Fermentation Process Modeling with Levenberg-Marquardt Algorithm and Runge-Kutta Method on Ethanol Production bySaccharomyces cerevisiae

Abstract

The core of the Chinese rice wine making is a typical simultaneous saccharification and fermentation (SSF) process. In order to control and optimize the SSF process of Chinese rice wine brewing, it is necessary to construct kinetic model and study the influence of temperature on the Chinese rice wine brewing process. An unstructured kinetic model containing 12 kinetics parameters was developed and used to describe the changing of kinetic parameters in Chinese rice wine fermentation at 22, 26, and 30°C. The effects of substrate and product inhibitions were included in the model, and four variable, including biomass, ethanol, sugar and substrate were considered. TheR-square values for the model are all above 0.95 revealing that the model prediction values could match experimental data very well. Our model conceivably contributes significantly to the improvement of the industrial process for the production of Chinese rice wine.

Kinetic Modeling of 1‐G Ethanol Fermentations

“…• Liu et al [75]: Fermentation Process Modeling with Levenberg-Marquardt Algorithm and Runge-Kutta Method on Ethanol Production by S. cerevisiae.…”

DEVELOPING CHEMICAL ENGINEERING ACUMEN by Brewing Kicking Mule Beer

“…[6,12,13] While accounting for the variables of sugar consumption rates, ethanol production rates, and biomass content, cadets fit their experimental data to models from literature, which includes the Monod, Aiba, Tiessier and Hinshelwood models. [13][14][15][16][17] By modeling the data, students observe how the temperature of the fermenter affects the reaction rate. A higher fermenter temperature yields a faster, more vigorous fermentation reaction rate.…”

“…where S is the concentration of the sugar, and Y x/s and Y p/s are the yield coefficients. [13][14][15][16][17] . The rate of consumption of substrate S is in proportion with the rates of production of both the cell concentration X and the product concentration P. The ratio of both products produced from the consumed substrate is represented by the yield coefficients Y x/s and Y p/s .…”

On-line identification of fermentation processes for ethanol production

“…Other unstructured models for the SSF process may also be found for other systems, for instance [67][68][69][70][71]. Focusing on the industrial use of the monitoring strategy, we have aimed at developing a model for the SSF of corn mash, keeping it as simple as possible, while still being capable of describing the dynamics of key species involved.…”