Vol.4, No.5B, 106-111 (2013) Agricultural Sciences
Evaluation of pesticide residues in fruit from Poland
and health risk assessment
B. Łozowicka*, P. Kaczyński, E. Rutkowska, M. Jankowska, I. Hrynko
Plant Protection Institute-National Research Institute, Laboratory of Pesticide Residues, Chełmońskiego 22, Białystok 15-195, Po-
land; *Corresponding Author: B.Lozowicka@iorpib.poznan.pl
Received 2013
In the present study an effort has been made to
evaluate the residues of insecticides, fungicides
and herbicides in fruit from Poland and their
health risks assessed. Accredited multiresidue
methods based on gas and liquid chromatog-
raphy, and spectroscopic technique were used
to determine the concentrations above 160 pes-
ticides. A total of 392 samples of 15 different
fruit were collected during the May 2010 to Oc-
tober 2012. In 48.2% of samples no residues
were found, 45.9% of samples contained pesti-
cide residues at or below the EU MRL, and 5.9%
of samples contained pesticide residues above
MRL. Sour cherries (66%) and apples (63%) were
the commodities in which pesticide residues the
most frequently occurred. Thirty one different
pesticides were detected in total. Dithiocar-
bamate, captan, cyprodinil and boscalid were
the pesticide most frequently found. Multiple
pesticides ( > 1 pesticide) were detected in about
30.1% samples. The dietary intake of residues of
some pesticides can pose acute hazards. Data
obtained were used for estimating the potential
health risks associated with the exposures to
these pesticides. The highest estimated daily
intakes (EDIs) for children were: 22% for di-
methoate and 112% for diazinone of the ADI. The
most critical commodity was apple, contributing
1.30 to the acute Hazard Index for flusilazole.
The results show that despite a high occurrence
of pesticide residues in fruit it could not be
considered a serious public health problem.
Nevertheless, an investigation into continuous
monitoring of pesticide residues in fruit is rec-
Keywords: Pesticides; Analytical Methods; Fruit;
Poland; Risk Assessment
Fruit are one of the supplementary sources of carbo-
hydrates, lipids, vitamins, minerals, antioxidants and
other important nutrients. The consumption of these
commodities with vegetables is almost 160 kg/per cap-
ita/year in Europe. A high intake of fruit has been en-
couraged not only to prevent consequences due to vita-
min deficiency but also to reduce the incidence of major
diseases such as cancer [1], cardiovascular diseases and
obesity. But fresh fruit could also be a potential source of
harmful and toxic substances. Thus, food safety has be-
come a major public concern worldwide [2].
Pesticides are chemical substances, which are com-
monly used in modern agriculture practices to protect the
crops from different pests and diseases [3]. Like other
crops, fruit are attacked by pests and diseases during
production and storage leading to damages that reduce
the quality and the yield. The use of pesticides have in-
creased because they have rapid action, decrease toxins
produced by ford infecting organisms and are less labor
intensive than other pest control methods.
However, the use of pesticides during production often
leads to the presence of pesticide residues in fruit after
harvest. Unfortunately, not all farmers follow legal prac-
tices with pesticides during production. Therefore, pesti-
cides should be controlled at optimum level due to their
relative toxicity to the human health. Pesticide residue
analysis is tremendously an important process in deter-
mining the safety of using certain pesticides. A number
of analytical methods are designed to determine multiple
pesticide residues. In the past few years, new extraction
procedures have been developed, such as solid-phase
microextraction [4] and supercritical fluid extraction [5].
Pesticides are usually determined by gas chromatography
(GC), GC-mass spectrometry, GC-ion trap mass spec-
trometry [6] and GC–tandem mass spectrometry [7].
Besides GC–MS methods, there are other traditional
quantification methods like high performance liquid
chromatography (HPLC) [8], HPLC–mass spectrometry,
low-pressure gas chromatography–mass spectrometry [9]
and liquid chromatography–tandem mass spectrometry.
Copyright © 2013 SciRes. Openly accessible at http://www.scirp.org/journal/as/
B. Łozowicka et al. / Agricultural Sciences 4 (2013) 106-111 107
In our research, accredited multiresidue methods based
on gas and liquid chromatography, and spectroscopic
technique were used to determine the concentrations
above 160 pesticides.
Fruit have been given a lot of attention in monitoring
programs each country since most of them are eaten raw,
it is expected that they contain higher pesticide residue
level compared to other food groups of plant origin. Ac-
cording to the Pesticide Residues Committee in the UK,
consumers are encouraged to eat at least five portions of
fruit and vegetables daily. Poland is an important fruit,
particularly apples, exporting area in to the Europe and
Russia. Therefore, assessing the risk of pesticide residues
in these commodities intended for human consumption is
The purpose of this paper was to present data on pesti-
cide residues in fruit from Poland carried out in 2010-
2012. Pesticide residue levels were evaluated in relation
to: Acceptable Daily Intakes (ADIs) [10] cute Reference
Doses (ARfDs) and Maximum Residue Levels (MRLs)
derived from toxicological studies. The results can be
used when designing future control programs for this
region and taking preventive actions to minimize human
health risks.
2.1. Standards, Reagents and Chemicals
Pesticide reference standards were purchased from Dr.
Ehrenstorfer (Augsburg, Germany). Pesticide standard
stock solutions (purity higher than 95%) of various con-
centrations were prepared in acetone and stored in dark
below 4℃.
All solvents used were analytical grade from J.T. Baker
(Deventer, Holland), as well as florisil (60 - 100 mesh)
and phosphate buffer pH = 8. Silica gel (230 - 400 mesh),
sodium sulfide nonahydrate and celite were obtained
from Merck (Darmstadt, Germany).
2.2. Samples
A total of 392 samples of various fruit (apples – 38.8%,
strawberries – 19.1%, sour cherries – 12.8%, currants –
9.7%, pears – 6.6%, plums – 3.8%, raspberries – 3.3%,
black chokeberries – 3.1% and other – 2.8%) were col-
lected from Poland.
2.3. Analytical Procedure
Sample preparation was done using three methods:
multiresidue method (MRM) for determination of 159
pesticide residues This method was described in our pre-
viously study [11] and two single residue method (SRM)
[12,13]. Figure 1 presents all sample preparation meth-
ods and instrumental analysis used for determination
pesticide residues in fruit samples.
2.4. Quality Check
The laboratory successfully participated in the profi-
ciency testing schemes organized and run by the Euro-
pean Commission (University of Almeria) and by the
Food Analysis Performance Assessment Scheme (FAPAS;
Central Science Laboratory in York). All of the analyses
were conducted with the use of an accredited method by
the Polish Centre of Accreditation (PCA).
2.5. Method Validation
The validation of the analytical methods was carried
out in accordance with European Commission (EC)
guidelines [14]. The validation studies were performed
using pesticide-free fruit samples, previously analyzed.
Calibration standards were prepared in matrix solution to
produce a final concentration of three spiking levels
(0.005 to 0.05 mg/kg, 0.05 - 0.5 mg/kg and 0.25 - 2.5
mg/kg). Method accuracy and precision were evaluated
by performing recovery studies and are expressed as
relative standard deviation (RSD, %) and mean recovery,
respectively. Repeatability was calculated for five days
using five replicates for each level of three different
concentration levels. The sensitivity was evaluated by
determining the limit of detection (LOD) and the limit of
quantification (LOQ) of the assay. The LOD and LOQ
were calculated using the signal-to-noise ratio (S/N) cri-
teria in all cases (LOD = 3 S/N, LOQ = 10 S/N).
159 pesticide residues
50g whole fruit 2g homogenized samples
Dithiocarbamate residuesCarbend azim residues
blending silica gel/florisil
hexane/ diethyl ether/ acetone
20g homogenized samples
SPE ChemElut/
25mL acetonitrile/methanol/water hexane/acetone
analysis GC Agilent 7890 A ECD/
NPD, HP-5 column
HPLC Waters Alliance 2695
carbendazim DAD/FLD,
λ=281nm/λex=285 nm,λem=315 nm,
Supelcosil LC-18 column
150 mL acetone
NaOH/S n Cl2 in HCl
reaction with N,N-Dimtehyl-1,4-
phenylenediammonium dichloride
Spectrophometer Helios Delta VIS
λ= 662 nm
Figure 1. Scheme of sample preparation procedures.
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B. Łozowicka et al. / Agricultural Sciences 4 (2013) 106-111
Copyright © 2013 SciRes. Openly accessible at http://www.scirp.org/journal/as/
2.6. Risk Assessment
Consumption data play a major role in the dietary risk
assessment of residues in food. This risk was calculated
through the comparison of found residues to the estab-
lished acceptable daily intake (ADI) and Acute Refer-
ences Doses (ARfD) values. The level of residue con-
centration in a product was determined as the arithmetic
mean of all the results obtained. Results under LOD of
analytical methods used for intake calculations were taken
as LOD values. Values of ADI and ARfD are elaborated
by Joint FAO/WHO Meeting on Pesticides Residues [15].
For consumer residues intake estimation were applied
new model from Pesticides Safety Directorate (PSD) of
the Department for Environment, British Food and Rural
Affairs [16]. Calculations were performed for two sub-
populations: small children (1.5 - 4 years) and adults
accepting consumption at the level of the 97.5 percentile.
The estimated daily intake (EDI) of pesticide residues
was calculated as follows:
EDI mean bodyweight
where: Fi - food consumption data, RLi - residue level to
the commodity.
The long-term risk assessment of the intakes compared
to the pesticide toxicological data were performed by
calculating the hazard quotient (HQ), by dividing the
estimated daily intake with the relevant acceptable daily
 (2)
The HQ was calculated both for pesticides and com-
modities. The HQs are summed up to give a chronic
hazard index (cHI):
cHI HQ (3)
Estimate of Short-Term Intake (ESTI) was calculated
according to the following formula:
ESTI mean bodyweight
where: F - full portion consumption data for the com-
modity unit, HR.P - the highest residue level.
An estimate of intake of pesticide in the diet was to
compare to the ARfD. The acute hazard index was calcu-
lated as follows:
Based on our analytical studies pesticide residues were
not observed in 48.2% of fruit samples (189). Whereas
pesticide residues were found in 203 samples (51.8%). In
most of analysed samples (45.9%) pesticide residues
were below MRLs, while in 5.9% (23) above safety lim-
its (MRLs). Pesticide residue levels were compared to
EU-MRLs [17].
3.1. Multiresidue Samples
Samples containing one (21.7%), as well as multiple
active substances: two, three and even seven residues
presents Figure 2.
Most commonly detected were combination of two
pesticides: flusilzole/dithiocarbamates, captan/dithiocar-
bamates and cyprodinil/fludioxonil.
3.2. Detected Groups of Pesticides
As present Figure 3 the most occurrence group was
fungicides (81.7%). The most frequently detected active
substances among them were: dithiocarbamates (104
samples) range 0.05 to 1.87 mg/kg and captan (80) range
0.01 to 2.83 mg/kg.
Chlorpiryfos (13) range 0.03 to 0.04 mg/kg,fenazaqui
n (10) range 0.02 to 0.240 mg/kg, and acetamipiryd (9)
range 0.01 to 0.03 mg/kg, were dominated among insec-
7 residues
6 res idues
5 residues
4 residues
3 residues
2 res idues
witho ut re sidue s
1 residue
Figure 2. Samples of fruit: without, with one and multiresidue
020406080100 120
Number of samples
azoxystrobin 0.3%
carbend azim 0.3%
fe narimol 0.5%
tolylf lua nid 0. 5%
ip rodione 0.7%
procymidone 0.7%
te buc ona z ole 0.7%
folp et 2.5%
fe nh ex amid 3.0%
fludioxonil 3.0%
tr ifloxy str obin 3.0%
flusilazole 4.3%
pirim e tha nil 4. 8%
boscalid 5.3%
cyprodinil 5. 6%
ca pt an 20.2%
dithiocarbamates 26.3%
icides 82%
detected compounds < or = MRLsdetected compounds > MRLsdetected forbidden compounds
deltam eth rin 0,3%
endosul fa n 0,3%
dimethoate 0,7%
phosal one 0,7%
diazinon 0,8%
alpha-cypermethrin 1,0%
es fen valerate 1,0%
fen itrothi o n 1,3%
cypermethrin 1 , 8 %
pi rimicarb 2 ,0%
acetamiprid 2,3%
fenaz aqu in 2,5%
chlo rpyrifos 3,3%
Insecticide s 18%
Figure 3. Fungicides and insecticides detected in fruit samples.
B. Łozowicka et al. / Agricultural Sciences 4 (2013) 106-111 109
3.3. Pesticide Residues in Fruit
The highest percentage of detected pesticide residues
showed sour cherry samples (66%). Grape, chokeberry,
blackberry, elderberry, wild strawberry, rose hips and sea
sallow thorn samples were free from residues. Apples
contained 59.2% samples with residues below MRL and
3.9% above MRL. The most frequently detected pesti-
cides in apple samples were: dithiocarbamates range 0.05
to 1.87 mg/kg, captan range 0.01 to 0.06 mg/kg, piryme-
thanil range 0.01 to 0.27 mg/kg, boscalid range 0.02 to
0.26 mg/kg, trifloxystrobin 0.01 to 0.100 mg/kg, diazi-
non range 0.02 to 0.03 mg/kg, dimethoate range 0.01 to
0.03 mg/kg, flusilazole range 0.01 to 0.09 mg/kg and
phosalone range 0.01 to 0.25 mg/kg. Currant contained
21% samples with residues below MRL and 39.5%
above MRL and not authorized for use. The largest
number of active substances in these samples was de-
tected, from 3 residues to 7 residues (Figure 2). The
most frequently detected pesticide above the permissible
limits were dithiocarbamates range 0.05 to 0.85 mg/kg,
fenazaquin range 0.05 to 0.24 mg/kg, fenitrothion range
0.02 to 0.03 mg/kg, esfenwalerate range 0.02 to 0.15
mg/kg and flusilazole range 0.01 to 0.09 mg/kg. Straw-
berries contained 40% of samples with residues below
MRL and 1.3% above MRL. 17 multiresidue samples
strawberries containing from 2 to 3 pesticides were re-
corded. There were also cases where not authorized fun-
gicides were detected (procymidone and tolylfluanid).
Raspberry samples with residues below MRL contained
38.5% of samples. There were two and three multiresi-
due samples detected.
3.4. Risk of Exposure
In order to assess the risk of exposure of human health
to the pesticide residues, first of all, the individual com-
ponents of dietary intakes must be known [10], taking
into account different age groups (e.g. infants, toddlers,
school children, adults etc.), as it relates to body weight
and nutritional prevention. The assessment of chronic
(long-term) health risk of consumers connected with the
consumption of apples from north-east Poland containing
pesticide residues was conducted on the basis of avail-
able epidemiological studies done for the British. There is
a lack of full studies done for Polish consumers since these
studies only take into account general population and av-
erage consumption (50 percentile) [18], and therefore had
no practical application in the current study. Accordingly,
13 GEMS/Food Consumption Cluster Diets were devel-
oped based on FAO Food Balance Sheet data from 183
The average intake for each food item at the cluster
level was weighed by the population size of the reporting
country. The western and central parts of Europe, such as
the United Kingdom, Poland, Germany, etc., have been
classified into the same Consumption Cluster Diets E
During the assessment of the long-term consumer risk
the study assumed a cautious approach by using conser-
vative guidelines, which inflated the risk. Based on the
results (Table 1), the chronic intakes of the thirty one
considered pesticide residues are rather low compared to
the ADI (mostly the cHI were < 1%).
Table 1. Health risk estimation for chronic effects associated
with average pesticide residue.
substance bw/daybw/day
x10-4 cHI Health
x 10-4
cHI Health
acetamipirid0.070.3 < 1 No 1.7 < 1No
cypermethrin 0.0150.2 < 1 No 0.6 < 1No
azoxystrobin0.2 0.7 < 1 No 1.5 < 1No
boscalid 0.041.0 < 1 No 3.7 < 1No
captan 0.1 2.3 < 1 No 9.3 < 1No
carbendazim0.020.5 < 1 No 3.0 2 No
chlorpyrifos0.010.5 < 1 No 2.3 2 No
methyl 0.010.1 < 1 No 0.4 < 1No
cypermethrin0.051.7 < 1 No 7.2 1 No
cyprodinil 0.030.5 < 1 No 2.5 < 1No
deltamethrin0.010.0 < 1 No 0.2 < 1No
diazinon 0.00020.4 22 No 2.2 112Yes
dimethoate 0.0010.6 6 No 2.2 22No
bamates 0.055.5 1 No 22.4 4 No
endosulfan 0.0060.2 < 1 No 0.7 1 No
esfenvalerate0.020.7 < 1 No 3.4 2 No
fenarimol 0.010.1 < 1 No 0.3 < 1No
fenazaquin 0.0050.7 1 No 3.6 7 No
fenhexamid0.2 1.0 < 1 No 3.4 < 1No
fenitrothion0.0050.3 < 1 No 1.7 3 No
fludioxonil 0.370.2 < 1 No 0.6 < 1No
flusilazole 0.0020.4 2 No 1.9 9 No
folpet 0.1 0.9 < 1 No 4.2 < 1No
iprodione 0.060.2 < 1 No 0.9 < 1No
phosalone 0.010.3 < 1 No 1.8 2 No
pirimicarb 0.0350.5 < 1 No 2.1 < 1No
pirimethanil0.170.5 < 1 No 2.7 < 1No
procymidone0.00280.5 2 No 1.0 4 No
tebuconazole0.030.4 < 1 No 1.8 < 1No
tolylfluanid0.1 0.2 < 1 No 0.5 < 1No
systrobin 0.1 0.5 < 1 No 2.5 < 1No
ADI - Acceptable Daily Intake [mg/kg]
HI - Hazard Index [%]
Copyright © 2013 SciRes. Openly accessible at http://www.scirp.org/journal/as/
B. Łozowicka et al. / Agricultural Sciences 4 (2013) 106-111
The safety of Polish consumer (adults) thus seems to
be generally under control in terms of pesticide intakes
through fruit and vegetables consumption. Nevertheless,
some residues such as diazinon and dimethoate need to
be considered more closely given that for a high con-
sumer (97.5 percentile) the cHI were 22% and 6% of the
ADI respectively.
With respect to children the ADI was significantly ex-
ceeded for diazinon at high and frequent fruit consump-
tion (apples), with the cHI 112%. This compound, be-
longing to the organophosphate insecticide group had the
lowest ADI value, at 0.0002 mg/kg body weight of all of
the pesticides being studied. It should be noted that the
residues of diazinon were found in only five of the 392
of tested samples.
Short-term exposure expressed as acute hazard index
(aHI) for children based on the highest consumption at
97.5 percentile and highest concentrations of pesticides
residues detected in fruit are presented in Table 2. In the
all of cases which exceed the MRLs only apple sample
containing flusilazole at concentration 0.09 mg/kg con-
stituted a real threat children health (aHI = 1.297). The
acute risk especially from dimethoate in plum is high and
aHI value approaches the limit value is equal to 1 (aHI =
In our work the assessment was based on worst-case
scenarios: the consumption data for consumers who eat a
large portion size of the food were combined with the
highest residue found in fruit from north-eastern Poland.
The evaluation of consumer health risk connected with
the contamination of fruit and vegetables with pesticide
residues shows that it did not pose a danger to neither
subpopulation of small children or adults.
The only noted possible risk for small children was
connected with the residues of diazinon. Children are a
vulnerable group of fruit and vegetables consumers, who
are due to their lower body weight, exposure to relatively
higher pesticide residue levels. A more profound study
regarding this consumer group is recommended.
In conclusion, the results showed that the majority of
fruit samples were in conformity with the relevant legis-
lation and did not contain detectable pesticide residues
(48.2%). Pesticide residues were found in 45.9% of all
monitored fruit samples at or below MRL. While, 5.9%
of samples were above MRL, however, they did not pose
a threat for public health, as demonstrated by the out-
comes of dietary risk assessment.
The results obtained suggest that despite the consum-
ers are exposed to various concentrations of pesticide
residues in fruit from Poland there is no reason for con-
cern and health risk can be excluded.
Copyright © 2013 SciRes. Openly accessible at http://www.scirp.org/journal/as/
B. Łozowicka et al. / Agricultural Sciences 4 (2013) 106-111
Copyright © 2013 SciRes. http://www.scirp.org/journal/as/
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