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dc.contributor.authorTenesaca Castillo, Oscar Vinicio
dc.contributor.authorDelgado Noboa, Jorge Washington
dc.contributor.authorSerpa Nieves, Andrea Carolina
dc.contributor.authorMoreno Delgado, Juan Fernando
dc.contributor.authorBernal Cedillo, Tamara Michelle
dc.date.accessioned2025-01-28T14:19:24Z-
dc.date.available2025-01-28T14:19:24Z-
dc.date.issued2024
dc.identifier.issn1939-019X, e 1939-019X
dc.identifier.urihttps://dspace.ucuenca.edu.ec/handle/123456789/45784-
dc.identifier.urihttps://onlinelibrary.wiley.com/doi/10.1002/cjce.25504
dc.descriptionThis work deals with the optimization of bioethanol production through a fermentation process of CCN-51 cocoa mucilage, based on increased concentrations of the Saccharomyces cerevisiae yeast. Cocoa mucilage, considered biomass waste, was selected for its high productivity and the large volumes generated in the cocoa industrial chain in Ecuador. The optimization of the fermentation process was performed using the Sequential Simplex method with two variables, and the results were experimentally confirmed by quantifying bioethanol through the microdiffusion method. The best operational conditions corresponded to a temperature of 35°C and a pH of 4. Regarding the concentration of yeast, it was found that the optimal value was 8 g/L, since lower concentrations led to low productivities, while higher concentrations resulted in inadequate functioning of the bioreactor. The best results reached a productivity of 1.35 ± 0.04 g/L·h and a maximum bioethanol concentration of 28.3 ± 0.8 g/L for a processing time of 21 h. The production of bioethanol was modelled using the modified Gompertz equation and simulated in MATLAB®, yielding a bioethanol production rate of 2.42 g/L·h with a correlation coefficient (R2) of 0.95. These results contribute to the knowledge of bioethanol production using cocoa mucilage and seek to add a positive value to this residue, whose management and final disposition have both undesirable environmental and economic effects.
dc.description.abstractThis work deals with the optimization of bioethanol production through a fermentation process of CCN-51 cocoa mucilage, based on increased concentrations of the Saccharomyces cerevisiae yeast. Cocoa mucilage, considered biomass waste, was selected for its high productivity and the large volumes generated in the cocoa industrial chain in Ecuador. The optimization of the fermentation process was performed using the Sequential Simplex method with two variables, and the results were experimentally confirmed by quantifying bioethanol through the microdiffusion method. The best operational conditions corresponded to a temperature of 35°C and a pH of 4. Regarding the concentration of yeast, it was found that the optimal value was 8 g/L, since lower concentrations led to low productivities, while higher concentrations resulted in inadequate functioning of the bioreactor. The best results reached a productivity of 1.35 ± 0.04 g/L·h and a maximum bioethanol concentration of 28.3 ± 0.8 g/L for a processing time of 21 h. The production of bioethanol was modelled using the modified Gompertz equation and simulated in MATLAB®, yielding a bioethanol production rate of 2.42 g/L·h with a correlation coefficient (R2) of 0.95. These results contribute to the knowledge of bioethanol production using cocoa mucilage and seek to add a positive value to this residue, whose management and final disposition have both undesirable environmental and economic effects.
dc.language.isoes_ES
dc.sourceThe Canadian Journal of Chemical EngineeringEarly ViewThe Canadian Journal of Chemical EngineeringEarly View
dc.subjectSequential simplex method
dc.subjectBioethanol production
dc.subjectBiomass fermentation
dc.subjectCocoa mucilage
dc.subjectModified Gompertz model
dc.titleOptimization and modelling of bioethanol production by the fermentation of CCN-51 cocoa mucilage using the sequential simplex method and the modified Gompertz model
dc.title.alternativeOptimization and modelling of bioethanol production by the fermentation of CCN-51 cocoa mucilage using the sequential simplex method and the modified Gompertz model
dc.typeARTÍCULO
dc.ucuenca.idautor0105738306
dc.ucuenca.idautor0106521370
dc.ucuenca.idautor0103599411
dc.ucuenca.idautor0105306666
dc.ucuenca.idautor0107219701
dc.identifier.doihttps://doi.org/10.1002/cjce.25504
dc.ucuenca.versionVersión publicada
dc.ucuenca.areaconocimientounescoamplio07 - Ingeniería, Industria y Construcción
dc.ucuenca.afiliacionTenesaca, O., Universidad de Cuenca, Departamento de Química Aplicada y Sistemas de Producción, Cuenca, Ecuador
dc.ucuenca.afiliacionSerpa, A., Universidad de Cuenca, Departamento de Química Aplicada y Sistemas de Producción, Cuenca, Ecuador
dc.ucuenca.afiliacionBernal, T., Universidad de Cuenca, Departamento de Química Aplicada y Sistemas de Producción, Cuenca, Ecuador
dc.ucuenca.afiliacionDelgado, J., Universidad de Cuenca, Cuenca, Ecuador
dc.ucuenca.afiliacionMoreno, J., Universidad de Cuenca, Departamento de Química Aplicada y Sistemas de Producción, Cuenca, Ecuador
dc.ucuenca.correspondenciaDelgado Noboa, Jorge Washington, jorge.delgado@ucuenca.edu.ec
dc.ucuenca.volumenVolumen 0, número 0
dc.ucuenca.indicebibliograficoSCOPUS
dc.ucuenca.factorimpacto0.402
dc.ucuenca.cuartilQ2
dc.ucuenca.numerocitaciones0
dc.ucuenca.areaconocimientofrascatiamplio2. Ingeniería y Tecnología
dc.ucuenca.areaconocimientofrascatiespecifico2.4 Ingeniería Química
dc.ucuenca.areaconocimientofrascatidetallado2.4.2 Ingeniería de Procesos Químicos
dc.ucuenca.areaconocimientounescoespecifico071 - Ingeniería y Profesiones Afines
dc.ucuenca.areaconocimientounescodetallado0711 - Ingeniería y Procesos Químicos
dc.ucuenca.urifuentehttps://onlinelibrary.wiley.com/journal/1939019x
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