SOURCE:

Faculty: Engineering
Department: Chemical Engineering

CONTRIBUTORS:

Onu, C. E.
Igbokwe, P. K.

ABSTRACT:

Kinetic modeling, drying characteristics and optimization of the drying of potato and cocoyam was studied. Four different drying methods were employed: open sun drying, solar cabinet drying (solar drying), oven drying and hot-air conventional drying. The dried products were compared with the undried products using proximate analysis. Scanning electron microscopy (SEM) was used to examine the surface morphology while the Fourier Transform Infra-Red (FTIR) was used to determine the functional groups. The effect of drying air speed, temperature and slice thickness on the drying of cocoyam and potato was investigated. The thermal properties such as thermal conductivity, specific heat capacity and thermal diffusivity were determined. The water activity was determined and used to calculate the estimated mold free shelf life (MFSL) which revealed that the dried products have an MFSL of more than 600 days. The effective moisture diffusivity ranged from 5.40 x 10-11 m2/s to 7.295 x 10-10 m2/s. The activation energy ranged from 28.1KJ/mol to 37.363 KJ/mol for cocoyam drying and 32.449KJ/mol to 41.71 KJ/mol for potato drying. Thermal conductivity, specific heat capacity and thermal diffusivity were determined as 0.282 W/mK, 1.981 KJ/kg and 1.21 x 10-4 m2/s respectively for potato and 0.291 W/mK, 2.007 KJ/kg and 1.04 x 10-4 m2/s respectively for cocoyam. The maximum total energy consumption and specific energy consumption were 65.665 KWh and 288.37 KWh/kg respectively for potato and 67.295 KW/h and 257.39 KWh/kg respectively for cocoyam . The convective heat transfer coefficient ranged from 2.83 Wm-2C-1 to 13.68 Wm-2C-1. The maximum system drying efficiency was 67.01% and 54.64% for potato and cocoyam drying respectively. Among the drying kinetic models employed, the Logarithmic model, the Modified Page I model, the Approximation of Diffusion model and the Two Term model best fitted the drying data. The drying process was optimized using Response Surface Methodology with a star-like point of 1.316. Lack-of-fit test was used to evaluate the adequacy of the models. The quadratic model best fitted the optimization process. The validation of the optimum condition revealed close agreement between the predicted value and the experimental value. A two-layer feed forward artificial neural network was used to fit the multi-dimensional mapping and the network was trained with Levenberg-Marquardt back propagation. Response surface methodology and the artificial neural network were adequate in modeling the drying of potato and cocoyam. The photovoltaic dryer was the best dryer with regards to the drying time and the quality of the dried products. The sensory evaluation shows that the most preferable flour is the one milled from the photovoltaic dried cocoyam. The engineering properties determined in this work will be useful in designing industrial dryers and equally as a useful addition to the data storage bank of research institutes and the government.