Cole–Cole, linear and multivariate modeling of capacitance data for on-line monitoring of biomass

Michal Dabros, Danielle Dennewald, David J. Currie, Mark H. Lee, Robert W. Todd, Ian W. Marison, Urs von Stockar

Research output: Contribution to journalArticlepeer-review

55 Citations (SciVal)

Abstract

This work evaluates three techniques of calibrating capacitance (dielectric) spectrometers used for on-line monitoring of biomass: modeling of cell properties using the theoretical Cole–Cole equation, linear regression of dual-frequency capacitance measurements on biomass concentration, and multivariate (PLS) modeling of scanning dielectric spectra. The performance and robustness of each technique is assessed during a sequence of validation batches in two experimental settings of differing signal noise. In more noisy conditions, the Cole–Cole model had significantly higher biomass concentration prediction errors than the linear and multivariate models. The PLS model was the most robust in handling signal noise. In less noisy conditions, the three models performed similarly. Estimates of the mean cell size were done additionally using the Cole–Cole and PLS models, the latter technique giving more satisfactory results.
Original languageEnglish
Pages (from-to)161-173
JournalBioprocess and Biosystems Engineering
Volume32
Issue number2
Early online date11 Jun 2008
DOIs
Publication statusPublished - 01 Feb 2009

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