Application of fractional factorial design and Doehlert matrix in the optimization of experimental variables associated with the ultrasonic-assisted acid digestion of chocolate samples for aluminum determination by atomic absorption spectrometry.

A simple and rapid method based on ultrasound energy is described for the determination of aluminum (AI) in complex matrixes of chocolate and candy samples by electrothermal atomic absorption spectrometry. The optimization strategy was carried out using multivariate methodologies. Five variables (temperature of the ultrasonic bath; exposure time to ultrasound energy; volumes of 2 acid mixtures, HNO3-H2SO4-H2O2 (1 + 1 + 1) and HNO3-H2O2 (1 + 1); and sample mass) were considered as factors in the optimization process. Interactions between analytical factors and their optimal levels were investigated using fractional factorial and Doehlert matrix designs. Validation of the ultrasonic-assisted acid digestion procedure was performed against standard reference materials, milk powder (SRM 8435) and wheat flour (SRM 1567a). The proposed procedure allowed Al determination with a detection limit of 2.3 microg/L (signal-to-noise = 3) and a precision, calculated as relative standard deviation, of 2.2% for a set of 10 measurements of certified samples. The recovery of Al by the proposed procedure was close to 100%, and no significant difference at the 95% confidence level was found between determined and certified values of Al. The proposed procedure was applied to the determination of Al in chocolate and candy samples. The results indicated that cocoa-based chocolates have higher contents of Al than milk- and sugar-based chocolates and candies.