Sensor Systems for Bioprocess Monitoring

Research output: ThesisDoctoral Thesis (compilation)

Abstract

Two different detection methods for on-line monitoring of substrates and products in ethanol fermentations have been studied. Amperometric biosensors were developed for use as detectors in flow injection or liquid chromatographic (LC) systems. Carbon paste was used as the electrode material and served as the supporting matrix to incorporate the enzymes alcohol oxidase or pyranose oxidase. Hydrogen peroxide produced in the enzymatic conversion of the substrates to these oxidases was further reduced by horseradish peroxidase (HRP) which was also incorporated into the carbon paste. Direct electron transfer between the electrode and the active site of HRP, measured within the optimal potential range for bioelectrochemical measurements (-50 mV vs. Ag/AgCl) resulted in sensitive and selective detection of ethanol and monosaccharides. The addition of various polyhydric alcohols and polyelectrolytes such as lactitol and polyethylenimine enhanced the performance of the electrodes regarding both sensitivity and stability. The amperometric biosensors were used in an on-line set-up in which microdialysis sampling, LC separation and simultaneous detection of both ethanol and monosaccharides were performed in ethanol fermentations.

The second approach was to analyse the off-gas from the bioreactor with an array of metal oxide semiconductor field effect transistors and semiconducting tin oxide sensors in combination with pattern recognition routines such as principal component analysis (PCA) and artificial neural networks (ANNs). PCA was used to extract important sensor parameters which were subsequently used in training an ANN with data sets obtained during several fermentations. Validation of the ANN on an independent data set indicated that state variables such as ethanol, acetaldehyde, acetic acid, glucose and biomass can be estimated.

Details

Authors
  • Helena Lidén
Organisations
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Analytical Chemistry

Keywords

  • on-line, pattern recognition, gas sensor array, electronic nose, monosaccharides, ethanol, biosensor, carbon paste electrode, Analytical chemistry, Analytisk kemi
Original languageEnglish
QualificationDoctor
Awarding Institution
Supervisors/Advisors
  • [unknown], [unknown], Supervisor, External person
Award date1998 May 20
Publisher
  • Analytical Chemistry, Lund University
StatePublished - 1998

Bibliographic note

Defence details Date: 1998-05-20 Time: 10:15 Place: Chemical Centre, Lecture hall B, Lund University External reviewer(s) Name: Kauffmann, Jean-Michel Title: Prof Affiliation: Free University of Brussels, Belgium --- The information about affiliations in this record was updated in December 2015. The record was previously connected to the following departments: Analytical Chemistry (S/LTH) (011001004)