Modification of the Luedeking and Piret model with a delay time parameter for biotechnological lactic acid production
Biotechnology Letters, ISSN: 1573-6776, Vol: 44, Issue: 3, Page: 415-427
2022
- 4Citations
- 10Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Objectives: To obtain a mathematical model that adequately describes the time lag between biomass generation and lactic acid production of lactic fermentations. Methods: Seven experimental kinetics from other research works were studied to validate our proposal: four studies of Fungal Submerged Fermentation and three cases of Bacterial Submerged Fermentation, including the data recollected by Luedeking and Piret. Results: We introduce a modification to the Luedeking and Piret model that consist in the introduction of a time delay parameter in the model, this parameter would account for the lag time that exists between the production of biomass and lactic acid. It is possible to determine this time delay in a simple way by approximating the biomass and product formation considering that they behave as a first order plus dead time system. The duration of this phenomenon, which is not described with the classical Luedeking and Piret model, is a function of microorganism physiology (ease of biomass growth), environment (nutrients) and type of inoculum. Conclusion: The Luedeking and Piret with delay model applications reveal an increase of the R in all cases, evidencing the quality of fit and the simplicity of the method proposed. These model would improve the accuracy of bioprocess scaling up.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85123864519&origin=inward; http://dx.doi.org/10.1007/s10529-022-03227-0; http://www.ncbi.nlm.nih.gov/pubmed/35092530; https://link.springer.com/10.1007/s10529-022-03227-0; https://dx.doi.org/10.1007/s10529-022-03227-0; https://link.springer.com/article/10.1007/s10529-022-03227-0
Springer Science and Business Media LLC
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