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Starch hydrolysis modeling: application to fuel ethanol production

Bioprocess and Biosystems Engineering volume 34, pages 879–890 (2011)Cite this article

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 (R 2 = 0.69–0.79) and DP4+ (R 2 = 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 (R 2 > 0.73) indicating that the model can be used to predict the glucose concentrations during starch hydrolysis.

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Abbreviations

A aa,max :

Maximum activity of α-amylase

A aa,std :

Activity of the α-amylase under standard conditions

A aa :

Activity of the α-amylase under operating conditions

A avg,dp :

Average degree of polymerization of amylose

AMW:

Average molecular weight of molecules in simulated mash

APavg,dp :

Average degree of polymerization of amylopectin

\(C_{{\rm DP}4^{+}}\) :

Concentration of DP4+ (% db) in corn mash

C effect :

Starch composition effect on the enzyme activities

C Glucose :

Concentration of glucose (% db) in corn mash

C Maltose :

Concentration of maltose (% db) in corn mash

C Maltotriose :

Concentration of maltotriose (% db) in corn mash

DE:

Dextrose equivalent of mash (%)

DPsimulated :

Total number of glucose molecules in simulated mash

DP4 +total :

Total number of DP4+ molecules in simulated mash

E m :

Amount of enzyme (mL) added to the corn mash

GA:

Concentration of glucoamylase (g/L)

GAactivity :

Activity of glucoamylase at given pH and temperature

G total :

Total number of glucose molecules in simulated mash

G :

Concentration of glucose (g/L)

G MW :

Molecular weight of glucose (g/mol)

GP:

Concentration of maltodextrins (g/L)

M total :

Total number of maltose molecules in simulated mash

MTtotal :

Total number of maltotriose molecules in simulated mash

MW:

Molecular weight

N h :

Number of bonds hydrolyzed by E m (mL) of enzyme per sec

N a :

Number of amylose molecules in mash

N ap :

Number of amylopectin molecules in mash

N hA :

Number of bonds hydrolyzed per amylose molecule

N hAP :

Number of bonds hydrolyzed per amylopectin molecule

pH:

Mash/fermenter pH

pHeffect :

Effect of pH on enzyme activity

pHstability :

Effect of pH on enzyme stability

PIeffect :

Effect of product inhibition on enzyme activity

R 2 :

Coefficient of determination

R m :

Mass ratio of amylose to amylopectin in starch

R N :

Number ratio of amylose to amylopectin in starch

RN A :

Relative number of amylose molecules in starch

RNAP :

Relative number of amylopectin molecules in starch

S :

Solids concentration (wet basis) in corn mash

Starchdp :

Total degree of polymerization of all starch molecules in mash

t sim :

Simulation time (min)

T effect :

Effect of temperature on enzyme activity

T stability :

Effect of temperature on enzyme stability

T :

Mash/fermenter temperature (°C)

W mash :

Total weight of the mash (g)

X starch :

Starch content (%) of the corn

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Author notes

  1. Ganti S. Murthy

    Present address: Biological and Ecological Engineering, Oregon State University, 122 Gilmore Hall, Corvallis, OR, 97331, USA

Authors and Affiliations

  1. Department of Agricultural and Biological Engineering, University of Illinois, 360G AESB, 1304 West Pennsylvania Avenue, Urbana, IL, 61801, USA

    Ganti S. Murthy, Kent D. Rausch, M. E. Tumbleson & Vijay Singh

  2. Eastern Regional Research Center, ARS, USDA, Wyndmoor, PA, 19038, USA

    David B. Johnston

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  1. Ganti S. Murthy
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  5. Vijay Singh
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Correspondence to Vijay Singh.

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Murthy, G.S., Johnston, D.B., Rausch, K.D. et al. Starch hydrolysis modeling: application to fuel ethanol production. Bioprocess Biosyst Eng 34, 879–890 (2011). https://doi.org/10.1007/s00449-011-0539-6

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Keywords

  • Starch hydrolysis
  • Amylose
  • Amylopectin
  • Liquefaction
  • Saccharification
  • Monte Carlo simulation