Software Sensor to Enhance Production of Fructose

Norliza Abd. Rahman, Mohd. Azlan Hussain, Jamaliah Md. Jahim, Siti Rozaimah Sheikh Abdullah

Abstract


Present studies describe the on-line prediction of fructose concentration by using Artificial Neural Network (ANN) that employed as software sensor in the batch reactor for the biosynthesis of fructose by Immobilised Glucose Isomerase (IGI) of S.murinus. The process of fermentation was carried out in a 2-L batch bioreactor (New Brunswick Scientific, USA) with a working volume of 1.5 L reactor. All of the parameters were automatically controlled with the help of attached software. The optimum pH and temperature, for the production of fructose by Immmobilised Glucose Isomerase (IGI) of S.murinus were found to be 8 and 60 oC, respectively. Accuracy of the proposed soft sensor was calculated by the correlation coefficient (R2) and mean square error (MSE). In this study, value R2 were greater than 0.95 and the values of MSE were less than 0.2, indicating a good fit of the ANN-soft sensor to the experimental data, accurate up to 95.7% for training and 100% for testing. Thus, the proposed ANN-soft sensor was the most precise in predicting fructose concentration.

Full Text: PDF DOI: 10.5539/mas.v8n3p158

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Modern Applied Science   ISSN 1913-1844 (Print)   ISSN 1913-1852 (Online)

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