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...
- 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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| 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 |
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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 |
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info:eu-repo/semantics/openAccess |
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http://purl.org/coar/access_right/c_abf2 |
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Derechos reservados - Está prohibida la reproducción parcial o total de esta publicación http://purl.org/coar/access_right/c_abf2 |
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openAccess |
| dc.format.extent.spa.fl_str_mv |
10 páginas |
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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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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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