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


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


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



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



Design of experiments

response can be defined by a linear function of independent

variables


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.


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



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.



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!



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.



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)


//upload.wikimedia.org/wikipedia/commons/d/db/Acetochlor.png


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



SP disc extraction


C18 DISC


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



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):



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



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



Results

The effects of sample volume and solvent ratio on the extraction yield of acetochlor



Results

800 ml of sample

40/60 dichloromethane/hexan

The best conditions for extraction of acetochlor from water are


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


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.


Here comes your footer "International Symposium on Current Trends in Plant Protection“ 25 - 28. September, Belgrade

This research is a part of project III43005 funded by Ministry of Education and Science of the Republic of Serbia

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APPLICATION OF RESPONSE SURFACE METHODOLOGY (RSM) FOR

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