Multivariate optimization of microwave-assisted extraction of zinc and copper from soybean

In this study, a simple and fast microwave-assisted extraction (MAE) method combined with flame atomic absorption spectrometry (FAAS) was developed and optimized for the extraction and determination of zinc and copper in soybean. The optimization of the MAE conditions was conducted using a full factorial design and Box-Behnken matrix. Firstly, the full factorial design was carried out for preliminary evaluation of the significance of the factors, the factors chosen being: irradiation power, temperature, extraction time, and concentration of nitric acid. The results showed that all of the factors were significant. Because of this, a Box-Behnken experimental design was carried out in order to determine the optimum condition. The total 27 experiments were conducted in the study towards the construction of a quadratic model. According to analysis of variance (ANOVA) results, the proposed model can be used to navigate the design space. High regression coefficient between the variables and the response (R (2) = 0.97) indicated excellent evaluation of experimental data by polynomial regression model. The method was applied to the determination of zinc and copper in soybean samples.