show
variability larger than a factor 100. Compared to the variability
across pesticides per target class (see Figure 4), some
substances show a larger variability than the variability across
substances of the corresponding target classes. This highlights
that dissipation kinetics are highly sensitive to varying study
conditions, vegetation species and harvested plant components.
Individual Pesticides: Cold Storage and Greenhouse
Conditions. As already discussed, part of the variability
shown in Figure 5a and b is associated with different study
conditions, especially for pesticides with reported half-lives
from distinct references, such as for the fungicide tebuconazole
(15 data points from 9 different references), as well as for the
insecticides methidathion (18 data points from 8 studies) and
parathion-methyl (46 data points from 9 references). At the
lower end, field half-lives as short as 0.1, 0.3, and 1.4 days were
observed for tebuconazole in chilli fruit in a tropical climate,73
and for methidathion and parathion-methyl on cotton leaf in a
hot and dry climate,27 respectively. At the upper end, very long
half-lives between 60 and 105 days were found for these three
pesticides under cold storage conditions.70,74,75 If we look at all
data points (n = 47) for substances under cold storage
conditions, we find geometric means of reported dissipation
half-lives between 2.2 days for bifenthrin and 690 days for
pyriproxifen, which are higher than the geometric means for
these substances without considering data points related to cold
storage conditions, that is, when only considering field
conditions. Long half-lives under cold storage conditions are
mostly due to reduced temperature and, hence, reduced
biological and chemical reaction activity. 10 In contrast,
substances applied in greenhouses show geometric means of
dissipation half-lives between 0.8 days for methamidophos and
137 days for spinosad. This large variability is mainly a function
of substance solubility, where for soluble pesticides higher
temperatures in greenhouses reduce their dissipation half-lives,
while for less soluble pesticides washoff (important for leaf
uptake) and leaching in soil (important for root uptake) are
reduced, thereby leading to increased half-lives.10
4. ASPECTS INFLUENCING PESTICIDE DISSIPATION
Most experimental studies only speculate about a wide range of
aspects and processes as being potentially responsible for
observed pesticide dissipation in plants. In the following,
however, we discuss aspects influencing pesticide dissipation
kinetics only for experimental studies that directly assessed one
or more of these aspects either qualitatively (35 studies) or
quantitatively (112 studies). These sum up to 147 studies
discussed below, thereby corresponding to 18% of all reviewed
references with 67, 31, and 49 studies assessing aspects related
to substance properties, plant characteristics and environmental/study conditions, respectively.
4.1. Substance-Related Aspects and Processes. Chemical and Microbial Decomposition. Pesticide decomposition
via chemical or microbial degradation mechanisms, also
referred to as metabolism or biotransformation, is generally a
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methyl dissipation was strongly accelerated in lemons with a
dissipation half-life that is about 2.5 times shorter than in
apples.157 Overall, reported contributions of plant sample
acidity to pesticide dissipation ranges from around 12% for
folpet in grapes56 to 60% for azinphos-methyl in lemons.157
Other Plant-Related Aspects. Further aspects related to
water or lipid content of plant species, shape, roughness and
wettability of leaf cuticles, or plant transpiration might
additionally influence pesticide dissipation kinetics,10,27,118,148
but have not been discussed in any of the reviewed studies.
4.3. Environmental and Study Conditions. Photodecomposition. Photodecomposition comprises processes
where molecular excitation by absorption of sunlight energy
results in organic reactions like hydroxylation or decarboxylation (direct photolysis) and where reactive oxygen species
oxidize a pesticide’s functional groups (indirect photolysis or
photosensitization).159,160 Photodecomposition mainly depends on meteorological conditions (irradiation intensity,
shading effects), on plant surface affinity to the pesticide
formulation, but also on surface wax composition,27,159−163
since pesticides applied via oil-based spray droplets dissolve in
the epicuticular waxes and are thus protected from photodecomposition.161 Hence, the large lipid-covered plant surface
forms an ideal sink for accumulating hydrophobic pesticides.159
Despite the importance of photodecomposition as a dissipation
pathway, effects have been explicitly reported as influencing
pesticide dissipation in plants by 1 study qualitatively162 and by
17 studies quantitatively,56,110,118,119,148,163−174 together summing up to only 2.2% of all considered studies. Reported
contributions of photodecomposition to pesticide dissipation
range from less than 6% for pendimethalin in turf foliage118 to
99% for rotenone in olive fruits.164,165 The influence of
pesticide formulation type and epiculticular waxes has been
addressed in 3 and 8 studies, respectively. Compared to the
active substance itself, pesticide formulations have in all cases
been reported to show less photostability and, hence, to
decrease up to 5 times faster.165−167 This is potentially
attributable to the fact that formulation additives may accelerate
photodecomposition processes.166 In contrast, epicuticular
waxes have been reported to decrease photodecomposition
for most pesticide−plant species combinations.110,166,168−171
However, little effect of epicuticular waxes on photodecomposition was reported for famoxadone on grapes,173 whereas no
effect at all was shown for plant-derived biopesticides rotenone
on olives164 and pyrethrins combined with the pesticide
synergist piperonyl butoxide on peach.168
Temperature. Increasing temperature is known to accelerate
numerous processes involved in pesticide dissipation10,27,159 by,
for example, increasing a substance’s solubility.10 Effects of
temperature on the dissipation of pesticides in plants have been
assessed by four studies qualitatively (mainly discussing
seasonal aspects with respect to growing seasons)134,163,175,176
and by 18 studies quantitatively,69−71,73,74,119,137,157,174,177−185
of which 14 studies explicitly investigated the influence of cold
storage conditions.70,71,73,74,119,137,157,177−183 The effect of
reduced temperatures in cold storage rooms varies significantly
ranging from reduced dissipation of carbendazim in mango
fruits by a factor 2 during storage at 15 °C (the corresponding
average temperature in the field study was 25 °C)179 to reduced
dissipation of pyriproxyfen in bell pepper fruits by a factor 24
during storage at 4 °C (the corresponding average temperature
in the field study was 24 °C).70 In two other studies, no
pesticide dissipation was observed at all during 21 days of cold
of sampled plant material, the proportion of residual pesticide
concentration (weight-based) decreases, which is also known as
“apparent elimination”.137 Growth dilution depends on
substance stability, that is, the more stable a pesticide, the
more growth dilution will usually contribute to its dissipation.138 Many studies explicitly avoided the effect of growth
dilution by considering equal periods between planting and
harvest, harvesting samples of equal size, or by expressing
residues on a harvest area basis rather than on a weight basis.
Nevertheless, 15 studies assessed growth dilution and its effect
on the persistence of pesticide residues in plants qualitatively80,139 or even quantitatively.65,85,91,140−148 In these studies,
reported contributions of growth dilution to pesticide
dissipation range from around 10% for thifensulfuron-methyl
in whole soybean plants85 to 82% for dimethoate in artichoke
heads.143 Some of the studies considering pesticide dilution due
to plant growth corrected dissipation half-lives by incorporating
a growth dilution factor.142−145 This factor expresses the
relationship between the pesticide residue on the day of
application multiplied by the plant component weight on the
day of application divided by the plant component weight on
the day of sampling.145 Growth dilution factors between 2 and
16 were reported, thereby indicating the influence on fixing
preharvest intervals and maximum residue limits,143 especially
for high dilution factors.
Volatilization. Volatilization is a composite term comprising
pesticide evaporation from plant surfaces as a function of
interception area and roughness, as well as transpiration as a
function of inner plant transpiration stream velocity driving the
subsequent loss of water as vapor through leaf stomata.10,149
However, volatilization from plant surfaces is also correlated
with substance-specific vapor pressure,139,149−151 and influenced by environmental parameters, such as diurnal fluctuations of temperature and solar irradiation.150,152 Twelve
reviewed studies assessed volatilization from plants as
contributing to dissipation of pesticide residues qualitatively52,151,153 or quantitatively.95,118,139,148,150−152,154−156 In
these studies, quick volatilization in the first days after
application compared to decreased volatilization afterward
was often reported52,150,152,155 and identified as being mainly
responsible for biphasic dissipation kinetics of some pesticides.52,150 Reported contributions of volatilization to overall
pesticide dissipation in plants vary significantly ranging from
less than 1% for clopyralid in dwarf bean leaves150 to more than
98% for cypermethrin in tea leaves.148 Compared to
volatilization from soil, which was additionally assessed in
some of the reviewed studies, pesticides volatilize considerably
faster from plants,52,118,151 mainly depending on different
affinities of a substance to sorb to plant surface and soil
lipids.118,151 Increasing air humidity improves the adsorption
affinity to plant surfaces, thereby reducing volatilization.139,154
Acidity. Many plant species grown for human or animal
consumption, in particular fruit crops, contain a certain amount
of organic acids (malic acid, citric acid, etc.). Only 4 reviewed
studies (0.5%), however, investigated the effect of acidity of
harvested plant samples on pesticide dissipation.56,74,157,158
Acidic sample conditions catalyze hydrolytic reactions of
pesticides.74 Hence, in cases where high plant component
acidity is unable to accelerate pesticide dissipation, oxidative
rather than hydrolytic processes are predominant. As an
example, while the higher acidity of lemons compared to the
acidity of apples did not affect dissipation of parathion-methyl,
which is reported to mainly dissipate via hydrolysis,74 azinphos3556
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storage,137,183 which is mainly explained by the fact that under
cold storage conditions, most dissipation processes, most
importantly volatilization and photodecomposition, but also
microbial degradation, are significantly reduced.119,159 Effects of
temperature under field conditions were assessed by 4
studies69,174,184,185 with corresponding pesticide dissipation
half-lives varying between a factor 2 for rimsulfuron in maize
shoots (15 °C temperature difference)69 and a factor 4 for
imidacloprid in Chinese mustard (21 °C temperature difference).174
Surface Washoff. Pesticide washoff from plant surfaces by
rainfall can be an important dissipation process, especially
shortly after substance application,186 and is an indirect route
by which many pesticides reach the soil.159 However, the ability
of rain to either help the pesticide penetrate into the plant
interior (usually systemic pesticides) or to wash it off (usually
nonsystemic or contact pesticides) depends on rain quantity,
time between pesticide application and rainfall, pesticide
solubility, the structure of the plant surface, and formulation.27,58 Only 8 studies (1%) assessed effects related to plant
surface washoff,58,64,65,139,162,186−188 with reported contributions of washoff to pesticide dissipation in plants ranging
between 20% for myclobutanil in wheat shoots187 and up to
67% for tribufos in cotton leaves.186 Washoff effects were in
addition reported to be higher on grape fruits than on grape
leaves,58 whereas washoff effects were reported to be higher on
leaves than on fruits for orange,64 which highlights the influence
of the roughness of the sampled plant component.
Spatial Variability. Spatial variability occurs from the field
scale to the global scale. At the field scale, spatial variability
refers to distribution profiles within the same agricultural field
that can be horizontal, like overlapping or missing treated areas,
or vertical as a function of plant structure and complexity. A
single study focused on assessing spatial distribution patterns of
azinphos-methyl applied to alfalfa at the field scale.189 This
study reported the highest residues in the canopy with only
13−30% reaching the soil surface, and a highly variable
horizontal distribution with the uneven structure of the plant
layer and the distance from the end of the spray boom as main
contributors. At larger scales, spatial variability refers to
different environmental study conditions (climate, soil, etc.)
and is known to be highly important for assessing pesticide
dissipation in soil.190,191 The influence of individual environmental study conditions has already been discussed above.
Measurement Uncertainty. Last but not least, there are
aspects affecting experimentally derived dissipation half-lives
that are related to application, external sampling and storage
operations, sample preparation and processing, and finally
extraction cleanup and instrumental determination.75 Such
effects are summarized as uncertainty of analytical results.
However, comparing different application doses applied in the
same study for 91 substances shows that at least this aspect
does not influence dissipation half-lives at all.
several currently used pesticides and pesticides that are banned
from the global market but persist in soil and may be taken up
by plants.3,192 For pesticides where our review does not provide
any or only very few half-lives, further experimental studies are
required. Future studies should thereby focus on pesticides
authorized for use in agriculture and crops considered
important in terms of production and consumption quantity,
but also on persistent pesticides that still contaminate
agricultural soils. In addition, data obtained for samples from
different plant components of the same pesticide−plant species
combination will help to improve our understanding of the
dynamics and dissipation behavior of pesticides, thereby
providing important input for international pesticide regulation,
such as identifying optimal minimum preharvest intervals or
maximum residue limits in different vegetal food items. For
very few pesticide−plant species combinations, we found a
large number of measured dissipation half-lives, such as for
methomyl in grapes, mexacarbate in balsam fir, and azinphosmethyl in pear with 83, 30, and 22 data points, respectively. For
these combinations, additional experimental residue studies will
most likely not result in improved mechanistic understanding.
Instead, we recommend considering pesticides for future
experiments that have so far not been reported at all for
certain crops, although they are authorized and registered for
use on these crops in several countries, such as imidacloprid
applied to apple or dimethomorph applied to lettuce.
Most residues follow pseudo-first-order dissipation kinetics.
If measured pesticide residues in plants from new experimental
studies do not seem to follow pseudo-first-order kinetics,
different models for approximating both residual concentration
curves and related dissipation half-lives can be applied as given
in Table 2.
Other Research Needs. Although monitoring of residues
in plants is considered the gold standard to evaluate pesticide
use or misuse,75 experiments are generally expensive and timeconsuming. Hence, developing models estimating dissipation
half-lives for pesticides without sufficient experimental data are
urgently required. Such predictive models must be based on a
full statistical analysis of our database of experimentally derived
dissipation half-lives to correct for the influence of temperature,
crop characteristics, pesticide physicochemical properties, and
other important aspects. However, attention is required with
respect to the small variability in dissipation half-lives across
pesticides and plant species, since the uncertainty in such
predictive models might quickly exceed the variability of the
measured data. This applies to both empirical and deterministic
models. Overall, we believe that the combined introduction of
additional experimental studies with focus on important
pesticide−plant species combinations, along with predictive
models for the combinations with insufficient experimental data
available would be able to reduce uncertainty and improve
assumptions in current risk and impact assessment practice.
Both experiments and models could thereby build upon the
findings and collected data of the present review.
Recommendations. For applying pesticide dissipation halflives in plants in risk and impact assessment or for human
exposure studies, we recommend to (a) use the geometric
mean over all data points of the same combination of pesticide,
plant species, and harvested component, in cases where this
combination is available in our database, (b) use the geometric
mean over all data points for a pesticide corrected for influential
parameters like temperature based on a full statistical analysis of
our database, where the pesticide−plant species combination of
5. FUTURE RESEARCH DIRECTIONS
Experimental Studies. With almost 500 pesticides
authorized alone in the European Union according to current
legislation (status “approved” or “pending”)18 for use on several
hundred plant species that are grown for human or animal
consumption, available studies on pesticide dissipation still
cover only a small fraction of possible pesticide−plant species
combinations. Our review constitutes a first step in providing a
source of dissipation half-lives in plants for assessing both
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interest is not listed in our database, and (c) develop a
predictive model based on our database, if no or insufficient
data points for the pesticide of interest are available. We
additionally recommend for the assessment of field conditions
to exclude all data points reported for cold storage and
greenhouse conditions but to use them only for assessing these
specific conditions. Our full database of experimentally derived
pesticide dissipation half-lives in plants is available free of
charge at http://dynamicrop.org.
■
ASSOCIATED CONTENT
S Supporting Information
*
We provide the whole database of collected pesticide
dissipation half-lives in various plant species. This material is
available free of charge via the Internet at http://pubs.acs.org.
■
AUTHOR INFORMATION
Corresponding Author
*Phone: +45-4525-4452. Fax: +45-4593-3435. E-mail: fantke@
dynamicrop.org.
Notes
The authors declare no competing financial interest.
■
ACKNOWLEDGMENTS
The authors would like to thank Prof. Olivier Jolliet and Dr.
Peter Wieland for their scientific support and Catherine Raptis
for editing.
■
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