Raymond Alex Ekemube1, Nnanna Chima Ajanwachuku2 and Adekunle Temidayo Atta3
1Department of Agricultural Engineering, Faculty of Engineering, University of Benin, Benin City, Nigeria
2Department of Postharvest Engineering Research, Nigerian Stored Product Research Institute, Port Harcourt Zonal Office, Nigeria
3Kenaf and Jute Improvement Program, Institute of Agricultural Research and Training, Obafemi Awolowo University, Moor Plantation, Ibadan, Nigeria
DOI: https://doi.org/10.63749/agrimech.5.1.1003s
ABSTRACT
The aim of this study was to optimize the sifting capacity of an enhanced dewatered cassava mash sifting machine through experiment design and application. The goal is to determine the best performance indicators between the response variable (sifting capacity) and the operational variables (cassava mash mass and operating time). General full factorial design (GFFD) is used in experiment design to accomplish this. Nine treatments with three replicates were included in the design, for a total of twenty-seven treatments. The mass of cassava mash, operating time, and sifting capacity were among the experimental test parameters that were established. The experiment was carried out at the Nigerian Stored Product Research Institute’s postharvest engineering research department, located in the Port Harcourt Zonal Office in
Nigeria. Statistical analyses, including analysis of variance (ANOVA), main and interaction effects, multiple linear regression model, and response optimization using MINITAB 21 software were used. Also, the validity of the model was checked using standard error (SE), coefficient of determination (r2), Adjusted r2, and prediction r2. The results revealed that the application of cassava mash mass and time of operation have the highest scapacity at 90 kg and 0.6 hr using the machine. According to ANOVA, sifting capacity was significantly impacted (P<0.05) by cassava mash mass and time of operation. The sifting capacity multiple regression model was created with coefficients determined in the models. The models’ above 95% prediction accuracy was substantiated. At a cassava mash mass of 90 kg and a time of operation of 0.6 hr, the optimal sifting capacity during sifting was attained.
Keywords: Cassava mash, general full factorial design, optimization, sifting machine, sifting capacity