Optimization of Solar Drying of Blanched and Unblanched Aerial Yam using Response Surface Methodology

This paper focuses on the application of response surface methodology RSM for the modelling and optimization of unblanched and blanched aerial yam drying using solar dryer. Mass in gram of the sample, slice thickness of the sample, and the airspeed of dryer are the independent variables considered, while the response of interest is the moisture content. RSM via central composite design CCD was used to optimize the variables of interest, while artificial neural network was used to validate the result. The result showed that a second order polynomial regression model could convincingly interpret the drying process of the aerial yam. A coefficient of determination R2 value of 0.9991 and 0.9828, model F value of 1186.03 and 60.75 for unblanched and blanched aerial yam respectively were obtained. P value 0.0001 , and low value of coefficient of variation 2.43 and 9.75 for unblanched and blanched sample indicated the fitness of the model. The optimum process variable obtained were 71 g, 3.2 mm and 1.5 m s, and 70 g, 3.0 mm and 1.5 m s for blanched and unblanched sample, respectively. Emmanuel C. Nwadike. | Matthew N. Abonyi. | Joseph T. Nwabanne. | Pascal E. Ohale "Optimization of Solar Drying of Blanched and Unblanched Aerial Yam using Response Surface Methodology" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30598.pdf