Conceptual and Mathematical Models of Batch Simultaneous Saccharification and Fermentation: Dimensionless Groups for Predicting Process Dynamics
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Since 1905, the Department of Agricultural Engineering, now the Department of Agricultural and Biosystems Engineering (ABE), has been a leader in providing engineering solutions to agricultural problems in the United States and the world. The department’s original mission was to mechanize agriculture. That mission has evolved to encompass a global view of the entire food production system–the wise management of natural resources in the production, processing, storage, handling, and use of food fiber and other biological products.
History
In 1905 Agricultural Engineering was recognized as a subdivision of the Department of Agronomy, and in 1907 it was recognized as a unique department. It was renamed the Department of Agricultural and Biosystems Engineering in 1990. The department merged with the Department of Industrial Education and Technology in 2004.
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1905–present
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- Department of Agricultural Engineering (1907–1990)
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- College of Agriculture and Life Sciences (parent college)
- College of Engineering (parent college)
- Department of Industrial Education and Technology, (merged, 2004)
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Abstract
This paper describes a modeling effort demonstrating that dimensionless groupings of classical process parameters can be used to predicting process dynamics of batch simultaneous saccharification and fermentation (SSF) processes. Michaelis–Menten enzyme kinetics and Monod growth kinetics were employed, and inhibition of enzyme action and inhibition of microbial growth were neglected. The SSF process was characterized by the relative durations of three phases: A microbially-limited phase, a hydrolysis-limited phase, and a monosaccharide-depletion phase. The duration of these three phases were interrelated, and well predicted by the dimensionless magnitude of the monosaccharide peak (MSP). Thus, the MSP could be used as a single-value descriptor of an SSF process. The dimensionless ratio of the initial hydrolysis rate to the initial substrate consumption rate was shown to predict MSP, and an overall system time constant was shown to predict the total run time of a batch SSF process.
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Electronic version of an article published as Journal of Biological Systems 20, no. 2 (June 2012): 195–211, doi:10.1142/S0218339012500064. © World Scientific Publishing Company, http://www.worldscientific.com/worldscinet/jbs.