Biotechnology and Bioprocess Engineering:BBE

The Korean Society for Biotechnology and Bioengineering (한국생물공학회)
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Application of Principal Component Analysis and Self-organizing Map to the Analysis of 2D Fluorescence Spectra and the Monitoring of Fermentation Processes

  • Rhee, Jong-Il (School of Applied Chemical Engineering, Chonnam National University) ;
  • Kang, Tae-Hyoung (Department of Industrial Engineering, Chonnam National University) ;
  • Lee, Kum-Il (Department of Industrial Engineering, Chonnam National University) ;
  • Sohn, Ok-Jae (Laboratory of BioProcess Technology, Chonnam National University) ;
  • Kim, Sun-Yong (Laboratory of BioProcess Technology, Chonnam National University) ;
  • Chung, Sang-Wook (Department of Industrial Engineering, Chonnam National University)
  • Published : 2006.10.30
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Abstract

2D fluorescence sensors produce a great deal of spectral data during fermentation processes, which can be analyzed using a variety of statistical techniques. Principal component analysis (PCA) and a self-organizing map (SOM) were used to analyze these 2D fluorescence spectra and to extract useful information from them. PCA resulted in scores and loadings that were visualized in the score-loading plots and used to monitor various fermentation processes with recombinant Escherichia coli and Saccharomyces cerevisiae. The SOM was found to be a useful and interpretative method of classifying the entire gamut of 2D fluorescence spectra and of selecting some significant combinations of excitation and emission wavelengths. The results, including the normalized weights and variances, indicated that the SOM network is capable of being used to interpret the fermentation processes monitored by a 2D fluorescence sensor.

Keywords

References

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