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The present paper approaches the application of response surface methodology (RSM) in the optimization of variables for analytical methods development. Some basic principles of this multivariate method are presented and characteristics of the main experimental designs are discussed. Examples of RSM application for optimization of analytical methods is also presented to illustrate the potentialities of these chemometric tools.

In this study, it was developed a method for Ca, Mg, Mn, Fe and Zn determination in palm oil samples by flame atomic absorption spectrometry (FAAS) after ultrasound-assisted emulsification and extraction induced by emulsion breaking (EIEB). Optimization of the method was carried out by a constrained mixture design. The developed method has presented limits of detection (LOD ) found in the samples were: 3.93-13.9 Ca, 0.37-2.26 Mg, > LOQ-0.32 Mn, 1.77-8.57 Fe and 0.38-2.54 Zn.

The present paper approaches the application of response surface methodology (RSM) in the optimization of mixture variables aiming the development of analytical methods. Some basic principles of this multivariate method are presented and characteristics of the main experimental designs are discussed. Examples of mixture design application for optimization of analytical methods is also presented for illustrated the potentialities of this chemometric tool.

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