This document describes a new sample preparation technique called fast agitated directly suspended droplet microextraction (FA-DSDME) for the extraction and pre-concentration of 18 organophosphorus pesticides from human blood samples prior to analysis by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The key advantages of this technique over other microextraction methods are that it uses automated agitation to deliberately split and recombine the organic extraction droplets, avoiding the need for dispersive solvents or centrifugation. Recoveries of 86-109% were obtained with detection limits ranging from 0.0009 to 0.122 μg/L. The method showed good precision, enrichment factors from 30 to 132, and was not

1. Journal of Chromatography A, 1377 (2015) 27–34
Contents lists available at ScienceDirect
Journal of Chromatography A
journal homepage: www.elsevier.com/locate/chroma
Fast agitated directly suspended droplet microextraction technique
for the rapid analysis of eighteen organophosphorus pesticides in
human blood
Rupender Kumaria,b
, Devendra K. Patela,b,∗
, Smita Panchala,b
, Rakesh R. Jhaa,b
,
G.N.V. Satyanarayanaa
, Ankita Asatia,b
, Nasreen G. Ansaria
, Manoj K. Pathakc
,
C. Kesavachandranc
, Ramesh C. Murthya
a
Analytical Chemistry Section, CSIR-Indian Institute of Toxicology Research, P.O. Box 80, Lucknow 226001, India
b
Academy of Scientific and Innovative Research (AcSIR), CSIR-Indian Institute of Toxicology Research Campus, P.O. Box 80, Lucknow 226001, India
c
Epidemiology Division, CSIR-Indian Institute of Toxicology Research, P.O. Box 80, Lucknow 226001, India
a r t i c l e i n f o
Article history:
Received 18 July 2014
Received in revised form
13 November 2014
Accepted 2 December 2014
Available online 11 December 2014
Keywords:
Eco-friendly sample preparation technique
Liquid chromatography mass spectrometry
Pesticides
Trace analysis and human blood
a b s t r a c t
A new sample preparation technique named as fast agitated directly suspended droplet microextrac-
tion (FA-DSDME) was proposed as an improved version of directly suspended droplet microextraction
(DSDME) for the extraction and pre-concentration of wide-range organophosphorus pesticides (OPPs)
from human blood prior to liquid chromatography tandem mass spectrometric (LC–MS/MS) analysis. In
this method, instead of protecting the unwanted rupturing of extraction droplet (organic solvent), it was
deliberately splintered into fine droplets by providing automated high-speed agitation to the biphasic
extraction system (extraction solvent and sample solution). Fine organic droplets were then recollected
into one, not by using a centrifuge machine but just by giving a very slow stirring to the bottom of the
extraction system. The present method has surmounted the problem of prolonged extraction time asso-
ciated with old DSDME. Under optimum extraction conditions, the method showed good sensitivity with
low detection limits ranging from 0.0009 to 0.122 ␮g L−1
. Mean recoveries were achieved in the range of
86–109% at three levels of spiking concentration (low, middle and high) from linearity range of individual
analyte. Intra-day and inter-day precisions were ≤4.68 and ≤9.57 (%RSD) respectively. Enrichment factor
(EF) for each analyte varied from 30 to 132 which prove the ability of this technique to pre-concentrate
the extracted analytes up to a good extent. The sample matrices have shown an insignificant influence
on method’s sensitivity. The proposed method may find immense use in epidemiological, toxicological,
regulatory and forensic laboratories.
© 2014 Elsevier B.V. All rights reserved.
1. Introduction
Among all classes of pesticides, organophosphorus pesticides
(OPPs) are majorly affecting our population, leading to lethality
and persistent health problems [1–3]. Especially in Asian countries,
pesticide poisonings (intended and accidental), are quite common
due to easy accessibility to pesticides [2]. As a result of ceaselessly
increasing poisoning problems due to OPPs, there is an urgent
need to develop a sensitive, reliable and cost-effective sample
preparation method for their trace analysis in biological fluids. A
∗ Corresponding author at: Analytical Chemistry Section, CSIR-Indian Institute
of Toxicology Research, P.O. Box 80, Mahatma Gandhi Marg, Lucknow 226001, UP,
India. Tel.: +91 522 2627586x228.
E-mail address: dkpatel@iitr.res.in (D.K. Patel).
number of sample preparation methods have been reported for the
quantitative evaluation of pesticides in biological samples [4–12].
However, most of them suffer from disadvantages as they involve
multiple steps viz. de-proteinization, plasma separation, multistep
extraction to achieve good recovery, concentrating large volumes
of extraction solvent, making them expensive and time consuming
[13]. A few years ago, a novel microextraction technique named as
dispersive liquid liquid microextraction (DLLME) was developed
involving a rapid injection of a mixture of extraction solvent and
dispersive solvent into the aqueous sample solution. The rapid
injection caused the cloud formation consisting of infinitely fine
droplets of extractant diffused entirely into the donor phase, leads
to instantaneous extraction of targeted compounds [14]. Certainly,
DLLME is a sensitive and fast pre-concentration technique but
the major limitations are; firstly, the DLLME process requires
halogenated extraction solvents, hazardous to the user and
http://dx.doi.org/10.1016/j.chroma.2014.12.006
0021-9673/© 2014 Elsevier B.V. All rights reserved.

2. 28 R. Kumari et al. / J. Chromatogr. A 1377 (2015) 27–34
environment. Secondly, the extra use of polar co-solvents (dis-
persive solvent) caused the extraction solvent and/or targeted
analytes to solubilize into the sample solution itself, which would
generate unwanted variations among successive experiments
[15]. Thirdly, it requires centrifugation to separate the extracted
layer from sample solution which unnecessarily enhanced the
processing time. Furthermore, DLLME is entirely a manual process
and all efforts made to automate the process have not yet been
achieved beneficial results [16–18].
Recently, air assisted liquid liquid microextraction (AALLME) –
a new pre-concentration method came into the existence, which
overcomes the unnecessary utilization of dispersive solvent in
DLLME process. This technique involves the repeated syringe
plunging of extractant and the sample solution for achieving imme-
diate extraction [15]. Although, the use of dispersive solvent has
been diminished but all other demerits remained the same. And the
processing becomes much tiring due to repeated injection, might
not be a suitable alternative. To circumvent these problems, there
is a need to develop an automated pre-concentration method such
as directly suspended droplet microextraction (DSDME); one of
the valuable modifications which was started progressively since
after the development of liquid phase microextraction, LPME in
1996 [19–21]. Unfortunately, DSDME suffered with the drawback
of unwanted dislodgement of extraction solvent’s droplet at high
agitation speed makes it very tricky to recollect completely. And
the concluding results vary according to the pattern in which the
solvent’s droplets are dispersed and collected.
Providentially, it was confirmed with the above-mentioned
techniques that rapid agitation works as a crucial parameter in the
extractionprocess.Thus, a new advancementwas madeto get a bet-
ter extraction in a very short time via deliberately spattering and
rejoining of organic droplets at varying but automated agitation of
the sample solution and then solidification of the extracted droplet
for easy collection. Most of the shortcomings of DLLME, AALLME
and DSDME technique were approached to surmount in the present
study. The proposed method ‘Fast Agitated Directly Suspended
Droplet Micro Extraction (FA-DSDME)’ chiefly involves the com-
bination of two microextraction techniques, i.e. DSDME/LPME and
solidified floating organic drop microextraction (SFODME) [22–29].
The key benefits of this innovative technique are (i) the auto-
mated agitation of binary liquid extraction system which tends to
minimize the inaccuracy of the results, occurred due to manual
processing, (ii) unlike DLLME and AALLME, temperature support
can also be employed to further enhance the extraction efficiency,
(iii) the controlled stirrings for splitting and rejoining the organic
droplets have avoided the use of dispersive solvents and also
unnecessitate the use of centrifuge machine, (iv) it’s application
does not require any prior treatment i.e. de-proteinization/plasma
separation, on blood sample, and (v) the entire process involves
only one step to extract the targeted analytes as well as to separate
and pre-concentrate the extracted phase.
2. Experimental
2.1. Chemicals and materials
Analytical grade standards of all organophosphorus pesti-
cides (chlorpyrifos, chlorpyrifos-methyl, dichlorvos, dimethoate,
fonofos, ethion, malathion, methidathion, monocrotophos,
paraoxon-methyl, phorate, phorate sulfone, phorate sulfoxide,
phosalone, pirimiphos-ethyl, pirimiphos-methyl, quinalphos
and triazophos) of highest purity (>99.9%) were procured from
Sigma Aldrich (Bellefonte, PA, USA). All solvents (1-dodecanol,
2-dodecanol, 1-undecanol, n-hexadecane and methanol) were
from Merck (Darmstadt, Germany). Glass vials of 7.0 mL capacity,
magnetic stir fleas and micro-syringe (50 ␮L) were obtained from
Sigma Aldrich (Bellefonte, PA, USA). Electronically controlled tem-
perature and stirring module was purchased from Sigma Aldrich.
Ultra pure water was obtained from in-house water purification
system having conductivity of 18 m (Milli-Q, Millipore Corp., MA,
USA). Human blood samples were collected from the villagers at
the time of pesticides spraying on agricultural fields in or around
Lucknow city after obtaining approval from Institutional Human
Ethics Committee and informed consent from the subjects. All the
samples were stored at −20 ◦C until processed for the analysis. No
minors/children participants were involved in this study.
2.2. Preparation of standard solution
An individual standard stock solution of 1000 ␮g mL−1 was
prepared by dissolving accurately weighed (10 mg) individual
pesticide in 10 mL of methanol. The working standard solutions
of lower concentration (0.1 ␮g mL−1) were prepared by diluting
successively with methanol. All the standards were stored in a
refrigerator at 4 ◦C, when not in use.
2.3. LC–MS/MS conditions
Liquid chromatographic analysis was performed on UPLC sys-
tem (Acquity-Waters, Miliford, USA) coupled to an API-4000 mass
spectrometric system (AB ScieX) with an electrospray ionization
(ESI) source. Analysis was done within 2.0 min on a Acquity UPLC®
BEH C-18 column (50 mm × 2.1 mm, 1.7 ␮m particle size) under an
isocratic elution of mobile phases, 5% – A (0.1% formic acid in water)
and 95% – B (0.1% formic acid in methanol) at a constant flow of
0.3 mL/min. Definite sample volume (10 ␮L) was injected using an
auto sampler of the UPLC.
Instrumental processing was controlled by AnalystTM software
(Version 1.4.1, AB ScieX, Foster City, CA, USA). The ESI was oper-
ated in positive mode with the source temperature at 300 ◦C, and
source voltage at 5500 V. The nebulizer gas (GS1), turbo gas (GS2),
collisionally activated dissociation gas (CAD) and curtain gas (CUR)
were programmed at 40 psi, 60 psi, 8 psi and 10 psi respectively.
Acquisition was performed over three time periods for each sample.
The mass spectrometric analysis was executed in selected reaction
monitoring (SRM) mode by keenly optimizing the dwell time var-
ied from ≥15 to ≤50 ms as shown in Table S1 (Supplementary data).
The suitable dwell times were adjusted in order to maintain appro-
priate number of data points (≥13) per chromatographic peak. The
pause time and target scan time were set to 3.0 ms and 1.0 s corre-
spondingly. Optimal conditions for the dependent characteristics
of the mass spectrometer for qualitative and quantitative analysis
of individual analyte are summarized in Table S1. Each analyte was
quantified on the basis of quantifier ion (high intensity peak), which
was presented in bold letters in Table S1.
2.4. Data handling and processing
The results obtained from chromatographic analysis based on
the peak area for individual analyte, were evaluated and tested
using, Microsoft Excel, 2007. Quantization was done by inferring
the integrated peak areas of individual analyte of unknown con-
centration into the calibration graph formula of their respective
analyte of known concentration. Using paired t-test, p-values were
calculated which were if found <0.05, then only can consider to
be insignificants the differences among repetitive tests (n − 3 or
more). Otherwise, the tests were regarded as not valid to rely on
their executed interpretations.

3. R. Kumari et al. / J. Chromatogr. A 1377 (2015) 27–34 29
2.5. Sample preparation
The blood sample (100 ␮L) was transferred to a glass vial and
diluted with 4.0 mL of ultrapure Milli-Q water. The pH of diluted
sample was adjusted to 5.5 by the addition of hydrochloric acid
(0.5 N). Subsequently, the PTFE coated magnetic stirrer flea was
introduced in the sample vial, 20 ␮L of 1-dodecanol was allowed
to float over the surface of the sample solution by using a microsy-
ringe. Thereafter, the vial was sealed and placed on a heating
module previously programmed at 55 ◦C. The stirring speed was
maintained at 1500 rpm for 9.0 min, to deliberately shatter the
organic droplet into several tiny droplets for complete extraction
from the bulk of the aqueous sample solution. Thereafter the tiny
droplets were allowed to recollect into one by agitating the sample
solution at 100 rpm for 2.0 min. The sample vial was then trans-
ferred into an ice bath for solidification of extractant’s droplet.
After 3.0 min the solidified droplet was collected with the help of
micro-spatula and transferred to a conical vial. Prior to injection
into LC–MS/MS, the extracted droplet was diluted with methanol
up to 200 ␮L.
3. Results and discussion
3.1. Method optimization
A number of parameters which can influence the optimum
extraction of desired analyte from the sample matrix such as selec-
tion of extracting solvent, volume of extracting solvent, sampling
temperature, extraction time, stirring rate, and solution pH, were
standardized for optimum extraction of desired analytes from the
sample matrix.
3.1.1. Selection of extraction solvent
The most important parameter is the selection of the extracting
solvent for the best possible extraction yield. Properties of a good
extraction solvent are: (1) immiscibility with the aqueous solution,
(2) high boiling point to avoid its evaporation during extraction, (3)
melting point between 10 and 30 ◦C for solidification of extracted
solvent near room temperature and (4) non-interference with the
peak of the analyte during chromatographic analysis [22–27].
By considering these stipulated characteristics, several organic
solvents like 1-undecanol (melting point (m.pt.) = 13–15 ◦C), 1-
dodecanol (m.pt. = 22–24 ◦C), 2-dodecanol (m.pt. = 17–18 ◦C) and
n-hexadecane (m.pt. = 18 ◦C) were tried as an extraction solvent for
the desired analytes from the sample matrix. Out of all these extrac-
tion solvents, 1-dodecanol was found to be the best as extracted
droplet gets easily solidified and collected out after completion of
the extraction process, and most importantly, it showed the highest
extraction efficiency as compared to other solvents tested.
3.1.2. Extracting solvent volume
As per the LLE equation, the facilitation of mass transfer of ana-
lytes from the sample matrix toward the organic phase directly
depends on the interfacial area between the two liquid phases
however inversely associated with the volume of organic phase
[30]. Effect of volume of extracting solvent on peak responses was
studied by increasing the volume from 5.0 to 30.0 ␮L at intervals
of 5.0 ␮L. It was observed that increase in solvent volume up to
20 ␮L caused a remarkable elevation in detector responses of the
desired analytes. Beyond >20 ␮L a decrease in signal response was
observed. The increase in the volume of extracting solvent led to
increasing in extraction efficiency only till the interfacial area pre-
dominates on the organic solvent volume as shown in Fig. S2-1
(Supplementary data). As soon as the organic solvent volume pre-
dominates it caused a considerable declination in extraction yield
[30]. So, organic solvent volume of 20 ␮L was selected for extraction
in further experiments.
3.1.3. Sample solution temperature
The temperature of the sample solution directly influences the
extraction yield. Generally in microextraction methods, rise of sam-
ple temperature led to high enrichment of extracted analytes.
Increase in sampling temperature increases the diffusion coeffi-
cient of the analytes and decreases the viscosity of solvent droplet
which in turn facilitates the smooth and fast mass transfer of
analytes from the sample matrix into the organic droplet [31].
Accordingly, the influence of sampling temperature on extraction
efficiency was studied from room temperature (27 ◦C) to 75 ◦C for
30 min by floating a 20 ␮L droplet of 1-dodecanol over the sur-
face of aqueous sample solution. Trials clearly showed a significant
rise in extraction efficiency along with the increase in tempera-
ture up to 55 ◦C as presented in Fig. S2-2 in Supplementary data.
However further increase (>55 ◦C) caused the loss in the volume
of organic solvent and so, in extraction yield. Also the maintained
equilibrium has disturbed between extraction solvent and sample
solution leads to reverse the extraction yield. Therefore, 55 ◦C was
chosen as sample solution temperature for further experiments.
3.1.4. Stirring rate
Proper agitation of the sample solution enhances the extraction
efficiency considerably. Increase in stirring speed (rpm) of the sam-
ple solution escalates the diffusion of analytes toward the solvent
droplet by decreasing the thickness of diffusion film in the aqueous
sample phase as per the film theory of convective-diffusion mass
transfer [32,33].
Stirring rate in the range of 200–600 rpm was studied to get the
optimum extraction yield. Plot of peak area against stirring speed
shows a rapid and repeatable increase in extraction efficiencies up
to 500 rpm as shown in Fig. S2-3 (Supplementary data). Thereafter
also, the enhancement in analytical signals was observed with fur-
ther increase in stirring speed (>500 rpm) but the repeatability of
the results was not good. The reason might be that at high stir-
ring speed (>500 rpm) the solvent droplet gets spattered/damaged
making it very tricky to collect the full droplet [32,34]. If the spat-
tering can be controlled, the extraction yield can easily be enhanced
much.
3.1.5. Extraction time
Generally the exposure time was selected when the sample
solution and the organic phase have reached in chemical (analyte)
equilibration. Equilibrium is the sampling duration where the max-
imum possible transfer of analytes from the sample solution into
the extracting droplet has occurred and further increase in time
cannot improve the extraction efficiency [21]. The influence of time
was examined in the range of 8–40 min by keeping all other param-
eters at constant. The results showed that the corresponding peak
areas enhanced with increase in time up to 32 min as presented
in Fig. S2-4 (Supplementary data). Considerable increase in peak
responses was observed as the equilibrium was not attained even
after 32 min of exposure. Another option of fast agitation via sev-
eral repeated rapid injections of extractant and sample solution
(AALLME) to the bottom of the sample vial was tried. Surprisingly,
it was found that there was no need to wait for 40 min for getting
better extraction yield [15]. The reason is that the rapid agitation,
aided in achieving instantaneous thermodynamic equilibrium of
targeted analyte in biphasic extraction system. Nonetheless, repet-
itive syringe plunging process facilitated the extraction, but this
process was not found as useful in terms of repeatability (intra-day
variation >6% RSD). So, the time factor was tried to minimize using
automated fast agitation (1500 rpm) for deliberately splintering the
solvent’s droplet, and then gently agitated (100 rpm) just to push

4. 30 R. Kumari et al. / J. Chromatogr. A 1377 (2015) 27–34
the recollection of tiny droplets into one. A series of experiments
were performed to scrutinize the stirring speed from 1500 rpm
onward while keeping extraction time constant for 15 min. As
expected, the extraction yield increased up to a great extent as
shown in Fig. S2-5 (Supplementary data). Thus, the stirring speed
of 1500 rpm was chosen to optimize the extraction time again. And
the extraction time has significantly reduced from >40 min to 9 min
as presented in Fig. S2-6 (Supplementary data). Even though, here
also the variations between repeated experiments (n − 10) were
noticeably increased but unlike rapidly injecting process, the reli-
ability values are satisfactorily laid between the precision ranges
given by Eurochem method validation guide [35]. Finally, auto-
mated fast agitation at 1500 rpm was opted for further study.
3.1.6. Potential hydrogenii (pH) effect
The pH of the sample solution also plays a major role in enhanc-
ing the extraction efficiency as the analytes can be extracted better
in neutral molecular form [36]. The effect of pH on extraction was
tested by adjusting the pH of the sample solution within the range
of 3.5–7.5 and change on extraction yield was monitored as pre-
sented in Fig. S2-7 (Supplementary data). Maximum extraction was
achieved when the pH of sample solution was kept at 5.5. There-
after, the analytical responses started decreasing possibly due to
the potential disintegration of the molecules [37]. Thus for further
study, pH 5.5 was opted.
3.2. Quality parameters
In order to check the performance of the proposed method
(FADSDME-ESI-LC–MS/MS), important analytical characteris-
tics (i.e. linearity, sensitivity, accuracy (recovery), and precision
(repeatability and reproducibility)), were appraised by treating
the aqueous sample solution with the known concentration of
OPPs standard solution. All the validation supportive values are
summarized in Table 1. Linearity of the method was evaluated
using a number of samples spiked in quintuplicate with a series of
concentrations. For each analyte, calibration curve was obtained
by plotting the extracted concentration against their respec-
tive detector responses (peak area). The method shows good
linearity behavior for all analytes in the concentration range of
0.01–32.0 ␮g L−1 with correlation coefficient (R2) ≥ 0.987 for each
analyte. Limit of detection (LOD) of the method was experimentally
estimated as three times from the standard deviation of the ana-
lyte’s signals obtained from the extraction of spiked blood samples
to the baseline noise of 10 blank samples for each compound
(S/N = 3). The method shows good sensitivity for targeted com-
pounds by obtaining very low detection limits ranged from 0.0009
to 0.122 ␮g L−1. Repeatability (intra-day precision) and repro-
ducibility (inter-day precision) of the method were determined
to check the variations among the outcomes of successive experi-
ments performed under constant conditions. These were estimated
by measuring six replicate samples in a day (intra-day precision)
and in three consecutive days (inter-day precision) by spiking the
aqueous samples 2.0 ng mL−1 of OPPs. The estimated values were
presented in terms of percent relative standard deviation (%RSD).
Consecutively, intra-day and inter-day variations were found less
than 4.68% and 9.57% respectively which assured the reliability of
the extraction technique. Further to ensure the feasibility of the
method, recovery study was also executed by treating the sample at
three level concentrations of OPPs standard (ng mL−1). The recov-
eries were calculated as the percent ratio of detector response to
the analyte’s concentration extracted into the solvent’s droplet to
the concentration initially spiked in the examined sample. Accord-
ing to which the mean recoveries were found varied between 86
and 109% at different spiking levels as per the individual compound
as depicted in Table 1. Each of the representative samples was
analyzed in quintuplicate. From the aforementioned results, it can
be concluded that the proposed method is satisfactorily accurate
and precise to investigate OPPs with sensitive detection limits.
Moreover in this study, three methods involving, (1) DSDME,
(2) FA-DSDME (present method) and (3) manual rapid injections
of donor and acceptor phases (AALLME), were tried and evaluated
in terms of reliability as depicted in Table 2. AALLME, as based on
the manual plunging process of extracting and donating solution,
is expected to generate uncontrollable manual variations between
repeated set of similar experiments. This was confirmed by obtain-
ing the insignificant deviation values up to 11.23% (%RSD) for the
extractions carried in a day with ten replicates. DSDME; a slow
agitation process is provably reliable by giving almost negligible
relative standard variations (0.85–2.14%) among repeated extrac-
tions, but considering prolonged extraction time, this method
cannot be the choice of an analyst. Modifications with adding vio-
lent agitation in DSDME, the method (FA-DSDME) have shown
comparatively less deviations (2.68–4.53%) in contrast to AALLME
(6.21–11.23%), but noticeably increased as comparing to slow agi-
tated DSDME (0.85–2.14%). The variations may take place due to
the erratic numbers of fine droplets formed, each of which extracts
some parts of targeted analytes from the aqueous sample solu-
tion. In repeated experiments, it is not always possible to manually
produce the similar splitting pattern of the organic droplet which
is the sole cause of deviation between results. So that, the varia-
tions are comparably much high >7% RSD [38], when the agitation
was performed by manual syringe plunging process, in contrast to
automated fast agitation through magnetic flea (present method)
(<5% RSD). It can be concluded that the automation of the sample
preparation method is mandatory to get reliable results without
compensating with the sensitivity of the method.
3.2.1. Method competence
Enrichment factor (EF) was determined to assess the extraction
competence of the proposed method. EF was calculated as the ratio
of detector responses (peak area) of each analyte, finally extracted
into the acceptor phase to the actual concentration initially spiked
into the donor phase [39]:
EF =
aCap
aCdp
where ‘aC’ notifies the concentration of analyte. The words written
in subscripts, ‘ap’ and ‘dp’ stands for the acceptor phase and donor
phase respectively.
For determining EF, five replicate extractions were conducted at
finally optimized conditions from the aqueous blood sample solu-
tion spiked with (2.0 ng mL−1). As the volume of the extractant is
very small (20 ␮L) as compared to sample solution (4.0 mL), that
would concentrate the analytes up to a great extent. The sample
dilution was conducted to facilitate the extraction by loosening
the interactions among components of the analyzed matrix (blood)
which otherwise would be very difficult to apply in sample prepa-
ration. Being the core matrix (100 ␮L) was treated into a diluted
aqueous suspension (4.0 mL), the resultant volume was considered
as a whole sample solution for assessing EF. Consequently, the EF
was found in the range of 30–132 which determine the aptness
of the method of pre-concentrating the extracted analytes up to a
good extent as depicted in Table 1.
3.2.2. Application to the real samples
In order to validate the applicability, proposed method was
employed to determine 18 organophosphorus pesticides in real
blood samples. Except one, neither of the samples was found to be
contaminated with the OPPs. A sample was surprisingly observed
to be exposed with around a half dozen of pesticides, which was

5. R. Kumari et al. / J. Chromatogr. A 1377 (2015) 27–34 31
Table 1
Proposed method’s validation parameters for all selected pesticides.
Compound LODa
DLRa
R2
EF Added conc.*
R% MME (%) ME (%) %RSD
Intra-day Inter-day
Dimethoate 0.004 0.02–1.28 0.989 56 0.08 101 2.32 1.31 2.23 5.68
0.32 104 2.52 6.21
1.28 99 3.21 6.58
Phorate 0.002 0.01–0.64 0.987 89 0.04 101 3.46 2.14 2.12 5.39
Sulfoxide 0.16 107 3.24 6.85
0.64 103 3.15 7.26
Phorate 0.013 0.05–3.2 0.991 58 0.20 97 1.05 0.85 3.42 6.35
Sulfone 0.80 106 4.12 7.84
3.20 104 4.21 8.87
Dichlorvos 0.002 0.01–0.64 0.991 61 0.04 98 0.94 1.52 2.98 7.32
0.16 102 3.21 7.98
0.64 100 3.74 8.57
Quinalphos 0.007 0.03–1.92 0.989 38 0.12 96 1.87 2.77 2.86 6.67
0.48 103 3.65 7.79
1.92 106 3.98 8.25
Chlorpyrifos 0.0009 0.01–0.64 0.999 132 0.04 102 0.56 1.69 1.69 5.69
0.16 109 2.54 6.35
0.64 107 2.68 7.42
Chlorpyrifos-methyl 0.015 0.05–3.2 0.993 95 0.20 96 0.76 1.47 2.25 6.86
0.80 104 2.98 8.14
3.20 103 3.66 8.71
Ethion 0.023 0.1–6.4 0.993 30 0.40 96 1.73 2.66 3.45 6.58
1.60 99 3.79 8.54
3.20 102 3.61 9.52
Monocrotophos 0.029 0.1–6.4 0.994 35 0.40 93 2.25 2.89 3.78 7.36
1.60 96 4.14 7.91
3.20 96 4.44 8.54
Malathion 0.043 0.2–12.8 0.998 41 0.80 86 3.06 4.32 2.54 6.24
3.20 92 3.22 6.89
12.8 95 3.54 7.85
Methidathion 0.034 0.2–12.8 0.998 35 0.80 96 1.31 3.96 3.56 5.94
3.20 103 3.98 6.73
12.8 102 4.25 8.06
Phorate 0.041 0.2–12.8 0.992 42 0.80 92 3.03 1.70 2.89 6.12
3.20 99 3.54 7.51
12.8 102 4.42 8.68
Paraoxon-methyl 0.031 0.1–6.4 0.989 34 0.40 88 1.24 2.49 3.22 5.48
1.60 96 3.67 6.16
3.20 93 3.98 8.45
Fonofos 0.038 0.2–12.8 0.991 35 0.80 88 0.86 2.57 4.68 9.57
3.20 95 4.21 9.41
12.8 95 3.58 9.15
Phosalone 0.009 0.05–3.2 0.995 77 0.20 95 1.06 3.65 3.74 7.84
0.80 98 4.11 8.62
3.20 104 3.87 9.07
Pirimiphos-ethyl 0.041 0.2–12.8 0.997 45 0.80 94 0.75 1.93 4.14 8.39
3.20 99 3.25 7.84
12.8 104 3.54 8.24
Pirimiphos-methyl 0.110 0.5–32 0.998 41 2.00 86 1.16 2.66 2.65 6.51
8.00 91 3.85 9.14
32.0 93 3.57 8.83
Triazophos 0.122 0.5–32 0.997 38 2.00 86 1.30 3.85 2.88 5.86
8.00 94 3.60 6.71
32.0 96 3.74 8.16
LOD, limit of detection; DLR, dynamic linearity range; R2
, correlation coefficient; R%, mean recovery percent; EF, enrichment factor; %RSD, percent relative standard deviation;
Conc., concentration; MME, matrix matched effect; and ME, matrix effect.
a
␮g L−1
.
presented in comparing with the spiked chromatogram of OPPs in
Fig. 1. Out of all the analytes detected in the contaminated sam-
ple, only three of them were found above quantification limits
(S/N = 10), at a level of 0.0088 (chlorpyrifos), 0.0838 (chlorpyrifos-
methyl) and 0.0713 (phosalone) ␮g L−1. It can be clearly seen from
Fig. 1 that the method is also suitable to inhibit the interferences
of unwanted peaks. And the quantitative result of the contami-
nated sample verifies that the method can successfully extract and
analyze the selected analytes up to trace content.
Furthermore, it is been obvious that the matrix components can
influence the recovery of particular analytes, either by improv-
ing or inhibiting their extraction efficiencies. In this study, two
types of matrix interferences have been evaluated, which can
influence the extraction efficiency of the method; (a) matrix effect
(ME) – the interferences caused by the sample matrix in com-
parison to ultrapure water sample, and (b) matrix matched effect
(MME) – the interferences caused due to different blood sam-
ples. Thus for assessing ME and MME, the ultrapure water samples
and all the inspected blood samples were also analyzed after
treating them with the OPPs standard, at the medium concentra-
tion level (0.16–8.00 ng mL−1), been utilized in recovery studies.
Their extracted analyte contents were then interpreted against the
standard results of a control blood sample, which was also spiked
at the same level of OPPs and the compared effects (ME and MME)
were expressed in terms of mean percent deviation in Table 1 for
each analyte. The results showed that the sample matrix have very

6. 32 R. Kumari et al. / J. Chromatogr. A 1377 (2015) 27–34
Table 2
Reliability test comparison of the present extraction technique with two others (DSDME and AALLME). All values are expressing the intra-day variation (repeatability) among
ten successive extractions (n − 10), represented in terms of percent relative standard deviation (%RSD).
Compound DSDME @ slow
agitation
FA-DSDME @ automated
vigorous agitation
AALLME (agitation with
rapid manual injections)
Dimethoate 1.81 4.31 7.45
Phorate Sulfoxide 1.02 3.94 7.12
Phorate Sulfone 1.77 3.78 8.32
Dichlorvos 1.22 2.98 9.12
Quinalphos 1.32 4.15 8.23
Chlorpyrifos 0.85 2.81 7.11
Chlorpyrifos-methyl 1.41 3.65 6.56
Ethion 0.94 4.18 7.25
Monocrotophos 1.2 4.53 8.15
Malathion 1.68 4.12 10.22
Methidathion 2.12 3.21 9.05
Phorate 1.54 2.68 6.87
Paraoxon-methyl 2.14 3.87 7.25
Fonofos 1.18 3.65 7.69
Phosalone 1.47 3.48 11.23
Pirimiphos-ethyl 1.08 3.14 7.45
Pirimiphos-methyl 1.25 3.84 6.21
Triazophos 0.86 3.04 10.23
Fig. 1. Comparative chromatograms: the one extracted from the control blood sample spiked with mixed standard solution of 18 pesticides at 3.0 ␮g L−1
(top) and the other
extracted from the real human blood sample (bottom) using proposed method. (1) Dimethoate, (2) Phorate Sulfoxide, (3) Phorate Sulfone, (4) Dichlorvos, (5) Quinalphos, (6)
Chlorpyrifos, (7) Chlorpyrifos-methyl, (8) Ethion, (9) Monocrotophos, (10) Malathion, (11) Methidathion, (12) Phorate, (13) Paraoxon-methyl, (14) Fonofos, (15) Phosalone,
(16) Pirimiphos-ethyl, (17) Pirimiphos-methyl and (18) Triazophos.
little effect (≤4.32%) on extraction efficiency of individual analyte
in contrary to ultrapure water sample. This might be happened
because the whole method conditions were optimized on the sam-
ple matrix itself. Further, the extent of interferences caused by real
blood samples comparing to the control blood sample were almost
negligible (≤3.46), which concludes that the sample matrix have
an insignificant influence on the performance of FA-DSDME.
4. Conclusions
In this study, a new, nearly automated and sensitive FA-DSDME
technique coupled with LC–MS/MS was developed for investigating
18 OPPs in human blood. All the factors, can affect the extraction
efficiency, were keenly optimized in this study which shows
that the agitation of the sample solution has mainly influence

7. R. Kumari et al. / J. Chromatogr. A 1377 (2015) 27–34 33
the extraction efficiency. By comparing the present method with
DSDME and AALLME, it was suggested that the manual agitation
would question the reliability of the method. The present study
found that the manual processing of the extraction procedure
tends to generate the inevitable errors among repeated tests which
in turn lead to fallacious interpretation. Thus, automated fast agi-
tation was approached to get the reliable and sensitive results.
The proposed method can successfully be applied on real blood
samples for analyzing organophosphorus pesticides with excellent
detection limits. It was concluded, that FA-DSDME–LC–MS/MS is
an easy, brisk, green and robust extraction technique which also
possesses a satisfactory pre-concentration competence to facilitate
the trace level detection. The present study suggests the automa-
tion of the extraction process in order to obtain reproducible
results without compensating with the sensitivity of the method.
Acknowledgements
The authors wish to thank the Director, Council of Scientific and
Industrial Research – Indian Institute of Toxicology Research (CSIR-
IITR), Lucknow, India, for providing the necessary facilities for this
research study. One of the authors (RK) thanks University Grants
Commission (UGC), New Delhi, India for financial assistance. The
authors do not have any relevant affiliations, financial involvement
and conflicts with any organization and person with the subject
matter and material discussed in the manuscript. The author did
not get any writing assistance for the production of this manuscript.
Appendix A. Supplementary data
Supplementary data associated with this article can be
found, in the online version, at http://dx.doi.org/10.1016/j.chroma.
2014.12.006.
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