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Oladayo Adeyi,Emmanuel Olusola Oke,Abiola John Adeyi,Bernard Iberzim Okolo,Abayomi Olusegun Olalere,John Adebayo Otolorin,Ayomide Adeola,Brown Dagogo,Akinola David Ogunsola,Sunday Oladunni 한국화학공학회 2022 Korean Journal of Chemical Engineering Vol.39 No.5
The drying characteristics of unblanched (UB), steam blanched (SB) and hot water blanched (WB) Cobra26 F1 tomatoes were investigated at drying temperature of 40, 50, 60 and 70 oC and constant air velocity of 1.2m/s in aconvective 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 employedto model and predict experimental kinetic data of UB, SB and WB samples. Blanching and increased drying temperaturereduced the drying time. The effective moisture diffusivity, activation energy, total and specific energy requirementfor UB, SB and WB ranged between 3.6466 E -10 - 2.5526 E -09m2/s, 27.86-43.65 kJ/mol, 7.08-18.33kW-h and1,069.12-2,768.80kW-h/kg, respectively. Increased drying temperature and pre-treatment reduced activation energy, totaland specific energy requirements of Cobra 26 F1 tomatoes. Investigated GPR-based models were suitable for modellingand 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 fordeveloping robust controllers applicable in auto-monitoring and control of Cobra 26 F1 tomatoes industrial drying.