Ciencia e Ingeniería en Alimentos y Biotecnología

URI permanente para esta comunidadhttp://repositorio.uta.edu.ec/handle/123456789/412

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Autor/a: search.filters.author.Acosta Lescano Valeria EstherTema: search.filters.subject.BIOTECNOLOGÍA INDUSTRIAL

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    Modelamiento matemático de la cinética de crecimiento de Lecanicillium lecanii en cultivo sumergido para la producción de ácido glicólico
    (Universidad Técnica de Ambato. Facultad de Ciencia e Ingeniería en Alimentos y Biotecnología. Carrera de Biotecnología, 2025-07)
    Acosta Lescano Valeria Esther
    ;
    García Pazmiño María Eugenia
    Glycolic acid is a highly demanded compound in the cosmetic and pharmaceutical industries due to its exfoliating and regenerative properties on the skin. It is traditionally produced on an industrial scale through chemical synthesis, a method that presents both environmental and economic limitations, thus prompting the need for sustainable and efficient biotechnological alternatives. In this context, the present research focused on developing a submerged culture of Lecanicillium lecanii using final cane molasses as a substrate for glycolic acid production, with strict monitoring of key process variables such as pH, acidity, reducing sugar concentration, and biomass production through analytical techniques including spectrophotometry and acid-base titration. Furthermore, microbial growth kinetics were fitted to mathematical models (Gompertz, Logistic, and Richards) to determine the model with the highest predictive capability, based on determination coefficients, standard error, and relative percentage error. The results indicate that L. lecanii is capable of producing glycolic acid under controlled conditions, with a higher bibliographically reported yield compared to other secondary metabolites, validating its potential as an alternative and sustainable biological system. Additionally, mathematical modeling enabled the establishment of growth patterns applicable to future production scales, providing a scientific foundation to optimize bioprocesses aimed at obtaining industrially relevant active ingredients with reduced environmental impact.