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This study carried out the performance and optimization evaluation of single barrel cassava grating machine on selected fresh and stored cassava species. Three cassava species were sourced from Michael Okpara University of Agriculture Umudike, Nigeria, namely UMUCASS 36, UMUCASS 37, UMUCASS 38. This species were used at different levels of moisture content, 74.4%db and 61.4%db depicting the average moisture contents obtained for fresh and stored cassava, respectively. The experimental design employed was a twolevel-two factor full factorial central composite response design, including 13 experimental runs each for dry and stored samples. The experimental design was carried out using Design Expert Software version 7.0.7.1 to determine the optimum operating conditions. The software was used to determine the levels of factors which gave optimum performance efficiency by obtaining a quadratic models for both dry and stored cassava. The correlation between the experimental and predicted performance efficiency was checked through a plot of experimental and predicted results and the data points were closely distributed along a diagonal line indicating good agreement. Hence, the generated models have sufficient accuracy to predict the machine performance. The machine performance was optimized to obtain optimal conditions for the grater. The analysis of the performance of the grating machine predicted optimum operating condition as follows: 6mm abrasive surface hole sizes for both fresh and stored cassava, feed rate of 11.5kg/min and 11.6kg/min for fresh and stored samples respectively, measured efficiency of 96.2% and 98.0% for fresh and stored samples and predicted efficiency of 96.6 and 98.6 for fresh and stored cassava samples, respectively. These results prove that the grating machines perform better with stored samples with less moisture content.

Performance Evaluation and Optimization of Single Barrel Cassava Grating Machine on Selected Fresh and Stored Cassava Species