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Two‐dimensional fluorometry coupled with artificial neural networks: A novel method for on‐line monitoring of complex biological processes
Author(s) -
Wolf Gundula,
Almeida Jonas S.,
Pinheiro Carmen,
Correia Vasco,
Rodrigues Carla,
Reis Maria A. M.,
Crespo João G.
Publication year - 2000
Publication title -
biotechnology and bioengineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 189
eISSN - 1097-0290
pISSN - 0006-3592
DOI - 10.1002/1097-0290(20010205)72:3<297::aid-bit6>3.0.co;2-b
Subject(s) - bioreactor , biological system , artificial neural network , fluorescence spectroscopy , fluorescence , nonlinear system , fingerprint (computing) , fluorescence spectrometry , chromatography , chemistry , computer science , artificial intelligence , organic chemistry , biology , physics , optics , quantum mechanics
The use of two‐dimensional scanning fluorometry as an on‐line, noninvasive, in situ bioreactor monitoring technique is extended to complex bioprocesses using mixed cultures, with particular attention to biofilm systems. Using the example of spectra subtraction, it is demonstrated that established methods for fluorescence data analysis have a limited capability of utilizing overall fluorometric information. Artificial neural networks (ANNs) are introduced as a novel nonlinear and nonmechanistic technique for interpreting the highly complex fluorescence maps. It is shown that ANNs are able to infer process performance parameters in a pattern recognition approach, based on the entire fluorescence “fingerprint” of the biological system. The studies were carried out using an extractive membrane bioreactor (EMB) for the degradation of chlorinated organic compounds, operating with mixed cultures. Model pollutants em‐ ployed were 1,2‐dichloroethane, 3‐chloro‐4‐methylaniline, and p ‐toluidine. © 2001 John Wiley & Sons, Inc. Biotechnol Bioeng 72: 297–306, 2001.