TitleStarch hydrolysis modeling: application to fuel ethanol production.
Publication TypeJournal Article
Year of Publication2011
AuthorsMurthy, GS, Johnston, DB, Rausch, KD, Tumbleson, ME, Singh, V
JournalBioprocess Biosyst Eng
Volume34
Issue7
Pagination879-90
Date Published2011 Sep
ISSN1615-7605
KeywordsAmylopectin, Amylose, Biofuels, Enzymes, Ethanol, Fermentation, Glucose, Hydrogen-Ion Concentration, Hydrolysis, Models, Chemical, Monte Carlo Method, Starch, Temperature, Zea mays
Abstract

Efficiency of the starch hydrolysis in the dry grind corn process is a determining factor for overall conversion of starch to ethanol. A model, based on a molecular approach, was developed to simulate structure and hydrolysis of starch. Starch structure was modeled based on a cluster model of amylopectin. Enzymatic hydrolysis of amylose and amylopectin was modeled using a Monte Carlo simulation method. The model included the effects of process variables such as temperature, pH, enzyme activity and enzyme dose. Pure starches from wet milled waxy and high-amylose corn hybrids and ground yellow dent corn were hydrolyzed to validate the model. Standard deviations in the model predictions for glucose concentration and DE values after saccharification were less than ± 0.15% (w/v) and ± 0.35%, respectively. Correlation coefficients for model predictions and experimental values were 0.60 and 0.91 for liquefaction and 0.84 and 0.71 for saccharification of amylose and amylopectin, respectively. Model predictions for glucose (R2 = 0.69-0.79) and DP4+ (R2 = 0.8-0.68) were more accurate than the maltotriose and maltose for hydrolysis of high-amylose and waxy corn starch. For yellow dent corn, simulation predictions for glucose were accurate (R2 > 0.73) indicating that the model can be used to predict the glucose concentrations during starch hydrolysis.

DOI10.1007/s00449-011-0539-6
Alternate JournalBioprocess Biosyst Eng
PubMed ID21487699