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Cited by 264

The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.

Investigation of bacterial growth on mixed substrates: Experimental evaluation of cybernetic models

Kompala, Dhinakar S., Ramkrishna, Doraiswami, Jansen, Norman B., Tsao, George T.·1986·Biotechnology and Bioengineering

Abstract

Cybernetic models, developed earlier by the authors, have been evaluated experimentally for the growth of Klebsiella oxytoca in batch cultures using mixed substrates from glucose, xylose, arabinose, lactose, and fructose. Based entirely on information procured from batch growth on single substrates, the models accurately predict without further parameter fitting, diauxic growth on mixed substrates, automatically predicting the order in which the substrates are consumed. Even triauxic growth on a mixture of glucose, xylose, and lactose is predicted by the model based on single substrate data. Growth on glucose‐fructose mixtures appears to need a slightly modified strategy for cybernetic variables.

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Metadata

Authors
Kompala, D. S., Ramkrishna, D., Jansen, N. B., & Tsao, G. T.
Venue
Biotechnology and Bioengineering
Publisher
Wiley
Published
1986-07
Volume
28
Issue
7
Pages
1044-1055
ISSN
  • 0006-3592 (ISSN-L)
  • 1097-0290
OpenAlex
W2152146387
Cited by
264
References
10
FWCI
2.21
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Investigation of bacterial growth on mixed substrates: Experimental evaluation of cybernetic models. https://app.cochat.ai/papers/10.1002/bit.260280715
The paper
Kompala, D. S., Ramkrishna, D., Jansen, N. B., & Tsao, G. T. (1986). Investigation of bacterial growth on mixed substrates: Experimental evaluation of cybernetic models. Biotechnology and Bioengineering. https://doi.org/10.1002/bit.260280715

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.