Industrial Crops and Products

Similar documents
The possibility of longan tree trimming waste for the bioethanol production

Optimization of the pretreatment of wheat straw for production of bioethanol

Improvements in Bioethanol Production Process from Straw

Summary & Conclusion

Simultaneous saccharification and fermentation of Arundo donax - Comparison of feeding strategies

MATERIALS & METHODS Microorganisms and cultivation. Keywords: Corncob; Cellulosic hydrolysates; Streptomyces sp.; Reducing sugar; Bioethanol

Effect of particle size on enzymatic hydrolysis of pretreated miscanthus

By Srinivas Reddy Kamireddy Department of Chemical Engineering University of North Dakota. Advisor Dr. Yun Ji

Optimization of ethanol production from cheese whey powder by Kluyveromyces fragilis using factorial design and response surface methodology

SWEET SORGHUM JUICE AND BAGASSE AS A POSSIBLE FEEDSTOCK FOR BIOETHANOL PRODUCTION

SACCHARIFICATION OF ACID-PRETREATED SWEET SORGHUM STRAW BY CELLULASE FOR BIOETHANOL PRODUCTION

The effect of acid pretreatment on bio-ethanol and bio-hydrogen production from sunflower straw

Pretreatment Methods for Banana Peel as a Substrate for the Bioproduction of Ethanol in SHF and SSF

Alternative Feed-stocks for Bioconversion to Ethanol: a techno-commercial appraisal

RESEARCH PAPERS FACULTY OF MATERIALS SCIENCE AND TECHNOLOGY IN TRNAVA SLOVAK UNIVERSITY OF TECHNOLOGY IN BRATISLAVA

Influence of harvesting time on biochemical composition and glucose yield from hemp

Biological Conversion of Cellulosic Biomass to Ethanol at UCR

Fed-Batch Mode Optimization of SSF for Cellulosic Ethanol Production from Steam-Exploded Corn Stover

Optimization of Controlled ph Liquid Hot Water Pretreatment of Corn Fiber and Stover

Evaluation of second generation biofuels production from native halophytes by chemical-characterization of Salicornia sinus-persica

Prospects for the New Bioeconomy

Fermentation of pretreated source separated organic (SSO) waste for ethanol production by different bacteria

Novozymes Cellic CTec3 HS - secure your plant's lowest cost

Recycling Cellulase from Enzymatic Hydrolyzate of Laser-Pretreated Corn Stover by UF Membrane

FABRICATION OF BIOREACTOR UTILIZING HOLLOW FIBER MEMBRANE FOR RUMEN HYDROLYSIS OF SWEET SORGHUM

Ethanol Production from Biomass - Optimization of Simultaneous Saccharification and Fermentation with Respect to Stirring and Heating

ETHANOL PRODUCTION FROM YAM BEAN USING YEAST Saccharomyces cerevisiae TISTR 5339

Moving towards commercialization of lignocellulosic biomass to fuels to chemicals. How to deal with heterogeneous biomass?

Introduction to BIOFUELS. David M. Mousdale. CRC Press. Taylor & Francis Group Boca Raton London New York

Effect of Liquid Hot Water Pretreatment on Switchgrass Hydrolysis

Effect Of Alkali Pretreatment and Enzymatic Saccharification on Bagasse Reducing Sugar For Bioethanol Production

Simultaneous saccharification and fermentation of steam-exploded corn stover at high glucan loading and high temperature

Bioethanol production: from wood to fuel

The Impact of Storage Parameters on Downstream Bioprocessing of Biomass

Rubbish or resources: an investigation into converting municipal solid waste to bio-ethanol production

Syamsul Falah Suryani Azmi Azhari. Department of Biochemistry Faculty of Matemathics and Natural Sciences Bogor Agricultural University

Comparative sugar recovery data from laboratory scale application of leading pretreatment technologies to corn stover

Developing Herbaceous Energy Crops

2G ethanol from the whole sugarcane lignocellulosic biomass

Steam Pretreatment Optimisation for Sugarcane Bagasse in Bioethanol Production

SECOND GENERATION BIOETHANOL FROM Eucalyptus globulus labill AND Nothofagus pumilio USING IONIC LIQUIDS. María Cristina Ravanal E.

INVESTIGATION ON CONVERSION OF FLOWER WASTES INTO BIOETHANOL AND PERFORMANCE EVALUATION ON SINGLE CYLINDER IC ENGINE

Ethanosolv Pretreatment of Bamboo with Dilute Acid for Efficient Enzymatic Saccharification

Increasing Ethanol Titer and Reducing Enzyme Dosage via Fed-Batch, Simultaneous Saccharification and Fermentation in a High Solids Bioreactor

Saccharification versus simultaneous saccharification and fermentation of kraft pulp

Biomass hydrolysis and ethanol production

FEASIBILITY OF ETHANOL PRODUCTION USING THE WHOLE SUGARCANE BIOMASS

(SIDCOP), Facultad de ingeniería, Universidad de Antioquia. Calle 67 No Medellín Colombia

BIOETHANOL PRODUCTION FROM RICE BRAN BY SACCHAROMYCES CEREVISIAE. *Corresponding author:

Study on Optimization of Bagasse Hemicellulose Enzymolysis with Response Surface Analysis

SCREEN AND IDENTIFY SUITABLE PLANT FEEDSTOCKS FOR LARGE SCALE PRE- TREATMENTS TO PRODUCE HIGH YIELD SUGAR AND HIGH QUALITY LIGNIN

Enzymatic hydrolysis of steam-exploded sugarcane bagasse by adding natural Sapindus peel

Pretreatment of Prevalent Canadian West Coast Softwoods Using the Ethanol Organosolv Process Assessing Robustness of the Ethanol Organosolv Process

THERMOPHILIC ENZYMES FOR BIOMASS CONVERSION

Challenges of Ethanol Production from Lignocellulosic Biomass

Executive Summary New Energy Company of Indiana CRADA Completed 1997 Public Release 1999

Effects of Liquid Hot Water Pretreatment on Enzyme Loading and Hydrolysis of Hardwood

Thomas Grotkjær Biomass Conversion, Business Development

Ethanol From Cellulose: A General Review

BIOETHANOL PRODUCTION FROM CELLULOSIC FIBERS: COMPARISON BETWEEN BATCH AND FED-BATCH SACCHARIFICATION

Trash into Gas: Powering Sustainable Transportation by Plants

Biofuel production using total sugars from lignocellulosic materials. Diego Alonso Zarrin Fatima Szczepan Bielatowicz Oda Kamilla Eide

BIOETHANOL PRODUCTION FROM CELLULOSIC FIBERS: COMPARISON BETWEEN BATCH AND FED-BATCH SACCHARIFICATION

Biofuels Research at the University of Washington

Distinct Roles of Residual Xylan and Lignin in Limiting Enzymatic Hydrolysis of Organosolv Pretreated Woody Biomass

Curtis L. Weller. Department of

Ethanol Production from Sweet Potato by Enzymatic Hydrolyzation and Saccharomyces cerevisiae YRK 017 Fermentation

Evaluation of bamboo as a feedstock for bioethanols in Taiwan

Kluyveromyces Marxianus Biofilm in Cheese Whey Fermentation for Bioethanol Production

International Journal of Nutrition and Agriculture Research

Production of Bioethanol from Elephant Grass (Pennisetum purpureum) Stem

Evaluation of agricultural wastes for the use in ethanol production by Candida shehatae TISTR 5843

Cellulosic Biomass Chemical Pretreatment Technologies

Characterization of tree and wood fractions for biorefinery applications SARA JOHANSSON COST FP0901 TURKU SEPTEMBER 18, 2013

From waste to fuel: bioconversion of domestic food wastes to energy carriers

Enhancing Biogas Production from Padauk Angsana Leave and Wastewater Feedstock through Alkaline and Enzyme Pretreatment

Nordic Association of Agricultural Scientists

Optimisation of the Fermentation of Dilute Acid Hydrolyzed Pine using Saccharomyces Cerevisiae for 2 nd Generation Bioethanol Production

TMP-Bio for Converting Cellulosic Biomass to 2nd Generation Sugar and Near-native Lignin

The Next Generation of Biofuels

Extraction of high molecular mass hemicelluloses prior to ethanol production. Alkali steam pretreatment of wheat and barley straw. Elisabeth Joelsson

UTILISATION OF INDUSTRIAL ENZYMES TO PRODUCE BIOETHANOL FROM AUTOCHTHONOUS ENERGY CROPS. Abstract

Optimization and improvement of bio-ethanol production processes

Rice Straws and Husks Biofuel: Emphasizing on Selection of Pre-Treatment Method Elza Firdiani Shofia, Kharisma Bangsa Senior High School, Indonesia

A facile and fast method for quantitating lignin in lignocellulosic biomass using acidic

Abstract Process Economics Program Report 280 COMPENDIUM OF LEADING BIOETHANOL TECHNOLOGIES (December 2011)

Abstract Process Economics Program Report 252 CHEMICALS FROM AGRICULTURAL WASTES (September 2004)

Activities in UW Forest Resources and Lignocellulosic Biorefineries

Bioconversion of Kraft Paper Mill Sludges to Ethanol by SSF and SSCF

The Potentially Promising Technologies for Conversion Woody Biomass to Sugars for Biofuel Production: Technology and Energy Consumption Evaluation

OZONOLYSISAS A PRE- PRETREATMENT FOR COMPACTED BIOENERGY FEEDSTOCK Nathan S. Mosier, Iman Beheshti Tabar*, Patrick T. Murphy,

Ethanol and biogas production after steam pretreatment of corn stover with or without the addition of sulphuric acid

Available online at ScienceDirect. Energy Procedia 47 (2014 )

Lignin Production by Organosolv Fractionation of Lignocellulosic Biomass W.J.J. Huijgen P.J. de Wild J.H. Reith

ENZYMATIC HYDROLYSIS OF AGRICULTURAL LIGNOCELLULOSIC BIOMASS HIDROLIZA ENZIMATICA A BIOMASEI LIGNOCELULOZICE DIN AGRICULTURA

BIOMASS (TO BIOETHANOL) SUPPLY CHAIN DESIGN AND OPTIMISATION

Butanol Fermentation from Low-Value Sugar-Based Feedstocks by Clostridia

Bioethanol Production from Cassava (Manihot esculenta) Peel Using Yeast Isolated from Durian (Durio zhibetinus)

Optimization of alkaline peroxide pretreatment of rice straw

The objective of this work was the production of ethanol

Transcription:

Industrial Crops and Products 42 (2013) 280 291 Contents lists available at SciVerse ScienceDirect Industrial Crops and Products journa l h o me pag e: www.elsevier.com/locate/indcrop Optimization of simultaneous saccharification and fermentation for the production of ethanol from sweet sorghum (Sorghum bicolor) bagasse using response surface methodology Lijun Wang a,b,, Zhenglin Luo b, Abolghasem Shahbazi a,b a Department of Natural Resources and Environmental Design, North Carolina Agricultural and Technical State University, Sockwell Hall, 1601 E Market Street, Greensboro, NC 27411, USA b Department of Chemical and Bioengineering, North Carolina Agricultural and Technical State University, Sockwell Hall, 1601 E Market Street, Greensboro, NC 27411, USA a r t i c l e i n f o Article history: Received 18 February 2012 Received in revised form 28 May 2012 Accepted 2 June 2012 Keywords: Bioconversion Ethanol Fermentation Optimization Modeling Sweet sorghum a b s t r a c t The response surface method was used to investigate the effects of process parameters, including temperature from 35 to 45 C, enzyme loading from 10 to 30 filter paper units (FPU)/g-glucan, yeast concentration from 0.5 to 1.5 g/l, and bagasse solid concentration from 4 to 10% on ethanol yield, concentration and production rate during simultaneous saccharification and fermentation (SSF) of sweet sorghum bagasse. The results showed that the maximum ethanol yield, concentration and production rate were obtained at different SSF conditions. Under the recommended SSF condition of the temperature at 37 C, yeast concentration at 1.4 g/l, enzyme loading at 25 FPU/g-glucan and bagasse solid concentration at 10%, the ethanol yield, concentration and production rate were 89.4%, 38 g/l and 1.28 g/l/h, respectively. The bagasse solid concentration had significant effects on the ethanol concentration and ethanol production rate. The optimum bagasse solid concentration for the ethanol yield was 7%. The increase of the bagasse solid concentration significantly increased the final ethanol concentration but decreased the ethanol production rate. Fed batch operation could be used to maintain the bagasse solid concentration at a low value (e.g., 7%) to achieve high ethanol yield and production rate while increasing the final ethanol concentration. 2012 Elsevier B.V. All rights reserved. 1. Introduction Bio-ethanol has become one of the dominating biofuels in the transportation sector. The United States of America and Brazil are the two largest producers of bio-ethanol representing 52% and 37% of the total world s ethanol production, respectively (Davila-Gomez et al., 2011). Currently, the ethanol for the fuel market is mainly produced from corn starch in the United States and sugarcane in Brazil. These food-grade raw materials will not be sufficient to meet the increasing demand for the fuel ethanol. The reduction of greenhouse gases by using the starch or sugar-based ethanol is not as high as desirable (Hahn-Hagerdal et al., 2006). Ethanol can also be produced from abundant and renewable biomass sources such as agricultural residues, forest residues and energy crops (Gnansounou and Dauriat, 2010; Wang et al., 2011). Corresponding author at: Department of Natural Resources and Environmental Design, North Carolina Agricultural and Technical State University, Sockwell Hall, 1601 E Market Street, Greensboro, NC 27411, USA. Tel.: +1 336 3347787; fax: +1 336 3347270. E-mail address: lwang@ncat.edu (L. Wang). Sweet sorghum (Sorghum bicolor) as a new industrial energy crop can be cultivated in almost all temperate and tropical climate areas due to its low requirement for water and fertilizer, wide adaptability for cultivation, and short growth period of 3 4 months (Laopaiboon et al., 2007; Wu et al., 2010). Sweet sorghum is an attractive feedstock for the production of fuel ethanol because it has high fermentable sugar content in its juice and high yield of green biomass. The yield of green biomass is approximately 2000 3000 dry tons/km 2, of which approximately 40 45% is fermentable sugars and starch (Wu et al., 2010). The potential ethanol yield from all fermentable sugars and starch in sweet sorghum could be 560,000 610,000 L/km 2 (or 600 650 gal/acre), compared to 420,000 L/km 2 (or 450 gal/acre) for corn on average in the United States (Wu et al., 2010). The bagasse residue after extracting the juice from the sweet sorghum stalks is a lignocellulosic material, which has a tough crystalline structure formed by cellulose, hemicelluloses and lignin. The lignocellulosic bagasse can be hydrolyzed into sugars and further fermented to ethanol (Shen et al., 2011). During simultaneous saccharification and fermentation (SSF), the sugars released from the lignocellulosic biomass during hydrolysis are promptly converted into ethanol to relieve the inhibition of the enzymes by the 0926-6690/$ see front matter 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.indcrop.2012.06.005

L. Wang et al. / Industrial Crops and Products 42 (2013) 280 291 281 sugars and reduce the capital cost (Ohgren et al., 2006). However, the challenge of the SSF process is to find the optimum operating condition for both enzymatic hydrolysis and ethanol fermentation with yeasts. During the SSF process, the ethanol yield, concentration and production rate are highly affected by the operating parameters, including solid biomass concentration, enzyme loading, temperature and yeast concentration. The response surface methodology (RSM) can be used to identify the effects of individual process variables on the responses of ethanol yield, concentration and production rate, and to determine the optimum condition during SSF of sweet sorghum bagasse. The RSM includes three major steps: (1) implementing a statistically designed experimental plan to collect data, (2) developing a regression model to correlate experimental data, and (3) predicting the response of target variables to the process parameters using the regression model (Vanderghem et al., 2011). The objective of this research was to develop regression models for predicting the ethanol yield, concentration and production rate during SSF of sweet sorghum bagasse and use the regression models to optimize the operating parameters of the SSF process including solid biomass concentration, enzyme loading, yeast concentration and temperature. 2. Materials and methods 2.1. Sweet sorghum bagasse and pretreatment Fresh sweet sorghum (Sugar Drip Variety) was provided by the agronomy farm of Purdue University in the Tippecanoe county, Indiana (Latitude: 40.4708676 and Longitude: 86.9905682). The sweet sorghum was grown at the Purdue agronomy farm and harvested at its peak brix content by hand with a knife in the late October of 2010. The fresh sweet sorghum was then bundled and stored in a deep freezer immediately after harvesting and shipped to North Carolina Agricultural and Technical State University using the FedEx overnight shipment. The stalk was extracted by a mechanical extractor (QJH-L100A, Zhejiang, China) and separated into juice and bagasse. The bagasse was air dried and ground to 1 mm mesh size using a Thomas Wiley mill (Model 4, Arthur H. Thomas Co., Philadelphia, PA). A dilute sulfuric acid solution was used to pretreat the sweet sorghum bagass to open its tough crystalline structure to enhance the further enzymatic hydrolysis with cellulase and ethanol fermentation with yeast. The pretreatment of the sweet sorghum bagasse was conducted in a 1 L high pressure Parr reactor (Parr 4570 reactor, Moline, IL, USA). During the pretreatment, a 750 ml slurry containing the dried and ground bagasse at a solid concentration of 10% by mass soaked in a 0.5% H 2 SO 4 solution was loaded into the Parr reactor. Nitrogen gas was used to purge air out of the reactor prior to heating the slurry. The bagasse slurry was heated up to the final temperature of 180 C at a heating rate of 5 C/min, held at 180 C for 5 min and then cooled to the room temperature at a cooling rate of 10 C/min using a water cooling coil inserted in the reactor. The pretreated slurry was then centrifuged at 1200 g for 10 min in a centrifuge (Gentra GP8R, Thermo IEC, Milford, MA, USA) to recover the solid bagasse. The solid bagasse was washed with deionized water three times to remove inhibitors of enzymes used during SSF. After washing, the ph value was around 7. The solid bagasse was stored in a refrigerator at 4 C immediately to be used for the SSF study. 2.2. Simultaneous saccharification and fermentation of the pretreated bagasse The enzymes used for the saccharification were provided by Novozymes North America (Franklinton, NC, USA), which included cellulase (NS50013), -gluosidase (NS50010) and hemicellulase (NS22002). The optimum hydrolysis condition for those enzymes provided by the company of Novozymes was a temperature at 50 C and a ph value at 4.9. The yeast of Saccharomyces cerevisiae (ATCC 24858), which was provided by the program of Food & Nutritional Sciences at North Carolina A&T State University, was used to ferment the sugars from the hydrolysis of sweet sorghum bagasse into ethanol. The yeast initially in a dry form was activated and cultured in a YM Broth (Becton, Dickinson and Company). The YM broth was prepared by mixing 21 g of YM broth powder in 1 L of deionized water, and autoclaved at 121 C for 15 min. The ph of the broth was 6.2 ± 0.2. The yeast was cultured in a flask with 400 ml YM broth, which was placed in an incubator (Incubator Shaker Series I26, New Brunswick Scientific Co., Inc., Edison, NJ, USA) at a temperature of 30 C and shaking speed of 150 revolutions per minute (rpm) for 24 h. The yeast culture was then centrifuged at 1200 g for 5 min in a centrifuge (Gentra GP8R, Thermo IEC, Milford, MA, USA). The supernatant was discarded and the precipitated yeast was washed three times with deionized water. The washed yeast cells were diluted by deionized water to around 20 g/l of yeast suspension to be used for the ethanol fermentation. The actual concentration of the yeast suspension was measured by drying a given volume of the suspension in an oven at 80 C for 24 h. The SSF of sweet sorghum bagasse was conducted in 250 ml bottles with a working volume of 100 ml. The ph value of the fermentation broth was maintained at 5.0 ± 0.1 by adding 2.5 ml of 1 M citrate buffer solution into the bagasse broth. Prior to the SSF, the bagasse broth was autoclaved at 121 C for 15 min and then cooled to the room temperature. A given amount of the enzymes and the activated yeast were added to the autoclaved bagasse broth. The fermentation bottles were placed in an incubator (Incubator Shaker Series I26, New Brunswick Scientific Co., Inc., Edison, NJ, USA) at a given temperature and shaking speed of 150 rpm. The SSF was preceded for 168 h and about 2 ml samples each were taken at 0, 4, 12, 24, 48, 72, 96, 120 and 168 h. The concentrations of ethanol and the sugars of glucose, xylose, fructose and sucrose in the samples were analyzed by the HPLC equipped with a KC-811 ion-exchange column and a Waters 410 refractive index detector (Waters, Milford, MA). The ethanol yield was expressed as the percentage of the theoretical yield using the following formula: Yield ethanol = [ ] (Cethanol,f C ethanol,i ) 100% (1) 0.568f C biomass where C ethanol,f : ethanol concentration at the end of the SSF (g/l), C ethanol,i : ethanol concentration at the beginning of the SSF (g/l), C biomass : dry biomass concentration at the beginning of the SSF (g/l); f: cellulose fraction of the dry biomass (g/g); 0.568: conversion factor from cellulose to ethanol. 2.3. Factional factorial experimental design for the SSF of bagasse A fractional 3 4 factorial experimental design with a total of 27 experiments as shown in Table 1 (Krishna and Chowdary, 2009; Laluce et al., 2009) was used to investigate the responses of ethanol yield, final ethanol concentration and ethanol production rate to the four process factors at three levels including temperature at 35, 40 and 45 C, solid bagasse concentration at 4, 7 and 10%, cellulase loading at 10, 20 and 30 FPU/g-glucan, and yeast concentration at 0.5, 1 and 1.5 g/l during SSF of sweet sorghum bagasse. During the SSF, another two enzymes of beta-glucosidase and hemicellulase were added to the bagasse broths at proper ratios of cellulase recommend by the provider of Novozymes.

282 L. Wang et al. / Industrial Crops and Products 42 (2013) 280 291 Table 1 The effects of process factors including temperature, cellulase loading, bagasse solid concentration and yeast concentration on the ethanol yield and final ethanol concentration during the SSF of sweet sorghum bagasse obtained by fractional 3 4 factorial design. No. Process parameters Response parameters x 1 x 2 x 3 x 4 Y C T ( C) Cellulase loading (FPU/g-glucan) Bagasse solid concentration (%) Yeast concentration (g/l) Ethanol yield (%) Ethanol concentration (g/l) 1 35 10 7 1 58.6 17.0 2 35 20 7 1.5 79.8 23.2 3 35 20 7 0.5 81.4 23.7 4 35 20 10 1 77.7 32.3 5 35 20 4 1 70.5 11.7 6 35 30 7 1 85.1 24.8 7 40 10 10 1 52.6 21.8 8 40 10 4 1 68.7 11.4 9 40 10 7 1.5 78.9 22.9 10 40 10 7 0.5 29.6 8.6 11 40 20 7 1 85.0 24.7 12 40 20 7 1 87.5 25.5 13 40 20 7 1 82.8 24.1 14 40 20 10 1.5 76.3 31.7 15 40 20 10 0.5 24.2 10.1 16 40 20 4 1.5 89.5 14.9 17 40 20 4 0.5 43.2 7.2 18 40 30 7 1.5 83.7 24.4 19 40 30 7 0.5 32.5 9.4 20 40 30 10 1 78.7 32.7 21 40 30 4 1 85.3 14.2 22 45 10 7 1 15.2 4.4 23 45 20 7 1.5 24.0 7.0 24 45 20 7 0.5 12.6 3.7 25 45 20 10 1 15.2 6.3 26 45 20 4 1 27.3 4.5 27 45 30 7 1 20.4 5.9 Table 2 Compositional analysis of raw and pretreated bagasse samples. Samples Glucan (% by mass) Xylan (% by mass) Lignin (% by mass) Ash (% by mass) Raw bagasse 43.5 18.0 19.7 2.0 Bagasse pretreated with 0.5% H 2SO 4 65.8 0.0 34.8 4.6 2.4. Regression analysis and response surface methodology Regression analysis of the experimental data and the response surface method were used to study the effects of SSF temperature, bagasse solid concentration, enzyme loading and yeast concentration on the ethanol yield, concentration and production rate during the SSF of sweet sorghum bagasse. A full quadratic polynomial regression model was used to correlate the experimental data. y = b 0 + i b i x i + 1 i b ii x 2 + i 1 i 1 j b ij x ij (2) 2 where y * are the response variables of ethanol yield, final ethanol concentration and ethanol production rate, x i is process factors including fermentation temperature, bagasse solid concentration, enzyme loading and yeast concentration, b 0 is the offset coefficient, b i is linear coefficients, b ii is quadratic coefficients and b ij is interaction coefficients. The regression analysis of experimental data was performed in Microsoft Excel 2007 to determine the coefficients in the model and the significance of the coefficients. The established polynomial equations were used to plot threedimensional (3-D) surfaces and two-dimensional (2-D) contours in MatLAB to visualize individual and interactive effects of the process Table 3 ANOVA results for the fitted quadratic models of the ethanol yield, final ethanol concentration and maximum production rate during the SSF of sweet sorghum bagasse. df SS MS F Significance F ANOVA for the regression of ethanol yield Regression 14 1.826 0.130 7.587 0.000587 Residual 12 0.206 0.0172 Total 26 2.032 ANOVA for the regression of final ethanol concentration Regression 14 21.185 1.513 10.016 0.000146 Residual 12 1.813 0.151 Total 26 22.998 ANOVA for the regression of maximum ethanol production rate Regression 14 34.509 2.465 9.526 0.000189 Residual 12 3.105 0.259 Total 26 37.614

L. Wang et al. / Industrial Crops and Products 42 (2013) 280 291 283 Fig. 1. Response of ethanol yield to bagass solid concentration and yeast concentration during the simultaneous saccharification and fermentation of sweet sorghum bagasse at a temperature of 40 C and cellulase loading of 20 FPU/g-glucan. factors on the response variables within their predefined ranges. A MatLAB program was developed to optimize the level of each factor for the maximum responses of ethanol, concentration and production rate. 3. Results and discussion 3.1. Compositions of raw and pretreated sweet sorghum bagasse The compositions of the sweet sorghum bagasse before and after pretreatment were given in Table 2. It can be seen from Table 2 that the 0.5% H 2 SO 4 solution at 180 C could remove all xylan in the bagasse and concentrate the glucan and lignin. The glucan contents of the raw bagasse and pretreated bgasse were 43.5% and 65.8%, respectively. 3.2. Response surface of the ethanol yield The ethanol yield or the fermentation efficiency was expressed as the ratio of the measured ethanol concentration after 96 h fermentation to the theoretical ethanol concentration determined by Fig. 2. Response of ethanol yield to enzyme loading and yeast concentration during the simultaneous saccharification and fermentation of sweet sorghum bagasse at a temperature of 40 C and bagasse solid concentration of 7%. the initial concentrations of glucan in the bagasse. It can be seen from Table 1 that the measured ethanol yields varied from 12.6% to 89.5% for the 27 experiments. The experimental data given in Table 1 was used to develop a four-variable quadratic polynomial regression model to predict the ethanol yield as a function of the four process parameters including temperature (x 1, C), cellulase loading (x 2, FPU/g-glucan), bagasse solid concentration (x 3, g/g), yeast concentration (x 4, g/l), which was given by: y = 16.585 + 0.813x 1 + 0.0871x 2 + 21.890x 3 + 0.957x 4 0.0105x 2 1 0.00110x 2 2 94.738x 2 3 0.609x 2 4 0.00110x 1 x 2 0.321x 1 x 3 + 0.0130x 1 x 4 + 0.0790x 2 x 3 +0.00100x 2 x 4 + 0.959x 3 x 4 (R 2 = 0.90) (3) The multiple R 2 value of the regression for the above model was 0.90, which indicated that 90% of the ethanol yield could be explained by the established model. The fitted model was evaluated by analysis of variance (ANOVA) given in Table 3. It showed that the established model was highly significant because of the Fisher s F-test (F-model, mean square regression/mean square residual = 7.587) and a very low probability value (Pmodel > F = 0.000587). The computed value of F exceeded the

284 L. Wang et al. / Industrial Crops and Products 42 (2013) 280 291 Fig. 3. Response of ethanol yield to enzyme loading and bagasse solid concentration during the simultaneous saccharification and fermentation of sweet sorghum bagasse at a temperature of 40 C and yeast concentration of 1 g/l. Fig. 4. Response of ethanol yield to temperature and yeast concentration during the simultaneous saccharification and fermentation of sweet sorghum bagasse at a cellulase loading of 20 FPU/g-glucan and bagasse solid concentration of 7%. Table 4 Coefficients and their significance levels for the fitted quadratic models of the ethanol yield, final ethanol concentration and maximum production rate during the SSF of sweet sorghum bagasse. Ethanol yield Final ethanol concentration Maximum production rate Coefficients p-value Coefficients p-value Coefficients p-value b 0 16.585 0.00250 52.841 0.00150 58.901 0.00453 b 1 0.813 0.00100 2.439 0.000905 2.522 0.00476 b 2 0.0871 0.177 0.225 0.235 0.475 0.0666 b 3 21.890 0.308 156.329 0.0249 163.707 0.0628 b 4 0.957 0.446 1.514 0.681 4.167 0.394 b 11 0.0105 0.0006 0.0296 0.000882 0.0311 0.00412 b 22 0.00110 0.0761 0.00325 0.0776 0.00168 0.461 b 33 94.738 0.159 344.493 0.0903 472.037 0.0778 b 44 0.609 0.0200 1.846 0.0179 2.485 0.0154 b 12 0.00110 0.431 0.00311 0.439 0.00834 0.127 b 13 0.321 0.477 3.127 0.0327 2.780 0.127 b 14 0.0130 0.628 0.0379 0.635 0.0809 0.442 b 23 0.0790 0.724 0.673 0.319 5.108 0.558 b 24 0.00100 0.939 0.00296 0.941 0.175 0.00486 b 34 0.959 0.830 23.236 0.0982 15.417 0.381

L. Wang et al. / Industrial Crops and Products 42 (2013) 280 291 285 Fig. 5. Response of ethanol yield to temperature and bagasse solid concentration during the simultaneous saccharification and fermentation of sweet sorghum bagasse at a cellulase loading of 20 FPU/g-glucan and yeast concentration of 1 g/l. tabulated value of F at a probability level of 0.000587, so that the null hypothesis (H 0 ) was rejected at the 0.000587 level of significance (Yu et al., 2009). This indicated that the combined effects of all the independent variables significantly contributed to the ethanol yield. The p-values from the t-test analysis given in Table 4 were used to determine the significance levels of four process parameters and their interactions on the ethanol yield. As shown in Table 4, the temperature had the most significant effect on the ethanol yield among the four process parameters. As the effect of the interaction between cellulase loading and yeast concentration on the ethanol yield was not significant, this interaction could be removed from Eq. (3) without significant effect on the accuracy of predicted ethanol yields. Eq. (3) was used to plot 3-D response surfaces and their corresponding 2-D contours in MatLAB to show the ethanol yields affected by the different levels of the four process variables. The surface and contour plots were shown in Figs. 1 6. The response surfaces can be used to explain how two process parameters were interacted with each other when the other two process parameters were fixed at their central levels. The response surfaces can also be used to determine the optimum levels of process parameters Fig. 6. Response of ethanol yield to temperature and enzyme loading during the simultaneous saccharification and fermentation of sweet sorghum bagasse at a bagasse solid concentration of 7% and yeast concentration of 1 g/l. for the maximum response of ethanol yield at the highest point of the surfaces. Each 3-D response surface curve has a corresponding 2-D contour curve to represent an infinite number of points of two independent process parameters in which the color level represents the different responses of the ethanol yield. The region for the highest response value was located on the area confined in the smallest ellipse indicated by darker color in the contour diagram. Figs. 1 6 showed that there were significant interactions between any two process parameters on the ethanol yield when the other two process parameters were fixed at their central levels. Figs. 1, 2 and 4 showed there were significant interactions of yeast concentration with other process parameters on the ethanol yield. Figs. 1 and 2 showed that the yeast concentration had more significant influence on the ethanol yield than the solid concentration and enzyme loading, because there were more ethanol yield levels of response lines located in the predefined range of yeast concentration as shown in Figs. 1(b) and 2(b). As shown in Fig. 4(b), the yeast concentration also had more significant influence on the ethanol yield than the temperature in the range from 35 to 40 C. However, if the temperature was higher than 40 C, the temperature became more influential on the ethanol yield than the yeast concentration. Figs. 1, 2 and 4 showed that a high ethanol yield could be achieved if the yeast concentration was in the range of

286 L. Wang et al. / Industrial Crops and Products 42 (2013) 280 291 1.2 1.4 g/l, which is determined by the overlap of three ranges of the yeast concentration in Figs. 1, 2 and 4. If the yeast concentration was too low (e.g., <1.2 g/l), the availability of the yeast would limit the ethanol fermentation. However, if the yeast concentration was too high concentration (>1.4 g/l), the extra amount of yeast could potentially consume more sugars for cell biomass and decrease the ethanol yield. In the central region confined by the yeast concentration from 1.2 to 1.4 g/l and bagasse solid concentration from 5.5 to 7% as shown in Fig. 1 (b), the ethanol yield was higher than 90% if the temperature was 40 C and enzyme loading was 20 FPU/g glucan. Figs. 2, 3 and 6 showed there were significant interactions of enzyme loading with other process parameters on the ethanol yield. Figs. 2, 3 and 6 showed that a high ethanol yield could be achieved if the enzyme loading was in the range from 20 to 27 FPU/g-glncan. Fig. 2 showed that at a high yeast concentration (e.g., 1.3 g/l), the ethanol yield increased significantly with the increase of the enzyme loading. However, at a low yeast concentration (e.g., 0.6 g/l), the increase of the enzyme loading could not significantly increase the ethanol yield. In the central region confined by the enzyme loading from 20 to 27 FPU/g-glucan and the yeast concentration from 1.15 to 1.45 g/l as shown in Fig. 2(b), the ethanol yield was higher than 90% if the temperature was 40 C and the bagasse solid concentration was 7%. It can be seen from Fig. 3 that there was a significant interaction between enzyme loading and bagasse solid concentration. If the temperature was 40 C and the yeast concentration was 1 g/l, the enzyme loading and bagasse solid concentration should be in the ranges from 20 to 27 FPU/g-glucan, and from 5 to 7.5%, respectively, to achieve a high ethanol yield. Figs. 4 6 showed there were significant interactions of the temperature with other process parameters on the ethanol yield. It can be seen from Figs. 4 6 that a high ethanol yield could be achieved if the temperature was in the range from 35.5 to 39 C, which was a compromising value between the optimum temperature of 30 C for the yeast and 50 C for the enzymes recommended by the providers of yeast and enzymes. The ethanol yield decreased sharply if the temperature increased to be higher than 45 C as shown in Fig. 4. Figs. 1, 3 and 5 showed that a high ethanol yield could be achieved if the bagasse solid concentration was in the range from 5.5 to 7%. The increase of the solid concentration could decrease the ethanol yield because the solid bagasse at a too high concentration could not be hydrolyzed efficiently by the cellulase due to the poor interaction between the bagasse and the cellulase. From Figs. 1 6, the operating condition of the SSF should be the yeast concentration in the range of 1.2 1.4 g/l, enzyme loading in the range of 20 27 FPU/g-glucan, temperature in the range of 35.5 39 C and the bagasse solid concentration in the range of 5.5 7% to achieve a high ethanol yield. Eq. (3) was further solved through a numerical iteration procedure using MATLAB codes to find the maximum value of the ethanol yield when the independent process variables of temperature, enzyme loading, solid concentration and yeast concentration were confined at the predefined region. The predicted maximum ethanol yield was 98.8%, which was obtained at a temperature of 37 C, enzyme loading of 25 FPU/g-glucan, bagasse solid concentration of 7%, and yeast concentration of 1.3 g/l. 3.3. Response surface of ethanol concentration The measured ethanol concentrations after 96-h fermentation varied from 4.4 to 32.7 g/l for the 27 experiments as shown in Table 1. The ethanol concentrations after 96-h fermentation given in Table 1 was used to develop a four-variable quadratic polynomial regression model to predict the final ethanol concentration response to temperature (x 1, C), cellulase loading Fig. 7. Response of final ethanol concentration to bagass solid concentration and yeast concentration during the simultaneous saccharification and fermentation of sweet sorghum bagasse at a temperature of 40 C and cellulase loading of 20 FPU/gglucan. (x 2, FPU/g-glucan), bagasse solid concentration (x 3, g/g), yeast concentration (x 4, g/l), which was given by: C = 52.841 + 2.439x 1 + 0.225x 2 + 156.329x 3 + 1.514x 4 0.0296x 2 1 0.00325x 2 2 334.493x 2 3 1.846x 2 4 0.00311x 1 x 2 3.127x 1 x 3 + 0.0379x 1 x 4 + 0.673x 2 x 3 + 0.00296x 2 x 4 + 23.236x 3 x 4 (R 2 = 0.92) (4) The results of ANOVA in Table 3 indicated that this model was highly significant. The R 2 value of this regression was 0.92, which means that 92% of experimental data could be explained by this regression model. Table 4 shows that the temperature among the four process parameter had the most significant effect on the final ethanol concentration. As the effect of the interaction between cellulase loading and yeast concentration on the ethanol concentration was not significant, this interaction could be removed from Eq. (4).

L. Wang et al. / Industrial Crops and Products 42 (2013) 280 291 287 Fig. 8. Response of final ethanol concentration to enzyme loading and yeast concentration during the simultaneous saccharification and fermentation of sweet sorghum bagasse at a temperature of 40 C and bagasse solid concentration of 7%. Figs. 7 12 give the 3-D response surfaces and their corresponding 2-D contours for the final ethanol concentration affected by the four process parameters. It can be seen from Figs. 7, 8 and 10 that the yeast concentration should be between 1.2 and 1.45 g/l to achieve a high ethanol concentration. Figs. 8, 9 and 12 showed that the enzyme loading should be in the range from 20 to 30 FPU/g-glucan to achieve a high ethanol concentration. As shown in Fig. 9, a high bagasse solid concentration required high enzyme loading to catalyze the hydrolysis. Figs. 10 12 showed that the temperature should be in the range from 35 to 39 C to achieve a high ethanol concentration. If the temperature was higher than 39 C, the ethanol concentration significantly decreased with the increase of temperature as shown in Figs. 10 12. It can be seen from Figs. 7, 9 and 11 that at the yeast concentration from 1.0 to 1.5 g/l, enzyme loading from 20 to 30 FPU/g-glucan, and temperature from 35 to 40 C, the ethanol concentration increased with the increase of the bagasse solid concentration. At the bagasse solid concentration of 10%, the final ethanol concentration was higher than 30 g/l. However, if the yeast loading was too low, the increase of bagasse solid concentration from 4% to 10% had negligible effect on the ethanol concentration as shown in Fig. 7. Eq. (4) was solved through a numerical iteration procedure using MATLAB codes to find the maximum value of the ethanol concentration when the SSF conditions were set at the temperature from Fig. 9. Response of final ethanol concentration to enzyme loading and bagasse solid concentration during the simultaneous saccharification and fermentation of sweet sorghum bagasse at a temperature of 40 C and yeast concentration of 1 g/l. 35 to 45 C, enzyme loading from 10 to 30 FPU/g-glucan, bagasse solid concentration from 4 to 10%, and yeast concentration from 0.5 to 1.5 g/l. The maximum ethanol concentration was found to be 39 g/l, which was achieved at the temperature of 35 C, enzyme loading of 29 FPU/g-glucan, solid concentration of 10%, and yeast of 1.4 g/l. 3.4. Fermentation kinetics The modified Gompertz s equation was used to determine the fermentation kinetics of the sweet sorghum bagasse under different SSF conditions (Mu et al., 2006; Zajsek and Gorsek, 2010), which was expressed as: C E = C E.max exp { exp [ RE.max exp(1) ]} C E.max (t L t) + 1 where, C E is the predicted ethanol concentration (g/l), C E.max is the maximum ethanol concentration (g/l), R E.max is the maximum ethanol production rate (g/l/h), t L is the lag phase time (h), and t is the independent variable of time (h). The coefficients, C E.max, R E.max, and t L for under a given fermentation condition were obtained by the nonlinear regression of experimental data given in Table 5 using the Microsoft Excel Solver. The three coefficients in the modified (5)

Table 5 Coefficients in the modified Gompertz s equation obtained by the regression of the ethanol concentrations at different times for the 27 experiments during the SSF of sweet sorghum bagasse. NO. Process parameters Measured ethanol concentration (g/l) Coefficients in Gompertz s equation R 2 of regression x 1 x 2 x 3 x 4 Time (h) C E.max (g/l) R E.max (g/l/h) t L (h) T ( C) Cellulase (FPU/g-glucan) Bagasse (%) Yeast (g/l) 4 24 48 72 96 120 168 1 35 10 7 1 4.62 11.47 14.77 16.25 17.03 17.20 16.69 16.64 0.51 0 0.97 2 35 20 7 1.5 7.15 17.38 21.52 22.58 23.20 23.78 24.28 23.21 0.84 0 0.97 3 35 20 7 0.5 6.38 17.78 21.52 22.90 23.68 24.23 24.70 23.58 0.84 0 0.98 4 35 20 10 1 3.54 21.25 27.91 30.44 32.26 33.46 34.76 32.52 0.92 1.53 0.99 5 35 20 4 1 4.82 10.75 12.08 12.11 11.72 10.93 10.25 11.31 2.17 1.78 0.98 6 35 30 7 1 7.79 19.60 23.88 24.34 24.75 25.16 25.40 24.69 1.03 0 0.98 7 40 10 10 1 5.93 17.29 22.19 21.91 21.84 21.65 21.13 21.72 0.90 0 0.99 8 40 10 4 1 4.02 10.15 11.58 11.62 11.42 11.42 11.34 11.26 1.67 1.59 0.99 9 40 10 7 1.5 6.45 15.68 20.29 22.09 22.94 23.75 23.97 23.00 0.69 0 0.97 10 40 10 7 0.5 4.21 8.42 8.67 8.66 8.62 8.69 8.64 8.62 1.87 1.74 1.00 11 40 20 7 1 6.94 19.43 23.01 24.17 24.73 24.89 24.89 24.37 0.99 0 0.98 12 40 20 7 1 7.57 20.11 23.76 24.89 25.45 25.54 25.48 25.01 1.06 0 0.98 13 40 20 7 1 7.51 20.22 23.61 24.20 24.07 24.13 23.71 1.30 0 0.98 14 40 20 10 1.5 4.13 24.77 31.02 31.86 31.71 31.65 31.54 31.66 1.29 2.03 1.00 15 40 20 10 0.5 4.39 9.12 10.13 10.11 10.07 10.08 10.09 9.93 1.93 1.72 0.99 16 40 20 4 1.5 5.49 13.68 14.84 14.71 14.87 14.83 14.90 14.64 2.43 1.74 0.99 17 40 20 4 0.5 4.13 7.27 7.22 7.21 7.17 7.15 7.09 7.19 2.15 2.04 1.00 18 40 30 7 1.5 9.52 22.17 24.06 24.47 24.35 24.25 24.17 23.91 4.21 1.74 1.00 19 40 30 7 0.5 4.86 9.36 9.40 9.42 9.44 9.46 9.41 9.42 1.89 1.41 0.99 20 40 30 10 1 7.41 26.60 32.30 32.88 32.68 32.55 32.53 32.61 1.35 0 1.00 21 40 30 4 1 6.42 13.33 14.53 14.17 14.18 14.18 14.19 14.10 2.73 1.64 0.99 22 45 10 7 1 4.17 4.56 4.53 4.49 4.43 4.42 4.39 4.47 1.83 0.70 1.00 23 45 20 7 1.5 6.53 7.11 7.05 6.99 6.97 6.92 7.01 3.70 1.45 1.00 24 45 20 7 0.5 3.70 3.78 3.76 3.65 3.66 3.64 3.56 3.68 4.50 0.48 1.00 25 45 20 10 1 5.97 6.60 6.49 6.45 6.32 6.26 6.19 6.39 3.82 1.73 1.00 26 45 20 4 1 3.90 4.69 4.66 4.61 4.54 4.59 4.52 4.60 3.40 2.61 1.00 27 45 30 7 1 5.79 6.11 6.08 6.01 5.93 5.89 5.78 5.97 4.02 1.54 1.00 288 L. Wang et al. / Industrial Crops and Products 42 (2013) 280 291

L. Wang et al. / Industrial Crops and Products 42 (2013) 280 291 289 Fig. 10. Response of final ethanol concentration to temperature and yeast concentration during the simultaneous saccharification and fermentation of sweet sorghum bagasse at a cellulase loading of 20 FPU/g-glucan and bagasse solid concentration of 7%. Gompertz s equation for each experimental condition were given in Table 5. The R 2 values of the regression for all 27 experiments were between 0.97 and 1.00, which means that the modified Gompertz s equation can be used to predict the process kinetics during SSF of sweet sorghum bagasse. As shown in Table 5, the maximum ethanol production rates were in the range from 0.51 to 4.50 g/l/h depending on the SSF conditions. The maximum ethanol production rates given in Table 5 were used to develop a four-variable quadratic polynomial regression model to predict the maximum ethanol production rate as a function of the temperature (x 1, C), cellulase loading (x 2, FPU/gglucan), bagasse solid concentration (x 3, g/g), yeast concentration (x 4, g/l), which was given by: R E.max = 58.901 2.522x 1 0.476x 2 163.707x 3 4.167x 4 + 0.0311x 2 1 + 0.00168x 2 2 + 472.037x 2 3 + 2.485x 2 4 + 0.00834x 1 x 2 + 2.780x 1 x 3 0.0809x 1 x 4 0.511x 2 x 3 + 0.175x 2 x 4 15.417x 3 x 4 (R 2 = 0.92) (6) The results of AVOVA in Table 3 indicated that this model was highly significant. The R 2 value of this regression was 0.92. As Fig. 11. Response of final ethanol concentration to temperature and bagasse solid concentration during the simultaneous saccharification and fermentation of sweet sorghum bagasse at a cellulase loading of 20 FPU/g-glucan and yeast concentration of 1 g/l. shown in Table 4, the temperature had the most significant effect on the maximum ethanol production rate. In the predefined region of the independent process parameters of temperature, enzyme loading, solid concentration and yeast concentration, the Eq. (6) was further solved through a numerical iteration procedure using MATLAB to find the optimum SSF condition for the highest value of R E.max. The predicted highest R E.max value was 6.42 g/l/h, which was obtained at a temperature of 45 C, enzyme loading of 30 FPU/g-glucan, solid concentration of 4%, and yeast concentration of 1.5 g/l. The results indicated that a high ethanol production rate during SSF was achieved at high temperature, enzyme loading and yeast concentration, and low bagasse solid concentration. 3.5. Optimization of the fermentation process The maximum ethanol yield, concentration and production rate during SSF of sweet sorghum bagasse were obtained at different SSF conditions. However, the temperature at 35 37 C and

290 L. Wang et al. / Industrial Crops and Products 42 (2013) 280 291 over-supply the sugars that would inhibit the yeast performance as well as increase the cost of the SSF process. If the SSF condition is the temperature at 37 C, yeast concentration at 1.4 g/l, enzyme loading at 25 FPU/g-glucan and bagasse solid concentration at 10%, the ethanol yield, final concentration and production rate will be 89.4%, 38 g/l and 1.28 g/l/h, respectively. Reduction of the bagasse solid concentration from 10% to 7% can increase the ethanol production rate from 1.28 to 1.73 g/l/h and the ethanol yield from 89.4 to 97.7% if other parameters remain the same. Fed batch operation could be used to maintain the bagasse solid concentration at a low value (e.g., 7%) to achieve a high ethanol production rate and ethanol yield while increasing the final ethanol concentration. 4. Conclusion Fig. 12. Response of final ethanol concentration to temperature and enzyme loading during the simultaneous saccharification and fermentation of sweet sorghum bagasse at a bagasse solid concentration of 7% and yeast concentration of 1 g/l. the yeast concentration at 1.3 1.4 g/l were within the optimum response regions of ethanol yield and final ethanol concentration. The optimum bagasse solid concentration for the ethanol yield was found to be 7%. The increase of the bagasse solid concentration significantly increased the final ethanol concentration but significantly decreased the ethanol production rate. The bagasse solid concentration had more significant effect on the final ethanol concentration than the yield. The enzyme loading at 25 30 FPU/g-glucan could achieve high ethanol yield, concentration and production rate. The enzyme loading affects the supply rate of sugars during SSF. The feed sugar concentration has significant effects on the ethanol yield, concentration and production rate during the fermentation with the yeast (Ozmihci and Kargi, 2007). During the fermentation with the yeast, most of sugars are converted to ethanol while a small amount of sugars are consumed by the yeast for its growth and metabolic maintenance. Under the specified temperature, yeast concentration and bagasse solid concentration, too low enzyme loading (e.g., <25 FPU/g-glucan) would limit the supply of the sugars for the yeast fermentation and higher percentage of sugars might be used for the growth and metabolic maintenance of the yeast itself, which decreased the ethanol yield and final concentration. Too high enzyme loading (e.g., >25 FPU/g-glucan) would The response surface was an effective method to optimize the operating parameters including temperature, solid bagasse concentration, cellulase loading and yeast concentration during the SSF of sweet sorghum bagasse for the maximum ethanol yield, final ethanol concentration and ethanol production rate. Under the predefined conditions of the temperature from 35 to 45 C, solid concentration from 4 to 10% by mass, cellulase loading from 10 to 30 FPU/g-glucan, and yeast concentration from 0.5 to 1.5 g/l, the maximum ethanol yield, final ethanol concentration and ethanol production rate were obtained at different SSF conditions. The maximum response of ethanol yield was 98.8%, which was achieved at a temperature of 37 C, enzyme loading of 25 FPU/g-glucan, solid concentration of 7%, and yeast concentration of 1.3 g/l. The maximum ethanol concentration was 39 g/l, which was achieved at a temperature of 35 C, enzyme loading of 29 FPU/g-glucan, bagasse solid concentration of 10% and yeast concentration of 1.4 g/l. The maximum predicted ethanol production rate was 6.42 g/l/h, which was obtained at a temperature of 45 C, enzyme loading of 30 FPU/gglucan, solid concentration of 4%, and yeast concentration of 1.5 g/l. If the SSF condition is the temperature at 37 C, yeast concentration at 1.4 g/l, enzyme loading at 25 FPU/g-glucan and bagasse solid concentration at 10%, the ethanol yield, final concentration and production rate will be 89.4%, 38 g/l and 1.28 g/l/h, respectively. The optimum bagasse solid concentration for the ethanol yield was found to be 7%. The increase of the bagasse solid concentration significantly increased the final ethanol concentration but significantly decreased the ethanol production rate. Reduction of the bagasse solid concentration from 10% to 7% can increase the ethanol production rate from 1.28 to 1.73 g/l/h and the ethanol yield from 89.4 to 97.7% if other parameters remain the same. Fed batch operation could be used to maintain the bagasse solid concentration at a low value (e.g., 7%) to achieve a high ethanol production rate and ethanol yield while increasing the final ethanol concentration. Acknowledgments A contribution of North Carolina Agricultural and Technical State University, in fully supported by funds provided by U.S. Department of Agriculture (USDA CSREES 2008-38814-04729). Mention of a trade name, proprietary products, or company name is for presentation clarity and does not imply endorsement by the authors or the university. The authors wish to thank Dr. Klein Ileleji at Purdue University for providing the sweet sorghum samples and Ms. Michele R. Mims at North Carolina A&T State University for the HPLC analysis of fermentation samples. References Davila-Gomez, F.J., Chuck-Hernandez, C., Perez-Carrillo, E., Rooney, W.L., Serna- Saldivar, S.O., 2011. Evaluation of bioethanol production from five different

L. Wang et al. / Industrial Crops and Products 42 (2013) 280 291 291 varieties of sweet and forage sorghum (Sorghum biocolor (L) Moench). Industrial Crops and Products 33, 611 616. Gnansounou, E., Dauriat, A., 2010. Techno-economic analysis of lignocellulosic ethanol: a review. Bioresource Technology 101, 4980 4991. Hahn-Hagerdal, B., Galbe, M., Gorwa-Grauslund, M.F., Liden, G., Zacchi, G., 2006. Bio-ethanol-the fuel of tomorrow from the residues of today. Trends in Biotechnology 24, 549 556. Krishna, S.H., Chowdary, G.V., 2009. Optimization of simultaneous saccharification and fermentation for the production of ethanol from lignocellulosic biomass. Journal of Agricultural and Food Chemistry 49, 1971 1976. Laluce, C., Tognolli, J.O., de Oliveira, K.F., Souza, C.S., Morais, M.R., 2009. Optimization of temperature, sugar concentration, and inoculum size to maximize ethanol production without significant decrease in yeast cell viability. Applied Microbiology and Biotechnology 83, 627 637. Laopaiboon, L., Thanonkeo, P., Jaisil, P., Laopaiboon, P., 2007. Ethanol production from sweet sorghum juice in batch and fed-batch fermentations by Saccharomyces cerevisiae. World Journal of Microbiology and Biotechnology 23, 1497 1501. Mu, Y., Wang, G., Yu, H.Q., 2006. Kinetic modeling of batch hydrogen production process by mixed anaerobic cultures. Bioresource Technology 97, 1302 1307. Ohgren, K., Rudolf, A., Galbe, M., Zacchi, G., 2006. Fuel ethanol production from steam-pretreated corn stover using SSF at higher dry matter content. Biomass and Bioenergy 30, 863 869. Ozmihci, S., Kargi, F., 2007. Effects of feed sugar concentration on continuous ethanol fermentation of cheese whey powder solution (CWP). Enzyme and Microbial Technology 41, 876 880. Shen, F., Saddler, J.N., Liu, R., Lin, L., Deng, S., Zhang, Y., Yang, G., Xiao, H., Li, Y., 2011. Evaluation of steam pretreatment on sweet sorghum bagasse for enzymatic hydrolysis and bioethanol production. Carbohydrate Polymers 86, 1542 1548. Vanderghem, C., Brostaux, Y., Jacquet, N., Blecker, C., Paquot, M., 2011. Optimization of formic/acetic acid delignification of Miscanthus giganteus for enzymatic hydrolysis using response surface methodology. Industrial Crops and Products 35, 280 286. Wang, L.J., Luo, Z.L., Xiu, S.N., Shahbazi, A., 2011. Pretreatment and fractionation of wheat straw with acetic acid to enhance enzymatic hydrolysis and ethanol fermentation. Energy Sources 33, 1230 1238. Wu, X., Staggenborg, S., Propheter, J.L., Rooney, W.L., Yu, J., Wang, D., 2010. Features of sweet sorghum juice and their performance in ethanol fermentation. Industrial Crops and Products 31, 164 170. Yu, J., Zhang, X., Tan, T., 2009. Optimization of media conditions for the production of ethanol from sweet sorghum juice by immobilized Saccharomyces cerevisiae. Biomass and Bioenergy 33, 521 526. Zajsek, K., Gorsek, A., 2010. Modelling of batch kefir fermentation kinetics for ethanol production by mixed natural microflora. Food and Bioproducts Processing 88, 55 60.