application of response surface methodology (rsm) for
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APPLICATION OF RESPONSE SURFACE
METHODOLOGY (RSM) FOR DETERMINATION
OF PESTICIDE RESIDUES IN WATER
Dragana Šunjka, Sanja Lazić, Nada Grahovac, Snežana Jakšić, Slavica Vuković
University of Novi Sad, Faculty of Agriculture, SERBIA
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The optimisation of an analytical procedure is frequently done
following a step-by-step approach which requires a high number of
experiments and does not consider interactions between the different
variables.
In this sense, alternative approaches like experimental design can
help to quickly achieve optimum conditions.
"International Symposium on Current Trends in Plant Protection“ 25 - 28. September, Belgrade
Introduction
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What is RSM?
Collection of mathematical and statistical techniques useful for the
modeling and analysis of problems in which a response of interest is
influenced by several variables and the objective is to optimize this
response.
Box and Draper, 1987
The statistical method using response surface methodology (RSM)
has been proposed to determine the influences of individual factors
and the influence of their interactions and successfully overcomes the
limitation of the classical method.
y = f (x1, x2, ………xk) + e
"International Symposium on Current Trends in Plant Protection“ 25 - 28. September, Belgrade
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Why RSM?
reducing a number of analysis
reducing the cost of expensive analysis methods
reducing the time for analysis
The most common applications of RSM are in Industrial,
Biological and Clinical Science, Social Science, Food Science,
Physical and Engineering Sciences.
designing, formulating, developing, and analyzing new
scientific studying and products
improvement of existing studies and products
"International Symposium on Current Trends in Plant Protection“ 25 - 28. September, Belgrade
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Design of experiments
response can be defined by a linear function of independent
variables
"International Symposium on Current Trends in Plant Protection“ 25 - 28. September, Belgrade
includes all the terms in the first-order model, plus all quadratic terms
and all cross product terms
FIRST-ORDER MODEL
SECOND -ORDER MODEL
The most common forms are low-order polynomials.
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Selection of appropriate experimental design is the
most important step in implementation of this
procedure.
Central-composite design (CCD)
Box-Behnken design (BBD)
full factorial plan (FFP) ...
Design of experiments
"International Symposium on Current Trends in Plant Protection“ 25 - 28. September, Belgrade
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Response surface plot
The response can be represented graphically, either in the three-
dimensional space or as contour plots that help visualize the shape of the
response surface.
"International Symposium on Current Trends in Plant Protection“ 25 - 28. September, Belgrade
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RSM in determination of pesticide residues
In determination of pesticide residues in different matrices the
problem presence the extraction of pesticide residues from
these matrices.
Many factors, such as type and ratio of solvent, sample
volume, extraction time, temperature, pH may significantly
influence on the extraction.
This problem can be solve using response surface
methodology.
Aim of the study!
"International Symposium on Current Trends in Plant Protection“ 25 - 28. September, Belgrade
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Aim of the study!
determination of optimum extraction conditions of
acetochlor from water
RSM was applied to optimise the solid-phase
extraction conditions using a C18 disc to determine
acetochlor in water.
"International Symposium on Current Trends in Plant Protection“ 25 - 28. September, Belgrade
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Acetochlor
chloroacetanilide herbicide
widely used for the control of broadleaf
weeds and annual grasses in row crops
might migrate into ground and surface waters
during the first season it was used, acetochlor was detected
in surface water in Minnesota at concentrations abowe MRL
[2-chloro-N-ethoxymethyl-N-[2-ethyl-6-methylphenyl]acetamide)
"International Symposium on Current Trends in Plant Protection“ 25 - 28. September, Belgrade
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Method optimization
full factorial plan (FFP)
two factors (sample volume, solvent ratio) at three levels
Parameter Coded values
-1 0 1
X1 Sample volume, ml 250 500 1000
X2 Solvent ratio, % 40/60 50/50 60/40
The levels of factors were selected according to results from previous research
"International Symposium on Current Trends in Plant Protection“ 25 - 28. September, Belgrade
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SP disc extraction
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C18 DISC
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GC/ECD analysis
Hewlett-Packard model 5890 Series II gas chromatograph; Supelco
column 24048 (SPBTM-5, 30mx0, 32 mm id, film tickness 0.25 mil) with
electron-capture detector Ni63
(ECD).
Operating mode splitless
Injection volume 2 μl
Injector temperature 250 C
Temperature detector 300 C
Initial column temperature 100 C
Speed of temperature rise 9 C/min
Final temperature 250 C
Determination conditions
"International Symposium on Current Trends in Plant Protection“ 25 - 28. September, Belgrade
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Statistical analysis
The adequacy of the model was evaluated
by the coefficient of determination (R2)
and model p-value.
Y=b0 + b1X1 + b2X2 + b11X12 + b22X2
2+ b12 X1 X2
b0 – intercept,
b1, b2 – represents the linear,
b11, b22 – quadratic and
b12 – interaction effect of the factors.
X1: sample volume
X2: solvent ratio
Statistical analysis of experimental data was made in StatSoft Statistica ver. 10.0.
For the description of the responses Y (recovery), a second-degree polynomial
model was fitted to data (Eq. 1):
"International Symposium on Current Trends in Plant Protection“ 25 - 28. September, Belgrade
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Results
Response Source
Acetochlor
Residual Model
F-value p-value R2 DF SS MS DF SS MS
3 23.444 7.8148 5 600.111 120.022 15.358 0.0239 0.981
Analysis of variance (ANOVA) for the modeled response of acetochlor
DF – Degree of Freedom; SS – Sum of Squares; MS – Mean Squares
"International Symposium on Current Trends in Plant Protection“ 25 - 28. September, Belgrade
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Results
Effects Acetochlor
Coefficient p-value
Intercept
X0 31.53681 0.215308
Linear
X1 0.19779 0.002923
X2 4.58923 0.067567
Quadratic
X11 0.00006 0.176777
X22 0.01245 0.221214
Interaction
X12 -0.00152 0.001971
Regression equation coefficients for the responses
"International Symposium on Current Trends in Plant Protection“ 25 - 28. September, Belgrade
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Results
The effects of sample volume and solvent ratio on the extraction yield of acetochlor
"International Symposium on Current Trends in Plant Protection“ 25 - 28. September, Belgrade
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Results
800 ml of sample
40/60 dichloromethane/hexan
The best conditions for extraction of acetochlor from water are
"International Symposium on Current Trends in Plant Protection“ 25 - 28. September, Belgrade
LOQ 0.01 µg/ml
Recovery values for acetochlor 93 – 96 %
Linear regression analysis
Concentration range 0.005 - 1.0 µg/ml
Y=ax + b 79.85x-0.093
r² 0.9995
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Summary
A simple and sensitive method for determination of acetochlor from
water using C18 disc and GC/ECD was developed.
The response surface methodology was used to optimize the
parameters of extraction and to investigate the interaction effects of
different factors.
Optimal conditions for acetochlor extraction from water were – sample
volume 800 ml; solvents 40/60 (v/v) dichloromethane/n-hexane.
Having regard to the foregoing RSM provides sufficient information to
allow us to select individual and/or simultaneous extraction conditions
that will yield a specific target recovery.
"International Symposium on Current Trends in Plant Protection“ 25 - 28. September, Belgrade