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An Identifiable State Model To Describe Light Intensity Influence on Microalgae Growth

Despite the high potential as feedstock for the production of fuels and chemicals, the industrial cultivation of microalgae still exhibits many issues. Yield in microalgae cultivation systems is limited by the solar energy that can be harvested. The availability of reliable models representing key p...

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Autores principales: Bernardi, A., Perin, G., Sforza, E., Galvanin, F., Morosinotto, T., Bezzo, F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2014
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4311933/
https://www.ncbi.nlm.nih.gov/pubmed/25678739
http://dx.doi.org/10.1021/ie500523z
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author Bernardi, A.
Perin, G.
Sforza, E.
Galvanin, F.
Morosinotto, T.
Bezzo, F.
author_facet Bernardi, A.
Perin, G.
Sforza, E.
Galvanin, F.
Morosinotto, T.
Bezzo, F.
author_sort Bernardi, A.
collection PubMed
description Despite the high potential as feedstock for the production of fuels and chemicals, the industrial cultivation of microalgae still exhibits many issues. Yield in microalgae cultivation systems is limited by the solar energy that can be harvested. The availability of reliable models representing key phenomena affecting algae growth may help designing and optimizing effective production systems at an industrial level. In this work the complex influence of different light regimes on seawater alga Nannochloropsis salina growth is represented by first principles models. Experimental data such as in vivo fluorescence measurements are employed to develop the model. The proposed model allows description of all growth curves and fluorescence data in a reliable way. The model structure is assessed and modified in order to guarantee the model identifiability and the estimation of its parametric set in a robust and reliable way.
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spelling pubmed-43119332015-03-24 An Identifiable State Model To Describe Light Intensity Influence on Microalgae Growth Bernardi, A. Perin, G. Sforza, E. Galvanin, F. Morosinotto, T. Bezzo, F. Ind Eng Chem Res Despite the high potential as feedstock for the production of fuels and chemicals, the industrial cultivation of microalgae still exhibits many issues. Yield in microalgae cultivation systems is limited by the solar energy that can be harvested. The availability of reliable models representing key phenomena affecting algae growth may help designing and optimizing effective production systems at an industrial level. In this work the complex influence of different light regimes on seawater alga Nannochloropsis salina growth is represented by first principles models. Experimental data such as in vivo fluorescence measurements are employed to develop the model. The proposed model allows description of all growth curves and fluorescence data in a reliable way. The model structure is assessed and modified in order to guarantee the model identifiability and the estimation of its parametric set in a robust and reliable way. American Chemical Society 2014-03-24 2014-04-23 /pmc/articles/PMC4311933/ /pubmed/25678739 http://dx.doi.org/10.1021/ie500523z Text en Copyright © 2014 American Chemical Society Terms of Use (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html)
spellingShingle Bernardi, A.
Perin, G.
Sforza, E.
Galvanin, F.
Morosinotto, T.
Bezzo, F.
An Identifiable State Model To Describe Light Intensity Influence on Microalgae Growth
title An Identifiable State Model To Describe Light Intensity Influence on Microalgae Growth
title_full An Identifiable State Model To Describe Light Intensity Influence on Microalgae Growth
title_fullStr An Identifiable State Model To Describe Light Intensity Influence on Microalgae Growth
title_full_unstemmed An Identifiable State Model To Describe Light Intensity Influence on Microalgae Growth
title_short An Identifiable State Model To Describe Light Intensity Influence on Microalgae Growth
title_sort identifiable state model to describe light intensity influence on microalgae growth
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4311933/
https://www.ncbi.nlm.nih.gov/pubmed/25678739
http://dx.doi.org/10.1021/ie500523z
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