Modelling of the kinetics of red tilapia (Oreochromis spp.) viscera enzymatic hydrolysis using mathematical and neural network models

ABSTRACT: The present work modelled the enzymatic hydrolysis of red tilapia (Oreochromis spp.) viscera with Alcalase® 2.4 L in both 0.5 and 5 L reactors. The best conditions for the enzymatic hydrolysis were 60°C and pH 10. The product inhibited the enzymatic hydrolysis, and the enzyme deactivated f...

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Autores:
Álvarez Montoya, Andrés Camilo
Sepúlveda Rincón, Cindy Tatiana
Zapata Montoya, José Edgar
Tipo de recurso:
Article of investigation
Fecha de publicación:
2022
Institución:
Universidad de Antioquia
Repositorio:
Repositorio UdeA
Idioma:
eng
OAI Identifier:
oai:bibliotecadigital.udea.edu.co:10495/39527
Acceso en línea:
https://hdl.handle.net/10495/39527
Palabra clave:
Redes Neurales de la Computación
Neural Networks, Computer
Cinética
Kinetics
Tilapia
Hidrólisis enzimática
Enzymatic hydrolysis
Oreochromis
http://aims.fao.org/aos/agrovoc/c_27512
http://aims.fao.org/aos/agrovoc/c_26596
https://id.nlm.nih.gov/mesh/D016571
https://id.nlm.nih.gov/mesh/D007700
https://id.nlm.nih.gov/mesh/D017210
Rights
openAccess
License
Derechos reservados - Está prohibida la reproducción parcial o total de esta publicación
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oai_identifier_str oai:bibliotecadigital.udea.edu.co:10495/39527
network_acronym_str UDEA2
network_name_str Repositorio UdeA
repository_id_str
dc.title.spa.fl_str_mv Modelling of the kinetics of red tilapia (Oreochromis spp.) viscera enzymatic hydrolysis using mathematical and neural network models
title Modelling of the kinetics of red tilapia (Oreochromis spp.) viscera enzymatic hydrolysis using mathematical and neural network models
spellingShingle Modelling of the kinetics of red tilapia (Oreochromis spp.) viscera enzymatic hydrolysis using mathematical and neural network models
Redes Neurales de la Computación
Neural Networks, Computer
Cinética
Kinetics
Tilapia
Hidrólisis enzimática
Enzymatic hydrolysis
Oreochromis
http://aims.fao.org/aos/agrovoc/c_27512
http://aims.fao.org/aos/agrovoc/c_26596
https://id.nlm.nih.gov/mesh/D016571
https://id.nlm.nih.gov/mesh/D007700
https://id.nlm.nih.gov/mesh/D017210
title_short Modelling of the kinetics of red tilapia (Oreochromis spp.) viscera enzymatic hydrolysis using mathematical and neural network models
title_full Modelling of the kinetics of red tilapia (Oreochromis spp.) viscera enzymatic hydrolysis using mathematical and neural network models
title_fullStr Modelling of the kinetics of red tilapia (Oreochromis spp.) viscera enzymatic hydrolysis using mathematical and neural network models
title_full_unstemmed Modelling of the kinetics of red tilapia (Oreochromis spp.) viscera enzymatic hydrolysis using mathematical and neural network models
title_sort Modelling of the kinetics of red tilapia (Oreochromis spp.) viscera enzymatic hydrolysis using mathematical and neural network models
dc.creator.fl_str_mv Álvarez Montoya, Andrés Camilo
Sepúlveda Rincón, Cindy Tatiana
Zapata Montoya, José Edgar
dc.contributor.author.none.fl_str_mv Álvarez Montoya, Andrés Camilo
Sepúlveda Rincón, Cindy Tatiana
Zapata Montoya, José Edgar
dc.contributor.researchgroup.spa.fl_str_mv Grupo de Nutrición y Tecnología de Alimentos
dc.subject.decs.none.fl_str_mv Redes Neurales de la Computación
Neural Networks, Computer
Cinética
Kinetics
Tilapia
topic Redes Neurales de la Computación
Neural Networks, Computer
Cinética
Kinetics
Tilapia
Hidrólisis enzimática
Enzymatic hydrolysis
Oreochromis
http://aims.fao.org/aos/agrovoc/c_27512
http://aims.fao.org/aos/agrovoc/c_26596
https://id.nlm.nih.gov/mesh/D016571
https://id.nlm.nih.gov/mesh/D007700
https://id.nlm.nih.gov/mesh/D017210
dc.subject.agrovoc.none.fl_str_mv Hidrólisis enzimática
Enzymatic hydrolysis
Oreochromis
dc.subject.agrovocuri.none.fl_str_mv http://aims.fao.org/aos/agrovoc/c_27512
http://aims.fao.org/aos/agrovoc/c_26596
dc.subject.meshuri.none.fl_str_mv https://id.nlm.nih.gov/mesh/D016571
https://id.nlm.nih.gov/mesh/D007700
https://id.nlm.nih.gov/mesh/D017210
description ABSTRACT: The present work modelled the enzymatic hydrolysis of red tilapia (Oreochromis spp.) viscera with Alcalase® 2.4 L in both 0.5 and 5 L reactors. The best conditions for the enzymatic hydrolysis were 60°C and pH 10. The product inhibited the enzymatic hydrolysis, and the enzyme deactivated following second-order reaction. KM and Kp from a secondary plot of KM app as a function of inhibitor concentration, and k2, p, and k3 were found by non-linear regression. While the obtained parameters modelled the 0.5 L reactor well, it did not model the 5 L reactor, probably because of unconsidered fluid dynamics in the model. To have a better modelling, a neural network (tensorflow.keras.models module) was built and trained. The neural network modelled the enzymatic hydrolysis of red tilapia at several concentrations of substrate and enzyme. This result proved that neural networks are a powerful tool for modelling biological processes.
publishDate 2022
dc.date.issued.none.fl_str_mv 2022
dc.date.accessioned.none.fl_str_mv 2024-06-01T18:33:41Z
dc.date.available.none.fl_str_mv 2024-06-01T18:33:41Z
dc.type.spa.fl_str_mv Artículo de investigación
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.redcol.spa.fl_str_mv https://purl.org/redcol/resource_type/ART
dc.type.coarversion.spa.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/article
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/publishedVersion
format http://purl.org/coar/resource_type/c_2df8fbb1
status_str publishedVersion
dc.identifier.issn.none.fl_str_mv 1985-4668
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/10495/39527
dc.identifier.doi.none.fl_str_mv 10.47836/ifrj.29.6.16
dc.identifier.eissn.none.fl_str_mv 2231-7546
identifier_str_mv 1985-4668
10.47836/ifrj.29.6.16
2231-7546
url https://hdl.handle.net/10495/39527
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.ispartofjournalabbrev.spa.fl_str_mv Int. Food. Res. J.
dc.relation.citationendpage.spa.fl_str_mv 1410
dc.relation.citationissue.spa.fl_str_mv 6
dc.relation.citationstartpage.spa.fl_str_mv 1401
dc.relation.citationvolume.spa.fl_str_mv 29
dc.relation.ispartofjournal.spa.fl_str_mv International Food Research Journal
dc.rights.uri.spa.fl_str_mv Derechos reservados - Está prohibida la reproducción parcial o total de esta publicación
dc.rights.accessrights.spa.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.coar.spa.fl_str_mv http://purl.org/coar/access_right/c_abf2
rights_invalid_str_mv Derechos reservados - Está prohibida la reproducción parcial o total de esta publicación
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.extent.spa.fl_str_mv 10 páginas
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Universiti Putra , Faculty of Food Science and Technology
dc.publisher.place.spa.fl_str_mv Seri Kembangan, Malasia
institution Universidad de Antioquia
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spelling Álvarez Montoya, Andrés CamiloSepúlveda Rincón, Cindy TatianaZapata Montoya, José EdgarGrupo de Nutrición y Tecnología de Alimentos2024-06-01T18:33:41Z2024-06-01T18:33:41Z20221985-4668https://hdl.handle.net/10495/3952710.47836/ifrj.29.6.162231-7546ABSTRACT: The present work modelled the enzymatic hydrolysis of red tilapia (Oreochromis spp.) viscera with Alcalase® 2.4 L in both 0.5 and 5 L reactors. The best conditions for the enzymatic hydrolysis were 60°C and pH 10. The product inhibited the enzymatic hydrolysis, and the enzyme deactivated following second-order reaction. KM and Kp from a secondary plot of KM app as a function of inhibitor concentration, and k2, p, and k3 were found by non-linear regression. While the obtained parameters modelled the 0.5 L reactor well, it did not model the 5 L reactor, probably because of unconsidered fluid dynamics in the model. To have a better modelling, a neural network (tensorflow.keras.models module) was built and trained. The neural network modelled the enzymatic hydrolysis of red tilapia at several concentrations of substrate and enzyme. This result proved that neural networks are a powerful tool for modelling biological processes.Universidad de Antioquia. Vicerrectoría de investigación. Comité para el Desarrollo de la Investigación - CODIColombia. Ministerio de Ciencia, Tecnología e Innovación - MinicienciasCOL001077110 páginasapplication/pdfengUniversiti Putra , Faculty of Food Science and TechnologySeri Kembangan, MalasiaDerechos reservados - Está prohibida la reproducción parcial o total de esta publicacióninfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Modelling of the kinetics of red tilapia (Oreochromis spp.) viscera enzymatic hydrolysis using mathematical and neural network modelsArtículo de investigaciónhttp://purl.org/coar/resource_type/c_2df8fbb1https://purl.org/redcol/resource_type/ARThttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionRedes Neurales de la ComputaciónNeural Networks, ComputerCinéticaKineticsTilapiaHidrólisis enzimáticaEnzymatic hydrolysisOreochromishttp://aims.fao.org/aos/agrovoc/c_27512http://aims.fao.org/aos/agrovoc/c_26596https://id.nlm.nih.gov/mesh/D016571https://id.nlm.nih.gov/mesh/D007700https://id.nlm.nih.gov/mesh/D017210Int. 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