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Optimized simultaneous saccharification and co-fermentation of rice straw for ethanol production by Saccharomyces cerevisiae and Scheffersomyces stipitis co-culture using design of experiments
Bioresource Technology 142 (2013) 171–178
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Optimized simultaneous saccharification and co-fermentation of rice straw for ethanol production by Saccharomyces cerevisiae and Scheffersomyces stipitis co-culture using design of experiments Nopparat Suriyachai a, Khatiya Weerasaia a, Navadol Laosiripojana a, Verawat Champreda b, Pornkamol Unrean b,⇑ a b
The Joint Graduate School of Energy and Environment, King Mongkut’s University of Technology Thonburi, 126 Pracha Uthit Rd., Tungkru, Bangkok 10140, Thailand National Center for Genetic Engineering and Biotechnology (BIOTEC), 113 Thailand Science Park, Paholyothin Road, Klong 1, Klong Luang, Pathumthani 12120, Thailand
h i g h l i g h t s Co-culture SSCF process of rice straw for ethanol production was optimized. Effect of solid loading on enzyme hydrolysis was examined. Co-culture was systematically optimized using design of experiment (DoE) approach. Highly efficient and scalable SSCF by co-culture yielded 99% of theoretical yield. Maximum ethanol concentration achieved by co-culture SSCF process was 28.6 g/L.
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Article history: Received 22 February 2013 Received in revised form 30 April 2013 Accepted 2 May 2013 Available online 10 May 2013 Keywords: Design of experiment Simultaneous saccharification and cofermentation (SSCF) optimization Co-culture Ethanol
a b s t r a c t Herein an ethanol production process from rice straw was optimized. Simultaneous saccharification and co-fermentation (SSCF) using Saccharomyces cerevisiae and Scheffersomyces stipitis co-culture was carried out to enhance ethanol production. The optimal saccharification solid loading was 5%. Key fermentation parameters for co-culture including cell ratio, agitation rate and temperature was rationally optimized using design of experiment (DoE). Optimized co-culture conditions for maximum ethanol production efficiency were at S. cerevisiae:S. stipitis cell ratio of 0.31, agitation rate of 116 rpm and temperature of 33.1 °C. The optimized SSCF process reached ethanol titer of 15.2 g/L and ethanol yield of 99% of theoretical yield, consistent with the DoE model prediction. Moreover, SSCF process under high biomass concentration resulted in high ethanol concentration of 28.6 g/L. This work suggests the efficiency and scalability of the developed SSCF process which could provide an important basis for the economic feasibility of ethanol production from lignocelluloses. Ó 2013 Elsevier Ltd. All rights reserved.
1. Introduction Current increase in industrialization and transportation causes the rising of energy demand which leads to a fast depleting of fossil fuel and oil reserve. Fossil fuel currently takes up approximately 80% of the world primary energy, resulting in increasing economic and environmental concerns (Nigam and Singh, 2011). Thus, finding suitable fuel alternative is an important energy security and environmental issues worldwide. At present, biofuels are considered potential clean alternatives, which can be produced as liquid, gas and/or solid fuels from lignocellulosic biomass. Bioethanol produced from lignocellulose is an attractive alternative since
⇑ Corresponding author. Tel.: +66 8 8681 6012. E-mail address: [email protected] (P. Unrean). 0960-8524/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.biortech.2013.05.003
lignocellulosic materials do not compete with the food supply and are less expensive than conventional agricultural feedstock. In general, lignocellulosic ethanol production requires several steps including pretreatment of biomass feedstock; saccharification process to release fermentable hexoses and pentoses from polysaccharides; fermentation of released sugars and distillation step for ethanol separation. Lignocellulosic biomass contains various hexoses and pentoses including glucose, xylose, mannose and arabinose which may not be efficiently converted to ethanol. Thus, developing an efficient process for hydrolysis of lignocellulose into sugars and for fermentation of all available sugars to ethanol could potentially decrease the cost of lignocellulosic ethanol production process. Biomass feedstock such as rice straw is considered one of the most abundant biomass in the world. Rice straw is naturally more recalcitrant to degradation than other agriculture residues. Several reports on pretreatment with enzymatic saccharification
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result in a high conversion yield of cellulose and hemicellulose to fermentable sugars up to 80–90% of the theoretical yield (Shinozaki and Kitamoto, 2011). However, content of lignin in hydrolysates often interferes with fermentation process resulting in low ethanol production efficiency. Herein we have applied optimized pretreatment process previously developed to maximize the removal of lignin from hydrolysates. However, hydrolysis and co-fermentation of hexoses and pentoses is a challenging task requiring optimization of multiple process parameters (Wingren et al., 2003; Qian et al., 2006). Since enzymatic hydrolysis and fermentation process of lignocelluosic hydrolysates requires multiple process parameters optimization to simultaneously determine the individual and interactive effects of many factors affecting ethanol production efficiency, we have optimized ethanol production from rice straw by simultaneous saccharification and co-fermentation (SSCF). The objective of the current work was to investigate hydrolysis and fermentation process of Saccharomyces cerevisiae and Scheffersomyces stipitis co-culture. Percent solid loading during enzymatic hydrolysis process was examined to maximize content of released sugars. Three fermentation process parameters: cell ratio, agitation and temperature were optimized for achieving high ethanol production yield. A systematic optimization based on statistical approach using Design of Experiment (DoE) was implemented. This approach permits a rapid and accurate optimization based on the statistical test to reduce residual variation. It is proven to be an efficient tool for minimizing number of experiments and for providing high accuracy of reasonable optimum prediction (Unrean and Nguyen, 2012). The optimized SSCF process present in this study permits an efficient conversion of both hexoses and pentoses from rice straw hydrolysates into ethanol. 2. Methods 2.1. Biomass feedstock preparation and pretreatment Rice straw was obtained from Suphanburi province (Thailand) and used as a substrate for ethanol production. For preparation step, the rice straw feedstock was cut by Retsch ZM200, passed through a sieve (mesh 18–35, an average size of 0.5–1.0 mm), air-dried in an oven at 70 °C for 24 h and stored at room temperature. The chemical compositions of feedstock were determined according to National Renewable Energy Laboratory (NREL) method (Sluiter et al., 2008). Milled rice straw was then pretreated using 5% sodium hydroxide at 90 °C for 20 min. The pretreatment was carried out at a ratio of 1 g (rice straw) per 5 ml of NaOH solution in an autoclave (Tomy autoclave SS-325, Tomy, Japan). After pretreatment, solid and liquid fractions were filtered through a filter paper (Whatman No. 5). The solid fractions were washed with tap water until pH was neutral. The pretreated substrate was dried at 105 °C and kept at room temperature for further experimental study. Samples were taken from solid fractions and analyzed for its composition after pretreatment using NREL method. The pretreatment efficiencies were determined based on biomass digestibility using a commercial cellulose substrate. 2.2. Enzymatic hydrolysis The pretreated rice straw was hydrolyzed with AccelleraseÒ 1500 enzyme (Danisco, Rochester, NY). The enzymatic hydrolysis was carried out using 5% (w/v) pretreated substrate in a 1 ml hydrolysis vessel containing 25 FPU/g, 50 mM sodium citrate buffer, pH 4.8 and 50 ll of 5% sodium azide. Sodium azide is used as a preservative for the enzyme. The mixture was incubated at 50 °C for 72 h with vertical rotation at 30 rpm. Hydrolysis experiments were
performed in triplicates. The released reducing sugar concentration was analyzed based on the amount of liberated reducing sugars using 3,5-dinitrosalisylic acid (DNS) method (Miller, 1959). Control reaction containing 30 g/L glucose was included. 2.3. Microorganisms and maintenance Hexose-utilizing yeast, S. cerevisiae (ThermosaccÒ Dry yeasts; Lallemand, Milwaukee, WI) and pentose-utilizing yeasts, Candida tropicalis (BCC30719) and S. stipitis (BCC15191), obtained from BIOTEC Culture Collection, BIOTEC, Thailand (http://biotec.or.th/bcc) were used in this study. The culture was maintained at 4 °C on a yeast minimal (YM) agar plate consisting of yeast extract, 10 g/L; peptone, 20 g/L; glucose, 20 g/L and agar, 16 g/L at pH of 4.8. 2.4. Inoculum preparation Seed cultures of S. cerevisiae, S. stipitis and C. tropicalis were used in all simultaneous saccharification and co-fermentation (SSCF) experiments. For preparation of inoculum, cells from agar plate were added into 250 ml flasks with a 100 ml working volume of yeast peptone dextrose (YPD) medium (1% yeast extract, 2% peptone and 2% glucose) and incubated at 30 °C on a rotary shaker at 150 rpm for 24 h. 2.5. Comparison of ethanol production performance by mono- and coculture The simultaneous saccharification and co-fermentation of ethanol by mono- or co-culture was performed in 250 ml screw-capped duran bottles containing 100 ml working volume of 4.6% (w/v) alkali pretreated and pre-hydrolyzed rice straw in basal medium with 50 mM sodium citrate buffer. The pre-hydrolysis reactions were incubated at 30 °C for 6 h before inoculation of YM medium overnight grown yeast cultures as specified to yield an initial OD600 of approximately 1. The inoculum was either mono-culture or co-culture at 1:1 cell ratio. The culture was incubated at 30 °C, pH 5.0 with a continuous mixing at 150 rpm for 48 h. Profiles of sugar utilization and ethanol production of these cultures were compared. The experiments were performed in triplicate. 2.6. Co-culture optimization by design of experiments The fermentation experiments were carried out in 46 g/L pretreated rice straw hydrolysate supplemented with yeast extract, 1 g/L; (NH4)2SO4, 5 g/L; MgSO47H2O, 0.025 g/L in 250 ml screwcapped duran bottle with a working volume of 100 ml, pH 5.0 for 48 h. The culture conditions were optimized using design of experiment by varying temperature at 25, 30 and 35 °C, with a shaking rate at 100, 150 and 200 rpm, and with a cell ratio of S. cerevisiae and S. stipitis at 0.25/0.75, 0.5/0.5 and 0.75/0.25. Each optimization experiments were performed in triplicate. Prior to fermentation, the biomass was pre-hydrolysed with 25 FPU/g accellerase at 30 °C for 6 h. Fermentation was carried out under examined condition for 48 h. Ethanol yield under various conditions were compared and their effects on the yield was examined using central composite design (CCD) and response surface methodology (RSM). The yield is present in percent of theoretical ethanol yield of consumed glucose and xylose, 0.511 g-ethanol/g-sugar. Data was analyzed using STATISTIC 8.0 (Statsoft, USA) for all statistical experimental design and graphical analysis. 2.7. Simultaneous saccharification and co-fermentation (SSCF) Batch SSCF experiments were performed in either 250 ml duran bottles with a final working volume of 100 ml or 2 L bioreactor
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(Biostat, B. Braun Biotech International) with a final working volume of 1 L. The fermentation medium contained rice straw at concentration as specified supplemented with 5 g/L (NH4)2SO4, 0.025 g/L MgSO47H2O, 1 g/L yeast extract, pH 5.0. The medium was sterilized at 121 °C for 20 min. The amount of enzyme loading was 25 FPU/g accellerase of WIS content. Enzyme was added at the beginning during pre-hydrolysis at 30 °C for 6 h. Fermentation was carried out under optimal cell ratio, temperature, and agitation as determined by DoE for maximizing ethanol fermentation by co-culture system. Samples were taken periodically for 72 h and analyzed for glucose, xylose and ethanol concentration. 2.8. Analysis Glucose, xylose and ethanol profiles were analyzed on a high performance liquid chromatography HPLC (SPD-M10A DAD, Shimadzu, Columbia, MD). The HPLC system is equipped with an autosampler (SIL-10AF), an Aminex HPX-87H column (Biorad Labs, Hercules, CA), a UV–vis detector (SPD-10A) and a refractive index detector (RID-10A). The column was run in an isocratic mode at 65 °C and 0.5 ml/min using a mobile phase of 5 mM H2SO4. The concentration of sugar and ethanol was determined from the standard curve correlating peak area to concentration. 3. Results and discussion 3.1. Alkaline pretreatment of rice straw The alkaline pretreatment step led to remarkable reduction in lignin content and substantial increase in cellulose content in the pretreated biomass feedstock. Table 1 shows the pretreated rice straw consisting of 69.8% cellulose, 18.1% hemicellulose, 3.2% lignin and 8.7% ash. Comparing the chemical components, alkaline pretreatment increased the proportion of cellulose by 79.6% and decreased the lignin proportion by 84.1%. The alkaline pretreatment condition used in this study improved digestibility of rice straw better than other pretreatment methods previously used for rice straw including ammonia pretreatment, acid pretreatment, organic solvent pretreatment and steam pretreatment. Additional effects by alkaline pretreatment also include decomposed lignin shield, decreased cellulose crystalline, increased surface area which permits more susceptibility of the alkaline pretreated biomass to subsequent enzymatic hydrolysis (Binod, 2010). This finding was also consistent with previous results that reported the delignification effects of alkaline pretreatment for lignocellulosic biomass like rapeseed straw, wheat straw and coastal bermuda grass. The pretreatment conditions were varied from 1.25 to 5% NaOH at 35–121 °C, resulting in 60–90% reduction of lignin (Brodeur et al., 2011). Interestingly, there was also a decrease in hemicelluloses content after pretreatment which is likely due to the effect of alkaline hydrolysis on hemicelluloses fraction. 3.2. Optimized percent solid loading for efficient enzymatic hydrolysis The effects of percent solid loading of alkaline pretreated rice straw on enzymatic hydrolysis were studied. It was found that Table 1 Composition of native rice straw and rice straw after pretreatment. Component
Cellulose Hemicellulose Lignin Ash
% (w/w) Native rice straw
Pretreated rice straw
38.89 23.21 20.65 17.25
69.87 18.09 3.28 8.76
Fig. 1. Effect of solid loading on release glucose (A) and xylose (B) concentration during enzymatic hydrolysis of alkaline pretreated rice straw. The reaction contained pretreated rice straw at different solid loading of 5%, 8%, 10% and 15% by weight with 25 FPU/g solid in 50 mM sodium citrate buffer pH 4.8 and incubated at 30 °C for 96 h. Symbols are for 5% solid loading; j for 8% solid loading; N for 10% solid loading and for 15% solid loading.
glucose and xylose concentration increased rapidly during the first 24 h of hydrolysis under all solid loading conditions. Increasing percent solid loading from 5% to 15% led to an increase in releasing glucose from 34.8 to 60.4 g/L (Fig. 1) while no significant increase in releasing xylose was observed under different solid loading. The yield of releasing glucose and xylose was decreased with increasing solid from 5% to 15%. This was likely due to a limitation in mixing at high percent solid loading (Cara et al., 2007). As a result, the optimal hydrolysis condition was carried out at 5% solid loading with hydrolysis time of 72 h. Under this condition, 42.8 g/L of reducing sugars was achieved which was equivalent to the release of 81.6% and 62.8% of available glucose from cellulose and available xylose from hemicelluloses, respectively. It should be noted that saccharification yield obtained from enzymatic hydrolysis can be varied depending on the chemical and physical properties of each biomass and type of pretreatment methods used. Nevertheless, the saccharification yield of pretreated rice straw obtained in this study was comparable to those of other pretreated biomass feedstock. For instance, sugarcane bagasse digested by cellulose of 15 FPU/g solid plus b-glucosidase of 10 CBU/g solid for 48 h yielded 85.3% of reducing glucose and 48.7% of reducing xylose (Zhao et al., 2011). The results, thus, indicated comparable efficiency of enzymatic hydrolysis of rice straw in this study with previous works. 3.3. Ethanol fermentation performance by mono- and co-culture Co-fermentation of biomass-derived sugars with glucose-consuming and xylose-consuming yeasts has been proposed as a
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Fig. 2. Comparison of ethanol production performance by mono- and co-culture in simultaneous saccharification and co-fermentation (SSCF) of rice straw: (A) monoculture of S. cerevisiae, (B) monoculture of S. stipitis, (C) monoculture of C. tropicalis, (D) co-culture of S. cerevisiae/S. stipitis and (E) co-culture of S. cerevisiae/C. tropicalis. The fermentation mixtures of 100 ml in 250 ml screw-capped bottles contained 4.6% pretreated rice straw in basal medium, pH 5.0 pre-hydrolysed with 25 FPU/g accellerase at 30 °C for 6 h, inoculated with initial OD600 of 1 for monoculture and of 0.5:0.5 for co-culture and incubated at 30 °C for 48 h with continuous shaking at 150 rpm. Symbols are for glucose; j for xylose; and N for ethanol.
Table 2 Comparative ethanol fermentation performance of mono- and co-culture in simultaneous saccharification and co-fermentation (SSCF) process. The culture with the highest ethanol fermentation efficiency is highlighted in bold. Experiments were performed in triplicate as described in Section 2. Strains
Initial OD600
EtOH conc. (g/L)
EtOH yield (g/g)
S. cerevisiae S. stipitis C. tropicalis S. cerevisiae/S. stipitis S. cerevisiae/C. tropicalis
1 1 1 0.5:0.5 0.5:0.5
12.17 ± 0.61 12.75 ± 1.28 13.38 ± 0.34 14.11 ± 0.62 13.00 ± 0.30
0.41 0.42 0.45 0.47 0.43
promising strategy for maximizing ethanol production from lignocellulosic biomass hydrolysates. In this study, co-fermentation process has been optimized for lignocellulosic ethanol production
from pretreated rice straw. Initially, fermentation performance by mono- and co-culture of ethanogenic yeasts (S. cerevisiae, S. stipitis and C. tropicalis) were compared in order to select for the most efficient combination of yeasts for maximizing ethanol production. As shown in Fig. 2 and Table 2, fermentation of pretreated rice straw with S. cerevisiae, S. stipitis, and C. tropicalis led to the final ethanol concentration of 12.1 g/L, 12.7 g/L, and 13.3 g/L, respectively. Glucose was efficiently utilized by all yeasts. On the other hand, xylose was not assimilated by S. cerevisiae while it was consumed by S. stipitis and C. tropicalis. In monoculture, the presence of glucose prevented xylose uptake in the early phase due to repression and competition of common transporters (Meinander and Hahn-hagerdal, 1999). Xylose consumption occurred after 24 h when the glucose concentration has been reduced below the threshold for xylose utilization in both S. stipitis and C. tropicalis
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cultures. Substantial higher glucose and xylose utilization was obtained in co-culture of S. cerevisiae and S. stipitis compared to monoculture of each yeast strain. Co-culture of S. cerevisiae and S. stipitis led to an enhanced ethanol production of 14.1 g/L (Fig. 2), approximately 11% improvement compared with monoculture. The S. cerevisiae/S. stipitis co-culture yielded the highest ethanol production efficiency with ethanol yield of 0.47 g/g, equivalent to 92% of theoretical yield based on the total reducing sugar yield. In this co-culture, conversion of glucose and xylose to ethanol was observed in the early phase, suggesting co-conversion of both glucose and xylose to ethanol by the co-culture. Interestingly, there was no improvement in ethanol production by the co-culture of S. cerevisiae and C. tropicalis compared to monoculture which could be due to the difference in growth characteristics and metabolite excretion profiles between these two yeasts (Urk et al., 1988). Table 2 summarizes ethanol fermentation performance of mono- and co-culture. The ethanol production performance of S. cerevisiae/S. stipitis co-culture in this study outperformed previous result which produced ethanol concentration of 12 g/L and ethanol yield of 0.40 g/g from pretreated rice straw by the co-culture (Yadav et al., 2011). Based on the results, co-culture system of S. cerevisiae and S. stipitis was then selected for further optimization. 3.4. Co-culture optimization by design of experiment for efficient ethanol fermentation Optimization of fermentation process parameters for S. cerevisiae and S. stipitis co-culture was performed using a systematic experimental design approach. Parameters influencing ethanol production performance examined in this study were (i) cell ratio of S. cerevisiae and S. stipitis, (ii) available dissolved oxygen, and (iii) culture temperature. Cell ratio between S. cerevisiae and S. stipitis is related to assimilation rate of glucose and xylose by the yeasts. Thus, this parameter is considered a major factor on ethanol production efficiency. Effect of oxygen availability, which is directly correlated to agitation speed, on ethanol production was also investigated. Temperature is also a key factor on yeast growth and metabolism. Therefore, this parameter was optimized as well for ethanol fermentation. For a systematic approach of process optimization, design of experiment (DoE) was applied in order to determine the optimal conditions for maximizing ethanol production. The optimization experiments were designed based on Central Composite Design (CCD) model to measure the effect of each parameter on ethanol production performance and to optimize for the maximal yield of ethanol. CCD is a type of DoE allowing
Fig. 3. Coefficient showing a relative impact of cell ratio, agitation, temperature and their interactions on the ethanol yield of S. cerevisiae/S. stipitis co-culture in simultaneous saccharification and co-fermentation (SSCF) of rice straw based on the CCD predictive model.
for the estimation of effects of multiple parameter and their interacting effects on process outputs. CCD was applied to evaluate their effects and interactions on the ethanol yield. Each variable was varied at three factional levels, coded as 1 (lowest value), 0 (middle value), and +1 (highest value). Investigative optimization conditions of the three parameters were summarized in Table 3. The parameters under investigation are temperature at 25, 30 and 35 °C; shaking rate at 100, 150 and 200 rpm; and S. cerevisiae/S. stipitis cell ratio at 0.25/0.75, 0.5/0.5 and 0.75/0.25. In this study, a total of 16 experimental runs with different conditions of three process parameters and duplicate of the center point were conducted. These 16 combinations include three blocks of five experiments with two center points. 3.5. Effect of co-culture process parameters on ethanol production performance As shown in Table 3 ethanol production varied under different fermentation conditions in the range of 11.7–14.6 g/L which is equivalent to percent theoretical yields of 76–95%. Analysis based on the CCD model revealed a high reliability between measured yield and yield predicted by the model with a slope of 0.99 and R2 of 0.89 (result not shown) suggesting the high accuracy of the model used in this study. Thus, the model was applied to predict
Table 3 Optimization experiment design and ethanol production performance of S. cerevisiae and S. stipitis co-culture by simultaneous saccharification and co-fermentation (SSCF). The culture with the highest ethanol fermentation efficiency is highlighted in bold. Experiments were performed in triplicate as described in Section 2. Run No.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Co-culture condition
Ethanol production performance
Cell ratio
RPM
Temp (°C)
Initial OD600 S.cerevisiae
Initial OD600 S.stipitis
OD ratio
EtoH conc. (g/L)
Etoh yield (g/g)
% Theoretical yield
0.25 0.25 0.25 0.25 0.75 0.75 0.75 0.75 0.25 0.75 0.5 0.5 0.5 0.5 0.5 0.5
100 100 200 200 100 100 200 200 150 150 100 200 150 150 150 150
25 35 25 35 25 35 25 35 30 30 30 30 25 35 30 30
0.25 0.25 0.25 0.25 0.75 0.75 0.75 0.75 0.25 0.75 0.5 0.5 0.5 0.5 0.5 0.5
0.75 0.75 0.75 0.75 0.25 0.25 0.25 0.25 0.75 0.25 0.5 0.5 0.5 0.5 0.5 0.5
1:3 1:3 1:3 1:3 3:1 3:1 3:1 3:1 1:3 3:1 1:1 1:1 1:1 1:1 1:1 1:1
13.52 ± 0.18 14.63 ± 0.12 11.76 ± 0.50 13.70 ± 0.11 12.68 ± 0.29 14.34 ± 0.61 11.93 ± 1.01 12.64 ± 0.40 14.66 ± 0.24 13.73 ± 0.36 14.02 ± 0.10 14.09±0.21 13.29±0.23 14.43±0.41 14.21±0.48 14.39±0.43
0.451 0.488 0.392 0.457 0.423 0.478 0.398 0.421 0.489 0.458 0.467 0.47 0.443 0.481 0.474 0.48
88.19 95.47 76.72 89.39 82.71 93.51 77.83 82.48 95.61 89.59 91.45 91.9 86.72 94.12 92.69 93.86
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Table 4 Predictive model to estimate a significant of variance by ANOVA analysis. Analysis of variance (ANOVA) measures the statistical significance of the relationship between the prediction and measured results. The fitness of the model (R2) was 90.18%, validating the model accuracy. Parameters with p value 60.05 highlighted in bold are considered significant parameters affecting the ethanol yield of the co-culture. Variances
Sum of squares
Means square
F Statistic
p Value
Cell ratio Cell ratio cell ratio Agitation Agitation agitation Temp Temp temp Cell ratio agitation Cell ratio temp Agitation temp
37.0911 7.1800 108.8806 17.5154 183.2236 38.6636 0.3273 2.5237 0.0715
Degree of freedom 1 1 1 1 1 1 1 1 1
37.0911 7.1800 108.8806 17.5154 183.2236 38.6636 0.3273 2.5237 0.0715
4.14184 0.80177 12.15834 1.95589 20.45998 4.31744 0.03655 0.28181 0.00798
0.088034 0.405053 0.013033 0.211460 0.004004 0.082982 0.854696 0.614581 0.931721
Residual Total
53.7313 547.5278
6 15
8.9552
the optimal conditions for ethanol production from simultaneous saccharification and co-fermentation (SSCF) of rice straw. Fig. 3 shows the degree of impact of each SSCF process parameter which is determined by the magnitude of the coefficients on ethanol production. A negative coefficient of the parameters suggested that decreasing such parameter would result in positive effect on the ethanol yield. As a result, a lower in cell ratio and agitation is preferred for an increase in ethanol yield. The lower cell ratio of S. cerevisiae permits a slow constant release of glucose during saccharification which is beneficial for xylose uptake by xylose-fermenting strain resulting in high ethanol yield at low cell ratio. The effect of agitation is directly correlated to dissolved oxygen in the culture. The results thus reflect an optimally balanced oxygenation condition between the glucose assimilating anaerobic ethanol producer, S. cerevisiae, and the xylose consuming aerobic ethanol producer, S. stipitis, which are different in optimal growth. At low agitation the dissolved oxygen was maintained at low level but sufficient for ethanol fermentation by S. stipitis which would result in high ethanol yield. Based on the magnitude of the
coefficients, temperature has the most significant impact on ethanol yield. Increasing in temperature resulted in an increase in yield of ethanol. This is likely due to the effect of temperature on enzyme kinetics that channeling fluxes towards ethanol fermentative pathway in yeast metabolism. 3.6. Identification of optimal co-culture conditions for maximizing ethanol yield The yield response was fitted with second-order polynomial model. On the basis of response surface regression, the ethanol yield can be predicted using the following equation:
Y EtOH ¼ 93:926 3:851 ðCell ratioÞ 3:300 ðCell ratioÞ2 6:599 ðAgitationÞ 5:155 ðAgitationÞ2 þ 8:560 ðTÞ 7:659 ðTÞ2 þ 0:404 ðCell ratioÞ ðAgitationÞ 1:123 ðCell ratioÞ ðTÞ 0:189 ðAgitationÞ
Fig. 4. Response surface of yield of ethanol showing the influence of (A) cell ratio and agitation, (B) cell ratio and temperature, and (C) agitation and temperature for S. cerevisiae/S. stipitis co-culture in simultaneous saccharification and co-fermentation (SSCF) process. The predicted optimal fermentation conditions for maximization of ethanol yield is at a cell ratio of 0.31:0.69, agitation rate of 116 rpm and temperature of 33.1 °C. The ethanol yield is present in percent of theoretical yield.
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Table 5 Predicted and measured ethanol fermentation performance under optimized culture conditions in small-scale and large-scale simultaneous saccharification and cofermentation (SSCF) process. Small-scale SSCF was conducted in 250 ml screw-capped bottle while large-scale SSCF was conducted in 2 L bioreactor for 72 h. Ethanol production performance
Model prediction
Small-scale SSCF
Large-scale SSCF
Ethanol concentration (g/L) Ethanol yield (g/g) Percent of theoretical yield (%)
14.8
15.2
15.1
0.49 97.0
0.507 99.1
0.505 98.9
Fig. 5. Fermentation kinetics of S. cerevisiae/S. stipitis co-culture in simultaneous saccharification and co-fermentation (SSCF) process in small-scale capped bottle (A) and in large-scale bioreactor (B). The fermentation was performed under optimal condition at cell ratio of 0.31:0.69, temperature of 33.1 °C and agitation of 116 rpm for 72 h. Symbols are for glucose; j for xylose; and N for ethanol. Results show high efficiency and scalability of SSCF process under optimized conditions.
where YEtOH is ethanol yield in gram of ethanol per gram of total sugar. All parameters are present in term of coded level values. The relation between coded level and actual values are cell ratio: actual = 0.5 (coded level) + 0.25; agitation: actual = 150 (coded level) + 50; temperature: actual = 150 (coded level) + 50. The model prediction equation simultaneously determined individual and interactive effects of three parameters affecting the yield of ethanol. The model was used to find the significant interaction effect of these parameters and the maximum point of ethanol production. Statistical assessment of variances (ANOVA) was also performed to predict the significance of each parameter on ethanol production performance. Table 4 shows significant effect of agitation and temperature (present in bold) on the ethanol yield based on the p-value of ANOVA analysis. Any parameter with the p-value of less than 0.05 is considered significant parameter on production outlet of the predicted model. Moreover, the result showed regression analysis (R2) of the model at 90.18%. This R2 value indicated the high accuracy of the model in predicting the ethanol yield. Response surface plot of theoretical yield as a function of different culture parameters are shown in Fig. 4. The plot illustrates effects of three parameters on ethanol yield. The maximal ethanol yield could be promoted at low cell ratio, low agitation rate and high temperature. The model predicted the optimal conditions as follows: cell ratio of S. cerevisiae:S. stipitis at 0.31; temperature at 33.1 °C and agitation at 116 rpm. The predicted maximum ethanol concentration is 14.8 g/L which is equivalent to 97% theoretical yield. The predictive results reflect the optimal balanced conditions of the co-culture of S. cerevisiae and S. stipitis which are different in optimal growth temperatures and dissolved oxygen level for conversion of composite biomass sugars to ethanol (Ruohonen et al., 2006). Verification of the predicted optimal parameters for the most efficient ethanol production performance in SSCF process was then performed.
Fig. 6. Fermentation kinetics of S. cerevisiae/S. stipitis co-culture in simultaneous saccharification and co-fermentation (SSCF) process in large-scale bioreactor at high biomass concentration at 8% by weight (A) and 10% by weight (B). The fermentation was performed under optimal conditions at cell ratio of 0.31:0.69, temperature of 33.1 °C and agitation of 116 rpm for 72 h. Symbols are for glucose; j for xylose; and N for ethanol. Results show high titer of ethanol with high yield achieved at high biomass concentration.
3.7. Model validation for the most efficient simultaneous saccharification and co-fermentation of ethanol To validate the predictive model, simultaneous saccharification and co-fermentation was performed in small-scale 250 ml capped bottle as well as was scaled-up in 2 L bioreactor under optimal conditions: cell ratio of 0.31:0.69, temperature of 33.1 °C and agitation of 116 rpm. Fig. 5 shows time profiles of sugar concentration and ethanol production. Glucose concentration initially increased due to an imbalance between rate of sugar release and rate of sugar uptake. The concentration of glucose rapidly decreased after 4 h and maintained at low concentration after 36 h. Xylose concentration continually increased in the first 30 h and quickly decreased at 48 h. Ethanol concentration increased in the first 24 h and level off after 48 h. Under optimal conditions the maximum ethanol concentration achieved was 15.2 g/L with the maximum ethanol yield of 0.50 g/g. The results were consistent with the model analysis
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which predicted the ethanol concentration of 14.8 g/L and the ethanol yield of 0.49 g/g under the optimal condition. Comparison between small scale and large scale fermentation shown in Table 5 are in good agreement suggesting the scalability of this SSCF process. 3.8. SSCF co-culture process under optimal conditions at high solid loading To meet economical feasibility in ethanol production processes from lignocellulosic biomass, high titer of ethanol must be achieved. Thus, batch SSCF process was performed at high biomass concentration of 8% and 10% by weight. The time profiles of sugar and ethanol concentration are shown in Fig. 6. The maximum ethanol concentration achieved was 23.5 g/L and 28.6 g/L, corresponding to ethanol yield of 88% and 86% at 8% and 10% biomass concentration, respectively. A decrease in ethanol yield is likely due to high viscosity and reduced mass transfer in fermentation process caused by high concentration of biomass. The decrease in yield at high solid concentration was also reported in other previous studies (Ohgren et al., 2006; Rudolf et al., 2008). To improve ethanol production, pre-hydrolysis as well as optimizing hydrolysis temperature and hydrolysis time is suggested to decrease the viscosity of high solid biomass fermentation. 4. Conclusion Rice straw SSCF process by S. cerevisiae and S. stipitis co-culture for ethanol production was systematically optimized using design of experiment. First, alkaline pretreatment was applied to remove lignin as well as to improve enzymatic digestibility of the pretreated biomass. High release sugar yield based on pretreated biomass was achieved from hydrolysis at optimized solid loading. Optimization of SSCF conditions using DoE model showed that the co-culture favored high temperature, low cell ratio and low agitation for maximizing ethanol production efficiency. This study could provide basis for improvement of ethanol production efficiency and economics in SSCF process of lignocellulosic biomass. Acknowledgement The authors would like to acknowledge financial support from King Mongkut’s University of Technology Thonburi and Thailand Research Fund and National Science and Technology Development Agency (Grant number DD 142).
References Binod, P., 2010. Bioethanol production from rice straw: an review. Bioresour. Technol. 101, 4767–4774. Brodeur, G., Yau, E., Badal, K., Collier, J., Ramachandran, K.B., Ramakrishnan, S., 2011. Chemical and physicochemical pretreatment of lignocellulosic biomass: a review. Enzyme Res.. http://dx.doi.org/10.4061/2011/787532. Cara, C., Moya, M., Ballesteros, I., Negro, M.J., Gonzalez, A., Ruiz, E., 2007. Influence of solid loading on enzymatic hydrolysis of steam exploded or liquid hot water pretreated olive tree biomass. Process Biochem. 42, 1003–1009. Meinander, N., Hahn-hagerdal, B., 1999. Fermentation of xylose/glucose mixtures by metabolically engineered Saccharomyces cerevisiae strains expressing XYL1 and XYL2 from pichia stipitis with and without overexpression of TAL1. Bioresour. Technol. 68, 79–87. Miller, G.L., 1959. Using dinitrosalicylic acid for determination of reducing sugar. Anal. Chem. 31, 426–428. Nigam, P.S., Singh, A., 2011. Production of liquid biofuels from renewable resources. Prog. Energy 37, 52–68. Ohgren, K., Bengtsson, O., Gorwa-Grauslund, M.F., Galbe, M., Hahn-Hagerdal, B., Zacchi, G., 2006. Simultaneous saccharification and co-fermentation of glucose and xylose in steam-pretreated corn stover at high fiber content with Saccharomyces cerevisiae TMB3400. J. Biotechnol. 126, 488–498. Qian, M., Tian, S., Li, X., Zhang, J., Pan, Y., Yang, X., 2006. Ethanol production from diluted-acid softwood hydrolysate by co-culture. Appl. Biochem. Biotechnol. 134, 273–283. Rudolf, A., Baudel, H., Zacchi, G., Hahn-Hagerdal, B., Liden, G., 2008. Simultaneous saccharification and fermentation of steam pretreated bagasse using Saccharomyces cerevisiae TMB3400 and Pichia stipitis CBS6054. Biotechnol. Bioeng. 99, 783–790. Ruohonen, L., Aristidou, A., Frey, A.D., Penttila, M., Kallio, P.T., 2006. Expression of Vitreoscilla hemoglobin improves the metabolism of xylose in recombinant yeast Saccharomyces cerevisiae under low oxygen conditions. Enzyme Microb. Technol. 39, 6–14. Shinozaki, Y., Kitamoto, H.K., 2011. Ethanol production from ensiled rice straw and whole-crop silage by the simultaneous enzymatic saccharification and fermentation process. Biosci. Bioeng. 111, 320–325. Sluiter, A., Hames, B., Ruiz, R., Scarlata, C., Sluiter, J., Templeton, D., 2008. Determination of Structural Carbohydrates and Lignin in Biomass. National Renewable Energy Laboratory, Golden, CO. Unrean, P., Nguyen, N.H., 2012. Rational optimization of culture conditions for the most efficient ethanol production in Scheffersomyces stipitis using design of experiments. Biotechnol. Prog. 28, 1119–1125. Urk, H.V., Mark, P.R., Scheffers, W.A., Van-Dijken, J.P., 1988. Metabolic responses of Saccharomyces cerevisiae CBS 8066 and Candida utilis CBS 621 upon transition from glucose limitation to glucose excess. Yeast 4, 283–291. Wingren, A., Galbe, M., Zacchi, G., 2003. Techno-economic evaluation of producing ethanol from soft wood a comparison of SSF and SHF and identification of bottlenecks. Biotechnol. Prog. 19, 1109–1117. Yadav, K.S., Naseeruddin, S., Prashanthi, G.S., Sateesh, L., Rao, L.V., 2011. Bioethanol fermentation of concentrated rice straw hydrolysate using co-culture of Saccharomyces cerevisiae and Pichia stipitis. Bioresour. Technol. 102, 6473–6478. Zhao, X., Song, Y., Liu, D., 2011. Enzymatic hydrolysis and simultaneous saccharification and fermentation of alkali/peracetic acid-pretreatment sugarcane bagasse for ethanol and 2,3-butanediol production. Enzyme Microb. Technol. 49, 413–419.
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Bioresource Technology journal homepage: www.elsevier.com/locate/biortech
Optimized simultaneous saccharification and co-fermentation of rice straw for ethanol production by Saccharomyces cerevisiae and Scheffersomyces stipitis co-culture using design of experiments Nopparat Suriyachai a, Khatiya Weerasaia a, Navadol Laosiripojana a, Verawat Champreda b, Pornkamol Unrean b,⇑ a b
The Joint Graduate School of Energy and Environment, King Mongkut’s University of Technology Thonburi, 126 Pracha Uthit Rd., Tungkru, Bangkok 10140, Thailand National Center for Genetic Engineering and Biotechnology (BIOTEC), 113 Thailand Science Park, Paholyothin Road, Klong 1, Klong Luang, Pathumthani 12120, Thailand
h i g h l i g h t s Co-culture SSCF process of rice straw for ethanol production was optimized. Effect of solid loading on enzyme hydrolysis was examined. Co-culture was systematically optimized using design of experiment (DoE) approach. Highly efficient and scalable SSCF by co-culture yielded 99% of theoretical yield. Maximum ethanol concentration achieved by co-culture SSCF process was 28.6 g/L.
a r t i c l e
i n f o
Article history: Received 22 February 2013 Received in revised form 30 April 2013 Accepted 2 May 2013 Available online 10 May 2013 Keywords: Design of experiment Simultaneous saccharification and cofermentation (SSCF) optimization Co-culture Ethanol
a b s t r a c t Herein an ethanol production process from rice straw was optimized. Simultaneous saccharification and co-fermentation (SSCF) using Saccharomyces cerevisiae and Scheffersomyces stipitis co-culture was carried out to enhance ethanol production. The optimal saccharification solid loading was 5%. Key fermentation parameters for co-culture including cell ratio, agitation rate and temperature was rationally optimized using design of experiment (DoE). Optimized co-culture conditions for maximum ethanol production efficiency were at S. cerevisiae:S. stipitis cell ratio of 0.31, agitation rate of 116 rpm and temperature of 33.1 °C. The optimized SSCF process reached ethanol titer of 15.2 g/L and ethanol yield of 99% of theoretical yield, consistent with the DoE model prediction. Moreover, SSCF process under high biomass concentration resulted in high ethanol concentration of 28.6 g/L. This work suggests the efficiency and scalability of the developed SSCF process which could provide an important basis for the economic feasibility of ethanol production from lignocelluloses. Ó 2013 Elsevier Ltd. All rights reserved.
1. Introduction Current increase in industrialization and transportation causes the rising of energy demand which leads to a fast depleting of fossil fuel and oil reserve. Fossil fuel currently takes up approximately 80% of the world primary energy, resulting in increasing economic and environmental concerns (Nigam and Singh, 2011). Thus, finding suitable fuel alternative is an important energy security and environmental issues worldwide. At present, biofuels are considered potential clean alternatives, which can be produced as liquid, gas and/or solid fuels from lignocellulosic biomass. Bioethanol produced from lignocellulose is an attractive alternative since
⇑ Corresponding author. Tel.: +66 8 8681 6012. E-mail address: [email protected] (P. Unrean). 0960-8524/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.biortech.2013.05.003
lignocellulosic materials do not compete with the food supply and are less expensive than conventional agricultural feedstock. In general, lignocellulosic ethanol production requires several steps including pretreatment of biomass feedstock; saccharification process to release fermentable hexoses and pentoses from polysaccharides; fermentation of released sugars and distillation step for ethanol separation. Lignocellulosic biomass contains various hexoses and pentoses including glucose, xylose, mannose and arabinose which may not be efficiently converted to ethanol. Thus, developing an efficient process for hydrolysis of lignocellulose into sugars and for fermentation of all available sugars to ethanol could potentially decrease the cost of lignocellulosic ethanol production process. Biomass feedstock such as rice straw is considered one of the most abundant biomass in the world. Rice straw is naturally more recalcitrant to degradation than other agriculture residues. Several reports on pretreatment with enzymatic saccharification
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result in a high conversion yield of cellulose and hemicellulose to fermentable sugars up to 80–90% of the theoretical yield (Shinozaki and Kitamoto, 2011). However, content of lignin in hydrolysates often interferes with fermentation process resulting in low ethanol production efficiency. Herein we have applied optimized pretreatment process previously developed to maximize the removal of lignin from hydrolysates. However, hydrolysis and co-fermentation of hexoses and pentoses is a challenging task requiring optimization of multiple process parameters (Wingren et al., 2003; Qian et al., 2006). Since enzymatic hydrolysis and fermentation process of lignocelluosic hydrolysates requires multiple process parameters optimization to simultaneously determine the individual and interactive effects of many factors affecting ethanol production efficiency, we have optimized ethanol production from rice straw by simultaneous saccharification and co-fermentation (SSCF). The objective of the current work was to investigate hydrolysis and fermentation process of Saccharomyces cerevisiae and Scheffersomyces stipitis co-culture. Percent solid loading during enzymatic hydrolysis process was examined to maximize content of released sugars. Three fermentation process parameters: cell ratio, agitation and temperature were optimized for achieving high ethanol production yield. A systematic optimization based on statistical approach using Design of Experiment (DoE) was implemented. This approach permits a rapid and accurate optimization based on the statistical test to reduce residual variation. It is proven to be an efficient tool for minimizing number of experiments and for providing high accuracy of reasonable optimum prediction (Unrean and Nguyen, 2012). The optimized SSCF process present in this study permits an efficient conversion of both hexoses and pentoses from rice straw hydrolysates into ethanol. 2. Methods 2.1. Biomass feedstock preparation and pretreatment Rice straw was obtained from Suphanburi province (Thailand) and used as a substrate for ethanol production. For preparation step, the rice straw feedstock was cut by Retsch ZM200, passed through a sieve (mesh 18–35, an average size of 0.5–1.0 mm), air-dried in an oven at 70 °C for 24 h and stored at room temperature. The chemical compositions of feedstock were determined according to National Renewable Energy Laboratory (NREL) method (Sluiter et al., 2008). Milled rice straw was then pretreated using 5% sodium hydroxide at 90 °C for 20 min. The pretreatment was carried out at a ratio of 1 g (rice straw) per 5 ml of NaOH solution in an autoclave (Tomy autoclave SS-325, Tomy, Japan). After pretreatment, solid and liquid fractions were filtered through a filter paper (Whatman No. 5). The solid fractions were washed with tap water until pH was neutral. The pretreated substrate was dried at 105 °C and kept at room temperature for further experimental study. Samples were taken from solid fractions and analyzed for its composition after pretreatment using NREL method. The pretreatment efficiencies were determined based on biomass digestibility using a commercial cellulose substrate. 2.2. Enzymatic hydrolysis The pretreated rice straw was hydrolyzed with AccelleraseÒ 1500 enzyme (Danisco, Rochester, NY). The enzymatic hydrolysis was carried out using 5% (w/v) pretreated substrate in a 1 ml hydrolysis vessel containing 25 FPU/g, 50 mM sodium citrate buffer, pH 4.8 and 50 ll of 5% sodium azide. Sodium azide is used as a preservative for the enzyme. The mixture was incubated at 50 °C for 72 h with vertical rotation at 30 rpm. Hydrolysis experiments were
performed in triplicates. The released reducing sugar concentration was analyzed based on the amount of liberated reducing sugars using 3,5-dinitrosalisylic acid (DNS) method (Miller, 1959). Control reaction containing 30 g/L glucose was included. 2.3. Microorganisms and maintenance Hexose-utilizing yeast, S. cerevisiae (ThermosaccÒ Dry yeasts; Lallemand, Milwaukee, WI) and pentose-utilizing yeasts, Candida tropicalis (BCC30719) and S. stipitis (BCC15191), obtained from BIOTEC Culture Collection, BIOTEC, Thailand (http://biotec.or.th/bcc) were used in this study. The culture was maintained at 4 °C on a yeast minimal (YM) agar plate consisting of yeast extract, 10 g/L; peptone, 20 g/L; glucose, 20 g/L and agar, 16 g/L at pH of 4.8. 2.4. Inoculum preparation Seed cultures of S. cerevisiae, S. stipitis and C. tropicalis were used in all simultaneous saccharification and co-fermentation (SSCF) experiments. For preparation of inoculum, cells from agar plate were added into 250 ml flasks with a 100 ml working volume of yeast peptone dextrose (YPD) medium (1% yeast extract, 2% peptone and 2% glucose) and incubated at 30 °C on a rotary shaker at 150 rpm for 24 h. 2.5. Comparison of ethanol production performance by mono- and coculture The simultaneous saccharification and co-fermentation of ethanol by mono- or co-culture was performed in 250 ml screw-capped duran bottles containing 100 ml working volume of 4.6% (w/v) alkali pretreated and pre-hydrolyzed rice straw in basal medium with 50 mM sodium citrate buffer. The pre-hydrolysis reactions were incubated at 30 °C for 6 h before inoculation of YM medium overnight grown yeast cultures as specified to yield an initial OD600 of approximately 1. The inoculum was either mono-culture or co-culture at 1:1 cell ratio. The culture was incubated at 30 °C, pH 5.0 with a continuous mixing at 150 rpm for 48 h. Profiles of sugar utilization and ethanol production of these cultures were compared. The experiments were performed in triplicate. 2.6. Co-culture optimization by design of experiments The fermentation experiments were carried out in 46 g/L pretreated rice straw hydrolysate supplemented with yeast extract, 1 g/L; (NH4)2SO4, 5 g/L; MgSO47H2O, 0.025 g/L in 250 ml screwcapped duran bottle with a working volume of 100 ml, pH 5.0 for 48 h. The culture conditions were optimized using design of experiment by varying temperature at 25, 30 and 35 °C, with a shaking rate at 100, 150 and 200 rpm, and with a cell ratio of S. cerevisiae and S. stipitis at 0.25/0.75, 0.5/0.5 and 0.75/0.25. Each optimization experiments were performed in triplicate. Prior to fermentation, the biomass was pre-hydrolysed with 25 FPU/g accellerase at 30 °C for 6 h. Fermentation was carried out under examined condition for 48 h. Ethanol yield under various conditions were compared and their effects on the yield was examined using central composite design (CCD) and response surface methodology (RSM). The yield is present in percent of theoretical ethanol yield of consumed glucose and xylose, 0.511 g-ethanol/g-sugar. Data was analyzed using STATISTIC 8.0 (Statsoft, USA) for all statistical experimental design and graphical analysis. 2.7. Simultaneous saccharification and co-fermentation (SSCF) Batch SSCF experiments were performed in either 250 ml duran bottles with a final working volume of 100 ml or 2 L bioreactor
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(Biostat, B. Braun Biotech International) with a final working volume of 1 L. The fermentation medium contained rice straw at concentration as specified supplemented with 5 g/L (NH4)2SO4, 0.025 g/L MgSO47H2O, 1 g/L yeast extract, pH 5.0. The medium was sterilized at 121 °C for 20 min. The amount of enzyme loading was 25 FPU/g accellerase of WIS content. Enzyme was added at the beginning during pre-hydrolysis at 30 °C for 6 h. Fermentation was carried out under optimal cell ratio, temperature, and agitation as determined by DoE for maximizing ethanol fermentation by co-culture system. Samples were taken periodically for 72 h and analyzed for glucose, xylose and ethanol concentration. 2.8. Analysis Glucose, xylose and ethanol profiles were analyzed on a high performance liquid chromatography HPLC (SPD-M10A DAD, Shimadzu, Columbia, MD). The HPLC system is equipped with an autosampler (SIL-10AF), an Aminex HPX-87H column (Biorad Labs, Hercules, CA), a UV–vis detector (SPD-10A) and a refractive index detector (RID-10A). The column was run in an isocratic mode at 65 °C and 0.5 ml/min using a mobile phase of 5 mM H2SO4. The concentration of sugar and ethanol was determined from the standard curve correlating peak area to concentration. 3. Results and discussion 3.1. Alkaline pretreatment of rice straw The alkaline pretreatment step led to remarkable reduction in lignin content and substantial increase in cellulose content in the pretreated biomass feedstock. Table 1 shows the pretreated rice straw consisting of 69.8% cellulose, 18.1% hemicellulose, 3.2% lignin and 8.7% ash. Comparing the chemical components, alkaline pretreatment increased the proportion of cellulose by 79.6% and decreased the lignin proportion by 84.1%. The alkaline pretreatment condition used in this study improved digestibility of rice straw better than other pretreatment methods previously used for rice straw including ammonia pretreatment, acid pretreatment, organic solvent pretreatment and steam pretreatment. Additional effects by alkaline pretreatment also include decomposed lignin shield, decreased cellulose crystalline, increased surface area which permits more susceptibility of the alkaline pretreated biomass to subsequent enzymatic hydrolysis (Binod, 2010). This finding was also consistent with previous results that reported the delignification effects of alkaline pretreatment for lignocellulosic biomass like rapeseed straw, wheat straw and coastal bermuda grass. The pretreatment conditions were varied from 1.25 to 5% NaOH at 35–121 °C, resulting in 60–90% reduction of lignin (Brodeur et al., 2011). Interestingly, there was also a decrease in hemicelluloses content after pretreatment which is likely due to the effect of alkaline hydrolysis on hemicelluloses fraction. 3.2. Optimized percent solid loading for efficient enzymatic hydrolysis The effects of percent solid loading of alkaline pretreated rice straw on enzymatic hydrolysis were studied. It was found that Table 1 Composition of native rice straw and rice straw after pretreatment. Component
Cellulose Hemicellulose Lignin Ash
% (w/w) Native rice straw
Pretreated rice straw
38.89 23.21 20.65 17.25
69.87 18.09 3.28 8.76
Fig. 1. Effect of solid loading on release glucose (A) and xylose (B) concentration during enzymatic hydrolysis of alkaline pretreated rice straw. The reaction contained pretreated rice straw at different solid loading of 5%, 8%, 10% and 15% by weight with 25 FPU/g solid in 50 mM sodium citrate buffer pH 4.8 and incubated at 30 °C for 96 h. Symbols are for 5% solid loading; j for 8% solid loading; N for 10% solid loading and for 15% solid loading.
glucose and xylose concentration increased rapidly during the first 24 h of hydrolysis under all solid loading conditions. Increasing percent solid loading from 5% to 15% led to an increase in releasing glucose from 34.8 to 60.4 g/L (Fig. 1) while no significant increase in releasing xylose was observed under different solid loading. The yield of releasing glucose and xylose was decreased with increasing solid from 5% to 15%. This was likely due to a limitation in mixing at high percent solid loading (Cara et al., 2007). As a result, the optimal hydrolysis condition was carried out at 5% solid loading with hydrolysis time of 72 h. Under this condition, 42.8 g/L of reducing sugars was achieved which was equivalent to the release of 81.6% and 62.8% of available glucose from cellulose and available xylose from hemicelluloses, respectively. It should be noted that saccharification yield obtained from enzymatic hydrolysis can be varied depending on the chemical and physical properties of each biomass and type of pretreatment methods used. Nevertheless, the saccharification yield of pretreated rice straw obtained in this study was comparable to those of other pretreated biomass feedstock. For instance, sugarcane bagasse digested by cellulose of 15 FPU/g solid plus b-glucosidase of 10 CBU/g solid for 48 h yielded 85.3% of reducing glucose and 48.7% of reducing xylose (Zhao et al., 2011). The results, thus, indicated comparable efficiency of enzymatic hydrolysis of rice straw in this study with previous works. 3.3. Ethanol fermentation performance by mono- and co-culture Co-fermentation of biomass-derived sugars with glucose-consuming and xylose-consuming yeasts has been proposed as a
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Fig. 2. Comparison of ethanol production performance by mono- and co-culture in simultaneous saccharification and co-fermentation (SSCF) of rice straw: (A) monoculture of S. cerevisiae, (B) monoculture of S. stipitis, (C) monoculture of C. tropicalis, (D) co-culture of S. cerevisiae/S. stipitis and (E) co-culture of S. cerevisiae/C. tropicalis. The fermentation mixtures of 100 ml in 250 ml screw-capped bottles contained 4.6% pretreated rice straw in basal medium, pH 5.0 pre-hydrolysed with 25 FPU/g accellerase at 30 °C for 6 h, inoculated with initial OD600 of 1 for monoculture and of 0.5:0.5 for co-culture and incubated at 30 °C for 48 h with continuous shaking at 150 rpm. Symbols are for glucose; j for xylose; and N for ethanol.
Table 2 Comparative ethanol fermentation performance of mono- and co-culture in simultaneous saccharification and co-fermentation (SSCF) process. The culture with the highest ethanol fermentation efficiency is highlighted in bold. Experiments were performed in triplicate as described in Section 2. Strains
Initial OD600
EtOH conc. (g/L)
EtOH yield (g/g)
S. cerevisiae S. stipitis C. tropicalis S. cerevisiae/S. stipitis S. cerevisiae/C. tropicalis
1 1 1 0.5:0.5 0.5:0.5
12.17 ± 0.61 12.75 ± 1.28 13.38 ± 0.34 14.11 ± 0.62 13.00 ± 0.30
0.41 0.42 0.45 0.47 0.43
promising strategy for maximizing ethanol production from lignocellulosic biomass hydrolysates. In this study, co-fermentation process has been optimized for lignocellulosic ethanol production
from pretreated rice straw. Initially, fermentation performance by mono- and co-culture of ethanogenic yeasts (S. cerevisiae, S. stipitis and C. tropicalis) were compared in order to select for the most efficient combination of yeasts for maximizing ethanol production. As shown in Fig. 2 and Table 2, fermentation of pretreated rice straw with S. cerevisiae, S. stipitis, and C. tropicalis led to the final ethanol concentration of 12.1 g/L, 12.7 g/L, and 13.3 g/L, respectively. Glucose was efficiently utilized by all yeasts. On the other hand, xylose was not assimilated by S. cerevisiae while it was consumed by S. stipitis and C. tropicalis. In monoculture, the presence of glucose prevented xylose uptake in the early phase due to repression and competition of common transporters (Meinander and Hahn-hagerdal, 1999). Xylose consumption occurred after 24 h when the glucose concentration has been reduced below the threshold for xylose utilization in both S. stipitis and C. tropicalis
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cultures. Substantial higher glucose and xylose utilization was obtained in co-culture of S. cerevisiae and S. stipitis compared to monoculture of each yeast strain. Co-culture of S. cerevisiae and S. stipitis led to an enhanced ethanol production of 14.1 g/L (Fig. 2), approximately 11% improvement compared with monoculture. The S. cerevisiae/S. stipitis co-culture yielded the highest ethanol production efficiency with ethanol yield of 0.47 g/g, equivalent to 92% of theoretical yield based on the total reducing sugar yield. In this co-culture, conversion of glucose and xylose to ethanol was observed in the early phase, suggesting co-conversion of both glucose and xylose to ethanol by the co-culture. Interestingly, there was no improvement in ethanol production by the co-culture of S. cerevisiae and C. tropicalis compared to monoculture which could be due to the difference in growth characteristics and metabolite excretion profiles between these two yeasts (Urk et al., 1988). Table 2 summarizes ethanol fermentation performance of mono- and co-culture. The ethanol production performance of S. cerevisiae/S. stipitis co-culture in this study outperformed previous result which produced ethanol concentration of 12 g/L and ethanol yield of 0.40 g/g from pretreated rice straw by the co-culture (Yadav et al., 2011). Based on the results, co-culture system of S. cerevisiae and S. stipitis was then selected for further optimization. 3.4. Co-culture optimization by design of experiment for efficient ethanol fermentation Optimization of fermentation process parameters for S. cerevisiae and S. stipitis co-culture was performed using a systematic experimental design approach. Parameters influencing ethanol production performance examined in this study were (i) cell ratio of S. cerevisiae and S. stipitis, (ii) available dissolved oxygen, and (iii) culture temperature. Cell ratio between S. cerevisiae and S. stipitis is related to assimilation rate of glucose and xylose by the yeasts. Thus, this parameter is considered a major factor on ethanol production efficiency. Effect of oxygen availability, which is directly correlated to agitation speed, on ethanol production was also investigated. Temperature is also a key factor on yeast growth and metabolism. Therefore, this parameter was optimized as well for ethanol fermentation. For a systematic approach of process optimization, design of experiment (DoE) was applied in order to determine the optimal conditions for maximizing ethanol production. The optimization experiments were designed based on Central Composite Design (CCD) model to measure the effect of each parameter on ethanol production performance and to optimize for the maximal yield of ethanol. CCD is a type of DoE allowing
Fig. 3. Coefficient showing a relative impact of cell ratio, agitation, temperature and their interactions on the ethanol yield of S. cerevisiae/S. stipitis co-culture in simultaneous saccharification and co-fermentation (SSCF) of rice straw based on the CCD predictive model.
for the estimation of effects of multiple parameter and their interacting effects on process outputs. CCD was applied to evaluate their effects and interactions on the ethanol yield. Each variable was varied at three factional levels, coded as 1 (lowest value), 0 (middle value), and +1 (highest value). Investigative optimization conditions of the three parameters were summarized in Table 3. The parameters under investigation are temperature at 25, 30 and 35 °C; shaking rate at 100, 150 and 200 rpm; and S. cerevisiae/S. stipitis cell ratio at 0.25/0.75, 0.5/0.5 and 0.75/0.25. In this study, a total of 16 experimental runs with different conditions of three process parameters and duplicate of the center point were conducted. These 16 combinations include three blocks of five experiments with two center points. 3.5. Effect of co-culture process parameters on ethanol production performance As shown in Table 3 ethanol production varied under different fermentation conditions in the range of 11.7–14.6 g/L which is equivalent to percent theoretical yields of 76–95%. Analysis based on the CCD model revealed a high reliability between measured yield and yield predicted by the model with a slope of 0.99 and R2 of 0.89 (result not shown) suggesting the high accuracy of the model used in this study. Thus, the model was applied to predict
Table 3 Optimization experiment design and ethanol production performance of S. cerevisiae and S. stipitis co-culture by simultaneous saccharification and co-fermentation (SSCF). The culture with the highest ethanol fermentation efficiency is highlighted in bold. Experiments were performed in triplicate as described in Section 2. Run No.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Co-culture condition
Ethanol production performance
Cell ratio
RPM
Temp (°C)
Initial OD600 S.cerevisiae
Initial OD600 S.stipitis
OD ratio
EtoH conc. (g/L)
Etoh yield (g/g)
% Theoretical yield
0.25 0.25 0.25 0.25 0.75 0.75 0.75 0.75 0.25 0.75 0.5 0.5 0.5 0.5 0.5 0.5
100 100 200 200 100 100 200 200 150 150 100 200 150 150 150 150
25 35 25 35 25 35 25 35 30 30 30 30 25 35 30 30
0.25 0.25 0.25 0.25 0.75 0.75 0.75 0.75 0.25 0.75 0.5 0.5 0.5 0.5 0.5 0.5
0.75 0.75 0.75 0.75 0.25 0.25 0.25 0.25 0.75 0.25 0.5 0.5 0.5 0.5 0.5 0.5
1:3 1:3 1:3 1:3 3:1 3:1 3:1 3:1 1:3 3:1 1:1 1:1 1:1 1:1 1:1 1:1
13.52 ± 0.18 14.63 ± 0.12 11.76 ± 0.50 13.70 ± 0.11 12.68 ± 0.29 14.34 ± 0.61 11.93 ± 1.01 12.64 ± 0.40 14.66 ± 0.24 13.73 ± 0.36 14.02 ± 0.10 14.09±0.21 13.29±0.23 14.43±0.41 14.21±0.48 14.39±0.43
0.451 0.488 0.392 0.457 0.423 0.478 0.398 0.421 0.489 0.458 0.467 0.47 0.443 0.481 0.474 0.48
88.19 95.47 76.72 89.39 82.71 93.51 77.83 82.48 95.61 89.59 91.45 91.9 86.72 94.12 92.69 93.86
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Table 4 Predictive model to estimate a significant of variance by ANOVA analysis. Analysis of variance (ANOVA) measures the statistical significance of the relationship between the prediction and measured results. The fitness of the model (R2) was 90.18%, validating the model accuracy. Parameters with p value 60.05 highlighted in bold are considered significant parameters affecting the ethanol yield of the co-culture. Variances
Sum of squares
Means square
F Statistic
p Value
Cell ratio Cell ratio cell ratio Agitation Agitation agitation Temp Temp temp Cell ratio agitation Cell ratio temp Agitation temp
37.0911 7.1800 108.8806 17.5154 183.2236 38.6636 0.3273 2.5237 0.0715
Degree of freedom 1 1 1 1 1 1 1 1 1
37.0911 7.1800 108.8806 17.5154 183.2236 38.6636 0.3273 2.5237 0.0715
4.14184 0.80177 12.15834 1.95589 20.45998 4.31744 0.03655 0.28181 0.00798
0.088034 0.405053 0.013033 0.211460 0.004004 0.082982 0.854696 0.614581 0.931721
Residual Total
53.7313 547.5278
6 15
8.9552
the optimal conditions for ethanol production from simultaneous saccharification and co-fermentation (SSCF) of rice straw. Fig. 3 shows the degree of impact of each SSCF process parameter which is determined by the magnitude of the coefficients on ethanol production. A negative coefficient of the parameters suggested that decreasing such parameter would result in positive effect on the ethanol yield. As a result, a lower in cell ratio and agitation is preferred for an increase in ethanol yield. The lower cell ratio of S. cerevisiae permits a slow constant release of glucose during saccharification which is beneficial for xylose uptake by xylose-fermenting strain resulting in high ethanol yield at low cell ratio. The effect of agitation is directly correlated to dissolved oxygen in the culture. The results thus reflect an optimally balanced oxygenation condition between the glucose assimilating anaerobic ethanol producer, S. cerevisiae, and the xylose consuming aerobic ethanol producer, S. stipitis, which are different in optimal growth. At low agitation the dissolved oxygen was maintained at low level but sufficient for ethanol fermentation by S. stipitis which would result in high ethanol yield. Based on the magnitude of the
coefficients, temperature has the most significant impact on ethanol yield. Increasing in temperature resulted in an increase in yield of ethanol. This is likely due to the effect of temperature on enzyme kinetics that channeling fluxes towards ethanol fermentative pathway in yeast metabolism. 3.6. Identification of optimal co-culture conditions for maximizing ethanol yield The yield response was fitted with second-order polynomial model. On the basis of response surface regression, the ethanol yield can be predicted using the following equation:
Y EtOH ¼ 93:926 3:851 ðCell ratioÞ 3:300 ðCell ratioÞ2 6:599 ðAgitationÞ 5:155 ðAgitationÞ2 þ 8:560 ðTÞ 7:659 ðTÞ2 þ 0:404 ðCell ratioÞ ðAgitationÞ 1:123 ðCell ratioÞ ðTÞ 0:189 ðAgitationÞ
Fig. 4. Response surface of yield of ethanol showing the influence of (A) cell ratio and agitation, (B) cell ratio and temperature, and (C) agitation and temperature for S. cerevisiae/S. stipitis co-culture in simultaneous saccharification and co-fermentation (SSCF) process. The predicted optimal fermentation conditions for maximization of ethanol yield is at a cell ratio of 0.31:0.69, agitation rate of 116 rpm and temperature of 33.1 °C. The ethanol yield is present in percent of theoretical yield.
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Table 5 Predicted and measured ethanol fermentation performance under optimized culture conditions in small-scale and large-scale simultaneous saccharification and cofermentation (SSCF) process. Small-scale SSCF was conducted in 250 ml screw-capped bottle while large-scale SSCF was conducted in 2 L bioreactor for 72 h. Ethanol production performance
Model prediction
Small-scale SSCF
Large-scale SSCF
Ethanol concentration (g/L) Ethanol yield (g/g) Percent of theoretical yield (%)
14.8
15.2
15.1
0.49 97.0
0.507 99.1
0.505 98.9
Fig. 5. Fermentation kinetics of S. cerevisiae/S. stipitis co-culture in simultaneous saccharification and co-fermentation (SSCF) process in small-scale capped bottle (A) and in large-scale bioreactor (B). The fermentation was performed under optimal condition at cell ratio of 0.31:0.69, temperature of 33.1 °C and agitation of 116 rpm for 72 h. Symbols are for glucose; j for xylose; and N for ethanol. Results show high efficiency and scalability of SSCF process under optimized conditions.
where YEtOH is ethanol yield in gram of ethanol per gram of total sugar. All parameters are present in term of coded level values. The relation between coded level and actual values are cell ratio: actual = 0.5 (coded level) + 0.25; agitation: actual = 150 (coded level) + 50; temperature: actual = 150 (coded level) + 50. The model prediction equation simultaneously determined individual and interactive effects of three parameters affecting the yield of ethanol. The model was used to find the significant interaction effect of these parameters and the maximum point of ethanol production. Statistical assessment of variances (ANOVA) was also performed to predict the significance of each parameter on ethanol production performance. Table 4 shows significant effect of agitation and temperature (present in bold) on the ethanol yield based on the p-value of ANOVA analysis. Any parameter with the p-value of less than 0.05 is considered significant parameter on production outlet of the predicted model. Moreover, the result showed regression analysis (R2) of the model at 90.18%. This R2 value indicated the high accuracy of the model in predicting the ethanol yield. Response surface plot of theoretical yield as a function of different culture parameters are shown in Fig. 4. The plot illustrates effects of three parameters on ethanol yield. The maximal ethanol yield could be promoted at low cell ratio, low agitation rate and high temperature. The model predicted the optimal conditions as follows: cell ratio of S. cerevisiae:S. stipitis at 0.31; temperature at 33.1 °C and agitation at 116 rpm. The predicted maximum ethanol concentration is 14.8 g/L which is equivalent to 97% theoretical yield. The predictive results reflect the optimal balanced conditions of the co-culture of S. cerevisiae and S. stipitis which are different in optimal growth temperatures and dissolved oxygen level for conversion of composite biomass sugars to ethanol (Ruohonen et al., 2006). Verification of the predicted optimal parameters for the most efficient ethanol production performance in SSCF process was then performed.
Fig. 6. Fermentation kinetics of S. cerevisiae/S. stipitis co-culture in simultaneous saccharification and co-fermentation (SSCF) process in large-scale bioreactor at high biomass concentration at 8% by weight (A) and 10% by weight (B). The fermentation was performed under optimal conditions at cell ratio of 0.31:0.69, temperature of 33.1 °C and agitation of 116 rpm for 72 h. Symbols are for glucose; j for xylose; and N for ethanol. Results show high titer of ethanol with high yield achieved at high biomass concentration.
3.7. Model validation for the most efficient simultaneous saccharification and co-fermentation of ethanol To validate the predictive model, simultaneous saccharification and co-fermentation was performed in small-scale 250 ml capped bottle as well as was scaled-up in 2 L bioreactor under optimal conditions: cell ratio of 0.31:0.69, temperature of 33.1 °C and agitation of 116 rpm. Fig. 5 shows time profiles of sugar concentration and ethanol production. Glucose concentration initially increased due to an imbalance between rate of sugar release and rate of sugar uptake. The concentration of glucose rapidly decreased after 4 h and maintained at low concentration after 36 h. Xylose concentration continually increased in the first 30 h and quickly decreased at 48 h. Ethanol concentration increased in the first 24 h and level off after 48 h. Under optimal conditions the maximum ethanol concentration achieved was 15.2 g/L with the maximum ethanol yield of 0.50 g/g. The results were consistent with the model analysis
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which predicted the ethanol concentration of 14.8 g/L and the ethanol yield of 0.49 g/g under the optimal condition. Comparison between small scale and large scale fermentation shown in Table 5 are in good agreement suggesting the scalability of this SSCF process. 3.8. SSCF co-culture process under optimal conditions at high solid loading To meet economical feasibility in ethanol production processes from lignocellulosic biomass, high titer of ethanol must be achieved. Thus, batch SSCF process was performed at high biomass concentration of 8% and 10% by weight. The time profiles of sugar and ethanol concentration are shown in Fig. 6. The maximum ethanol concentration achieved was 23.5 g/L and 28.6 g/L, corresponding to ethanol yield of 88% and 86% at 8% and 10% biomass concentration, respectively. A decrease in ethanol yield is likely due to high viscosity and reduced mass transfer in fermentation process caused by high concentration of biomass. The decrease in yield at high solid concentration was also reported in other previous studies (Ohgren et al., 2006; Rudolf et al., 2008). To improve ethanol production, pre-hydrolysis as well as optimizing hydrolysis temperature and hydrolysis time is suggested to decrease the viscosity of high solid biomass fermentation. 4. Conclusion Rice straw SSCF process by S. cerevisiae and S. stipitis co-culture for ethanol production was systematically optimized using design of experiment. First, alkaline pretreatment was applied to remove lignin as well as to improve enzymatic digestibility of the pretreated biomass. High release sugar yield based on pretreated biomass was achieved from hydrolysis at optimized solid loading. Optimization of SSCF conditions using DoE model showed that the co-culture favored high temperature, low cell ratio and low agitation for maximizing ethanol production efficiency. This study could provide basis for improvement of ethanol production efficiency and economics in SSCF process of lignocellulosic biomass. Acknowledgement The authors would like to acknowledge financial support from King Mongkut’s University of Technology Thonburi and Thailand Research Fund and National Science and Technology Development Agency (Grant number DD 142).
References Binod, P., 2010. Bioethanol production from rice straw: an review. Bioresour. Technol. 101, 4767–4774. Brodeur, G., Yau, E., Badal, K., Collier, J., Ramachandran, K.B., Ramakrishnan, S., 2011. Chemical and physicochemical pretreatment of lignocellulosic biomass: a review. Enzyme Res.. http://dx.doi.org/10.4061/2011/787532. Cara, C., Moya, M., Ballesteros, I., Negro, M.J., Gonzalez, A., Ruiz, E., 2007. Influence of solid loading on enzymatic hydrolysis of steam exploded or liquid hot water pretreated olive tree biomass. Process Biochem. 42, 1003–1009. Meinander, N., Hahn-hagerdal, B., 1999. Fermentation of xylose/glucose mixtures by metabolically engineered Saccharomyces cerevisiae strains expressing XYL1 and XYL2 from pichia stipitis with and without overexpression of TAL1. Bioresour. Technol. 68, 79–87. Miller, G.L., 1959. Using dinitrosalicylic acid for determination of reducing sugar. Anal. Chem. 31, 426–428. Nigam, P.S., Singh, A., 2011. Production of liquid biofuels from renewable resources. Prog. Energy 37, 52–68. Ohgren, K., Bengtsson, O., Gorwa-Grauslund, M.F., Galbe, M., Hahn-Hagerdal, B., Zacchi, G., 2006. Simultaneous saccharification and co-fermentation of glucose and xylose in steam-pretreated corn stover at high fiber content with Saccharomyces cerevisiae TMB3400. J. Biotechnol. 126, 488–498. Qian, M., Tian, S., Li, X., Zhang, J., Pan, Y., Yang, X., 2006. Ethanol production from diluted-acid softwood hydrolysate by co-culture. Appl. Biochem. Biotechnol. 134, 273–283. Rudolf, A., Baudel, H., Zacchi, G., Hahn-Hagerdal, B., Liden, G., 2008. Simultaneous saccharification and fermentation of steam pretreated bagasse using Saccharomyces cerevisiae TMB3400 and Pichia stipitis CBS6054. Biotechnol. Bioeng. 99, 783–790. Ruohonen, L., Aristidou, A., Frey, A.D., Penttila, M., Kallio, P.T., 2006. Expression of Vitreoscilla hemoglobin improves the metabolism of xylose in recombinant yeast Saccharomyces cerevisiae under low oxygen conditions. Enzyme Microb. Technol. 39, 6–14. Shinozaki, Y., Kitamoto, H.K., 2011. Ethanol production from ensiled rice straw and whole-crop silage by the simultaneous enzymatic saccharification and fermentation process. Biosci. Bioeng. 111, 320–325. Sluiter, A., Hames, B., Ruiz, R., Scarlata, C., Sluiter, J., Templeton, D., 2008. Determination of Structural Carbohydrates and Lignin in Biomass. National Renewable Energy Laboratory, Golden, CO. Unrean, P., Nguyen, N.H., 2012. Rational optimization of culture conditions for the most efficient ethanol production in Scheffersomyces stipitis using design of experiments. Biotechnol. Prog. 28, 1119–1125. Urk, H.V., Mark, P.R., Scheffers, W.A., Van-Dijken, J.P., 1988. Metabolic responses of Saccharomyces cerevisiae CBS 8066 and Candida utilis CBS 621 upon transition from glucose limitation to glucose excess. Yeast 4, 283–291. Wingren, A., Galbe, M., Zacchi, G., 2003. Techno-economic evaluation of producing ethanol from soft wood a comparison of SSF and SHF and identification of bottlenecks. Biotechnol. Prog. 19, 1109–1117. Yadav, K.S., Naseeruddin, S., Prashanthi, G.S., Sateesh, L., Rao, L.V., 2011. Bioethanol fermentation of concentrated rice straw hydrolysate using co-culture of Saccharomyces cerevisiae and Pichia stipitis. Bioresour. Technol. 102, 6473–6478. Zhao, X., Song, Y., Liu, D., 2011. Enzymatic hydrolysis and simultaneous saccharification and fermentation of alkali/peracetic acid-pretreatment sugarcane bagasse for ethanol and 2,3-butanediol production. Enzyme Microb. Technol. 49, 413–419.