Optimization analysis of heat energy required in garrification process using a garri fryer powered by electrical filaments as heat source.

Abstract

Frying is the most tedious unit of garri processing. The amount of heat applied during the processing operation determines the end quality and market value of the product. Thus, this study is aimed at investigating the effect of pre-processing conditions on the heat energy of an auto garri frying machine. A 4-factor, 5-level D-optimal design of response surface methodology (RSM) was used for modeling and optimization of the process. The mash quantity, frying time, initial moisture content and temperature were varied over 10, 20, 30, 40, and 50 kg; 15, 30, 45, 60, and 75 mins; 30, 35, 40, 45, and 50% wet basis (wb); and 140, 160, 180, 200, and 220 °C, respectively. The results show that a linear model F- value of 61.08 implies that the model was significant with value of R2 (0.8526) and Adj-R2 (0.9092) indicating that there was a high correlation between the dependent and independent variables. In optimizing the process, the heat energy was maximized while the independent variables were set at ranges. Optimum heat energy of 14,000 J was obtained at 45.33 kg mash quantity, 67.37 mins frying time, 40% wb initial moisture content and 180 °C frying temperature at the desirability of 1. At α = 0.05, the analysis of variance (ANOVA) showed that the mash quantity, frying time and temperature had direct significant impacts on heat energy of the garri frying machine while the initial moisture content had no significant effect on the heat energy.