Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Principal-component analysis for microbial L-phenylalanine production


Based on experimental results of eight fed-batch fermentations using a recombinant L-phenylalanine-producing Escherichia coli strain, the applicability of principal-component analysis (PCA) for fermentation analysis was studied. Three principal components were identified, representing approximately 90% of total variance. Among them, concentrations of tyrosine and acetate were identified as key fermentation parameters. Their significance was also confirmed when measurement errors were taken into consideration by Monte-Carlo estimations. The error estimation approach was also used to investigate PCA suitability for the time-specific analysis of different fermentation phases. Relatively large principal-component score errors were calculated that limit the applicability of PCA for detailed fermentation course analysis.

This is a preview of subscription content, log in to check access.

Author information

Additional information

Electronic Publication

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Takors, .R., Gerigk, .M., Paschold, .H. et al. Principal-component analysis for microbial L-phenylalanine production. Bioprocess Biosyst Eng 24, 93–99 (2001). https://doi.org/10.1007/s004490100232

Download citation


  • Escherichia Coli
  • Fermentation
  • Tyrosine
  • Error Estimation
  • Total Variance