Convective drying of unripe plantain: a comparative response surface methodology and genetic algorithm optimization study, certainty and sensitivity analysis

Abstract

The requirement for reduction of post-harvest losses increased production, and cost-effectiveness of foods are driving continuous food process investigations. In this study, Response Surface Methodology (RSM) was utilized to understand, model, and optimize the effect of selected process factors on the moisture content (MC) of convectively dried unripe plantain fruit. For technical accuracies, Multi Gene Genetic Programming (MGGP) was also used to model the process and both MGGP and RSM models were statistically compared. Furthermore, Monte Carlo Simulation (MCS) was used to conduct sensitivity analysis of unripe plantain’s MC to each selected process factor. Results showed that increased sample thickness increased the MC while increased drying temperature and drying time decreased the MC of unripe plantain. RSM model had Chi-square, MBE, t-value, RMSE and R2 values of 15.2131, 0.7531, 7.6170, 0.9193 and 0.9674, respectively; while MGGP model had 3.0415, 0.2563, 2.6871, 0.4111 and 0.9956, respectively. Sensitivity analysis showed that sample thickness, drying temperature and drying time had +89.5 %, -10.2 % and -0.3 % contribution to the variances of MC, respectively. These results are useful in unripe plantain drying process prediction, optimization, and product standardization.