EFFECT OF EXTRUSION PROCESSING CONDITIONS OF A LOCALLY DEVELOPED EXTRUDER ON THE PRODUCT TEMPERATURE OF SELECTED STARCH CROPS
Product temperature is a very important system parameter as well as an indicator of extrusion process. In this study, the product temperature response of a single screw extruder developed locally was investigated for the extrusion process of the flour and starch of maize and cassava which are grown in Nigeria in large quantity but with high post-harvest losses. These were compared with wheat flour which is commonly used for the production of alimentary pastes. A factorial experiment in completely randomized design was employed to study the effect of extrusion variables: feed moisture (30, 40, 50 %), extruder temperature (40, 70, 100oC) built up by varying the duration of sampling and screw speed (100, 150, 200 rpm) on Product temperature. A maximum temperature of 150oC was attained in 30 minutes through viscous dissipation and up to a moisture loss of 55% w.b. Also, product temperature is strongly related to the starch type and the extrusion process parameters under study. Product temperature decreased with increasing moisture content. The highest values of product temperature were demonstrated by maize starch and cassava flour extrudates while the lowest values were observed on maize flour and wheat flour extrudates. Generally, it was easier for cassava to cook/gelatinize under the heat provided by the extruder. Maize starch requires more shear/cooking to form than cassava starch. This extruder is by far more cost efficient for cassava than other products i.e. Maize and wheat. Process Parameters were expected to have effects on the product temperature of the final extrudates. Thus, model-fitting using response surface methodology was performed to examine their effect on product temperature. Quadratic coefficients fit the extrusion data very well, better than linear models. Furthermore, additional research could optimize product temperature for a specific product application. The equations relating the various dependent and independent variables were established to predict the performance of the machine.
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