Modeling and Optimization of the Hot Compressed Water Extraction of Palm Oil Using Artificial Neural Network

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  • Md Sarip Mohd Sharizan
    Shizen Conversion and Separation Technology (SHiZEN), iKohza, 
Universiti Teknologi Malaysia Malaysia Japan International Institute of Technology, 
Universiti Teknologi Malaysia
  • Yamashita Yoshiyuki
    Department of Chemical Engineering, 
Tokyo University of Agriculture and Technology
  • Morad Noor Azian
    Shizen Conversion and Separation Technology (SHiZEN), iKohza, 
Universiti Teknologi Malaysia Malaysia Japan International Institute of Technology, 
Universiti Teknologi Malaysia
  • Che Yunus Mohd Azizi
    Centre of Lipid Engineering Applied Research, Faculty of Chemical Engineering, 
Universiti Teknologi Malaysia
  • Abdul Aziz Mustafa Kamal
    Department of Chemical & Environmental Engineering, 
University of Nottingham Malaysia

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Abstract

<p>Hot compressed water extraction (HCWE) is a promising green alternative to the screw press in the palm oil processing. In this study, the steady-state characteristic of the HCWE was modeled by using an artificial neural network (ANN). The overall oil yield and other outputs; β-carotene, α-tocopherol and α-tocotrienol concentration, were described by the pressure and temperature in the HCWE. The results show that the predicted yield and concentrations agree well with experimental data. These models were used to estimate the optimum conditions of the HCWE process.</p>

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