Learning from fluorescence

Detalhes bibliográficos
Autor(a) principal: Brandão, Pedro R.
Data de Publicação: 2023
Outros Autores: Sá, Marta, Galinha, Cláudia F.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/164174
Resumo: Funding Information: This project has received funding from the Bio Based Industries Joint Undertaking (JU) under grant agreement No. 512 887227 - MULTI-STR3AM. The JU receives support from the European Union's Horizon 2020 research and innovation programme and the Bio Based Industries Consortium. Publisher Copyright: © 2023
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spelling Learning from fluorescenceA tool for online multiparameter monitoring of a microalgae culture2D fluorescenceBioprocess monitoringExcitation-emission matrices (EEMs)Machine learningMicroalgae cultivationProjection to latent structures regression (PLSR)Chemical Engineering(all)Computer Science ApplicationsFunding Information: This project has received funding from the Bio Based Industries Joint Undertaking (JU) under grant agreement No. 512 887227 - MULTI-STR3AM. The JU receives support from the European Union's Horizon 2020 research and innovation programme and the Bio Based Industries Consortium. Publisher Copyright: © 2023We propose a systematic approach for monitoring important productivity parameters in a Dunaliella salina culture using 2D fluorescence data. For this purpose, a methodology based on Machine Learning algorithm Projection to Latent Structures Regression (PLSR) coupled with variable selection strategies was used. Additionally, a robustness analysis is proposed to support the validation of the yielded models and provide a measure of their reliability. Robust (i.e., Q2 ≥ 0.5) and parsimonious (i.e., selecting down to 3 % of the fluorescence variables present in a 250–700 nm wavelength excitation-emission matrix) models were obtained for monitoring cell count, chlorophyll b, total carotenoids and β-carotene culture concentration, and the ratio between total carotenoids and total chlorophylls, all of which were validated with a left-out batch performing with R2 higher than 0.7 except for β-carotene (R2 = 0.54).DQ - Departamento de QuímicaLAQV@REQUIMTERUNBrandão, Pedro R.Sá, MartaGalinha, Cláudia F.2024-02-26T23:55:42Z2023-112023-11-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article8application/pdfhttp://hdl.handle.net/10362/164174eng0098-1354PURE: 83890432https://doi.org/10.1016/j.compchemeng.2023.108452info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:51:01Zoai:run.unl.pt:10362/164174Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T04:00:04.103015Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Learning from fluorescence
A tool for online multiparameter monitoring of a microalgae culture
title Learning from fluorescence
spellingShingle Learning from fluorescence
Brandão, Pedro R.
2D fluorescence
Bioprocess monitoring
Excitation-emission matrices (EEMs)
Machine learning
Microalgae cultivation
Projection to latent structures regression (PLSR)
Chemical Engineering(all)
Computer Science Applications
title_short Learning from fluorescence
title_full Learning from fluorescence
title_fullStr Learning from fluorescence
title_full_unstemmed Learning from fluorescence
title_sort Learning from fluorescence
author Brandão, Pedro R.
author_facet Brandão, Pedro R.
Sá, Marta
Galinha, Cláudia F.
author_role author
author2 Sá, Marta
Galinha, Cláudia F.
author2_role author
author
dc.contributor.none.fl_str_mv DQ - Departamento de Química
LAQV@REQUIMTE
RUN
dc.contributor.author.fl_str_mv Brandão, Pedro R.
Sá, Marta
Galinha, Cláudia F.
dc.subject.por.fl_str_mv 2D fluorescence
Bioprocess monitoring
Excitation-emission matrices (EEMs)
Machine learning
Microalgae cultivation
Projection to latent structures regression (PLSR)
Chemical Engineering(all)
Computer Science Applications
topic 2D fluorescence
Bioprocess monitoring
Excitation-emission matrices (EEMs)
Machine learning
Microalgae cultivation
Projection to latent structures regression (PLSR)
Chemical Engineering(all)
Computer Science Applications
description Funding Information: This project has received funding from the Bio Based Industries Joint Undertaking (JU) under grant agreement No. 512 887227 - MULTI-STR3AM. The JU receives support from the European Union's Horizon 2020 research and innovation programme and the Bio Based Industries Consortium. Publisher Copyright: © 2023
publishDate 2023
dc.date.none.fl_str_mv 2023-11
2023-11-01T00:00:00Z
2024-02-26T23:55:42Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/164174
url http://hdl.handle.net/10362/164174
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0098-1354
PURE: 83890432
https://doi.org/10.1016/j.compchemeng.2023.108452
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 8
application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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