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

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

Research output: Contribution to journalArticlepeer-review

1 Citation (SciVal)

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.

Original languageEnglish
Pages (from-to)1135-1145
Number of pages11
JournalKorean Journal of Chemical Engineering
Volume39
Issue number5
Early online date8 Feb 2022
DOIs
Publication statusPublished - 31 May 2022

Bibliographical note

FUNDING
This work did not receive any funds either from public, commercial or not-for-profit grant agencies.

Keywords

  • Cobra 26 F1 Tomatoes
  • Gaussian Process Regression-based Models
  • Steam Blanched and Hot Water Blanched
  • Thermal Pre-treatment

ASJC Scopus subject areas

  • Chemistry(all)
  • Chemical Engineering(all)

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