Multivariate optimization of a dispersive liquid-liquid microextraction method for determination of copper and manganese in coconut water by FAAS.

In this study, multivariate methodologies were applied in the optimization of a dispersive liquid-liquid microextraction (DLLME) method, aiming at the determination of Cu and Mn in coconut water samples by flame atomic absorption spectrometry. Some extractors (chloroform and CCl), dispersants (ethanol, methanol and acetonitrile) and complexing agents (5-Br-PADAP and Dithzone) were previously tested in the extraction. A mixture design was used to optimize the component proportions formed by chloroform (10%), acetonitrile (76%), and 0.

Multivariate optimization of a goat meat alkaline solubilization procedure using tetramethylammonium hydroxide for metals determination using FAAS.

In the present work, multivariate designs were used to optimize an alkaline dissolution, assisted by ultrasound energy, procedure of goat meat using tetramethylammonium hydroxide (TMAH) aiming to determine Ca, Cu, Fe, K, Mg, Na and Zn by flame atomic absorption (FAAS) and emission (FAES) spectrometry. The optimal conditions found for the dissolution were in the following ranges: 0.4-0.

An alkaline dissolution-based method using tetramethylammonium hydroxide for metals determination in cow milk samples.

This study approaches the development of a method for the determination of Ca, Mg, Zn, and Fe in liquid and powdered cow milk. The method is based on sample dissolution assisted by ultrasound energy in tetramethylammonium hydroxide (TMAH) media and determination by flame atomic absorption spectrometry (FAAS). Central composite design (CCD) associated with response surface methodology and desirability function allowed the fast and efficient optimization of the variables involved in the performance of the dissolution.