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Physico-chemical pretreatment and enzymatic hydrolysis of cotton stalk for ethanol production by Saccharomyces cerevisiae
Accepted Manuscript Physico-chemical pretreatment and enzymatic hydrolysis of cotton stalk for ethanol production by Saccharomyces cerevisiae Anita Singh, Somvir Bajar, Narsi R. Bishnoi PII: DOI: Reference:
S0960-8524(17)31239-7 http://dx.doi.org/10.1016/j.biortech.2017.07.123 BITE 18543
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Bioresource Technology
Received Date: Revised Date: Accepted Date:
17 May 2017 19 July 2017 21 July 2017
Please cite this article as: Singh, A., Bajar, S., Bishnoi, N.R., Physico-chemical pretreatment and enzymatic hydrolysis of cotton stalk for ethanol production by Saccharomyces cerevisiae, Bioresource Technology (2017), doi: http://dx.doi.org/10.1016/j.biortech.2017.07.123
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Physico-chemical pretreatment and enzymatic hydrolysis of cotton stalk for ethanol production by Saccharomyces cerevisiae Anita Singh1,2, Somvir Bajar1,3, Narsi R. Bishnoi1 1 Department of Environmental Science and Engineering Guru Jambheshwar University of Science and Technology, Hisar-125001, Haryana (India) 2Department of Environmental Sciences, Central University of Jammu, Jammu-180011, Jammu and Kashmir (India) 3 Department of Environmental Sciences, Central University of Haryana, Haryana (India) Abstract The aim of this work was to study the physico-chemical pretreatment and enzymatic hydrolysis of cotton stalk for ethanol production by Saccharomyces cerevisiae. Firstly, factors affecting pretreatment were screened out by Plackett-Burman design (PBD) and most significant factors were further optimized by Box-Behnken design (BBD). As shown by experimental study, most significant factors were FeCl3 concentration (FC), irradiation time (IT) and substrate concentration (SC) affecting pretreatment of cotton stalk among all studied factors. Under optimum conditions of pretreatment FC 0.15 mol/l, IT 20 min and SC 55 g/L, the release of reducing sugar was 6.6 g/l. Hydrolysis of pretreated cotton stalk was done by crude on-site produced enzymes and hydrolysate was concentrated. Ethanol production by Saccharomyces cerevisiae using concentrated cotton stalk hydrolysate was 9.8 gp/L, with ethanol yield 0.37 gp/gs on consumed sugars. The data indicated that microwave FeCl3 pretreated cotton stalk hydrolyses by crude unprocessed enzyme cocktail was good, and ethanol can be produced by fermentation of hydrolysate.
Keywords: FeCl3, cotton stalk, cellulase, ethanol, microwave, RSM
1. Introduction Cotton is the most abundant crop in tropical and sub-tropical countries and economy of nearly 90 countries is influenced by cotton. Major Cotton producing countries are India, China, USA, Brazil, Uzbekistan, Turkey, Australia, Turkmenistan, Greece, Syria, Egypt etc. (Shaikh et al., 2011). The increase in cotton plantation leads to the economic growth of any country, but after harvesting of cotton, stalks and leaves left in the field create solid waste management problem as well as delays the subsequent plantation. Most of the stalk, an agricultural residue was considered as waste though a part is used as fuel in rural area, rest is burnt off in the field after harvesting, which creates environmental pollution (Kaur et al., 2012). So cotton stalk is to be removed from the field to combat with solid waste as well as pollution. In China, nearly 40 million tons of cotton stalks is produced annually (Du et al., 2013), and in India about 29 million metric tons per annum cotton stalk is generated (Binod et al., 2012). Out of the total produced cotton stalk residue, nearly 11.8 million metric tons is in surplus amount with no other uses and can produce ethanol upto 2.95 million metric tons annually (Binod et al., 2012). Thus, cotton stalk can be used as a potential source for production of bioethanol and biomaterials. Cotton stalk contains about 45-70% holocellulose, 19-28% lignin and 5.5 % ash, according to the variety type, age of the plant, sampling place, soil condition and irrigation system (Silverstein et al., 2007). Cotton stalk, like other agricultural residues is difficult to hydrolyse due to its complex structure and large amount of lignin present in it. Basic steps involved in bioconversion process of lignocellulosic biomass are: pre-treatment (physical, chemical, biological and their combination) for cell wall
destruction, hydrolysis (acid or enzymatic) for soluble sugar release, and fermentation (bacteria or yeast) for ethanol production. Due to recalcitrant nature of lignin and its binding with holocellululose, pretreatment step is required for fractioning of different cell wall components. Pretreatment expose the cellulose surface for enzymatic attack, improve enzymatic digestibility and subsequent processes. Pre-treatment identifies one of the major economic costs in the bioconversion process (Alvira et al., 2010). Different types of pretreatment studies were conducted for cotton stalk like alkaline, acidic, steam explosion etc. Alkaline pretreatment was used to utilize cotton stalk for generation value –added products (Chang and Holtzapple, 2000; Binod et al., 2012; Kaur et al., 2012). Different researchers studied different type of pretreatment on cotton stalk for production of fermentable sugars like Gaur et al. (2016) studied bench scale dilute acid pretreatment; Huang et al (2015) studied steam explosion pretreatment; Jiang et al (2015) studied liquid hot water pretreatment on different parts of cotton stalk; Keshav et al (2016) studied steam explosion followed by alkaline extraction and Du et al (2016) studied pressure assisted alkali pre-treatment. In the present study, microwave assisted FeCl3 was used for pre-treatment of cotton stalk. Microwave assisted FeCl3 pre-treatment was considered as physic-chemical pretreatment since both thermal and non-thermal effects are often involved (Singh et al., 2011). Microwave pre-treatment disrupt the lignocellulosic biomass recalcitrant structure as well as silica- containing waxy surface which otherwise create hindrance during hydrolysis process (Maa et al., 2009). Liu et al. (2009) studied that FeCl3 pretreatment disordered the lignocellulosic structure by disrupting almost all ether linkages and some ester linkages between lignin and carbohydrates. FeCl3 pretreatment could easily and effectively solubilize hemicellulose, remove amorphous structure and increase external surface area but did not affect delignification (Liu et al., 2009). Metal salts such as FeCl3 in combination with microwave alter the structure of lignocellulosic biomass and improve enzymatic hydrolysis
yield (Liu et al., 2009) but the mechanism by which these salts affect lignocellulosic biomass and improve enzyme access are not completely understood (Zhao et al., 2011). Pre-treated biomass is hydrolysed either by acid or by enzymes and the hydrolysate containing sugar is thus fermented into ethanol with the help of bacteria or yeast. In the present study, factors affecting pre-treatment were screened and optimized using statistical methodologies for maximising the production of reducing sugar from cotton stalk. Plackett-Burman design was used for screening of parameters affecting pre-treatment followed by Response surface methodology (Box-Benhken design) for further optimization of screened factors. The microwave assisted FeCl3 pre-treated cotton stalk was used as a substrate for on-site enzyme production by Aspergillus flavus. It was hypothesized that onsite produced crude unprocessed enzyme cocktail can be used for hydrolysis process in lieu of costly enzyme preparations. The enzymatic hydrolysate was concentrated and used for ethanol production by S. cerevisiae. 2. Materials and Methods 2.1 Material The cotton stalks (Gossypium arboretum), harvested in mid-November 2009, were obtained from Village Ludesher (29o22’00.68’’N, 75 o06’17.08’’E, at elevation 664ft), Distt. Sirsa, Haryana (India). The six month old stalks were shredded and bailed in the field soon after the cotton was picked, then transported to Guru Jambheshwar University of Science and Technology, Hisar. The biomass mainly consisted of stalks, leaves, and cotton residue. Before any pre-treatment cotton stalks were cut to nominally 1-2 cm length and washed thoroughly with tap water until the washings were clean and then air-dried. The 1-2 cm long cotton stalks with moisture content8.6% were grounded to 0.2 and 1mm size and stored in air tight containers at room temperature until used for pre-treatment.
2.2 Microorganism and innoculum preparation Microorganisms Aspergillus flavus ITCC 7680 isolated from degrading wood and Saccharomyces cerevisiae MTCC 174 was purchased from Institute of Microbial Technology, Chandigarh (IMTEC), India were used for present study. The fungus was maintained on PDA medium and yeast maintained on yeast extract, peptone dextrose agar (YEPDA) medium. Yeast inoculum was prepared in 500-mL Erlenmeyer flasks having medium volume of 200 ml, consisting of (gL-1): glucose 30; yeast extract 5; (NH4)2SO4 10; KH2PO4 4.5; MgSO4·7H2O 1, initial pH of the media was adjusted at 5.0 (1 N HCl or 1 N NaOH). The medium was sterilized in an autoclave at 121°C temperature, 15 psi pressure for 10 min. 1 ml yeast innoculum added to the flask after cooling of the medium and the flasks were incubated at temperature 30±2°C for 48 h at 120 rpm. 2.3 Pretreatment Microwave assisted FeCl3 pretreatment was carried out in a microwave oven. The samples were placed in microwave oven in sealed vessel for pretreatment as per the design matrix given in Table 1 and 2. After pretreatment, the samples were collected and washed thoroughly with tap water for neutralization with last wash by deionised water. The neutralised slurry was filtered through a Whatman filter paper for separation of solid and liquid part. Before storing, the solid residue was dried in hot air oven at 45 oC. Reducing sugar was analysed in liquid part produced during microwave FeCl3 pretreatment. 2.4 Optimization of parameters for pretreatment Parameters for pretreatment were optimized sequentially in two stages: Plackett-Burman design (PBD) and Box-Behnken design (BBD). Firstly 9 variables were selected for pretreatment depending upon literature survey and screened for their significance on pretreatment by PBD. In the next stage, most significant factors were further optimized using BBD of Response Surface methodology.
2.4.1 PBD Plackett-Burman design is a mathematical tool to screen most significant variables among the all studied variables. PBD was used for screening of variables with their significance level that affect the response but does not consider the interactive effects between the studied variables (Singh et al., 2011). In this study, 9 independent variables as microwave power, soak time in alkali, irradiation time, FeCl3 concentration, substrate concentration (cotton stalk), liquid- solid ratio, particle size, Tween 80 and pre-soak time (in water) were selected. Each variable was studied at two levels: high level and low level and a total of 12 experiments were designed by the software to see their significant effect on response (Table 1). All experiments were conducted in triplicate and the mean values were taken as response. The t-test was used to study the significance of regression coefficients.
2.4.2 BBD The variables screened out by PBD were further optimized by BBD. In the present study, three variables: FC (A), IT (B), and SC (C) as screened out by PBD experiment were further expanded to evaluate their main and interaction effects on reducing sugar yield (RSY). Table 2 showed design matrix having range and level of variables and observed response. To evaluate the effect of each independent variable to the response, a polynomial quadratic equation was used: Y = β0 + β1A + β2B + β3C +β11A
2
+ β22 B
2
+ β33 C
2
+ β12AB + β13 AC
+ β23 BC
Eq.1 Where Y is the predicted response; β0 is a constant; β1, β2, β3 are the linear coefficients; β12, β23, β13 are the cross-coefficients; β11, β22, β33 are the quadratic coefficients while A,B, C, A2, B2, C2, AB, AC and BC are level of independent variables. Analysis of variance (ANOVA)
was used to analyse significance of the variables and to check the statistical significance of the quadratic model. The goodness of fit of the polynomial equation was expressed by coefficient of determination R2. Analysis also includes Fisher test (F-test) and its associated probability P(F). Response surface and contour plots (3D surface plots) were drawn to show the effects of independent variables on the response and interaction between the significant factors. The desirability was kept at maximum. Each experimental design was carried out in triplicate and mean values were given. In addition to this five confirmatory experiments were also conducted to validate the model. Design expert (trial version) statistical software was used for optimization and interpretation of the data. 2.5 Enzyme production A.
flavus was grown on pretreated cotton stalk (under optimum conditions) via solid
substrate fermentation for secreation of extracellulasr cellulolytic enzymes. 2 g of pretreated cotton stalk was taken in 250 ml conical flask for enzyme production and 70 % moisture level maintained by using Czapeck- Dox inorganic medium (composition Kg m-3: NaNO3 2, KCl 0.5, FeSO4.7H2O 0.01, KH2PO4 0.5, MgSO4.7H2O 0.5, pH 5.5). The flasks were autoclaved, cooled down and inoculated with 1 ml of 2 x 108 spores/ flask of A. flavus spore suspension under sterilized conditions for cellulase and xylanase production. The content were mixed thoroughly and incubated for 120 h at 30±2oC temperature in humidified incubator with 90% relative humidity under static condition with control sample. After 120 hrs citrate buffer (50 mM, pH 4.8) was added to each flask for extraction of enzyme. The flasks were shaked in incubator shaker at 30±2oC for 1 h and at 150 rpm for formation of slurry. The solid and liquid part of this slurry was separated through muslin cloth followed by centrifugation (7200 rpm; 15 min) at 4oC. After biomass separation, the supernatant was used as crude enzyme sample. All experiments were carried out in triplicate and mean value was presented.
2.6 Saccharification of pretreated cotton stalk Pre-treated cotton stalk was used as substrate for enzymatic hydrolysis in 3 L bioreactor (BioAge, Mohali, India) which is having agitator for stirring and temperature control system. 50 g substrate was soaked in 1.5 L citrate buffer (50 mM, pH 5.0 ± 0.2, 50 ± 0.5 0C) for 2 hrs in bioreactor before addition of any enzyme. Sodium azide (0.005%) was added to bioreactor for restriction of any kind of microbial growth in bioreactor. After two hrs of soaking, crude enzymes with activities total cellulase 8.3±1.1 FPU/g, endoglucanase (CMCase) 136±3.5 IU/g, b-glucosidase 96±2.9 IU/g and xylanase 175±4.8 IU/g of the dry substrate was added to the bioreactor with controlled 100rpm. Samples were withdrawn after a regular time period and analysed for total released reducing sugar. The hydrolysate containing reducing sugar was concentrated in a Rotatory evaporator by evaporation process (temperature was maintained at 70 0C) as the method given by Dehkhoda et al. (2008). During concentration process, reducing sugar was assessed before and after experiments. 2.7 Ethanol production The hydrolysate was concentrated by evaporation and concentrated enzymatic hydrolysate (5% reducing sugar) of microwave FeCl3 pretreated cotton stalk was inoculated with yeast S. cerevisiae (volume 2% v/v of a 48 h old seed culture) for ethanol production. The content was incubated in stoppered flask at room temperature (28 ± 2oC) under static conditions. After particular time incubation, 5 ml sample was withdrawn, centrifuged for 10 min at 4oC at 10,000 rpm and supernatant was analyzed on spectrophotometer for ethanol content (Caputi et al., 1968). 2.8 Analytical methods
Goering and Van Soest method (1970) was used for estimation of cellulose, hemicellulose and lignin contents. Total cellulase activity in the crude enzyme was assessed according to the method of Ghose (1987) and units expressed as filter paper units (FPU). Endoglucanase activity was also assessed by the method of Ghose (1987) using carboxy methyl cellulose as substrate and units expressed as IU/g (units per gram dry substrate). Oat splet xylan was used as a substrate for assessing xylanase activity (Singh et al., 2011). Beta-glucosidase activity was determined by method of Ghosh and Bisaria (1979) using p-nitrophenyl b-Dglucopyranoside as substrate. DNS method was used for the estimation of total reducing sugar in enzymatic hydrolysate (Miller, 1959). The concentration of reducing sugar in hydrolysate was increased by the methods of Dehkhoda et al. (2008). Spectrophotometric method was used for the estimation of ethanol (Caputi et al., 1968).
Enzymatic hydrolysis yield (%)
= (released reducing sugar (g) * 0.9* 100)/ grams of cellulose in cotton stalk
2.9 Fermentation parameters Ethanol volumetric productivity (g/l/h) was represented by the ratio of ethanol concentration (g/l) at the end of the run which is divided by the fermentation time (t, h). Ratio of ethanol concentration to the sugar consumption was defined by the yield of ethanol to the consumed sugar (g/g). Sugar conversion (%) was calculated by the difference of initial sugar with residual sugar which divided by 100. Theoretical yield of ethanol (ή, %) was calculated as ethanol yield divided by 0.51. 3
Results and discussion 3.1 PBD study
The factors affecting pre-treatment firstly screened by PBD, and their standardized effects and contribution percentage were shown in Table 1. Among all the studied variables, FeCl3 shows most significant effect on pretreatment with standardized effect 13.6 and contribution percentage 99.5% as shown in Table 1. Other factors having significant effect on reducing sugar yield above 95% were substrate concentration (standardized effect 8.85 and contribution percentage of 98.7%) followed by irradiation time (standardized effect 8.22 and contribution percentage of 98.6%). Soak time in FeCl3 was also a significant factor with contribution percentage of 98.2 % on reducing sugar yield and its standardized effect was 7.27. This shows that soaking times plays an important role, so 2 h soak time was used for further study. The concentration of FeCl3 for soaking of cotton stalk were same as per design matrix (Table 1). Particle size was a significant variable with contribution percentage was 92.6 % but with negative standardized effect of -3.48. If there is decrease in yield when the variable shift from low level to high level, it is represented by negative sign (negative standardized effect), while the positive sign in front of standardized effect means increase in yield from low level to high level (Singh et al., 2011). Soak time and solid to liquid ratio were fixed at upper level because their standardized effects were 0.95 and 2.53, respectively. Whereas microwave power and Tween 80 were fixed at lower level because their standardized effects were - 3.79 and -0.63, respectively.
3.2 BBD study Depending upon the screening by PBD, three most significant factors affecting pre-treatment of cotton stalk were FeCl3 concentration (A=0.10–0.20 mol/L), irradiation time (B=15–25 min) and substrate concentration (C=40-70 g/L). These three variables were further optimized by employing BBD was used for further optimization of screened three variables using polynomial quadratic model and equation was shown as below
Reducing sugar yield = +6.46 +0.31 * A+ 0.16 * B -0.48 * C -1.58 * A2-0.63 * B2 -0.50 * C2 + 0.50 * A* B -0.33 *A*C +0.38*B* C
(eq…2)
Evaluation of the effects of the variables and their probably existed interactions was studied by an analysis of variance. The non-significant value of lack of fit (F=3.16) showed the model is fitted with good prediction (R2= 0.99) (Table 3). The coefficient of determination R2= 0.99 was high which indicates that upto 99% of the variations in response could be explained by the independent studied variables. The model shows a close agreement between the experimental results and the theoretical values predicted by the model as shown by the of R2 (0.99) and adjusted R2 (Adj R2 = 0.986) values.
Coefficients of the full model were analyzed for their significant variables, insignificant variables and their interactions. The insignificant variables (p-value > 0.05) were eliminated from the model by backward elimination and the reduced model was adjusted for further study. Table 3 shows results of ANOVA for the adjusted model and p-value (lower than 0.0001) of the adjusted model representing that the model is statistically valid. And the pvalues of A, B, C, A2 , B2, C2, AB, AC and BC were all lower than 0.05 demonstrating that they all were significant factors. Response surface plots and their corresponding contour plots were constructing to study the optimum level of each studied variables and effect of their interaction on release of reducing sugar. The response surface plots were showing interaction of two variables at one time within the experimental range while keeping the third variable constant at its middle value. The shapes of the contour plots show whether the mutual interaction between independent variables was significant or not. Different shapes of contour plots shows different type of interactions between the variables like circular nature of contour plots shows less prominent or negligible interactions, and elliptical nature of the contour plots shows comparatively
prominent interactions (Singh et al., 2011). As shown by fig. 1a-1c, each response surface shows a clear peak, which means that the optimum point for optimization pre-treatment conditions was inside the boundary layer of the studied design. Table 3 shows that interaction between FC, IT and SC were significant variables and affect the reducing sugar production response. Fig. 1a showed positive interaction of IT and FC on reducing sugar yield (g/l) while keeping SC constant at middle level. As shown by fig. 1a that as the conc. of IT and FC increase, reducing sugar yield increases but upto middle level only, further increases in both decrease the reducing sugar yield. Fig. 1b shows the interaction of SC and FC on reducing sugar yield and shows that central point of both have highest reducing sugar yield as compared to lower and higher level. Fig. 1c shows interactive effect of SC and IT on reducing sugar yield and shows the similar pattern as highest reducing sugar yield at middle level of both studied variables while keeping third variable (FC) constant. P Value in all three cases was less than 0.05 which indicates positive interaction between the studied variables. Fig. 1a-1c showed that variables FC, IT and SC at middle level were optimum for response (reducing sugar yield). 3.3 Optimization and confirmation experiments The method of pretreatment had a pronounced effect on the yield of reducing sugars. The adequacy and validation of the model was studied by performing 5 additional verification experiments within the range of experimental data as shown in table 4. Validation experiment data was also statistically analysed and found that the correlation coefficient (R2=0.99) between experimental and predicted which also shows the accuracy of the studied model... The main composition of untreated cotton stalk was determined to be 35% cellulose, 22% hemicellulose, 19% lignin, 6.5 % ash content. Under optimum conditions (as optimized by BBD) of microwave-assisted FeCl3 pretreated cotton stalk consisted of 52.1% cellulose, 15.6% hemicellulose, 11.8% lignin, ash content 3.5% . Microwave-assisted FeCl3
pretreatment increased the proportion of cellulose by 48.8% and decreased that of hemicelluloses, lignin and ash by 29% and 37 %, 46 %, respectively, while compared with untreated cotton stalk. The microwave-assisted FeCl3 pretreatment was effective in fractionating the hemicellulose and lignin components (Lu and Zhou, 2011). Liu and Zhou (2011) studied microwave-assisted FeCl3 pretreatment of rice straw and found 35 % decrease in hemicellulose content and 39.5% decrease in lignin content after pretreatment. During pretreatment, there is always a loss of lignin and hemicellulose part due to breaking of bonds between cellulose, hemicellulose and lignin complex. Both components are solubilized into different components like phenylic compounds and monomeric sugars, respectively, during pretreatment. In this study, nearly 68% hemicellulose is still present after the pretreatment, which can be converted into pentose sugars by exposing it to xylanase. The simultaneous conversation of both cellulose and hemicellulose part into hexose and pentose sugars, respectively, increases the efficiency of ethanol production from biomass.
3.4 Enzyme production and saccharification Major bottleneck in biomass to ethanol conversion is the cost of cellulase enzymes and any strategy which can bring down the production cost of cellulases can significantly reduce the cost of bio-ethanol (Sukumaran et al., 2009). Enzymatic hydrolysis of pretreated cotton stalk was carried out with crude supernatant from A. flavus for depolymerization of cell wall carbohydrate fraction into fermentable sugars. The present study indicates that microbial biotransformed cotton stalk can be a rich substrate for enzyme production. Solid state fermentation needs lesser infrastructure, low level of water, relatively less skilled manpower and solid medium was used both as solid support and substrate for enzyme production. Cheaper raw material like agro-industrial waste can be used for enzyme production under SSF. Under SSF more concentrated product is produced, which in this case is very much
advantageous (Aswathy et al., 2009). The A. flavus enzyme had activities of total cellulase 8.3±1.1 FPU/g, endoglucanase (CMCase) 136±3.5 IU/g, b-glucosidase 96±2.9 IU/g and xylanase 175±4.8 IU/g. Similar results of enzyme production were found by Ahamed and Vermette (2008) & Dhillion et al. (2011). Cellulose accessibility by the cellulase enzyme depends upon many factors like available surface area, cellulose crystallinity, pore volume, particle size etc. (Yang et al., 2011). Hydrolysis of biomass requires cellulase enzyme to penetrate the polymer and bind with specific binding sites of the substrate, so that the enzyme sits on the polymer and effects a slow degradation (Sukumaran et al., 2009; Singh et al., 2013). During enzymatic hydrolysis highest reducing sugars concentration obtained with pretreated cotton stalk was 13.7 g/L after 72 h of incubation. The hydrolysate was concentrated by evaporation to reducing sugar content of 5 % used for ethanol production. In the present study enzymatic hydrolysis yield reaches upto 84.6 % with cotton stalk. Similar results obtained by Liu et al. (2009) with microwave FeCl3 pretreated corn stover. This shows that microwave FeCl3 pretreatment could enhance the enzymatic hydrolysis of biomass by removing hemicellulose present and increasing the accessibility of cellulase to cellulose (Liu et al., 2009; Lu et al., 2011).
3.5 Ethanol production Hydrolyzed enzymes ferment the complex sugars to reducing sugars and then to ethanol. Concentrated enzymatic hydrolysate of cotton stalk with a reducing sugar concentration of 50 g/l was used for the fermentation experiments. Fig. 2 shows the reducing sugar consumption and ethanol production from microwave assisted microwave-assisted FeCl3 pretreatment of Cotton stalk using S. cerevisiae. Ethanol production using cotton stalk hydrolysate was 9.8 gp/l, ethanol volumetric productivity was 0.27 gp/l/h and ethanol yield on consumed sugars was 0.37 gp/gs about 52 % sugar consumed (initial sugar concentration was 50 gs/l) and
efficiency of sugar conversion to ethanol reached upto 72 % with fermentation time of 36 h. However, the ethanol yield obtained from cellulosic hydrolysate using S. cerevisiae (0.37 g/g) were comparable with the previous results of ethanol yield 0.44 g/g from cotton stalk (Keshav et al., 2016); 0.027 g/g from cotton stalks (Shi et al., 2008); 18.3, 16.27 and 21.08 g/100 g was achieved from stem, branch and boll shell of cotton stalk (Jiang et al., 2015).
4
Conclusions
Pretreatment of cotton stalk was optimized by two statistical methodologies PBD and BBD in this study. The conditions for microwave-assisted FeCl3 pretreatment of Cotton stalk were optimized by using PBD and significant factors were further optimized by BBD. Microwaveassisted FeCl3 pretreatment make lingo-cellulose more accessible for enzyme production. The crude unprocessed enzyme cocktail used for saccharification of pretreated cotton stalk with production of reducing sugar was 13.7 g/l. The concentrated enzymatic hydrolysate fermented by S. cerevisiae with ethanol yield of 0.37gs/gp. Present environmental problems due to accumulation and burning of cotton stalk can also be eradicated apart from the production of industrially important enzymes and biofuel- ethanol.
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26. Singh A, Tuteja S, Singh N, Bishnoi N R. Enhanced saccharification of rice straw and hulls by microwave- alkali pretreatment and lignocellulolytic enzyme production. Bioresour Technol 2011; 102: 1773-1782. 27. Singh, A., Sharma, P., Saran, A.K., Singh, N., Bishnoi, N.R. (2013). Comparative study on ethanol production from pretreated sugarcane bagasse using immobilized Saccahromyces cerevisiae on various matrices. Renewable Energy 28. Sukumaran RK, Singhania RR, Mathew GM, Pandey A. Cellulase production using biomass feed stock and its application in lignocellulose saccharification for bioethanol production. Renewable Energy 2009;34: 421–424. 29. Yang, B., Dai, Z., Ding, S.Y., Wyman, C.E. (2011). Enzymatic hydrolysis of cellulosic biomass. Biofuels; 2(4):421-450 30. Zhao, J., Zhang, H., Zheng, R., Lin, Z., Huang, H., 2011. The enhancement of pretreatment and enzymatic hydrolysis of corn stover by FeSO4 pretreatment. Biochem. Eng. J. 56, 158–164
Figure captions:
Figure 1a. Response surface plots showing the interactive effects of FC (mol/l) and IT (min) on reducing sugar yield (g/l) at constant SC (g/l) Figure 1b. Response surface plots showing the interactive effects of FC (mol/l) and SC (g/l) on reducing sugar yield (g/l) at constant IT (min) Figure 1c. Response surface plots showing the interactive effects of SC (g/l) and IT (min) on reducing sugar yield (g/l) at constant FC (mol/l) Figure 2: Time course of sugar consumption and Ethanol production from microwave assisted microwave-assisted FeCl3 pretreatment of Cotton stalk using S. cerevisiae
Table 1. Levels and results of variables tested in PBD. Code Parameter name
Low level High level t value (-1)
(+1)
P value
Confidence level, %
A
Irradiation time (min.)
10
30
8.22
0.014
98.6
B
Pre-soak time in water 10
20
0.95
0.443
55.7
(hours) C
Liquid- solid ratio
5
8
2.53
0.127
87.3
D
Soak time in FeCl3 0
2
7.27
0.018
98.2
700
-3.79
0.063
93.7
(hours) E
Microwave
power 500
(Watt) F
Tween 80 (%)
0
0.01
-0.63
0.592
40.8
G
Substrate
5.0
50.0
8.85
0.013
98.7
0.15
13.6
0.005
99.5
1.0
-3.48
0.074
92.6
concentration (g/l) H
FeCl3
concentration 0.05
(mol/l) I
Particle size (mm)
0.2
Table 2. Design and results of BBD. Run
FC
IT
SC
Reducing sugars (g/l)
1
0.15
20
55
6.3
2
0.2
20
40
5.6
3
0.15
15
40
5.6
4
0.15
15
70
4.3
5
0.15
25
70
5.5
6
0.15
20
55
6.6
7
0.1
15
55
4.4
8
0.2
25
55
5.1
9
0.15
20
55
6.5
10
0.15
25
40
5.9
11
0.1
25
55
3.6
12
0.15
20
55
6.6
13
0.15
20
55
6.5
14
0.2
15
55
3.9
15
0.2
20
70
3.9
16
0.1
20
40
4.2
17
0.1
20
70
3.8
FC= FeCl3 Concentration (mol/l); IT= Irradiation time (min); SC=Substrate concentration (g/l)
Table 3. ANOVA table for the adjusted model of response from reducing sugar yield from cotton stalk. Sum of Source Squares DF Model 19.05 A 0.781 B 0.211 C 1.80 A2 10.484 B2 1.66 C2 1.065 AB 1 AC 0.42 BC 0.56 Residual 0.117 Lack of Fit 0.082 Pure Error 0.034 Cor Total 19.176
9 1 1 1 1 1 1 1 1 1 7 3 4 16
Mean F Square Value Prob > F 2.117 126.461 < 0.0001 0.781 46.65 0.0002 0.211 12.61 0.0093 1.80 107.78 < 0.0001 10.484 626.1 < 0.0001 1.66 99.16 < 0.0001 1.065 63.61 < 0.0001 1 59.716 0.0001 0.422 25.23 0.0015 0.562 33.59 0.0007 0.016 0.027 3.168 0.147 0.008
significant
not significant
Table 4. Confirmatory experiments Number
FC
IT
SC
Reducing sugar (g/l)
1
0.15
20.11
49.40
6.64
2
0.15
22.32
50.63
6.60
3
0.15
20.67
48.50
6.66
4
0.15
20.95
45.66
6.66
5
0.16
21.07
51.15
6.64
FC= FeCl3 Concentration (mol/l); IT= Irradiation time (min); SC=Substrate concentration (g/l)
6.48885 5.76664
RSY (g/l)
5.04443 4.32221 3.6
25.00 0.20 22.50 0.18 20.00
IT (min)
0.15 17.50
0.13 15.00
0.10
Fig. 1a
FC (mol/l)
6.59963 5.9216
RSY (g/l)
5.24357 4.56553 3.8875
70.00 0.20 62.50 0.18 55.00
SC (g/l)
0.15 47.50
0.13 40.00
0.10
Fig. 1b
FC (mol/l)
6.56775 6.00394
RSY (g/l)
5.44013 4.87631 4.3125
70.00 25.00 62.50 22.50 55.00
SC (g/l)
20.00 47.50
17.50 40.00
15.00
Fig. 1c
IT (m in)
12
50
10
40
8
30
6
20
4 Reducing sugar (g/L)
10
2
Ethanol (g/L)
0
0 4
8
12
24 Time (h)
Fig. 2.
36
48
Ethanol conc. (g/L)
Reducing sugar (g/L)
60
Highlights: 1. 2. 3. 4. 5.
Optimization of pre-treatment using sequential statistical methodology. Pre-treated cotton stalk used for enzyme production. Hydrolysis of biomass by crude enzymes at bioreactor level. Concentration of hydrolysate and ethanol production. Energy production as well as solid waste management.
S0960-8524(17)31239-7 http://dx.doi.org/10.1016/j.biortech.2017.07.123 BITE 18543
To appear in:
Bioresource Technology
Received Date: Revised Date: Accepted Date:
17 May 2017 19 July 2017 21 July 2017
Please cite this article as: Singh, A., Bajar, S., Bishnoi, N.R., Physico-chemical pretreatment and enzymatic hydrolysis of cotton stalk for ethanol production by Saccharomyces cerevisiae, Bioresource Technology (2017), doi: http://dx.doi.org/10.1016/j.biortech.2017.07.123
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Physico-chemical pretreatment and enzymatic hydrolysis of cotton stalk for ethanol production by Saccharomyces cerevisiae Anita Singh1,2, Somvir Bajar1,3, Narsi R. Bishnoi1 1 Department of Environmental Science and Engineering Guru Jambheshwar University of Science and Technology, Hisar-125001, Haryana (India) 2Department of Environmental Sciences, Central University of Jammu, Jammu-180011, Jammu and Kashmir (India) 3 Department of Environmental Sciences, Central University of Haryana, Haryana (India) Abstract The aim of this work was to study the physico-chemical pretreatment and enzymatic hydrolysis of cotton stalk for ethanol production by Saccharomyces cerevisiae. Firstly, factors affecting pretreatment were screened out by Plackett-Burman design (PBD) and most significant factors were further optimized by Box-Behnken design (BBD). As shown by experimental study, most significant factors were FeCl3 concentration (FC), irradiation time (IT) and substrate concentration (SC) affecting pretreatment of cotton stalk among all studied factors. Under optimum conditions of pretreatment FC 0.15 mol/l, IT 20 min and SC 55 g/L, the release of reducing sugar was 6.6 g/l. Hydrolysis of pretreated cotton stalk was done by crude on-site produced enzymes and hydrolysate was concentrated. Ethanol production by Saccharomyces cerevisiae using concentrated cotton stalk hydrolysate was 9.8 gp/L, with ethanol yield 0.37 gp/gs on consumed sugars. The data indicated that microwave FeCl3 pretreated cotton stalk hydrolyses by crude unprocessed enzyme cocktail was good, and ethanol can be produced by fermentation of hydrolysate.
Keywords: FeCl3, cotton stalk, cellulase, ethanol, microwave, RSM
1. Introduction Cotton is the most abundant crop in tropical and sub-tropical countries and economy of nearly 90 countries is influenced by cotton. Major Cotton producing countries are India, China, USA, Brazil, Uzbekistan, Turkey, Australia, Turkmenistan, Greece, Syria, Egypt etc. (Shaikh et al., 2011). The increase in cotton plantation leads to the economic growth of any country, but after harvesting of cotton, stalks and leaves left in the field create solid waste management problem as well as delays the subsequent plantation. Most of the stalk, an agricultural residue was considered as waste though a part is used as fuel in rural area, rest is burnt off in the field after harvesting, which creates environmental pollution (Kaur et al., 2012). So cotton stalk is to be removed from the field to combat with solid waste as well as pollution. In China, nearly 40 million tons of cotton stalks is produced annually (Du et al., 2013), and in India about 29 million metric tons per annum cotton stalk is generated (Binod et al., 2012). Out of the total produced cotton stalk residue, nearly 11.8 million metric tons is in surplus amount with no other uses and can produce ethanol upto 2.95 million metric tons annually (Binod et al., 2012). Thus, cotton stalk can be used as a potential source for production of bioethanol and biomaterials. Cotton stalk contains about 45-70% holocellulose, 19-28% lignin and 5.5 % ash, according to the variety type, age of the plant, sampling place, soil condition and irrigation system (Silverstein et al., 2007). Cotton stalk, like other agricultural residues is difficult to hydrolyse due to its complex structure and large amount of lignin present in it. Basic steps involved in bioconversion process of lignocellulosic biomass are: pre-treatment (physical, chemical, biological and their combination) for cell wall
destruction, hydrolysis (acid or enzymatic) for soluble sugar release, and fermentation (bacteria or yeast) for ethanol production. Due to recalcitrant nature of lignin and its binding with holocellululose, pretreatment step is required for fractioning of different cell wall components. Pretreatment expose the cellulose surface for enzymatic attack, improve enzymatic digestibility and subsequent processes. Pre-treatment identifies one of the major economic costs in the bioconversion process (Alvira et al., 2010). Different types of pretreatment studies were conducted for cotton stalk like alkaline, acidic, steam explosion etc. Alkaline pretreatment was used to utilize cotton stalk for generation value –added products (Chang and Holtzapple, 2000; Binod et al., 2012; Kaur et al., 2012). Different researchers studied different type of pretreatment on cotton stalk for production of fermentable sugars like Gaur et al. (2016) studied bench scale dilute acid pretreatment; Huang et al (2015) studied steam explosion pretreatment; Jiang et al (2015) studied liquid hot water pretreatment on different parts of cotton stalk; Keshav et al (2016) studied steam explosion followed by alkaline extraction and Du et al (2016) studied pressure assisted alkali pre-treatment. In the present study, microwave assisted FeCl3 was used for pre-treatment of cotton stalk. Microwave assisted FeCl3 pre-treatment was considered as physic-chemical pretreatment since both thermal and non-thermal effects are often involved (Singh et al., 2011). Microwave pre-treatment disrupt the lignocellulosic biomass recalcitrant structure as well as silica- containing waxy surface which otherwise create hindrance during hydrolysis process (Maa et al., 2009). Liu et al. (2009) studied that FeCl3 pretreatment disordered the lignocellulosic structure by disrupting almost all ether linkages and some ester linkages between lignin and carbohydrates. FeCl3 pretreatment could easily and effectively solubilize hemicellulose, remove amorphous structure and increase external surface area but did not affect delignification (Liu et al., 2009). Metal salts such as FeCl3 in combination with microwave alter the structure of lignocellulosic biomass and improve enzymatic hydrolysis
yield (Liu et al., 2009) but the mechanism by which these salts affect lignocellulosic biomass and improve enzyme access are not completely understood (Zhao et al., 2011). Pre-treated biomass is hydrolysed either by acid or by enzymes and the hydrolysate containing sugar is thus fermented into ethanol with the help of bacteria or yeast. In the present study, factors affecting pre-treatment were screened and optimized using statistical methodologies for maximising the production of reducing sugar from cotton stalk. Plackett-Burman design was used for screening of parameters affecting pre-treatment followed by Response surface methodology (Box-Benhken design) for further optimization of screened factors. The microwave assisted FeCl3 pre-treated cotton stalk was used as a substrate for on-site enzyme production by Aspergillus flavus. It was hypothesized that onsite produced crude unprocessed enzyme cocktail can be used for hydrolysis process in lieu of costly enzyme preparations. The enzymatic hydrolysate was concentrated and used for ethanol production by S. cerevisiae. 2. Materials and Methods 2.1 Material The cotton stalks (Gossypium arboretum), harvested in mid-November 2009, were obtained from Village Ludesher (29o22’00.68’’N, 75 o06’17.08’’E, at elevation 664ft), Distt. Sirsa, Haryana (India). The six month old stalks were shredded and bailed in the field soon after the cotton was picked, then transported to Guru Jambheshwar University of Science and Technology, Hisar. The biomass mainly consisted of stalks, leaves, and cotton residue. Before any pre-treatment cotton stalks were cut to nominally 1-2 cm length and washed thoroughly with tap water until the washings were clean and then air-dried. The 1-2 cm long cotton stalks with moisture content8.6% were grounded to 0.2 and 1mm size and stored in air tight containers at room temperature until used for pre-treatment.
2.2 Microorganism and innoculum preparation Microorganisms Aspergillus flavus ITCC 7680 isolated from degrading wood and Saccharomyces cerevisiae MTCC 174 was purchased from Institute of Microbial Technology, Chandigarh (IMTEC), India were used for present study. The fungus was maintained on PDA medium and yeast maintained on yeast extract, peptone dextrose agar (YEPDA) medium. Yeast inoculum was prepared in 500-mL Erlenmeyer flasks having medium volume of 200 ml, consisting of (gL-1): glucose 30; yeast extract 5; (NH4)2SO4 10; KH2PO4 4.5; MgSO4·7H2O 1, initial pH of the media was adjusted at 5.0 (1 N HCl or 1 N NaOH). The medium was sterilized in an autoclave at 121°C temperature, 15 psi pressure for 10 min. 1 ml yeast innoculum added to the flask after cooling of the medium and the flasks were incubated at temperature 30±2°C for 48 h at 120 rpm. 2.3 Pretreatment Microwave assisted FeCl3 pretreatment was carried out in a microwave oven. The samples were placed in microwave oven in sealed vessel for pretreatment as per the design matrix given in Table 1 and 2. After pretreatment, the samples were collected and washed thoroughly with tap water for neutralization with last wash by deionised water. The neutralised slurry was filtered through a Whatman filter paper for separation of solid and liquid part. Before storing, the solid residue was dried in hot air oven at 45 oC. Reducing sugar was analysed in liquid part produced during microwave FeCl3 pretreatment. 2.4 Optimization of parameters for pretreatment Parameters for pretreatment were optimized sequentially in two stages: Plackett-Burman design (PBD) and Box-Behnken design (BBD). Firstly 9 variables were selected for pretreatment depending upon literature survey and screened for their significance on pretreatment by PBD. In the next stage, most significant factors were further optimized using BBD of Response Surface methodology.
2.4.1 PBD Plackett-Burman design is a mathematical tool to screen most significant variables among the all studied variables. PBD was used for screening of variables with their significance level that affect the response but does not consider the interactive effects between the studied variables (Singh et al., 2011). In this study, 9 independent variables as microwave power, soak time in alkali, irradiation time, FeCl3 concentration, substrate concentration (cotton stalk), liquid- solid ratio, particle size, Tween 80 and pre-soak time (in water) were selected. Each variable was studied at two levels: high level and low level and a total of 12 experiments were designed by the software to see their significant effect on response (Table 1). All experiments were conducted in triplicate and the mean values were taken as response. The t-test was used to study the significance of regression coefficients.
2.4.2 BBD The variables screened out by PBD were further optimized by BBD. In the present study, three variables: FC (A), IT (B), and SC (C) as screened out by PBD experiment were further expanded to evaluate their main and interaction effects on reducing sugar yield (RSY). Table 2 showed design matrix having range and level of variables and observed response. To evaluate the effect of each independent variable to the response, a polynomial quadratic equation was used: Y = β0 + β1A + β2B + β3C +β11A
2
+ β22 B
2
+ β33 C
2
+ β12AB + β13 AC
+ β23 BC
Eq.1 Where Y is the predicted response; β0 is a constant; β1, β2, β3 are the linear coefficients; β12, β23, β13 are the cross-coefficients; β11, β22, β33 are the quadratic coefficients while A,B, C, A2, B2, C2, AB, AC and BC are level of independent variables. Analysis of variance (ANOVA)
was used to analyse significance of the variables and to check the statistical significance of the quadratic model. The goodness of fit of the polynomial equation was expressed by coefficient of determination R2. Analysis also includes Fisher test (F-test) and its associated probability P(F). Response surface and contour plots (3D surface plots) were drawn to show the effects of independent variables on the response and interaction between the significant factors. The desirability was kept at maximum. Each experimental design was carried out in triplicate and mean values were given. In addition to this five confirmatory experiments were also conducted to validate the model. Design expert (trial version) statistical software was used for optimization and interpretation of the data. 2.5 Enzyme production A.
flavus was grown on pretreated cotton stalk (under optimum conditions) via solid
substrate fermentation for secreation of extracellulasr cellulolytic enzymes. 2 g of pretreated cotton stalk was taken in 250 ml conical flask for enzyme production and 70 % moisture level maintained by using Czapeck- Dox inorganic medium (composition Kg m-3: NaNO3 2, KCl 0.5, FeSO4.7H2O 0.01, KH2PO4 0.5, MgSO4.7H2O 0.5, pH 5.5). The flasks were autoclaved, cooled down and inoculated with 1 ml of 2 x 108 spores/ flask of A. flavus spore suspension under sterilized conditions for cellulase and xylanase production. The content were mixed thoroughly and incubated for 120 h at 30±2oC temperature in humidified incubator with 90% relative humidity under static condition with control sample. After 120 hrs citrate buffer (50 mM, pH 4.8) was added to each flask for extraction of enzyme. The flasks were shaked in incubator shaker at 30±2oC for 1 h and at 150 rpm for formation of slurry. The solid and liquid part of this slurry was separated through muslin cloth followed by centrifugation (7200 rpm; 15 min) at 4oC. After biomass separation, the supernatant was used as crude enzyme sample. All experiments were carried out in triplicate and mean value was presented.
2.6 Saccharification of pretreated cotton stalk Pre-treated cotton stalk was used as substrate for enzymatic hydrolysis in 3 L bioreactor (BioAge, Mohali, India) which is having agitator for stirring and temperature control system. 50 g substrate was soaked in 1.5 L citrate buffer (50 mM, pH 5.0 ± 0.2, 50 ± 0.5 0C) for 2 hrs in bioreactor before addition of any enzyme. Sodium azide (0.005%) was added to bioreactor for restriction of any kind of microbial growth in bioreactor. After two hrs of soaking, crude enzymes with activities total cellulase 8.3±1.1 FPU/g, endoglucanase (CMCase) 136±3.5 IU/g, b-glucosidase 96±2.9 IU/g and xylanase 175±4.8 IU/g of the dry substrate was added to the bioreactor with controlled 100rpm. Samples were withdrawn after a regular time period and analysed for total released reducing sugar. The hydrolysate containing reducing sugar was concentrated in a Rotatory evaporator by evaporation process (temperature was maintained at 70 0C) as the method given by Dehkhoda et al. (2008). During concentration process, reducing sugar was assessed before and after experiments. 2.7 Ethanol production The hydrolysate was concentrated by evaporation and concentrated enzymatic hydrolysate (5% reducing sugar) of microwave FeCl3 pretreated cotton stalk was inoculated with yeast S. cerevisiae (volume 2% v/v of a 48 h old seed culture) for ethanol production. The content was incubated in stoppered flask at room temperature (28 ± 2oC) under static conditions. After particular time incubation, 5 ml sample was withdrawn, centrifuged for 10 min at 4oC at 10,000 rpm and supernatant was analyzed on spectrophotometer for ethanol content (Caputi et al., 1968). 2.8 Analytical methods
Goering and Van Soest method (1970) was used for estimation of cellulose, hemicellulose and lignin contents. Total cellulase activity in the crude enzyme was assessed according to the method of Ghose (1987) and units expressed as filter paper units (FPU). Endoglucanase activity was also assessed by the method of Ghose (1987) using carboxy methyl cellulose as substrate and units expressed as IU/g (units per gram dry substrate). Oat splet xylan was used as a substrate for assessing xylanase activity (Singh et al., 2011). Beta-glucosidase activity was determined by method of Ghosh and Bisaria (1979) using p-nitrophenyl b-Dglucopyranoside as substrate. DNS method was used for the estimation of total reducing sugar in enzymatic hydrolysate (Miller, 1959). The concentration of reducing sugar in hydrolysate was increased by the methods of Dehkhoda et al. (2008). Spectrophotometric method was used for the estimation of ethanol (Caputi et al., 1968).
Enzymatic hydrolysis yield (%)
= (released reducing sugar (g) * 0.9* 100)/ grams of cellulose in cotton stalk
2.9 Fermentation parameters Ethanol volumetric productivity (g/l/h) was represented by the ratio of ethanol concentration (g/l) at the end of the run which is divided by the fermentation time (t, h). Ratio of ethanol concentration to the sugar consumption was defined by the yield of ethanol to the consumed sugar (g/g). Sugar conversion (%) was calculated by the difference of initial sugar with residual sugar which divided by 100. Theoretical yield of ethanol (ή, %) was calculated as ethanol yield divided by 0.51. 3
Results and discussion 3.1 PBD study
The factors affecting pre-treatment firstly screened by PBD, and their standardized effects and contribution percentage were shown in Table 1. Among all the studied variables, FeCl3 shows most significant effect on pretreatment with standardized effect 13.6 and contribution percentage 99.5% as shown in Table 1. Other factors having significant effect on reducing sugar yield above 95% were substrate concentration (standardized effect 8.85 and contribution percentage of 98.7%) followed by irradiation time (standardized effect 8.22 and contribution percentage of 98.6%). Soak time in FeCl3 was also a significant factor with contribution percentage of 98.2 % on reducing sugar yield and its standardized effect was 7.27. This shows that soaking times plays an important role, so 2 h soak time was used for further study. The concentration of FeCl3 for soaking of cotton stalk were same as per design matrix (Table 1). Particle size was a significant variable with contribution percentage was 92.6 % but with negative standardized effect of -3.48. If there is decrease in yield when the variable shift from low level to high level, it is represented by negative sign (negative standardized effect), while the positive sign in front of standardized effect means increase in yield from low level to high level (Singh et al., 2011). Soak time and solid to liquid ratio were fixed at upper level because their standardized effects were 0.95 and 2.53, respectively. Whereas microwave power and Tween 80 were fixed at lower level because their standardized effects were - 3.79 and -0.63, respectively.
3.2 BBD study Depending upon the screening by PBD, three most significant factors affecting pre-treatment of cotton stalk were FeCl3 concentration (A=0.10–0.20 mol/L), irradiation time (B=15–25 min) and substrate concentration (C=40-70 g/L). These three variables were further optimized by employing BBD was used for further optimization of screened three variables using polynomial quadratic model and equation was shown as below
Reducing sugar yield = +6.46 +0.31 * A+ 0.16 * B -0.48 * C -1.58 * A2-0.63 * B2 -0.50 * C2 + 0.50 * A* B -0.33 *A*C +0.38*B* C
(eq…2)
Evaluation of the effects of the variables and their probably existed interactions was studied by an analysis of variance. The non-significant value of lack of fit (F=3.16) showed the model is fitted with good prediction (R2= 0.99) (Table 3). The coefficient of determination R2= 0.99 was high which indicates that upto 99% of the variations in response could be explained by the independent studied variables. The model shows a close agreement between the experimental results and the theoretical values predicted by the model as shown by the of R2 (0.99) and adjusted R2 (Adj R2 = 0.986) values.
Coefficients of the full model were analyzed for their significant variables, insignificant variables and their interactions. The insignificant variables (p-value > 0.05) were eliminated from the model by backward elimination and the reduced model was adjusted for further study. Table 3 shows results of ANOVA for the adjusted model and p-value (lower than 0.0001) of the adjusted model representing that the model is statistically valid. And the pvalues of A, B, C, A2 , B2, C2, AB, AC and BC were all lower than 0.05 demonstrating that they all were significant factors. Response surface plots and their corresponding contour plots were constructing to study the optimum level of each studied variables and effect of their interaction on release of reducing sugar. The response surface plots were showing interaction of two variables at one time within the experimental range while keeping the third variable constant at its middle value. The shapes of the contour plots show whether the mutual interaction between independent variables was significant or not. Different shapes of contour plots shows different type of interactions between the variables like circular nature of contour plots shows less prominent or negligible interactions, and elliptical nature of the contour plots shows comparatively
prominent interactions (Singh et al., 2011). As shown by fig. 1a-1c, each response surface shows a clear peak, which means that the optimum point for optimization pre-treatment conditions was inside the boundary layer of the studied design. Table 3 shows that interaction between FC, IT and SC were significant variables and affect the reducing sugar production response. Fig. 1a showed positive interaction of IT and FC on reducing sugar yield (g/l) while keeping SC constant at middle level. As shown by fig. 1a that as the conc. of IT and FC increase, reducing sugar yield increases but upto middle level only, further increases in both decrease the reducing sugar yield. Fig. 1b shows the interaction of SC and FC on reducing sugar yield and shows that central point of both have highest reducing sugar yield as compared to lower and higher level. Fig. 1c shows interactive effect of SC and IT on reducing sugar yield and shows the similar pattern as highest reducing sugar yield at middle level of both studied variables while keeping third variable (FC) constant. P Value in all three cases was less than 0.05 which indicates positive interaction between the studied variables. Fig. 1a-1c showed that variables FC, IT and SC at middle level were optimum for response (reducing sugar yield). 3.3 Optimization and confirmation experiments The method of pretreatment had a pronounced effect on the yield of reducing sugars. The adequacy and validation of the model was studied by performing 5 additional verification experiments within the range of experimental data as shown in table 4. Validation experiment data was also statistically analysed and found that the correlation coefficient (R2=0.99) between experimental and predicted which also shows the accuracy of the studied model... The main composition of untreated cotton stalk was determined to be 35% cellulose, 22% hemicellulose, 19% lignin, 6.5 % ash content. Under optimum conditions (as optimized by BBD) of microwave-assisted FeCl3 pretreated cotton stalk consisted of 52.1% cellulose, 15.6% hemicellulose, 11.8% lignin, ash content 3.5% . Microwave-assisted FeCl3
pretreatment increased the proportion of cellulose by 48.8% and decreased that of hemicelluloses, lignin and ash by 29% and 37 %, 46 %, respectively, while compared with untreated cotton stalk. The microwave-assisted FeCl3 pretreatment was effective in fractionating the hemicellulose and lignin components (Lu and Zhou, 2011). Liu and Zhou (2011) studied microwave-assisted FeCl3 pretreatment of rice straw and found 35 % decrease in hemicellulose content and 39.5% decrease in lignin content after pretreatment. During pretreatment, there is always a loss of lignin and hemicellulose part due to breaking of bonds between cellulose, hemicellulose and lignin complex. Both components are solubilized into different components like phenylic compounds and monomeric sugars, respectively, during pretreatment. In this study, nearly 68% hemicellulose is still present after the pretreatment, which can be converted into pentose sugars by exposing it to xylanase. The simultaneous conversation of both cellulose and hemicellulose part into hexose and pentose sugars, respectively, increases the efficiency of ethanol production from biomass.
3.4 Enzyme production and saccharification Major bottleneck in biomass to ethanol conversion is the cost of cellulase enzymes and any strategy which can bring down the production cost of cellulases can significantly reduce the cost of bio-ethanol (Sukumaran et al., 2009). Enzymatic hydrolysis of pretreated cotton stalk was carried out with crude supernatant from A. flavus for depolymerization of cell wall carbohydrate fraction into fermentable sugars. The present study indicates that microbial biotransformed cotton stalk can be a rich substrate for enzyme production. Solid state fermentation needs lesser infrastructure, low level of water, relatively less skilled manpower and solid medium was used both as solid support and substrate for enzyme production. Cheaper raw material like agro-industrial waste can be used for enzyme production under SSF. Under SSF more concentrated product is produced, which in this case is very much
advantageous (Aswathy et al., 2009). The A. flavus enzyme had activities of total cellulase 8.3±1.1 FPU/g, endoglucanase (CMCase) 136±3.5 IU/g, b-glucosidase 96±2.9 IU/g and xylanase 175±4.8 IU/g. Similar results of enzyme production were found by Ahamed and Vermette (2008) & Dhillion et al. (2011). Cellulose accessibility by the cellulase enzyme depends upon many factors like available surface area, cellulose crystallinity, pore volume, particle size etc. (Yang et al., 2011). Hydrolysis of biomass requires cellulase enzyme to penetrate the polymer and bind with specific binding sites of the substrate, so that the enzyme sits on the polymer and effects a slow degradation (Sukumaran et al., 2009; Singh et al., 2013). During enzymatic hydrolysis highest reducing sugars concentration obtained with pretreated cotton stalk was 13.7 g/L after 72 h of incubation. The hydrolysate was concentrated by evaporation to reducing sugar content of 5 % used for ethanol production. In the present study enzymatic hydrolysis yield reaches upto 84.6 % with cotton stalk. Similar results obtained by Liu et al. (2009) with microwave FeCl3 pretreated corn stover. This shows that microwave FeCl3 pretreatment could enhance the enzymatic hydrolysis of biomass by removing hemicellulose present and increasing the accessibility of cellulase to cellulose (Liu et al., 2009; Lu et al., 2011).
3.5 Ethanol production Hydrolyzed enzymes ferment the complex sugars to reducing sugars and then to ethanol. Concentrated enzymatic hydrolysate of cotton stalk with a reducing sugar concentration of 50 g/l was used for the fermentation experiments. Fig. 2 shows the reducing sugar consumption and ethanol production from microwave assisted microwave-assisted FeCl3 pretreatment of Cotton stalk using S. cerevisiae. Ethanol production using cotton stalk hydrolysate was 9.8 gp/l, ethanol volumetric productivity was 0.27 gp/l/h and ethanol yield on consumed sugars was 0.37 gp/gs about 52 % sugar consumed (initial sugar concentration was 50 gs/l) and
efficiency of sugar conversion to ethanol reached upto 72 % with fermentation time of 36 h. However, the ethanol yield obtained from cellulosic hydrolysate using S. cerevisiae (0.37 g/g) were comparable with the previous results of ethanol yield 0.44 g/g from cotton stalk (Keshav et al., 2016); 0.027 g/g from cotton stalks (Shi et al., 2008); 18.3, 16.27 and 21.08 g/100 g was achieved from stem, branch and boll shell of cotton stalk (Jiang et al., 2015).
4
Conclusions
Pretreatment of cotton stalk was optimized by two statistical methodologies PBD and BBD in this study. The conditions for microwave-assisted FeCl3 pretreatment of Cotton stalk were optimized by using PBD and significant factors were further optimized by BBD. Microwaveassisted FeCl3 pretreatment make lingo-cellulose more accessible for enzyme production. The crude unprocessed enzyme cocktail used for saccharification of pretreated cotton stalk with production of reducing sugar was 13.7 g/l. The concentrated enzymatic hydrolysate fermented by S. cerevisiae with ethanol yield of 0.37gs/gp. Present environmental problems due to accumulation and burning of cotton stalk can also be eradicated apart from the production of industrially important enzymes and biofuel- ethanol.
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Figure captions:
Figure 1a. Response surface plots showing the interactive effects of FC (mol/l) and IT (min) on reducing sugar yield (g/l) at constant SC (g/l) Figure 1b. Response surface plots showing the interactive effects of FC (mol/l) and SC (g/l) on reducing sugar yield (g/l) at constant IT (min) Figure 1c. Response surface plots showing the interactive effects of SC (g/l) and IT (min) on reducing sugar yield (g/l) at constant FC (mol/l) Figure 2: Time course of sugar consumption and Ethanol production from microwave assisted microwave-assisted FeCl3 pretreatment of Cotton stalk using S. cerevisiae
Table 1. Levels and results of variables tested in PBD. Code Parameter name
Low level High level t value (-1)
(+1)
P value
Confidence level, %
A
Irradiation time (min.)
10
30
8.22
0.014
98.6
B
Pre-soak time in water 10
20
0.95
0.443
55.7
(hours) C
Liquid- solid ratio
5
8
2.53
0.127
87.3
D
Soak time in FeCl3 0
2
7.27
0.018
98.2
700
-3.79
0.063
93.7
(hours) E
Microwave
power 500
(Watt) F
Tween 80 (%)
0
0.01
-0.63
0.592
40.8
G
Substrate
5.0
50.0
8.85
0.013
98.7
0.15
13.6
0.005
99.5
1.0
-3.48
0.074
92.6
concentration (g/l) H
FeCl3
concentration 0.05
(mol/l) I
Particle size (mm)
0.2
Table 2. Design and results of BBD. Run
FC
IT
SC
Reducing sugars (g/l)
1
0.15
20
55
6.3
2
0.2
20
40
5.6
3
0.15
15
40
5.6
4
0.15
15
70
4.3
5
0.15
25
70
5.5
6
0.15
20
55
6.6
7
0.1
15
55
4.4
8
0.2
25
55
5.1
9
0.15
20
55
6.5
10
0.15
25
40
5.9
11
0.1
25
55
3.6
12
0.15
20
55
6.6
13
0.15
20
55
6.5
14
0.2
15
55
3.9
15
0.2
20
70
3.9
16
0.1
20
40
4.2
17
0.1
20
70
3.8
FC= FeCl3 Concentration (mol/l); IT= Irradiation time (min); SC=Substrate concentration (g/l)
Table 3. ANOVA table for the adjusted model of response from reducing sugar yield from cotton stalk. Sum of Source Squares DF Model 19.05 A 0.781 B 0.211 C 1.80 A2 10.484 B2 1.66 C2 1.065 AB 1 AC 0.42 BC 0.56 Residual 0.117 Lack of Fit 0.082 Pure Error 0.034 Cor Total 19.176
9 1 1 1 1 1 1 1 1 1 7 3 4 16
Mean F Square Value Prob > F 2.117 126.461 < 0.0001 0.781 46.65 0.0002 0.211 12.61 0.0093 1.80 107.78 < 0.0001 10.484 626.1 < 0.0001 1.66 99.16 < 0.0001 1.065 63.61 < 0.0001 1 59.716 0.0001 0.422 25.23 0.0015 0.562 33.59 0.0007 0.016 0.027 3.168 0.147 0.008
significant
not significant
Table 4. Confirmatory experiments Number
FC
IT
SC
Reducing sugar (g/l)
1
0.15
20.11
49.40
6.64
2
0.15
22.32
50.63
6.60
3
0.15
20.67
48.50
6.66
4
0.15
20.95
45.66
6.66
5
0.16
21.07
51.15
6.64
FC= FeCl3 Concentration (mol/l); IT= Irradiation time (min); SC=Substrate concentration (g/l)
6.48885 5.76664
RSY (g/l)
5.04443 4.32221 3.6
25.00 0.20 22.50 0.18 20.00
IT (min)
0.15 17.50
0.13 15.00
0.10
Fig. 1a
FC (mol/l)
6.59963 5.9216
RSY (g/l)
5.24357 4.56553 3.8875
70.00 0.20 62.50 0.18 55.00
SC (g/l)
0.15 47.50
0.13 40.00
0.10
Fig. 1b
FC (mol/l)
6.56775 6.00394
RSY (g/l)
5.44013 4.87631 4.3125
70.00 25.00 62.50 22.50 55.00
SC (g/l)
20.00 47.50
17.50 40.00
15.00
Fig. 1c
IT (m in)
12
50
10
40
8
30
6
20
4 Reducing sugar (g/L)
10
2
Ethanol (g/L)
0
0 4
8
12
24 Time (h)
Fig. 2.
36
48
Ethanol conc. (g/L)
Reducing sugar (g/L)
60
Highlights: 1. 2. 3. 4. 5.
Optimization of pre-treatment using sequential statistical methodology. Pre-treated cotton stalk used for enzyme production. Hydrolysis of biomass by crude enzymes at bioreactor level. Concentration of hydrolysate and ethanol production. Energy production as well as solid waste management.