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  4. Modelos cinéticos sigmoidales aplicados al crecimiento de Saccharomyces boulardii

Modelos cinéticos sigmoidales aplicados al crecimiento de Saccharomyces boulardii

Author(s)
Universidad Peruana Unión, Juliaca, Perú
Ana Mónica Torres Jiménez
Universidad Peruana Unión, Juliaca, Perú
Date Issued
15 de enero de 2021
Type
Article
Volume
23
Issue
1
Start Page
47
End Page
54
DOI
10.18271/ria.2021.213
Abstract
Predictive microbiology is an interesting tool that allows evaluating the behavior of biomass and metabolites in different culture media, providing multiple benefits, whether scientific or industrial, for these and other reasons the objective of this research was to evaluate applied sigmoidal kinetic models to the growth of Saccharomyces boulardii in milk. For this purpose, flasks were prepared with 200 mL of fresh cow's milk, previously sterilized at 121 ° C x 15 min, then the strains were inoculated at a temperature of 37 ° C and incubated at the same temperature under constant shaking of 20 revolutions per minute (rpm) in a water bath with shaking, for 7 h; To construct the curves and obtain the growth constants, colony-forming units were counted per milliliter (cfu / ml) at one-hour intervals, with a monocular microscope and Neubauer chamber. Also, the pH and titratable acidity expressed in lactic acid were measured. The data obtained were converted to a logarithmic scale to apply the sigmoidal equations of Gompertz, Logistic, Modified Logistic and Weibull. The results of the kinetic modeling gave us that the modified Logistics and Logistics models presented a better fit compared to the rest. Likewise, the Weibull model presented the lowest value of adjustment, on the other hand, in the analysis of the statistical criteria, all models except Weibull present similarity. Finally, each sigmoidal model allowed to evaluate the growth of Saccharomyces boulardii with each of its kinetic constants.
Subjects

Gompertz function

Saccharomyces boulard...

Mathematics

Weibull distribution

Food science

Sigmoid function

Chemistry

Biology

Statistics

Computer science

Machine learning

Artificial neural net...

Probiotic

Genetics

Bacteria

Gompertz function

Saccharomyces boulard...

Mathematics

Weibull distribution

Food science

Sigmoid function

Chemistry

Biology

Statistics

Computer science

Life Sciences Agricul...

Life Sciences Biochem...

Life Sciences Biochem...

Metrics
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