Prediction and optimization of the laccase-mediated synthesis of the antimicrobial compound iodine (I2)
M Schubert1, A Fey1, J Ihssen2
1Empa, Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Applied Wood Materials, Lerchenfeldstrasse 5, CH-9014 St. Gallen, Switzerland.
Abstract:
An artificial neural network (ANN) and genetic algorithm (GA) were applied to improve the laccase-mediated oxidation of iodide (I(-)) to elemental iodine (I2). Biosynthesis of iodine (I2) was studied with a 5-level-4-factor central composite design (CCD). The generated ANN network was mathematically evaluated by several statistical indices and revealed better results than a classical quadratic response surface (RS) model. Determination of the relative significance of model input parameters, ranking the process parameters in order of importance (pH>laccase>mediator>iodide), was performed by sensitivity analysis. ANN-GA methodology was used to optimize the input space of the neural network model to find optimal settings for the laccase-mediated synthesis of iodine. ANN-GA optimized parameters resulted in a 9.9% increase in the conversion rate.
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