Modelling of the kinetics of red tilapia (Oreochromis spp.) viscera enzymatic hydrolysis using mathematical and neural network models
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| Titel: | Modelling of the kinetics of red tilapia (Oreochromis spp.) viscera enzymatic hydrolysis using mathematical and neural network models |
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| Autoren: | Álvarez Montoya, Andrés Camilo, Sepúlveda Rincón, Cindy Tatiana, Zapata Montoya, José Edgar |
| Weitere Verfasser: | Grupo de Nutrición y Tecnología de Alimentos |
| Verlagsinformationen: | Universiti Putra , Faculty of Food Science and Technology Seri Kembangan, Malasia |
| Publikationsjahr: | 2022 |
| Bestand: | Universidad de Antioquia (UdeA): Biblioteca Digital |
| Schlagwörter: | 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 |
| Beschreibung: | 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 - CODI ; Colombia. Ministerio de Ciencia, Tecnología e Innovación - Miniciencias ; COL0010771 |
| Publikationsart: | article in journal/newspaper |
| Dateibeschreibung: | 10 páginas; application/pdf |
| Sprache: | English |
| Relation: | Int. Food. Res. J.; 1410; 1401; 29; International Food Research Journal; https://hdl.handle.net/10495/39527 |
| DOI: | 10.47836/ifrj.29.6.16 |
| Verfügbarkeit: | https://hdl.handle.net/10495/39527 https://doi.org/10.47836/ifrj.29.6.16 |
| Rights: | Derechos reservados - Está prohibida la reproducción parcial o total de esta publicación ; info:eu-repo/semantics/openAccess ; http://purl.org/coar/access_right/c_abf2 |
| Dokumentencode: | edsbas.A81CD0AF |
| Datenbank: | BASE |
Nájsť tento článok vo Web of Science | 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. ; Universidad de Antioquia. Vicerrectoría de investigación. Comité para el Desarrollo de la Investigación - CODI ; Colombia. Ministerio de Ciencia, Tecnología e Innovación - Miniciencias ; COL0010771 |
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| DOI: | 10.47836/ifrj.29.6.16 |