A mathematical model of intracellular behavior of microalgae for predicting growth and intracellular components syntheses under nutrient-replete and -deplete conditions

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dc.contributor.authorRyu, Kyung Hwanko
dc.contributor.authorSung, Min Gyuko
dc.contributor.authorKim, Boeunko
dc.contributor.authorHeo, Seongminko
dc.contributor.authorChang, Yong Keunko
dc.contributor.authorLee, Jay Hyungko
dc.date.accessioned2018-11-12T04:51:07Z-
dc.date.available2018-11-12T04:51:07Z-
dc.date.created2018-10-29-
dc.date.created2018-10-29-
dc.date.created2018-10-29-
dc.date.created2018-10-29-
dc.date.issued2018-10-
dc.identifier.citationBIOTECHNOLOGY AND BIOENGINEERING, v.115, no.10, pp.2441 - 2455-
dc.identifier.issn0006-3592-
dc.identifier.urihttp://hdl.handle.net/10203/246550-
dc.description.abstractMicroalgae is a promising biomass source for renewable fuels and chemicals production. To describe microalgal behavior and improve their cultivation, various kinetic models have been proposed. However, previous works have focused on biomass formation and lipids production only, even though carbohydrates and proteins are also important products, not only for understanding the metabolic behavior of microalgae but also for enhancing the economic viability through value-added side products. In this study, a new mathematical model is proposed to explain core biological mechanisms of growth and macromolecules syntheses based on the central metabolism of carbon and nitrogen. In the model, microalgal growth is separated as hyperplasia and hypertrophy, to describe the cell growth more precisely under nutrient-replete and -deplete conditions. Sensitivity analysis performed using the model indicates that cell state (e.g., cell death rate) has a strong effect on the lipid production explaining the difficulty of reproducing a microalgae culture experiment.-
dc.languageEnglish-
dc.publisherWILEY-
dc.titleA mathematical model of intracellular behavior of microalgae for predicting growth and intracellular components syntheses under nutrient-replete and -deplete conditions-
dc.typeArticle-
dc.identifier.wosid000447122900005-
dc.identifier.scopusid2-s2.0-85054764211-
dc.type.rimsART-
dc.citation.volume115-
dc.citation.issue10-
dc.citation.beginningpage2441-
dc.citation.endingpage2455-
dc.citation.publicationnameBIOTECHNOLOGY AND BIOENGINEERING-
dc.identifier.doi10.1002/bit.26744-
dc.contributor.localauthorHeo, Seongmin-
dc.contributor.localauthorChang, Yong Keun-
dc.contributor.localauthorLee, Jay Hyung-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorcell growth-
dc.subject.keywordAuthorlipids-
dc.subject.keywordAuthormacromolecules synthesis-
dc.subject.keywordAuthormathematical modeling-
dc.subject.keywordAuthormicroalgae-
dc.subject.keywordPlusFLUX BALANCE ANALYSIS-
dc.subject.keywordPlusCHLAMYDOMONAS-REINHARDTII-
dc.subject.keywordPlusCARBON METABOLISM-
dc.subject.keywordPlusBIODIESEL PRODUCTION-
dc.subject.keywordPlusBIOFUEL PRODUCTION-
dc.subject.keywordPlusGENETIC ALGORITHM-
dc.subject.keywordPlusGREEN-ALGAE-
dc.subject.keywordPlusNITROGEN-
dc.subject.keywordPlusCULTIVATION-
dc.subject.keywordPlusOPTIMIZATION-
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