Modification of the Luedeking and Piret model with a delay time parameter for biotechnological lactic acid production
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 Fermen...
Gespeichert in:
| Veröffentlicht in: | Biotechnology letters 2022-03, Vol.44 (3), p.415-427 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 427 |
|---|---|
| container_issue | 3 |
| container_start_page | 415 |
| container_title | Biotechnology letters |
| container_volume | 44 |
| creator | Groff, M. Carla Scaglia, Gustavo Ortiz, Oscar A. Noriega, Sandra E. |
| 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
2
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. |
| doi_str_mv | 10.1007/s10529-022-03227-0 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2623889733</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2623889733</sourcerecordid><originalsourceid>FETCH-LOGICAL-c375t-3de7ac0a8332460260b1d9c320855dfa0fd106b063ac402cb4528f589a251a023</originalsourceid><addsrcrecordid>eNp9kcFO3DAQhq2qFSyUF-ihstQLl7RjO46TY4VaQNoKDvRsOfZk1zSJt7YjxNvjZWmReuhpLM03_2_pI-QDg88MQH1JDCTvKuC8AsG5quANWTGpRNUo1bwlK2A1q2Td8WNyktI9AHQK1BE5FhI6LgWsyPIjOD94a7IPMw0DzVuk6wUd_vLzhprZ0VsfMdMpOBzpg89bamh5mkea_YR0Z6KZMGOkQ4i09yGj3c5hDJsSOtLR2OwtNdY7uovBLXZf9J68G8yY8OxlnpKf37_dXVxV65vL64uv68oKJXMlHCpjwbRC8LoB3kDPXGcFh1ZKNxgYHIOmh0YYWwO3fS15O8i2M1wyA1yckvNDbqn-vWDKevLJ4jiaGcOSNG-4aNtOCVHQT_-g92GJc_ldoeq2EaAkFIofKBtDShEHvYt-MvFRM9B7KfogRRcp-lmK3h99fIle-gnd35M_FgogDkAqq3mD8bX7P7FP5-mXCQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2648630750</pqid></control><display><type>article</type><title>Modification of the Luedeking and Piret model with a delay time parameter for biotechnological lactic acid production</title><source>MEDLINE</source><source>SpringerLink Journals - AutoHoldings</source><creator>Groff, M. Carla ; Scaglia, Gustavo ; Ortiz, Oscar A. ; Noriega, Sandra E.</creator><creatorcontrib>Groff, M. Carla ; Scaglia, Gustavo ; Ortiz, Oscar A. ; Noriega, Sandra E.</creatorcontrib><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
2
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.</description><identifier>ISSN: 0141-5492</identifier><identifier>EISSN: 1573-6776</identifier><identifier>DOI: 10.1007/s10529-022-03227-0</identifier><identifier>PMID: 35092530</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Acid production ; Applied Microbiology ; Biochemistry ; Biomass ; Biomedical and Life Sciences ; Biotechnology ; Delay time ; Fermentation ; Inoculum ; Kinetics ; Lactic Acid ; Lag time ; Life Sciences ; Mathematical models ; Microbiology ; Models, Biological ; Nutrients ; Original Research Paper ; Parameters ; Production methods ; Response time ; Time lag</subject><ispartof>Biotechnology letters, 2022-03, Vol.44 (3), p.415-427</ispartof><rights>The Author(s), under exclusive licence to Springer Nature B.V. 2022</rights><rights>2022. The Author(s), under exclusive licence to Springer Nature B.V.</rights><rights>The Author(s), under exclusive licence to Springer Nature B.V. 2022.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-3de7ac0a8332460260b1d9c320855dfa0fd106b063ac402cb4528f589a251a023</citedby><cites>FETCH-LOGICAL-c375t-3de7ac0a8332460260b1d9c320855dfa0fd106b063ac402cb4528f589a251a023</cites><orcidid>0000-0002-7133-1582</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10529-022-03227-0$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10529-022-03227-0$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35092530$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Groff, M. Carla</creatorcontrib><creatorcontrib>Scaglia, Gustavo</creatorcontrib><creatorcontrib>Ortiz, Oscar A.</creatorcontrib><creatorcontrib>Noriega, Sandra E.</creatorcontrib><title>Modification of the Luedeking and Piret model with a delay time parameter for biotechnological lactic acid production</title><title>Biotechnology letters</title><addtitle>Biotechnol Lett</addtitle><addtitle>Biotechnol Lett</addtitle><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
2
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.</description><subject>Acid production</subject><subject>Applied Microbiology</subject><subject>Biochemistry</subject><subject>Biomass</subject><subject>Biomedical and Life Sciences</subject><subject>Biotechnology</subject><subject>Delay time</subject><subject>Fermentation</subject><subject>Inoculum</subject><subject>Kinetics</subject><subject>Lactic Acid</subject><subject>Lag time</subject><subject>Life Sciences</subject><subject>Mathematical models</subject><subject>Microbiology</subject><subject>Models, Biological</subject><subject>Nutrients</subject><subject>Original Research Paper</subject><subject>Parameters</subject><subject>Production methods</subject><subject>Response time</subject><subject>Time lag</subject><issn>0141-5492</issn><issn>1573-6776</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kcFO3DAQhq2qFSyUF-ihstQLl7RjO46TY4VaQNoKDvRsOfZk1zSJt7YjxNvjZWmReuhpLM03_2_pI-QDg88MQH1JDCTvKuC8AsG5quANWTGpRNUo1bwlK2A1q2Td8WNyktI9AHQK1BE5FhI6LgWsyPIjOD94a7IPMw0DzVuk6wUd_vLzhprZ0VsfMdMpOBzpg89bamh5mkea_YR0Z6KZMGOkQ4i09yGj3c5hDJsSOtLR2OwtNdY7uovBLXZf9J68G8yY8OxlnpKf37_dXVxV65vL64uv68oKJXMlHCpjwbRC8LoB3kDPXGcFh1ZKNxgYHIOmh0YYWwO3fS15O8i2M1wyA1yckvNDbqn-vWDKevLJ4jiaGcOSNG-4aNtOCVHQT_-g92GJc_ldoeq2EaAkFIofKBtDShEHvYt-MvFRM9B7KfogRRcp-lmK3h99fIle-gnd35M_FgogDkAqq3mD8bX7P7FP5-mXCQ</recordid><startdate>20220301</startdate><enddate>20220301</enddate><creator>Groff, M. Carla</creator><creator>Scaglia, Gustavo</creator><creator>Ortiz, Oscar A.</creator><creator>Noriega, Sandra E.</creator><general>Springer Netherlands</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QL</scope><scope>7QR</scope><scope>7T7</scope><scope>7TB</scope><scope>7U5</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>88I</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>L6V</scope><scope>L7M</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-7133-1582</orcidid></search><sort><creationdate>20220301</creationdate><title>Modification of the Luedeking and Piret model with a delay time parameter for biotechnological lactic acid production</title><author>Groff, M. Carla ; Scaglia, Gustavo ; Ortiz, Oscar A. ; Noriega, Sandra E.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c375t-3de7ac0a8332460260b1d9c320855dfa0fd106b063ac402cb4528f589a251a023</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Acid production</topic><topic>Applied Microbiology</topic><topic>Biochemistry</topic><topic>Biomass</topic><topic>Biomedical and Life Sciences</topic><topic>Biotechnology</topic><topic>Delay time</topic><topic>Fermentation</topic><topic>Inoculum</topic><topic>Kinetics</topic><topic>Lactic Acid</topic><topic>Lag time</topic><topic>Life Sciences</topic><topic>Mathematical models</topic><topic>Microbiology</topic><topic>Models, Biological</topic><topic>Nutrients</topic><topic>Original Research Paper</topic><topic>Parameters</topic><topic>Production methods</topic><topic>Response time</topic><topic>Time lag</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Groff, M. Carla</creatorcontrib><creatorcontrib>Scaglia, Gustavo</creatorcontrib><creatorcontrib>Ortiz, Oscar A.</creatorcontrib><creatorcontrib>Noriega, Sandra E.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Chemoreception Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Science Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><jtitle>Biotechnology letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Groff, M. Carla</au><au>Scaglia, Gustavo</au><au>Ortiz, Oscar A.</au><au>Noriega, Sandra E.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modification of the Luedeking and Piret model with a delay time parameter for biotechnological lactic acid production</atitle><jtitle>Biotechnology letters</jtitle><stitle>Biotechnol Lett</stitle><addtitle>Biotechnol Lett</addtitle><date>2022-03-01</date><risdate>2022</risdate><volume>44</volume><issue>3</issue><spage>415</spage><epage>427</epage><pages>415-427</pages><issn>0141-5492</issn><eissn>1573-6776</eissn><abstract>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
2
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.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><pmid>35092530</pmid><doi>10.1007/s10529-022-03227-0</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-7133-1582</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0141-5492 |
| ispartof | Biotechnology letters, 2022-03, Vol.44 (3), p.415-427 |
| issn | 0141-5492 1573-6776 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_2623889733 |
| source | MEDLINE; SpringerLink Journals - AutoHoldings |
| subjects | Acid production Applied Microbiology Biochemistry Biomass Biomedical and Life Sciences Biotechnology Delay time Fermentation Inoculum Kinetics Lactic Acid Lag time Life Sciences Mathematical models Microbiology Models, Biological Nutrients Original Research Paper Parameters Production methods Response time Time lag |
| title | Modification of the Luedeking and Piret model with a delay time parameter for biotechnological lactic acid production |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-07T23%3A09%3A01IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Modification%20of%20the%20Luedeking%20and%20Piret%20model%20with%20a%20delay%20time%20parameter%20for%20biotechnological%20lactic%20acid%20production&rft.jtitle=Biotechnology%20letters&rft.au=Groff,%20M.%20Carla&rft.date=2022-03-01&rft.volume=44&rft.issue=3&rft.spage=415&rft.epage=427&rft.pages=415-427&rft.issn=0141-5492&rft.eissn=1573-6776&rft_id=info:doi/10.1007/s10529-022-03227-0&rft_dat=%3Cproquest_cross%3E2623889733%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2648630750&rft_id=info:pmid/35092530&rfr_iscdi=true |