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An improved method for two-dimensional fluorescence monitoring of complex bioreactors

Paper ID Volume ID Publish Year Pages File Format Full-Text
25321 43567 2007 12 PDF Available
Title
An improved method for two-dimensional fluorescence monitoring of complex bioreactors
Abstract

An improved method for deconvoluting complex spectral maps from bidimensional fluorescence monitoring is presented, relying on a combination of principal component analysis (PCA) and feedforward artificial neural networks (ANN). With the aim of reducing ANN complexity, spectral maps are first subjected to PCA, and the scores of the retained principal components are subsequently used as ANN input vector. The method is presented using the case study of an extractive membrane biofilm reactor, where fluorescence maps of a membrane-attached biofilm were analysed, which were collected under different reactor operating conditions. During ANN training, the spectral information is associated with process performance indicators. Originally, 231 excitation/emission pairs per fluorescence map were used as ANN input vector. Using PCA, each fluorescence map could be represented by a maximum of six principal components, thereby catching 99.5% of its variance. As a result, the dimension of the ANN input vector and hence the complexity of the artificial neural network was significantly reduced, and ANN training speed was increased. Correlations between principal components and ANN predicted process performance parameters were good with correlation coefficients in the order of 0.7 or higher.

Keywords
Two-dimensional scanning fluorometry; Principal components analysis; Artificial neural networks; Spectra deconvolution; Extractive membrane bioreactor; Biofilm
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An improved method for two-dimensional fluorescence monitoring of complex bioreactors
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Publisher
Database: Elsevier - ScienceDirect
Journal: Journal of Biotechnology - Volume 128, Issue 4, 10 March 2007, Pages 801–812
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us