This preprint is under consideration at Bioresources and Bioprocessing. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
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Research
Fantao Kong
Dalian University of Technology
Corresponding Author
ORCiD: https://orcid.org/0000-0003-2847-2838
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This work is licensed under a CC BY 4.0 License. Read Full License
Dunaliella salina is a green alga with the great potential to generate natural β-carotene. However, the corresponding mathematical models to guide optimized production of β-carotene in Dunaliella salina is not yet available. In this study, dynamic models were proposed to simulate effects of environmental factors on cell growth and β-carotene production in D. salina using online monitoring system. Moreover, the identification model of the parameter variables was established, and an adaptive particle swarm optimization algorithm based on parameter sensitivity analysis was constructed to solve the premature problem of particle swarm algorithm. The proposed kinetic model is characterized by high accuracy and predictability through experimental verification, which indicates its competence for future process design, control and optimization. Based on the model established in this study, the optimal environment factors for both β-carotene production and microalgae growth were identified. The approaches created are potentially useful for microalgae cultivation and high-value compounds production.
Keywords
Dunaliella salina, Dynamic kinetic modelling, Cultivation optimization, Environmental factors, β-carotene production
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CURRENT STATUS: Under Review
Version 1
Posted 03 Nov, 2021
No community comments so far
Reviewer #3 agreed
On 10 Nov, 2021
Reviews received
Received 02 Nov, 2021
Reviewer #2 agreed
On 01 Nov, 2021
Reviewer #1 agreed
On 01 Nov, 2021
Reviewers invited
Invitations sent on 01 Nov, 2021
Editor assigned
On 29 Oct, 2021
Submission checks complete
On 28 Oct, 2021
Editor invited
On 28 Oct, 2021
First submitted
On 25 Oct, 2021
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This preprint is under consideration at Bioresources and Bioprocessing. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
Fantao Kong
Dalian University of Technology
Corresponding Author
ORCiD: https://orcid.org/0000-0003-2847-2838
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 03 Nov, 2021
No community comments so far
Reviewer #3 agreed
On 10 Nov, 2021
Reviews received
Received 02 Nov, 2021
Reviewer #2 agreed
On 01 Nov, 2021
Reviewer #1 agreed
On 01 Nov, 2021
Reviewers invited
Invitations sent on 01 Nov, 2021
Editor assigned
On 29 Oct, 2021
Submission checks complete
On 28 Oct, 2021
Editor invited
On 28 Oct, 2021
First submitted
On 25 Oct, 2021
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Dunaliella salina is a green alga with the great potential to generate natural β-carotene. However, the corresponding mathematical models to guide optimized production of β-carotene in Dunaliella salina is not yet available. In this study, dynamic models were proposed to simulate effects of environmental factors on cell growth and β-carotene production in D. salina using online monitoring system. Moreover, the identification model of the parameter variables was established, and an adaptive particle swarm optimization algorithm based on parameter sensitivity analysis was constructed to solve the premature problem of particle swarm algorithm. The proposed kinetic model is characterized by high accuracy and predictability through experimental verification, which indicates its competence for future process design, control and optimization. Based on the model established in this study, the optimal environment factors for both β-carotene production and microalgae growth were identified. The approaches created are potentially useful for microalgae cultivation and high-value compounds production.
This preprint is available for download as a PDF.
This is a list of supplementary files associated with this preprint. Click to download.
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