A new approach to reduce the effects of omitted minor variables on food engineering experiments: Transforming the variable-result interaction into image

Abstract

In food engineering experiments aiming the optimization, only the combinations of major variables are tested. Moreover, only the constant optimal value (single value) is suggested to each independent variable in these experiments. However, the suggested values may not always be optimal in future studies due to minor variables that not considered in the experiments. Therefore, it is more accurate to suggest the range of variable values that produce the almost same optimal results rather than a constant optimal value. So that the effect of the minor variables can be minimized. For this reason, in this study, the values of variables obtained by polynomial model were transformed to images then an image processing method was performed to represent the relevant values of the variables as a single colour shade. Thus, the optimal ranges represented by single shade of color were determined. The limits of these ranges were the variable values corresponding to the values of maximum or minimum color shade and very close to the maximum or minimum constant value. The proposed method was tested in an experiment aiming the nisin production optimization depending on three independent variables. Since the same optimization experiment that has been tried with another method is also available in the literature the findings of this study were also compared with the previously suggested constant optimal values. As a result, the superiorities and availabilities of method proposed in this study were discussed.