Multichannal biosensor to detect the content of glucose, methanol and ethanol in mixtures
2008
Arlyapov, V.A. | Ponomareva, O.N. | Alferov, V.A., Tula State Univ.
An automatic multichannel biosensor setup on the basis of immobilized microorganisms Ghiconobacter oxydans and Pichia angusta for selective detection of glucose, methanol and ethanol in mixture has been developed. The use of artificial neural networks technology in the experimental data processing allowed to make the selective analysis of each component in the range of concentrations from 1,00 micro mole to 5,00 micro mole. Analysis of model mixtures and desert wines was carried out. It was shown that a relative error in the measurement of compound concentrations using neural networks was within the range of 2% to 33% at the optimal network configuration. Thus, the method is not acceptable for finished products at their sertification can be effectively used to monitoring of biotechnological processes in alcohol production industry
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