Drying characteristics of thermally pre-treated Cobra 26 F1 tomato slabs and applicability of Gaussian process regression-based models for the prediction of experimental kinetic data

Abstract

The drying characteristics of unblanched (UB), steam blanched (SB) and hot water blanched (WB) Cobra 26 F1 tomatoes were investigated at drying temperature of 40, 50, 60 and 70 °C and constant air velocity of 1.2 m/s in a convective oven. Gaussian process regression (GPR)-based models defined with squared-exponential kernel (GPR-SE), rational quadratic kernel (GPR-RQ), Matérn 5/2 kernel (GPR-M 5/2) and exponential kernel (GPR-Ex) were employed to model and predict experimental kinetic data of UB, SB and WB samples. Blanching and increased drying temperature reduced the drying time. The effective moisture diffusivity, activation energy, total and specific energy requirement for UB, SB and WB ranged between 3.6466 E-10-2.5526 E-09m²/s, 27.86`-43.65 kJ/mol, 7.08`-18.33 kW-h and 1,069.12`-2,768.80 kW-h/kg, respectively. Increased drying temperature and pre-treatment reduced activation energy, total and specific energy requirements of Cobra 26 F1 tomatoes. Investigated GPR-based models were suitable for modelling and prediction of experimental kinetic data of Cobra 26 F1 tomatoes, GPR-M 5/2 was, however, marginally better. Hence, GPR-based models showed high suitability in handling multi-dimensional drying variables and can be used for developing robust controllers applicable in auto-monitoring and control of Cobra 26 F1 tomatoes industrial drying.