Application of Response Surface Methodology (RSM) and Central Composite Design (CCD) to Optimize Minerals Composition of Rice-Cowpea Composite Blends during Extrusion Cooking

摘要

Significant loss of nutrients has been reported during extrusion cooking, and processing food with this technology therefore requires careful optimization of the process parameters. In this experiment, the effect of process variables on the mineral content of rice-cowpea extrudates was investigated using response surface methodology and central composite design. Barrel temperature (X_(1)), feed moisture composition (X_(2)) and blend composition (X_(3)) were the independent variables considered, while mineral composition was the response variables. Results showed that X_(1), X_(2) and X_(3) all had a significant effect on the mineral composition (p< 0.001). The interactions between the threefactors were also found to be significant at 0.001 level of probability. At X_(1) between 86 - 140~(o)C, X_(2) between 15 - 25% and X_(3) between 8 - 24% the mineral contents in terms of Mn, Fe, Cu, Zn and Ca contents of rice-cowpea extrudates increased. The optimization of the analyzed responses demonstrated that the best peak conditions for extrusion under the different variables were 12.06mg/100g, 5.59mg/100g, 10.98mg/100g, 2.36mg/100g, 4.24mg/100g, and 25.99mg/100g for Mg, Mn, Fe, Cu, Zn and Ca respectively. At moisture content slightly above 22% and blend composition of 20%, Mg content start to decrease. Calcium and Cu contents decrease with increasing moisture and feed blend contents and gradually increases when moisture content raise above 20% and feed blend composition greater than 10%. The correlation coefficients of 0.992, 0.987, 0.969, 0.866, 0.974 and 0.980 observed between the predicted and actual values for the response variables are evidence that the regression model can represent the experimental data well. It can be concluded therefore that minerals present in the extrudates may be maximized when process conditions are carefully adjusted within the reported values.