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Comparison of two pretreatments methods to produce second-generation bioethanol resulting from sugarcane bagasse
Industrial Crops & Products 122 (2018) 414–421
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Comparison of two pretreatments methods to produce second-generation bioethanol resulting from sugarcane bagasse
T
⁎
Daniel José Bernier-Oviedoa,c, , John Anderson Rincón-Morenoa, José Fernando Solanilla-Duquéb, José Aldemar Muñoz-Hernándeza, Henry Alexander Váquiro-Herreraa a
Crop Production and Health Department, Agronomic Engineering Faculty, Universidad del Tolima, Ibagué, Colombia Agroindustry Department, Agricultural Science Faculty, Universidad del Cauca, Popayán, Colombia c Food and Agro-industry Research Group, Universidad de Caldas, Manizales, Colombia b
A R T I C LE I N FO
A B S T R A C T
Keywords: Sugarcane bagasse Steam explosion Acid hydrolysis Carbohydrate Bioethanol
Non-centrifugal cane sugar (NCS) is a high carbohydrate-content food obtained by boil evaporation of the sugarcane juice. In the manufacturing process, the by-product of NCS called bagasse is used as foul for the boilers, underestimating its potential as a lignocellulosic source for second-generation bioethanol. In order to assess the bioethanol potential of the by-product resulting from the NCS production, pretreatments were applied to breakdown the lignocellulosic structure for the study in hand. Therefore, this study carried out a comparison of two pretreatment methods steam explosion (SE) and acid hydrolysis (AH) applied to the sugarcane bagasse to produce second-generation bioethanol. It was evidenced that both pretreatments redistribute lignin and hemicelluloses and enhances the accessible surface area of the biomass which further benefitted the subsequent fermentation process as the reducing sugars were available enough to foster the production of bioethanol. The study found that the SE pretreatment was likely to obtain more bioethanol as the reducing sugars (glucose) production outperformed other pretreatments under different residence times and concentrations. Considering the necessity to develop second-generation biofuel production, this study presented the sugarcane bagasse as a promising and abundance lignocellulosic substrate to be investigated more in depth in the Colombian context.
1. Introduction Nowadays the growing demand of energy for transportation and industrial processes have increased substantially. Large quantities of fuel, especially petroleum-based liquid fuel, are constantly required to meet this demand. Nevertheless, this is a highly pollutant non-renewable fuel extracted from fossils. Hence, it is crucial to foster the quest for fuels obtained from renewable sources that do not contaminate the environment (Saini et al., 2015). Under those circumstances, biofuels such as bioethanol have emerged as an ideal renewable fuel that meets these requirements in a sustainable fashion. Essentially bioethanol has higher oxygen content than petroleum, which can boost combustion and reduce hydrocarbon, carbon monoxide and particulate emissions and can be obtained from different low-priced substrates (Zabed et al., 2016). The substrates used to produce biofuel are numerous which has led to a considerably increasing in the worldwide production from 31 billion barrels in 2001 up to 50 billion barrels in 2015 (Sarkar et al.,
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2012). The U.S.A and Brazil are regarded the largest producers of the ‘first generation’ bioethanol in the world with a 62% of market share. So far, U.S has supported corn-based bioethanol production and Brazil has focused on sugar-based bioethanol (Jonker et al., 2016). Although corn-based and sugar based-ethanol are promising substitutes to petroleum-based fuel production, they are not enough to substitute a considerable portion of the one trillion gallons of fossil fuels consumed worldwide each year (Cai et al., 2017). With regards to the Colombian market, sugarcane-based ethanol production was of 366.75 million liters in 2017 harvested in 238,304 ha, which has permitted to comply with the mandatory 10% blend of ethanol in gasoline (E10) in cities with populations larger than 500,000 inhabitants (Fedebiocombustibles, 2015). However, it is expected to observe a high-demand for bioethanol due to a mandatory blend of 30% of ethanol in gasoline projected by the year 2030. The production of solely "first-generation bioethanol" from sugarcane stance uncertainties on the sustainable production of this biofuel as the harvest of this crop might cause competition over land-use (Larsen et al., 2012).
Corresponding author at: Facultad de Ingeniería Agronómica, Universidad del Tolima, B. Santa Helena A.A. 546, Ibagué, Colombia. E-mail address: [email protected] (D.J. Bernier-Oviedo).
https://doi.org/10.1016/j.indcrop.2018.06.012 Received 27 November 2017; Received in revised form 8 May 2018; Accepted 4 June 2018 0926-6690/ © 2018 Elsevier B.V. All rights reserved.
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2015).
Despite the concerns on land-use, the biofuel production, so far, have had a positive impact to National policies on environmental sustainability initiatives such as the National Biofuels Program, the Low Carbon Development Strategy, and the implementation of a Bill on renewable energy and energy efficiency in which biomass is included. As a result of this environmental package backed by the Ministry of Environment and Sustainable Development, the bioethanol is also contributing to achieve Colombia's climate change commitment of 20% reduction of Greenhouse Gases (GHG) emissions under the Paris Climate Agreement (MINAMBIENTE et al., 2015). This evidence was observed in a study carried out by the Inter-American Development bank (BID) and Ministry of Mines and Energy in which the bioethanol produced in Colombia could reduce the GHG emissions in about 74% compared to the emissions released by the burning of fossil fuels (BID et al., 2012). Therefore, it is essential to obtain biofuels from other sources that does not compete for the land-use and in the same fashion reduce GHG emissions. (Larsen et al., 2012) Thus, the sort of biofuel that might contribute to meet those requirements is the second-generation bioethanol. It is currently the most advanced, environmentally friendly biofuel made from non-edible crops and it can substitute fossil fuels as transport fuel (Zucaro et al., 2016). Among several raw materials, the lignocellulosic biomass appears as a suitable option that can be used in the second-generation bioethanol industry (Akgul et al., 2012; Matías et al., 2015). Additionally, lignocellulosic biomass can be supplied on a large-scale basis from different sources as the lignocellulosic materials are no longer used in the value chain. So, their availability and low-cost make them appropriate for use as a “second generation biofuel” (Singh et al., 2016). Currently the most favorable cellulosic feedstocks derived from plant residues in the U.S., South America, Asia and Europe are from corn stover, sugarcane bagasse, rice and wheat straws, respectively (Aditiya et al., 2016). Despite the benefits of using this sort of feedstock, the lignocellulosic biomass contains a high degree of complexity inherent to the processing of this material due to its physicochemical matrix and composition. This means that the biomass requires an intensive labor to break down the cellulose and hemicellulose into fermentable sugars (Quintero et al., 2013). So, in order to obtain the second-generation bioethanol, it is necessary to apply previous processes that reorganize the structural composition of lignin, hemicellulose and cellulose contained in it. This previous step is called pretreatment and is significant to reduce operational costs and to increase the efficiency gains in further fermentation process (Chen et al., 2014). The pretreatments are a crucial step that influences the effectiveness of the lignocellulosic materials to be converted into second generation biofuel (Haghighi Mood et al., 2013). The pretreatment, as the beginning stage of bioethanol production, therefore, must be carried out carefully to optimize the result. For this reason, it is necessary to assess different pretreatments applied to agricultural by-products to evaluate the concentration of fermentable sugars to produce bioethanol (Aditiya et al., 2016). This study aimed to determine the technical viability of sugarcanebagasse bioethanol through the comparison of the most effective pretreatment among a physical pretreatment (SE) and a chemical pretreatment (AH) applied to sugarcane bagasse. Afterwards, the effects of pretreatments on sugarcane bagasse were assessed together with the determination of the inhibitory compounds. Later, the pretreatment that delivered a high yield of fermentable sugars was then submitted in a subsequent enzymatic saccharification and a further fermentation process. A non-linear regression analysis was carried out to model the enzymatic saccharification. Finally, conclusions are presented. Since there is no a fit-for-all pretreatment solution to any sort of lignocellulosic material, it is expected that this study builds up a state-ofart regarding sugarcane bagasse as a raw material to produce secondgeneration bioethanol in Colombia to help to reduce the current 8% GHG emitted by the transportation sector in Colombia (United Nations,
2. Materials and methods 2.1. Raw material Sugarcane bagasse was obtained from a commercial farm located in the municipality of Alvarado (Tolima, Colombia), located at 439 masl, 26 °C mean annual temperature, and 70% mean annual relative humidity. The raw material was dried in a forced convection dryer (Thermolab TH 53, DIES, Colombia) at 70 °C for 48 h until constant weight was obtained. The dried sugarcane bagasse, with a moisture content of 10 ± 0.2% (dry basis), were then ground in a hammer mill (Model 4 Thomas-Wiley Laboratory Mill, Thomas Scientific, USA) to reduce particle size to pass a 2 mm screen. The resulting material was stored at 4 °C for 3 days prior to use. 2.2. Pretreatments 2.2.1. Steam Explosion (SE) The SE pretreatment was based on the method proposed by Viola et al. (2013). Samples of sugarcane bagasse were placed in a laboratory bioreactor (ITEMSA, Colombia) with saturated steam supplied from a fire-tube boiler of 2 BHP and flow of 69 lb/h (Equipos y Calderas Industriales EU, Colombia). SE pretreatments were performed at 100 psi over different residence times (15, 30 and 60 min). Afterwards, the pretreated material was filtered and washed out with distilled water to remove inhibitory substances along with the water-soluble hemicellulose. The resulting liquid fraction was stored at 4 °C for 1 h to be used for determination of total carbohydrates (TC) and reducing sugars (RS). The solid residue remaining after filtration was dried (at 70 °C for 18 h) to be used in the enzymatic hydrolysis. 2.2.2. Acid hydrolysis (AH) The AH was carried out based on the method described by Jackson de Moraes Rocha et al. (2011). Samples of sugarcane bagasse were mixed with different sulphuric acid solutions (2.5%, 5% and 10%) in a sample/solution ratio of 1:30 (w/v) and submitted to AH at 100 °C for 60 min. As in the SE pretreatment, each hydrolysate was filtered and washed. Liquid fractions were used for determination of total carbohydrates and reducing sugars, and solid fractions were dried and used in the enzymatic hydrolysis. 2.3. Effects of pretreatments on lignocellulosic biomass (sugarcane bagasse) 2.3.1. Total carbohydrate determination The total carbohydrates of the lignocellulosic material were quantified before and after the pretreatments were completed (SE and AH). The contents of TC were measured spectrophotometrically at 620 nm (Helios gamma spectrophotometer, Thermo Fisher Scientific, Waltham, USA) according to the anthrone-sulfuric acid methodology (Hackmann et al., 2013; Leyva et al., 2008). 2.3.2. Determination of reducing sugars The liquid fractions resulting from enzymatic hydrolysis and fermentation (0–48 h) was quantified spectrophotometrically at a wavelength of 540 nm through the DNS (glucose) method with a Helios gamma spectrophotometer (Thermo Fisher Scientific, Waltham, USA) (Ghose, 1987; Miller, 1959; Saqib and Whitney, 2011). 2.3.3. Characterization of Lignocellulosic biomass The biomass was submitted to an acid detergent fiber (ADF), neutral detergent fiber (NDF) and acid detergent lignin (ADL) tests to determine the contents of cellulose, hemicellulose and lignin using a modified method described by Van Soest et al. (1991). 415
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2.4. Determination of inhibitory compounds 2.4.1. Determination of acetic acid content The quantification of acetic acid was verified before and after the pretreatments were applied (SE and AH) according to Cheng et al. (2008). 2.4.2. Determination of phenolic compounds and furfural The content of phenolic compounds was quantified according to the procedure developed by Singleton et al. (1999) in a spectrophotometer (Helios gamma; Thermo Fisher Scientific, Waltham, USA) at 760 nm. The quantification of furfural was done according to 9097 and 9098 methods by the AOAC (1984) with absorption spectrum at 277 nm. 2.5. Enzymatic hydrolysis - activity and saccharification The enzymatic activity of the enzyme celluclast 1.5 L (endoglucanase/cellobiohydrolase) was quantified according to the procedure described by Ghose (1987). The enzymatic saccharification was applied using the 1.5 L celluclast enzyme over a period of 48 h. The enzyme concentrations were of 7.5, 15 and 30 filter-paper units (FPU) per gram based on the parameters used by Wang et al. (2015a, 2015b). The process was monitored every 12 h and the results were expressed in milligrams equivalent of glucose per gram of dry sample (mg GE/g ds). 2.6. Fermentation The inoculum (0.4 g) used in the fermentation test was diluted in 100 mL of a medium (30 °C, pH 5.0) containing urea (0.23 g), the enzymatic hydrolysates and those hydrolysates obtained in the pretreatments. The final cell concentration in the fermentation was of 108 cells/ mL. The process was monitored for 48 h to determine the conversion rate of fermentable sugar (glucose) and ethanol concentrations. The latter was quantified using a gas chromatograph (Hewlett Packard 6890 Series, Agilent Technologies Inc., USA) equipped with an HP-BALC column (7.5 m × 0.20 mm) at 165 °C and an internal Flame Ionization Detector (FID) at 270 °C. Isopropanol was used as standard and nitrogen (15 mL/min) as the entrainment gas. The fermentation process followed the methodology proposed by Pereira et al. (2011).
Fig. 1. Effect of SE on the yields of total carbohydrates (A) and reducing sugars (B) in sugarcane bagasse. Error bars represent standard deviation from the mean. Means with different letters indicate significant difference (p < 0.05).
2.7. Statistic analysis error (MRE) (Eq. (3)) (Villa-Vélez et al., 2015). The results obtained in the study were expressed as mean and standard deviation of three determinations for each pretreatment. Analysis of variance (ANOVA) at the 95% confidence level was used to compare the mean values of each determination among the different pretreatments. Multiple range tests (MRT) were used to determine which means were significantly different from the others by using the Tukey’s honestly significant difference procedure. ANOVA and MRT were performed using “anova1” and “multcompare” functions of the Statistic Toolbox of MATLAB® R2016b (The MathWorks Inc., Natick, MA, USA), respectively. A non-linear regression analysis was carried out to model the enzymatic saccharification by using the Weibull model (Eq. (1)) (PiñerosCastro and Velásquez-Lozano, 2014).
y = y0 + (ymax −y0 )[1−exp(−kt )]
2 Radj = 1−
MRE =
2 Syx
s y2
n |yi* −yi | 100 ∑ n i = 1 yi*
(2)
(3)
where Sy is the standard deviation for the sample, Syx is the standard deviation for the model estimation, yi* represents the experimental values; yi represents the estimated values; and n is the number of experimental data points used in the regression analysis. 3. Results and discussion
(1)
3.1. Incidence of the steam in carbohydrate yield
where y0, y and ymax represent the initial RS fraction, the RS fraction at time t, and maximum RS content (mg GE/g, ds), respectively; k represents the kinetic rate constant (1/s). The model parameters k and ymax (Eq. (1)) were estimated using “nlinfit” function of the Statistic Toolbox of MATLAB® R2016b. (The MathWorks Inc., Natick, MA, USA). The statistical significance of the estimated parameters was evaluated through their 95% confidence intervals, whereas the goodness of model fit was quantified by the adjusted coefficient of determination (R2adj) (Eq. (2)) and the mean relative
Fig. 1 shows the yields of total carbohydrate and reducing sugars obtained through the SE applied to the sugarcane bagasse at different residence times (15, 30 and 60 min). The maximum amount of total carbohydrates in the residual material was obtained at the residence time of 30 min (160 °C and 100 psi) (Fig. 1A). An increase of 23% compared to the same pretreatment applied for 15 min was observed. It was also noted that SE pretreatment increased six-fold the carbohydrates available. Although the residence time of 60 min showed that the 416
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Table 1 Composition of cell wall in sugarcane bagasse before and after pretreatment. Composition (%)
Without Pretreatment
Acid hydrolysis t = 1 h; 10 % H2SO4
Steam explosion t = 30 min
ADF ADL NDF Cellulose Hemicellulose Lignin Cellular content Silicon dioxide
34.66 ± 0.54 9.66 ± 0.44 53.80 ± 0.20 25.00 ± 0.11 19.14 ± 0.34 9.16 ± 0.46 46.20 ± 0.21 0.50 ± 0.01
86.81 ± 3.37 20.69 ± 1.18 87.61 ± 0.04 66.11 ± 3.36 0.06 ± 0.00 0.36 ± 0.29 12.39 ± 0.04 20.33 ± 0.98
81.96 ± 3.42 20.54 ± 6.77 90.00 ± 1.03 57.97 ± 0.67 8.04 ± 2.60 0.84 ± 0.41 10.00 ± 1.03 22.24 ± 1.52
a ADF (Acid detergent fiber), bADL (Acid Detergent lignin), cNDF (Neutral detergent fiber).
total amount of carbohydrates after this time had decreased (104 mg TC/g dry sample). Thus, the SE is not convenient when residence times last more than 30 min. Reducing sugars showed a similar trend to that of total carbohydrates. It was noted that a 33% increase of reducing sugars was obtained on residence time lasting 30 min compared to the process applied for 15 min (Fig. 1B). Nonetheless, an increase in the exposure time of the material to the pretreatment reduced the concentration of the total carbohydrates. Therefore, applying SE enhanced the amount available of TC and RS compared to the material that did not undertake any previous treatment. Thus, the action of the steam to breakdown the protective structure of the hemicellulose and the lignin on the cellulose seemed to be effective. This structure breakdown might be attributed to the aromatic structures of the lignin which contain less oxygen than the carbohydrates of the cellulose; the lignin is therefore less susceptible to the attack of biological or physical factors than the cellulose. Due to these conditions, hemicellulose is the polysaccharide with the greatest potential for selective solubilization (Table 1) by the SE pretreatment (Monschein and Nidetzky, 2016). The downside is that the degradation of hemicellulose simultaneously produces derivatives such as xylans (Balat, 2011), which in turn produce water, methanol, formic, acetic, propionic, 1-hydroxypropanone, 1hydroxybutanone, 2furfuraldehyde and furfural (Ask et al., 2013; Tomás-Pejó et al., 2011).
Fig. 2. Effect of AH on the yield of total carbohydrates (A) and reducing sugars (B) in sugarcane bagasse. Error bars represent standard deviation from the mean. Means with different letters indicate significant difference (p < 0.05).
3.2. Chemical pretreatment Likewise, the fractionation of its matrix to subtract the lignin might have degraded the carbohydrates (Benjamin et al., 2014). In that sense, authors such as Kumar et al. (2015) discussed similar results on reducing sugar concentrations when the pretreatments with diluted acids and 121 °C were applied to the sample material. According to these authors residences times greater than 75 min do not increase the concentrations of carbohydrates. It was also found that the amount of RS is higher in the lignocellulosic material after both pretreatments SE and AH were applied compared to the no pretreated samples. Therefore, residence times greater than 30 min (SE) and 1 h (AH) evidenced that in both scenarios increasing the residence time caused a fragmentation of RS. This is due to the breakdown of these bonds into inhibitory compounds such as acetic acid and furfural (Xiao et al., 2011).
Effect of acid concentration The chemical pretreatment was undertaken using sulfuric acid at three different concentrations: 2.5%; 5% and 10% to breakdown the lignocellulosic structure of sugarcane bagasse. As shown in Fig. 2A, there is a direct relationship between dosage (acid concentration) and response (amount of total carbohydrate). As a result, residence times of 1 h and 2 h yielded 251.1 mg TC/g sample and 308.8 mg TC/g sample, respectively. Both residence times used a sulfuric acid concentration of 10%. These yields might be due to more depolymerization of polysaccharides such as hemicellulose (Table 1) as stated by Chen et al. (2012). Although, the yields increase up to 23%, the energy consumption of the 2 h pretreatment raised the cost of operation by 96%, considerably affecting the viability in the process. It was also noticed that the RS concentrations after the pretreatment at 1 h did not appear to have a significant difference between those concentrations of 2.5%, 5% and 10% acid solutions (Fig. 2B). Nevertheless, the average concentration obtained by the AH was 43 mg TC/g. This result is higher compared to the no pretreated sample (28 mg TC/g sample). Moreover, the yields decreased to 33 and 27 mg TC/g sample with 2 h and 3 h of residence times, respectively (Fig. 2B). This reduction might be caused by the overexposure of the cellulose through the hydrolysis of hemicellulose due to residence times lasting more than 60 min (Yoon et al., 2014).
3.3. Modification sugarcane bagasse cell wall The effect of the two pretreatments on the structural components of the lignocellulosic biomass (cellulose, hemicellulose and lignin) is showed in Table 1. The hemicellulose was the structural component heavily affected due to the pretreatment. This was proven during the SE pretreatment (t = 30 min) where the hemicellulose content was reduced from an initial 19.14% down to 8.04%, whereas AH pretreatment (t = 1 h, 10%) removed 19.08% of hemicellulose. Comparatively, the 417
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lignin contents were reduced to 0.36% in AH and 0.84% for SE. This might be caused due to the solubilization of lignin and hemicellulose caused by pretreatments, hence increasing the cellulose content (57.97% for SE and 66.11% for AH). This rearrangement in the cell wall composition of the lignocellulosic biomass could be explained by the protective action of hemicellulose and lignin on cellulose and the strength of ether bonds (α-O-4, B-O-4, 4-O-5) and carbon-carbon bonds of the lignin (Han et al., 2012); that triggered a structural rearrangement after the pretreatments were applied. This was done without reaching a complete solubilization (Cardona et al., 2014; Ibrahim et al., 2011), and without enzymes. Similar changes in the cell wall were corroborated by (Soares et al., 2011) who managed to reduce the hemicellulose content in 13% and increase the cellulose content available in 30.5%. These results demonstrated that the removal of hemicellulose, partial delignification and the exposure of the cellulose are highly related to the application of physical and chemical pretreatments on lignocellulosic material to enhance a following enzymatic saccharification. 3.4. Enzymatic hydrolysis The enzyme effect using different enzyme concentrations (7.5, 15 and 30 FPU/g) on the sample material pretreated with AH (t = 1 h, 10% H2SO4) and SE (t = 30 min) was assessed. The experimental results of enzymatic hydrolysis are shown in Table 2. Hydrolysis was performed to compare the kinetic effect of the enzyme (endoglucanase/ cellulose hydrolysis - Celluclast 1.5 L) on the lignocellulosic material of the pretreated sugarcane bagasse and its cellulose to RS conversion rate as shown in Fig. 3. The experimental data obtained for the enzymatic hydrolysis were adjusted applying the Weibull kinetic model. The identified model parameters and their 95% confidence intervals are shown in Table 3 for the hydrolysis kinetics of WP, SE and AH at enzymatic activities of 7.5, 15 and 30 FPU/g. Considering the identified parameters, satisfactory simulations of the hydrolysis kinetics were obtained (Fig. 3) in terms of both MRE and R2adj. Thus, the Weibull model was able to represent more than 97% of the variation of all experimental data with estimates deviated on average less than 5% from the real values. According confidence intervals, all model parameters were statistically significant at p < 0.05. Some authors also successfully used the Weibull model to describe enzymatic saccharification kinetics (Kansou et al., 2015; Piñeros-Castro and Velásquez-Lozano, 2014; Wang et al., 2015a, 2015b). The values for the model parameters of the different pretreatments and enzyme concentrations were found to be between 0.089 and 0.217
Fig. 3. Amount of RS, expressed as glucose, released during the enzymatic hydrolysis of sugarcane bagasse pretreated by AH (A) and SE (B). AH: (t = 1 h, 10% H2SO4); SE: (30 min); WP: without pretreatment.
1/h for the rate constant (k) and between 128 and 417 mg GE/g ds for maximum RS content (ymax) (Table 3). The higher is k, the steeper is the hydrolysis rate during the first stage of hydrolysis and vice versa (Kansou et al., 2015). Thus, pretreatments where hydrolysis kinetics showed k values greater than 0.141 1/h presented more initial susceptibility of the hydrolysable fraction by the enzyme, and the kinetics showed an asymptotic behavior from times around 20 h (Fig. 3). However, the value of the hydrolysis extent at the end time (ymax) represents the final fraction of biomass hydrolyzed. According the highest ymax, RS could increase by 47.3% for SE at 30 FPU/g as compared with WE at the same enzyme concentration. In Fig. 3(A and B), an exponential enzymatic activity was observed in the first 12 h, afterwards the enzymatic hydrolysis reached a steady state until the maximum conversion rate peaked (48 h). So that, the enzymatic hydrolysis showed effectiveness when a pretreatment is applied compared to the untreated sample material (WP). This is due to the increase of the biomass structure porosity which leads to a higher cellulose exposure (Han et al., 2012). As can be seen, the initial velocities and the enzymatic concentration in the first hours of saccharification is directly linked to a higher content of glucose on the pretreated material. Therefore, the pretreatment was observed as a mean to an enhanced enzyme hydrolysis performance, insomuch as the effectiveness of the
Table 2 Experimental results for the enzymatic saccharification (mg GE/g ds)*. Enzyme concentration
t (h)
Without Pretreatment
Acid hydrolysis t = 1 h; 10 % H2SO4
Steam explosion t = 30 min
7.5 FPU/g
12 24 36 48
107.50 123.15 126.89 129.34
± ± ± ±
3.05a 5.55a 3.37a 6.62a
192.55 207.39 210.25 229.17
± ± ± ±
0.41b 3.79b 4.33b 28.29b
159.88 197.97 205.29 211.66
± ± ± ±
9.55c 8.10b 4.92b 8.23b
15 FPU/g
12 24 36 48
163.69 184.90 191.61 194.76
± ± ± ±
2.50a 5.87a 0.88a 5.94a
284.15 299.70 301.61 305.20
± ± ± ±
4.84b 4.58b 3.57b 3.41b
324.02 384.49 396.74 402.97
± ± ± ±
2.42c 5.65c 9.08c 9.53c
30 FPU/g
12 24 36 48
261.62 280.77 282.64 283.81
± ± ± ±
4.70a 7.37a 9.08a 3.90a
279.36 393.27 400.80 403.15
± ± ± ±
9.62a 11.78b 17.42b 8.96b
274.00 362.30 387.45 391.72
± ± ± ±
12.25a 10.00c 10.27b 10.18b
* Mean and standard deviation of three replicates. Means with different superscripts within a row indicate significant difference (p < 0.05) between pretreatments. 418
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Table 3 Estimated parameters, confidence intervals and goodness-of-fit statistics of the hydrolysis models. Parameters*
95% Confidence intervals
Pretreatment
FPU/g
k
ymax
k
ymax
MRE (%)
R2adj
Without pretreatment
7.5 15 30
0.128 0.141 0.206
128 193 283
[0.105, 0.152] [0.125, 0.157] [0.176, 0.235]
[125, 132] [190, 196] [279, 287]
2.91 1.77 2.01
0.990 0.997 0.997
Steam explosion (t = 30 min)
7.5 15 30
0.159 0.217 0.090
216 303 417
[0.107, 0.211] [0.193, 0.242] [0.074, 0.106]
[207, 224] [300, 306] [399, 434]
3.25 1.82 3.83
0.977 0.999 0.989
Acid hydrolysis (t = 1 h, 10 % H2SO4)
7.5 15 30
0.099 0.127 0.089
212 402 400
[0.082, 0.116] [0.117, 0.137] [0.079, 0.099]
[205, 219] [396, 408] [390, 411]
4.48 2.87 3.67
0.990 0.998 0.995
* ymax: maximum RS content (mg GE/g, ds); k: kinetic rate constant (1/h). Table 4 Inhibitory compounds contained in pretreated sugarcane bagasse. Pretreatment
Acetic acid (mg AAE/ mL)*
Furfural (mg/ mL)
Phenolic compounds (mg GAE/mL)**
Without Pretreatment SE (t = 30 min) AH (t = 1 h, 10 % H2SO4)
0.10 0.54 13.37
0.00 0.44 1.52
2.13 6.56 6.57
* mg AAE: milligrams of acetic acid equivalent. ** mg GAE: milligrams of gallic acid equivalent.
previous stages allowed a higher fermentable sugars conversion rate (Sarkar et al., 2012). To sum up the best RS result was obtained on the SE (t = 30 min) at an enzymatic concentration of 30 FPU/g (Fig. 3B); 403.1 mg GE/g ds. While for HA (1 h and 10% H2SO4) (Fig. 3A) the best results were obtained utilizing an enzymatic concentration of 15 and 30 FPU/g; 402.4 and 392 mg GE/g ds, respectively. Nevertheless, there was no significant difference between the concentrations of 15 and 30 FPU/g. This might be caused by the enzymes used in this study which contains endoglucanases. This enzyme might have triggered a negative effect by producing non-desirable sugars that accumulated during the process, mainly cellobiose; a potential inhibitor of the enzyme activity (Ask et al., 2012). The action of endoglucanases releasing glucose and cellobiose molecules could have attacked the regions of low crystallinity of the cellulose generating non-reducing free ends and cellubiohydrolases that act on the non-reducing ends, hence, the low yields (Sarkar et al., 2012). However, an enzymatic inhibition could be avoided recurring to what some authors have accomplished in previous studies; enzymatic cocktails that outperform those one-single enzymes in the hydrolysis (Balat, 2011; Soares et al., 2011). However, such preparations have an economic impact on the production of bioethanol. 3.5. Determination of inhibitors and fermentation The RS obtained after the pretreatments were applied also produced inhibitory compounds to the fermentation process such as acetic acid, furfural and phenolic compounds. In Table 4, the concentrations of these compounds after the pretreatments were done and their association with the structural composition of the biomass are shown. The acetic acid formed in the AH reached a concentration of 13.37 mg/mL, compared to SE (0.54 mg/mL). This compound is a consequence of the incomplete fractionation of the lignin-carbohydrate matrix by the action of vapor pressure (Table 1). This compound hinders rapid thermal expansion to penetrate the structure of the biomass making it difficult to hydrolyze the acetyl groups of this polysaccharide (El-Zawawy et al., 2011). Another inhibitory compound to the fermentation such as furfural
Fig. 4. Bioethanol obtained from pretreated bagasse samples, enzymatically saccharified and fermented from pretreatments (A) SE and (B) AH.
with concentrations of 0.44 mg/mL and 1.53 mg/mL in the SE and AH respectively was found. The highest concentration in AH is attributed to the dehydration of pentoses, specifically xylose, which boost its degradation to furfural when found in an acid medium (Chiaramonti et al., 2012). In like manner, the concentrations of phenolic compounds increased through the action of both pretreatments, showing 419
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Notwithstanding, a study carried out by Pereira et al. (2011), has shown that yields as high as 86% ethanol is technically feasible on biomass employing two different industrial isolated Saccharomyces Cerevisiae strains. Although, this study did not use this type of industrial isolates, the results are still valuable as it shows the effectiveness of the pretreatments applied with lower fermentation time (48 h) and a comercial Saccharomyces Cerevisiae strain. 4. Conclusions This study emphasizes the importance of applying pretreatments in lignocellulosic materials to foster further research and production of second-generation bioethanol in Colombia. As such, both pretreatments (SE and AH) proved that the initial composition of the lignin, hemicellulose and cellulose was in fact altered due to the pretreatments' action. This alteration of the cell structure allowed a better performance of the enzyme on the sample material due to a better exposure of the active sites. It was also observed that the SE pretreatment produced lower concentrations of inhibitory compounds prior the fermentation (acetic acid and furfural), producing more reducing sugars to obtain ethanol with regards to AH pretreatment. On balance, SE pretreatment seems to be practical to obtain ethanol as the reducing sugars (glucose) obtained outperform other pretreatments. Whereas, some scholars obtained higher fermentation yields, the yields presented in this study might perform better if other stages such as detoxification to remove inhibitory compounds are aggregated into the process.
Fig. 5. Concentrations of ethanol and glucose during the fermentation process with AH (10% H2SO4) and SE (t = 30 min) pretreatments.
concentrations of 2.13 mg GAE/mL for the no-pretreated material and 6.5 mg GAE/mL for both pretreatments. These concentrations are heavily related to the solubilization and partial degradation of lignin (Doherty et al., 2011). Fig. 4 shows the bioethanol content reached from pretreated, enzymatically saccharified and fermented (Saccharomyces cerevisiae) samples of sugarcane bagasse. The intensity of the electrical signal is expressed in peak amperes (pA). Each of the peaks shown in the two Fig. 4A (SE) and B (AH) are directly proportional to the concentration of ethanol obtained during the fermentation time (t = 0, 2, 4, 6, 8, 16, 24, 48 h). For this purpose, the area under the curve of each of the ethanol peaks was compared. The high concentrations of ethanol attained from the biomass pretreated with SE (t = 30 min) compared to those obtained with AH (t = 1 h, 10% H2SO4), presented a higher applicability potential in the ethanol production process. This result is linked to the effectiveness reached in the enzymatic saccharification that produced a modification in the hemicellulose and lignin with low concentrations of acetic acid and furfural (Table 4) (Fujitomi et al., 2012). Fig. 5 shows the relationship between ethanol and RS concentrations (mg GE/mL) during the 48 h of fermentation of the pretreated lignocellulosic material. The initial amount of substrate (glucose) attained by AH (t = 1 h and 10% H2SO4) along with subsequent enzymatic scarification was 203.89 mg GE/mL. On the other hand, the concentration reached by SE (t = 30 min) was higher (257.87 mg GE/ mL). For both cases, the highest rate of substrate consumption occurred in the first 24 h, after that the concentration of the reducing sugars remained stable until the process was completed. In fact, the highest production rate of ethanol was accomplished in the first 24 h, then the process displayed a steady state. At the end of the fermentation the concentration of ethanol obtained with SE (87.16 mg/mL) was higher than the one achieved with AH (58.7 mg/mL). The percentages of theoretical conversion yield for lignocellulosic biomass were calculated using the maximum concentration of ethanol produced (0.511 g ethanol/g glucose). The biomass pretreated with AH (t = 1 h, 10% H2SO4) and SE (t = 30 min) yielded 71% and 79%, respectively. Several scholars have reached different yields in the fermentation process on biomass pretreated; some studies had a lower theoretical percentage attained were compared to our study with values found between 65.5% and 61.1% on pre-treated straw with diluted acid (López-Linares et al., 2014). Other studies obtained similar yields as the ones reported in this study, where it was evidenced yields of 79.1% and 63.1% using fermented pretreated reed with hot water and fir chips pretreated with peroxide (Lu et al., 2012; Zhang et al., 2014).
Acknowledgements The authors acknowledge the support given by the Universidad del Tolima and its research groups; CEDAGRITOL, GIPRONUT and the Scientific Research and Development Office of the University of Tolima. References Aditiya, H.B., Mahlia, T.M.I., Chong, W.T., Nur, H., Sebayang, A.H., 2016. Second generation bioethanol production: a critical review. Renew. Sustain. Energy Rev. 66, 631–653. http://dx.doi.org/10.1016/j.rser.2016.07.015. Akgul, O., Shah, N., Papageorgiou, L.G., 2012. An optimisation framework for a hybrid first/second generation bioethanol supply chain. Comput. Chem. Eng. 42, 101–114. http://dx.doi.org/10.1016/j.compchemeng.2012.01.012. AOAC, 1984. Official Methods of Analysis of the Association of Official Analytical Chemists, 14th ed. Washington D.C. Ask, M., Bettiga, M., Mapelli, V., Olsson, L., 2013. The influence of HMF and furfural on redox-balance and energy-state of xylose-utilizing Saccharomyces cerevisiae. Biotechnol. Biofuels 6, 1–22. http://dx.doi.org/10.1186/1754-6834-6-22. Ask, M., Olofsson, K., Di Felice, T., Ruohonen, L., Penttilä, M., Lidén, G., Olsson, L., 2012. Challenges in enzymatic hydrolysis and fermentation of pretreated Arundo donax revealed by a comparison between SHF and SSF. Process Biochem. 47, 1452–1459. http://dx.doi.org/10.1016/j.procbio.2012.05.016. Balat, M., 2011. Production of bioethanol from lignocellulosic materials via the biochemical pathway: a review. Energy Convers. Manage. 52, 858–875. http://dx.doi. org/10.1016/j.enconman.2010.08.013. Benjamin, Y., Cheng, H., Görgens, J.F., 2014. Optimization of dilute sulfuric acid pretreatment to maximize combined sugar yield from sugarcane bagasse for ethanol production. Appl. Biochem. Biotechnol. 172, 610–630. http://dx.doi.org/10.1007/ s12010-013-0545-z. BID, Ministerio de minas y energia Colombia, CUE, C, 2012. Evaluación del ciclo de vida de la cadena de producción de biocombustibles en Colombia. Cai, J., He, Y., Yu, X., Banks, S.W., Yang, Y., Zhang, X., Yu, Y., Liu, R., Bridgwater, A.V., 2017. Review of physicochemical properties and analytical characterization of lignocellulosic biomass. Renew. Sustain. Energy Rev. 76, 309–322. http://dx.doi.org/ 10.1016/j.rser.2017.03.072. Cardona, E., Rios, J., Peña, J., Rios, L., 2014. Effects of the pretreatment method on enzymatic hydrolysis and ethanol fermentability of the cellulosic fraction from elephant grass. Fuel 118, 41–47. http://dx.doi.org/10.1016/j.fuel.2013.10.055. Chen, W.-H., Ye, S.-C., Sheen, H.-K., 2012. Hydrolysis characteristics of sugarcane bagasse pretreated by dilute acid solution in a microwave irradiation environment. Appl. Energy 93, 237–244. http://dx.doi.org/10.1016/j.apenergy.2011.12.014. Chen, Y., Zhang, X., Zhang, S., Qin, W., Guo, C., Guo, X., Xiao, D., 2014. Enhanced enzymatic xylose/cellulose fractionation from alkaline liquor-pretreated corn cob by surfactant addition and separate fermentation to bioethanol. Turk. J. Biol. http://dx. doi.org/10.3906/biy-1310-16. Cheng, K.-K., Cai, B.-Y., Zhang, J.-A., Ling, H.-Z., Zhou, Y.-J., Ge, J.-P., Xu, J.-M., 2008. Sugarcane bagasse hemicellulose hydrolysate for ethanol production by acid recovery
420
Industrial Crops & Products 122 (2018) 414–421
D.J. Bernier-Oviedo et al.
hydrolysis time courses. Bioresour. Technol. 200, 287–296. http://dx.doi.org/10. 1016/j.biortech.2015.10.020. Pereira, F.B., Guimarães, P.M.R., Teixeira, J.A., Domingues, L., 2011. Robust industrial Saccharomyces cerevisiae strains for very high gravity bio-ethanol fermentations. J. Biosci. Bioeng. 112, 130–136. http://dx.doi.org/10.1016/j.jbiosc.2011.03.022. Piñeros-Castro, Y., Velásquez-Lozano, M., 2014. Biodegradation kinetics of oil palm empty fruit bunches by white rot fungi. Int. Biodeterior. Biodegrad. 91, 24–28. http://dx.doi.org/10.1016/j.ibiod.2014.03.009. Quintero, J.A., Moncada, J., Cardona, C.A., 2013. Techno-economic analysis of bioethanol production from lignocellulosic residues in Colombia: a process simulation approach. Bioresour. Technol. 139, 300–307. http://dx.doi.org/10.1016/j.biortech. 2013.04.048. Saini, J.K., Saini, R., Tewari, L., 2015. Lignocellulosic agriculture wastes as biomass feedstocks for second-generation bioethanol production: concepts and recent developments. 3 Biotech 5, 337–353. http://dx.doi.org/10.1007/s13205-014-0246-5. Saqib, A.A.N., Whitney, P.J., 2011. Differential behaviour of the dinitrosalicylic acid (DNS) reagent towards mono- and di-saccharide sugars. Biomass Bioenergy 35, 4748–4750. http://dx.doi.org/10.1016/j.biombioe.2011.09.013. Sarkar, N., Ghosh, S.K., Bannerjee, S., Aikat, K., 2012. Bioethanol production from agricultural wastes: an overview. Renew. Energy 37, 19–27. http://dx.doi.org/10. 1016/j.renene.2011.06.045. Singh, R., Srivastava, M., Shukla, A., 2016. Environmental sustainability of bioethanol production from rice straw in India: a review. Renew. Sustain. Energy Rev. 54, 202–216. http://dx.doi.org/10.1016/j.rser.2015.10.005. Singleton, V.L., Orthofer, R., Lamuela-Raventós, R.M., 1999. Analysis of total phenols and other oxidation substrates and antioxidants by means of folin-ciocalteu reagent. Methods Enzymol. 152–178. http://dx.doi.org/10.1016/S0076-6879(99)99017-1. Soares, I.B., Travassos, J.A., Baudel, H.M., Benachour, M., Abreu, C.A.M., 2011. Effects of washing, milling and loading enzymes on the enzymatic hydrolysis of a steam pretreated sugarcane bagasse. Ind. Crops Prod. 33, 670–675. http://dx.doi.org/10.1016/ j.indcrop.2011.01.003. Tomás-Pejó, E., Alvira, P., Ballesteros, M., Negro, M.J., 2011. Chapter 7 – Pretreatment technologies for lignocellulose-to-bioethanol conversion. Biofuels. pp. 149–176. http://dx.doi.org/10.1016/B978-0-12-385099-7.00007-3. United Nations, 2015. Millennium Development Goals Indicators [WWW Document]. (accessed 4.4.18). http://mdgs.un.org/unsd/mdg/seriesdetail.aspx?srid=749. Van Soest, P.J., Robertson, J.B., Lewis, B.A., 1991. Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition. J. Dairy Sci. 74, 3583–3597. http://dx.doi.org/10.3168/jds.S0022-0302(91)78551-2. Villa-Vélez, H.A., Váquiro, H.A., Lopes-Filho, J.F., Telis, V.R.N., Telis-Romero, J., 2015. Study of the specific heat capacity of biomass from banana waste for application in the second-generation ethanol industry. Environ. Prog. Sustain. Energy 34, 1221–1228. http://dx.doi.org/10.1002/ep.12090. Viola, E., Zimbardi, F., Valerio, V., Nanna, F., Battafarano, A., 2013. Use of a twochamber reactor to improve enzymatic hydrolysis and fermentation of lignocellulosic materials. Appl. Energy 102, 198–203. http://dx.doi.org/10.1016/j.apenergy.2012. 04.044. Wang, M., Han, L., Liu, S., Zhao, X., Yang, J., Loh, S.K., Sun, X., Zhang, C., Fang, X., 2015a. A Weibull statistics-based lignocellulose saccharification model and a built-in parameter accurately predict lignocellulose hydrolysis performance. Biotechnol. J. 10, 1424–1433. http://dx.doi.org/10.1002/biot.201400723. Wang, P., Chang, J., Yin, Q., Wang, E., Zhu, Q., Song, A., Lu, F., 2015b. Effects of thermochemical pretreatment plus microbial fermentation and enzymatic hydrolysis on saccharification and lignocellulose degradation of corn straw. Bioresour. Technol. 194, 165–171. http://dx.doi.org/10.1016/j.biortech.2015.07.012. Xiao, L.-P., Sun, Z.-J., Shi, Z.-J., Xu, F., Sun, R.-C., 2011. Impact of hot compressed water pretreatment on the structural changes of woody biomass for bioethanol producti on. BioResources 6, 1576–1598. http://dx.doi.org/10.15376/biores.6.2.1576-1598. Yoon, S.-Y., Han, S.-H., Shin, S.-J., 2014. The effect of hemicelluloses and lignin on acid hydrolysis of cellulose. Energy 77, 19–24. http://dx.doi.org/10.1016/j.energy.2014. 01.104. Zabed, H., Sahu, J.N., Boyce, A.N., Faruq, G., 2016. Fuel ethanol production from lignocellulosic biomass: an overview on feedstocks and technological approaches. Renew. Sustain. Energy Rev. 66, 751–774. http://dx.doi.org/10.1016/j.rser.2016.08. 038. Zhang, L., You, T., Zhang, L., Yang, H., Xu, F., 2014. Enhanced fermentability of poplar by combination of alkaline peroxide pretreatment and semi-simultaneous saccharification and fermentation. Bioresour. Technol. 164, 292–298. http://dx.doi.org/10. 1016/j.biortech.2014.04.075. Zucaro, A., Forte, A., Basosi, R., Fagnano, M., Fierro, A., 2016. Life cycle assessment of second generation bioethanol produced from low-input dedicated crops of Arundo donax L. Bioresour. Technol. 219, 589–599. http://dx.doi.org/10.1016/j.biortech. 2016.08.022.
process. Biochem. Eng. J. 38, 105–109. http://dx.doi.org/10.1016/j.bej.2007.07. 012. Chiaramonti, D., Prussi, M., Ferrero, S., Oriani, L., Ottonello, P., Torre, P., Cherchi, F., 2012. Review of pretreatment processes for lignocellulosic ethanol production, and development of an innovative method. Biomass Bioenergy 46, 25–35. http://dx.doi. org/10.1016/j.biombioe.2012.04.020. Doherty, W.O.S., Mousavioun, P., Fellows, C.M., 2011. Value-adding to cellulosic ethanol: lignin polymers. Ind. Crops Prod. 33, 259–276. http://dx.doi.org/10.1016/j.indcrop. 2010.10.022. El-Zawawy, W.K., Ibrahim, M.M., Abdel-Fattah, Y.R., Soliman, N.A., Mahmoud, M.M., 2011. Acid and enzyme hydrolysis to convert pretreated lignocellulosic materials into glucose for ethanol production. Carbohydr. Polym. 84, 865–871. http://dx.doi.org/ 10.1016/j.carbpol.2010.12.022. Fedebiocombustibles, 2015. Federación Nacional de Biocombustibles de Colombia, Información Estadística Sector Biocombustibles [WWW Document]. (accessed 4.4.18). http://www.fedebiocombustibles.com/. Fujitomi, K., Sanda, T., Hasunuma, T., Kondo, A., 2012. Deletion of the PHO13 gene in Saccharomyces cerevisiae improves ethanol production from lignocellulosic hydrolysate in the presence of acetic and formic acids, and furfural. Bioresour. Technol. 111, 161–166. http://dx.doi.org/10.1016/j.biortech.2012.01.161. Ghose, T.K., 1987. Measurement of cellulase activities. Pure Appl. Chem. 59, 257–268. http://dx.doi.org/10.1351/pac198759020257. Hackmann, T.J., Keyser, B.L., Firkins, J.L., 2013. Evaluation of methods to detect changes in reserve carbohydrate for mixed rumen microbes. J. Microbiol. Methods 93, 284–291. http://dx.doi.org/10.1016/j.mimet.2013.03.025. Haghighi Mood, S., Hossein Golfeshan, A., Tabatabaei, M., Salehi Jouzani, G., Najafi, G.H., Gholami, M., Ardjmand, M., 2013. Lignocellulosic biomass to bioethanol, a comprehensive review with a focus on pretreatment. Renew. Sustain. Energy Rev. 27, 77–93. http://dx.doi.org/10.1016/j.rser.2013.06.033. Han, L., Feng, J., Zhang, S., Ma, Z., Wang, Y., Zhang, X., 2012. Alkali pretreated of wheat straw and its enzymatic hydrolysis. Braz. J. Microbiol. 43, 53–61. http://dx.doi.org/ 10.1590/S1517-83822012000100006. Ibrahim, M.M., El-Zawawy, W.K., Abdel-Fattah, Y.R., Soliman, N.A., Agblevor, F.A., 2011. Comparison of alkaline pulping with steam explosion for glucose production from rice straw. Carbohydr. Polym. 83, 720–726. http://dx.doi.org/10.1016/j.carbpol. 2010.08.046. Jackson de Moraes Rocha, G., Martin, C., Soares, I.B., Souto Maior, A.M., Baudel, H.M., Moraes de Abreu, C.A., 2011. Dilute mixed-acid pretreatment of sugarcane bagasse for ethanol production. Biomass Bioenergy 35, 663–670. http://dx.doi.org/10.1016/ j.biombioe.2010.10.018. Jonker, J.G.G., Junginger, H.M., Verstegen, J.A., Lin, T., Rodríguez, L.F., Ting, K.C., Faaij, A.P.C., van der Hilst, F., 2016. Supply chain optimization of sugarcane first generation and eucalyptus second generation ethanol production in Brazil. Appl. Energy 173, 494–510. http://dx.doi.org/10.1016/j.apenergy.2016.04.069. Kansou, K., Buléon, A., Gérard, C., Rolland-Sabaté, A., 2015. Multivariate model to characterise relations between maize mutant starches and hydrolysis kinetics. Carbohydr. Polym. 133, 497–506. http://dx.doi.org/10.1016/j.carbpol.2015.07.042. Kumar, S., Dheeran, P., Singh, S.P., Mishra, I.M., Adhikari, D.K., 2015. Kinetic studies of two-stage sulphuric acid hydrolysis of sugarcane bagasse. Renew. Energy 83, 850–858. http://dx.doi.org/10.1016/j.renene.2015.05.033. Larsen, J., Haven, M.Ø., Thirup, L., 2012. Inbicon makes lignocellulosic ethanol a commercial reality. Biomass Bioenergy 46, 36–45. http://dx.doi.org/10.1016/j. biombioe.2012.03.033. Leyva, A., Quintana, A., Sánchez, M., Rodríguez, E.N., Cremata, J., Sánchez, J.C., 2008. Rapid and sensitive anthrone–sulfuric acid assay in microplate format to quantify carbohydrate in biopharmaceutical products: method development and validation. Biologicals 36, 134–141. http://dx.doi.org/10.1016/j.biologicals.2007.09.001. López-Linares, J.C., Romero, I., Cara, C., Ruiz, E., Moya, M., Castro, E., 2014. Bioethanol production from rapeseed straw at high solids loading with different process configurations. Fuel 122, 112–118. http://dx.doi.org/10.1016/j.fuel.2014.01.024. Lu, J., Li, X., Zhao, J., Qu, Y., 2012. Enzymatic saccharification and ethanol fermentation of reed pretreated with liquid hot water. J. Biomed. Biotechnol. 2012, 1–9. http://dx. doi.org/10.1155/2012/276278. Matías, J., Encinar, J.M., González, J., González, J.F., 2015. Optimisation of ethanol fermentation of Jerusalem artichoke tuber juice using simple technology for a decentralised and sustainable ethanol production. Energy Sustain. Dev. 25, 34–39. http://dx.doi.org/10.1016/j.esd.2014.12.009. Miller, G.L., 1959. Use of dinitrosalicylic acid reagent for determination of reducing sugar. Anal. Chem. 31, 426–428. http://dx.doi.org/10.1021/ac60147a030. MINAMBIENTE, Ministry of Environment and Sustainable Development, C, Barrera, X., Gómez, R., Suarez, R., 2015. El ABC de los compromisos de Colombia para la COP21. Monschein, M., Nidetzky, B., 2016. Effect of pretreatment severity in continuous steam explosion on enzymatic conversion of wheat straw: evidence from kinetic analysis of
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Comparison of two pretreatments methods to produce second-generation bioethanol resulting from sugarcane bagasse
T
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Daniel José Bernier-Oviedoa,c, , John Anderson Rincón-Morenoa, José Fernando Solanilla-Duquéb, José Aldemar Muñoz-Hernándeza, Henry Alexander Váquiro-Herreraa a
Crop Production and Health Department, Agronomic Engineering Faculty, Universidad del Tolima, Ibagué, Colombia Agroindustry Department, Agricultural Science Faculty, Universidad del Cauca, Popayán, Colombia c Food and Agro-industry Research Group, Universidad de Caldas, Manizales, Colombia b
A R T I C LE I N FO
A B S T R A C T
Keywords: Sugarcane bagasse Steam explosion Acid hydrolysis Carbohydrate Bioethanol
Non-centrifugal cane sugar (NCS) is a high carbohydrate-content food obtained by boil evaporation of the sugarcane juice. In the manufacturing process, the by-product of NCS called bagasse is used as foul for the boilers, underestimating its potential as a lignocellulosic source for second-generation bioethanol. In order to assess the bioethanol potential of the by-product resulting from the NCS production, pretreatments were applied to breakdown the lignocellulosic structure for the study in hand. Therefore, this study carried out a comparison of two pretreatment methods steam explosion (SE) and acid hydrolysis (AH) applied to the sugarcane bagasse to produce second-generation bioethanol. It was evidenced that both pretreatments redistribute lignin and hemicelluloses and enhances the accessible surface area of the biomass which further benefitted the subsequent fermentation process as the reducing sugars were available enough to foster the production of bioethanol. The study found that the SE pretreatment was likely to obtain more bioethanol as the reducing sugars (glucose) production outperformed other pretreatments under different residence times and concentrations. Considering the necessity to develop second-generation biofuel production, this study presented the sugarcane bagasse as a promising and abundance lignocellulosic substrate to be investigated more in depth in the Colombian context.
1. Introduction Nowadays the growing demand of energy for transportation and industrial processes have increased substantially. Large quantities of fuel, especially petroleum-based liquid fuel, are constantly required to meet this demand. Nevertheless, this is a highly pollutant non-renewable fuel extracted from fossils. Hence, it is crucial to foster the quest for fuels obtained from renewable sources that do not contaminate the environment (Saini et al., 2015). Under those circumstances, biofuels such as bioethanol have emerged as an ideal renewable fuel that meets these requirements in a sustainable fashion. Essentially bioethanol has higher oxygen content than petroleum, which can boost combustion and reduce hydrocarbon, carbon monoxide and particulate emissions and can be obtained from different low-priced substrates (Zabed et al., 2016). The substrates used to produce biofuel are numerous which has led to a considerably increasing in the worldwide production from 31 billion barrels in 2001 up to 50 billion barrels in 2015 (Sarkar et al.,
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2012). The U.S.A and Brazil are regarded the largest producers of the ‘first generation’ bioethanol in the world with a 62% of market share. So far, U.S has supported corn-based bioethanol production and Brazil has focused on sugar-based bioethanol (Jonker et al., 2016). Although corn-based and sugar based-ethanol are promising substitutes to petroleum-based fuel production, they are not enough to substitute a considerable portion of the one trillion gallons of fossil fuels consumed worldwide each year (Cai et al., 2017). With regards to the Colombian market, sugarcane-based ethanol production was of 366.75 million liters in 2017 harvested in 238,304 ha, which has permitted to comply with the mandatory 10% blend of ethanol in gasoline (E10) in cities with populations larger than 500,000 inhabitants (Fedebiocombustibles, 2015). However, it is expected to observe a high-demand for bioethanol due to a mandatory blend of 30% of ethanol in gasoline projected by the year 2030. The production of solely "first-generation bioethanol" from sugarcane stance uncertainties on the sustainable production of this biofuel as the harvest of this crop might cause competition over land-use (Larsen et al., 2012).
Corresponding author at: Facultad de Ingeniería Agronómica, Universidad del Tolima, B. Santa Helena A.A. 546, Ibagué, Colombia. E-mail address: [email protected] (D.J. Bernier-Oviedo).
https://doi.org/10.1016/j.indcrop.2018.06.012 Received 27 November 2017; Received in revised form 8 May 2018; Accepted 4 June 2018 0926-6690/ © 2018 Elsevier B.V. All rights reserved.
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2015).
Despite the concerns on land-use, the biofuel production, so far, have had a positive impact to National policies on environmental sustainability initiatives such as the National Biofuels Program, the Low Carbon Development Strategy, and the implementation of a Bill on renewable energy and energy efficiency in which biomass is included. As a result of this environmental package backed by the Ministry of Environment and Sustainable Development, the bioethanol is also contributing to achieve Colombia's climate change commitment of 20% reduction of Greenhouse Gases (GHG) emissions under the Paris Climate Agreement (MINAMBIENTE et al., 2015). This evidence was observed in a study carried out by the Inter-American Development bank (BID) and Ministry of Mines and Energy in which the bioethanol produced in Colombia could reduce the GHG emissions in about 74% compared to the emissions released by the burning of fossil fuels (BID et al., 2012). Therefore, it is essential to obtain biofuels from other sources that does not compete for the land-use and in the same fashion reduce GHG emissions. (Larsen et al., 2012) Thus, the sort of biofuel that might contribute to meet those requirements is the second-generation bioethanol. It is currently the most advanced, environmentally friendly biofuel made from non-edible crops and it can substitute fossil fuels as transport fuel (Zucaro et al., 2016). Among several raw materials, the lignocellulosic biomass appears as a suitable option that can be used in the second-generation bioethanol industry (Akgul et al., 2012; Matías et al., 2015). Additionally, lignocellulosic biomass can be supplied on a large-scale basis from different sources as the lignocellulosic materials are no longer used in the value chain. So, their availability and low-cost make them appropriate for use as a “second generation biofuel” (Singh et al., 2016). Currently the most favorable cellulosic feedstocks derived from plant residues in the U.S., South America, Asia and Europe are from corn stover, sugarcane bagasse, rice and wheat straws, respectively (Aditiya et al., 2016). Despite the benefits of using this sort of feedstock, the lignocellulosic biomass contains a high degree of complexity inherent to the processing of this material due to its physicochemical matrix and composition. This means that the biomass requires an intensive labor to break down the cellulose and hemicellulose into fermentable sugars (Quintero et al., 2013). So, in order to obtain the second-generation bioethanol, it is necessary to apply previous processes that reorganize the structural composition of lignin, hemicellulose and cellulose contained in it. This previous step is called pretreatment and is significant to reduce operational costs and to increase the efficiency gains in further fermentation process (Chen et al., 2014). The pretreatments are a crucial step that influences the effectiveness of the lignocellulosic materials to be converted into second generation biofuel (Haghighi Mood et al., 2013). The pretreatment, as the beginning stage of bioethanol production, therefore, must be carried out carefully to optimize the result. For this reason, it is necessary to assess different pretreatments applied to agricultural by-products to evaluate the concentration of fermentable sugars to produce bioethanol (Aditiya et al., 2016). This study aimed to determine the technical viability of sugarcanebagasse bioethanol through the comparison of the most effective pretreatment among a physical pretreatment (SE) and a chemical pretreatment (AH) applied to sugarcane bagasse. Afterwards, the effects of pretreatments on sugarcane bagasse were assessed together with the determination of the inhibitory compounds. Later, the pretreatment that delivered a high yield of fermentable sugars was then submitted in a subsequent enzymatic saccharification and a further fermentation process. A non-linear regression analysis was carried out to model the enzymatic saccharification. Finally, conclusions are presented. Since there is no a fit-for-all pretreatment solution to any sort of lignocellulosic material, it is expected that this study builds up a state-ofart regarding sugarcane bagasse as a raw material to produce secondgeneration bioethanol in Colombia to help to reduce the current 8% GHG emitted by the transportation sector in Colombia (United Nations,
2. Materials and methods 2.1. Raw material Sugarcane bagasse was obtained from a commercial farm located in the municipality of Alvarado (Tolima, Colombia), located at 439 masl, 26 °C mean annual temperature, and 70% mean annual relative humidity. The raw material was dried in a forced convection dryer (Thermolab TH 53, DIES, Colombia) at 70 °C for 48 h until constant weight was obtained. The dried sugarcane bagasse, with a moisture content of 10 ± 0.2% (dry basis), were then ground in a hammer mill (Model 4 Thomas-Wiley Laboratory Mill, Thomas Scientific, USA) to reduce particle size to pass a 2 mm screen. The resulting material was stored at 4 °C for 3 days prior to use. 2.2. Pretreatments 2.2.1. Steam Explosion (SE) The SE pretreatment was based on the method proposed by Viola et al. (2013). Samples of sugarcane bagasse were placed in a laboratory bioreactor (ITEMSA, Colombia) with saturated steam supplied from a fire-tube boiler of 2 BHP and flow of 69 lb/h (Equipos y Calderas Industriales EU, Colombia). SE pretreatments were performed at 100 psi over different residence times (15, 30 and 60 min). Afterwards, the pretreated material was filtered and washed out with distilled water to remove inhibitory substances along with the water-soluble hemicellulose. The resulting liquid fraction was stored at 4 °C for 1 h to be used for determination of total carbohydrates (TC) and reducing sugars (RS). The solid residue remaining after filtration was dried (at 70 °C for 18 h) to be used in the enzymatic hydrolysis. 2.2.2. Acid hydrolysis (AH) The AH was carried out based on the method described by Jackson de Moraes Rocha et al. (2011). Samples of sugarcane bagasse were mixed with different sulphuric acid solutions (2.5%, 5% and 10%) in a sample/solution ratio of 1:30 (w/v) and submitted to AH at 100 °C for 60 min. As in the SE pretreatment, each hydrolysate was filtered and washed. Liquid fractions were used for determination of total carbohydrates and reducing sugars, and solid fractions were dried and used in the enzymatic hydrolysis. 2.3. Effects of pretreatments on lignocellulosic biomass (sugarcane bagasse) 2.3.1. Total carbohydrate determination The total carbohydrates of the lignocellulosic material were quantified before and after the pretreatments were completed (SE and AH). The contents of TC were measured spectrophotometrically at 620 nm (Helios gamma spectrophotometer, Thermo Fisher Scientific, Waltham, USA) according to the anthrone-sulfuric acid methodology (Hackmann et al., 2013; Leyva et al., 2008). 2.3.2. Determination of reducing sugars The liquid fractions resulting from enzymatic hydrolysis and fermentation (0–48 h) was quantified spectrophotometrically at a wavelength of 540 nm through the DNS (glucose) method with a Helios gamma spectrophotometer (Thermo Fisher Scientific, Waltham, USA) (Ghose, 1987; Miller, 1959; Saqib and Whitney, 2011). 2.3.3. Characterization of Lignocellulosic biomass The biomass was submitted to an acid detergent fiber (ADF), neutral detergent fiber (NDF) and acid detergent lignin (ADL) tests to determine the contents of cellulose, hemicellulose and lignin using a modified method described by Van Soest et al. (1991). 415
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2.4. Determination of inhibitory compounds 2.4.1. Determination of acetic acid content The quantification of acetic acid was verified before and after the pretreatments were applied (SE and AH) according to Cheng et al. (2008). 2.4.2. Determination of phenolic compounds and furfural The content of phenolic compounds was quantified according to the procedure developed by Singleton et al. (1999) in a spectrophotometer (Helios gamma; Thermo Fisher Scientific, Waltham, USA) at 760 nm. The quantification of furfural was done according to 9097 and 9098 methods by the AOAC (1984) with absorption spectrum at 277 nm. 2.5. Enzymatic hydrolysis - activity and saccharification The enzymatic activity of the enzyme celluclast 1.5 L (endoglucanase/cellobiohydrolase) was quantified according to the procedure described by Ghose (1987). The enzymatic saccharification was applied using the 1.5 L celluclast enzyme over a period of 48 h. The enzyme concentrations were of 7.5, 15 and 30 filter-paper units (FPU) per gram based on the parameters used by Wang et al. (2015a, 2015b). The process was monitored every 12 h and the results were expressed in milligrams equivalent of glucose per gram of dry sample (mg GE/g ds). 2.6. Fermentation The inoculum (0.4 g) used in the fermentation test was diluted in 100 mL of a medium (30 °C, pH 5.0) containing urea (0.23 g), the enzymatic hydrolysates and those hydrolysates obtained in the pretreatments. The final cell concentration in the fermentation was of 108 cells/ mL. The process was monitored for 48 h to determine the conversion rate of fermentable sugar (glucose) and ethanol concentrations. The latter was quantified using a gas chromatograph (Hewlett Packard 6890 Series, Agilent Technologies Inc., USA) equipped with an HP-BALC column (7.5 m × 0.20 mm) at 165 °C and an internal Flame Ionization Detector (FID) at 270 °C. Isopropanol was used as standard and nitrogen (15 mL/min) as the entrainment gas. The fermentation process followed the methodology proposed by Pereira et al. (2011).
Fig. 1. Effect of SE on the yields of total carbohydrates (A) and reducing sugars (B) in sugarcane bagasse. Error bars represent standard deviation from the mean. Means with different letters indicate significant difference (p < 0.05).
2.7. Statistic analysis error (MRE) (Eq. (3)) (Villa-Vélez et al., 2015). The results obtained in the study were expressed as mean and standard deviation of three determinations for each pretreatment. Analysis of variance (ANOVA) at the 95% confidence level was used to compare the mean values of each determination among the different pretreatments. Multiple range tests (MRT) were used to determine which means were significantly different from the others by using the Tukey’s honestly significant difference procedure. ANOVA and MRT were performed using “anova1” and “multcompare” functions of the Statistic Toolbox of MATLAB® R2016b (The MathWorks Inc., Natick, MA, USA), respectively. A non-linear regression analysis was carried out to model the enzymatic saccharification by using the Weibull model (Eq. (1)) (PiñerosCastro and Velásquez-Lozano, 2014).
y = y0 + (ymax −y0 )[1−exp(−kt )]
2 Radj = 1−
MRE =
2 Syx
s y2
n |yi* −yi | 100 ∑ n i = 1 yi*
(2)
(3)
where Sy is the standard deviation for the sample, Syx is the standard deviation for the model estimation, yi* represents the experimental values; yi represents the estimated values; and n is the number of experimental data points used in the regression analysis. 3. Results and discussion
(1)
3.1. Incidence of the steam in carbohydrate yield
where y0, y and ymax represent the initial RS fraction, the RS fraction at time t, and maximum RS content (mg GE/g, ds), respectively; k represents the kinetic rate constant (1/s). The model parameters k and ymax (Eq. (1)) were estimated using “nlinfit” function of the Statistic Toolbox of MATLAB® R2016b. (The MathWorks Inc., Natick, MA, USA). The statistical significance of the estimated parameters was evaluated through their 95% confidence intervals, whereas the goodness of model fit was quantified by the adjusted coefficient of determination (R2adj) (Eq. (2)) and the mean relative
Fig. 1 shows the yields of total carbohydrate and reducing sugars obtained through the SE applied to the sugarcane bagasse at different residence times (15, 30 and 60 min). The maximum amount of total carbohydrates in the residual material was obtained at the residence time of 30 min (160 °C and 100 psi) (Fig. 1A). An increase of 23% compared to the same pretreatment applied for 15 min was observed. It was also noted that SE pretreatment increased six-fold the carbohydrates available. Although the residence time of 60 min showed that the 416
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Table 1 Composition of cell wall in sugarcane bagasse before and after pretreatment. Composition (%)
Without Pretreatment
Acid hydrolysis t = 1 h; 10 % H2SO4
Steam explosion t = 30 min
ADF ADL NDF Cellulose Hemicellulose Lignin Cellular content Silicon dioxide
34.66 ± 0.54 9.66 ± 0.44 53.80 ± 0.20 25.00 ± 0.11 19.14 ± 0.34 9.16 ± 0.46 46.20 ± 0.21 0.50 ± 0.01
86.81 ± 3.37 20.69 ± 1.18 87.61 ± 0.04 66.11 ± 3.36 0.06 ± 0.00 0.36 ± 0.29 12.39 ± 0.04 20.33 ± 0.98
81.96 ± 3.42 20.54 ± 6.77 90.00 ± 1.03 57.97 ± 0.67 8.04 ± 2.60 0.84 ± 0.41 10.00 ± 1.03 22.24 ± 1.52
a ADF (Acid detergent fiber), bADL (Acid Detergent lignin), cNDF (Neutral detergent fiber).
total amount of carbohydrates after this time had decreased (104 mg TC/g dry sample). Thus, the SE is not convenient when residence times last more than 30 min. Reducing sugars showed a similar trend to that of total carbohydrates. It was noted that a 33% increase of reducing sugars was obtained on residence time lasting 30 min compared to the process applied for 15 min (Fig. 1B). Nonetheless, an increase in the exposure time of the material to the pretreatment reduced the concentration of the total carbohydrates. Therefore, applying SE enhanced the amount available of TC and RS compared to the material that did not undertake any previous treatment. Thus, the action of the steam to breakdown the protective structure of the hemicellulose and the lignin on the cellulose seemed to be effective. This structure breakdown might be attributed to the aromatic structures of the lignin which contain less oxygen than the carbohydrates of the cellulose; the lignin is therefore less susceptible to the attack of biological or physical factors than the cellulose. Due to these conditions, hemicellulose is the polysaccharide with the greatest potential for selective solubilization (Table 1) by the SE pretreatment (Monschein and Nidetzky, 2016). The downside is that the degradation of hemicellulose simultaneously produces derivatives such as xylans (Balat, 2011), which in turn produce water, methanol, formic, acetic, propionic, 1-hydroxypropanone, 1hydroxybutanone, 2furfuraldehyde and furfural (Ask et al., 2013; Tomás-Pejó et al., 2011).
Fig. 2. Effect of AH on the yield of total carbohydrates (A) and reducing sugars (B) in sugarcane bagasse. Error bars represent standard deviation from the mean. Means with different letters indicate significant difference (p < 0.05).
3.2. Chemical pretreatment Likewise, the fractionation of its matrix to subtract the lignin might have degraded the carbohydrates (Benjamin et al., 2014). In that sense, authors such as Kumar et al. (2015) discussed similar results on reducing sugar concentrations when the pretreatments with diluted acids and 121 °C were applied to the sample material. According to these authors residences times greater than 75 min do not increase the concentrations of carbohydrates. It was also found that the amount of RS is higher in the lignocellulosic material after both pretreatments SE and AH were applied compared to the no pretreated samples. Therefore, residence times greater than 30 min (SE) and 1 h (AH) evidenced that in both scenarios increasing the residence time caused a fragmentation of RS. This is due to the breakdown of these bonds into inhibitory compounds such as acetic acid and furfural (Xiao et al., 2011).
Effect of acid concentration The chemical pretreatment was undertaken using sulfuric acid at three different concentrations: 2.5%; 5% and 10% to breakdown the lignocellulosic structure of sugarcane bagasse. As shown in Fig. 2A, there is a direct relationship between dosage (acid concentration) and response (amount of total carbohydrate). As a result, residence times of 1 h and 2 h yielded 251.1 mg TC/g sample and 308.8 mg TC/g sample, respectively. Both residence times used a sulfuric acid concentration of 10%. These yields might be due to more depolymerization of polysaccharides such as hemicellulose (Table 1) as stated by Chen et al. (2012). Although, the yields increase up to 23%, the energy consumption of the 2 h pretreatment raised the cost of operation by 96%, considerably affecting the viability in the process. It was also noticed that the RS concentrations after the pretreatment at 1 h did not appear to have a significant difference between those concentrations of 2.5%, 5% and 10% acid solutions (Fig. 2B). Nevertheless, the average concentration obtained by the AH was 43 mg TC/g. This result is higher compared to the no pretreated sample (28 mg TC/g sample). Moreover, the yields decreased to 33 and 27 mg TC/g sample with 2 h and 3 h of residence times, respectively (Fig. 2B). This reduction might be caused by the overexposure of the cellulose through the hydrolysis of hemicellulose due to residence times lasting more than 60 min (Yoon et al., 2014).
3.3. Modification sugarcane bagasse cell wall The effect of the two pretreatments on the structural components of the lignocellulosic biomass (cellulose, hemicellulose and lignin) is showed in Table 1. The hemicellulose was the structural component heavily affected due to the pretreatment. This was proven during the SE pretreatment (t = 30 min) where the hemicellulose content was reduced from an initial 19.14% down to 8.04%, whereas AH pretreatment (t = 1 h, 10%) removed 19.08% of hemicellulose. Comparatively, the 417
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lignin contents were reduced to 0.36% in AH and 0.84% for SE. This might be caused due to the solubilization of lignin and hemicellulose caused by pretreatments, hence increasing the cellulose content (57.97% for SE and 66.11% for AH). This rearrangement in the cell wall composition of the lignocellulosic biomass could be explained by the protective action of hemicellulose and lignin on cellulose and the strength of ether bonds (α-O-4, B-O-4, 4-O-5) and carbon-carbon bonds of the lignin (Han et al., 2012); that triggered a structural rearrangement after the pretreatments were applied. This was done without reaching a complete solubilization (Cardona et al., 2014; Ibrahim et al., 2011), and without enzymes. Similar changes in the cell wall were corroborated by (Soares et al., 2011) who managed to reduce the hemicellulose content in 13% and increase the cellulose content available in 30.5%. These results demonstrated that the removal of hemicellulose, partial delignification and the exposure of the cellulose are highly related to the application of physical and chemical pretreatments on lignocellulosic material to enhance a following enzymatic saccharification. 3.4. Enzymatic hydrolysis The enzyme effect using different enzyme concentrations (7.5, 15 and 30 FPU/g) on the sample material pretreated with AH (t = 1 h, 10% H2SO4) and SE (t = 30 min) was assessed. The experimental results of enzymatic hydrolysis are shown in Table 2. Hydrolysis was performed to compare the kinetic effect of the enzyme (endoglucanase/ cellulose hydrolysis - Celluclast 1.5 L) on the lignocellulosic material of the pretreated sugarcane bagasse and its cellulose to RS conversion rate as shown in Fig. 3. The experimental data obtained for the enzymatic hydrolysis were adjusted applying the Weibull kinetic model. The identified model parameters and their 95% confidence intervals are shown in Table 3 for the hydrolysis kinetics of WP, SE and AH at enzymatic activities of 7.5, 15 and 30 FPU/g. Considering the identified parameters, satisfactory simulations of the hydrolysis kinetics were obtained (Fig. 3) in terms of both MRE and R2adj. Thus, the Weibull model was able to represent more than 97% of the variation of all experimental data with estimates deviated on average less than 5% from the real values. According confidence intervals, all model parameters were statistically significant at p < 0.05. Some authors also successfully used the Weibull model to describe enzymatic saccharification kinetics (Kansou et al., 2015; Piñeros-Castro and Velásquez-Lozano, 2014; Wang et al., 2015a, 2015b). The values for the model parameters of the different pretreatments and enzyme concentrations were found to be between 0.089 and 0.217
Fig. 3. Amount of RS, expressed as glucose, released during the enzymatic hydrolysis of sugarcane bagasse pretreated by AH (A) and SE (B). AH: (t = 1 h, 10% H2SO4); SE: (30 min); WP: without pretreatment.
1/h for the rate constant (k) and between 128 and 417 mg GE/g ds for maximum RS content (ymax) (Table 3). The higher is k, the steeper is the hydrolysis rate during the first stage of hydrolysis and vice versa (Kansou et al., 2015). Thus, pretreatments where hydrolysis kinetics showed k values greater than 0.141 1/h presented more initial susceptibility of the hydrolysable fraction by the enzyme, and the kinetics showed an asymptotic behavior from times around 20 h (Fig. 3). However, the value of the hydrolysis extent at the end time (ymax) represents the final fraction of biomass hydrolyzed. According the highest ymax, RS could increase by 47.3% for SE at 30 FPU/g as compared with WE at the same enzyme concentration. In Fig. 3(A and B), an exponential enzymatic activity was observed in the first 12 h, afterwards the enzymatic hydrolysis reached a steady state until the maximum conversion rate peaked (48 h). So that, the enzymatic hydrolysis showed effectiveness when a pretreatment is applied compared to the untreated sample material (WP). This is due to the increase of the biomass structure porosity which leads to a higher cellulose exposure (Han et al., 2012). As can be seen, the initial velocities and the enzymatic concentration in the first hours of saccharification is directly linked to a higher content of glucose on the pretreated material. Therefore, the pretreatment was observed as a mean to an enhanced enzyme hydrolysis performance, insomuch as the effectiveness of the
Table 2 Experimental results for the enzymatic saccharification (mg GE/g ds)*. Enzyme concentration
t (h)
Without Pretreatment
Acid hydrolysis t = 1 h; 10 % H2SO4
Steam explosion t = 30 min
7.5 FPU/g
12 24 36 48
107.50 123.15 126.89 129.34
± ± ± ±
3.05a 5.55a 3.37a 6.62a
192.55 207.39 210.25 229.17
± ± ± ±
0.41b 3.79b 4.33b 28.29b
159.88 197.97 205.29 211.66
± ± ± ±
9.55c 8.10b 4.92b 8.23b
15 FPU/g
12 24 36 48
163.69 184.90 191.61 194.76
± ± ± ±
2.50a 5.87a 0.88a 5.94a
284.15 299.70 301.61 305.20
± ± ± ±
4.84b 4.58b 3.57b 3.41b
324.02 384.49 396.74 402.97
± ± ± ±
2.42c 5.65c 9.08c 9.53c
30 FPU/g
12 24 36 48
261.62 280.77 282.64 283.81
± ± ± ±
4.70a 7.37a 9.08a 3.90a
279.36 393.27 400.80 403.15
± ± ± ±
9.62a 11.78b 17.42b 8.96b
274.00 362.30 387.45 391.72
± ± ± ±
12.25a 10.00c 10.27b 10.18b
* Mean and standard deviation of three replicates. Means with different superscripts within a row indicate significant difference (p < 0.05) between pretreatments. 418
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Table 3 Estimated parameters, confidence intervals and goodness-of-fit statistics of the hydrolysis models. Parameters*
95% Confidence intervals
Pretreatment
FPU/g
k
ymax
k
ymax
MRE (%)
R2adj
Without pretreatment
7.5 15 30
0.128 0.141 0.206
128 193 283
[0.105, 0.152] [0.125, 0.157] [0.176, 0.235]
[125, 132] [190, 196] [279, 287]
2.91 1.77 2.01
0.990 0.997 0.997
Steam explosion (t = 30 min)
7.5 15 30
0.159 0.217 0.090
216 303 417
[0.107, 0.211] [0.193, 0.242] [0.074, 0.106]
[207, 224] [300, 306] [399, 434]
3.25 1.82 3.83
0.977 0.999 0.989
Acid hydrolysis (t = 1 h, 10 % H2SO4)
7.5 15 30
0.099 0.127 0.089
212 402 400
[0.082, 0.116] [0.117, 0.137] [0.079, 0.099]
[205, 219] [396, 408] [390, 411]
4.48 2.87 3.67
0.990 0.998 0.995
* ymax: maximum RS content (mg GE/g, ds); k: kinetic rate constant (1/h). Table 4 Inhibitory compounds contained in pretreated sugarcane bagasse. Pretreatment
Acetic acid (mg AAE/ mL)*
Furfural (mg/ mL)
Phenolic compounds (mg GAE/mL)**
Without Pretreatment SE (t = 30 min) AH (t = 1 h, 10 % H2SO4)
0.10 0.54 13.37
0.00 0.44 1.52
2.13 6.56 6.57
* mg AAE: milligrams of acetic acid equivalent. ** mg GAE: milligrams of gallic acid equivalent.
previous stages allowed a higher fermentable sugars conversion rate (Sarkar et al., 2012). To sum up the best RS result was obtained on the SE (t = 30 min) at an enzymatic concentration of 30 FPU/g (Fig. 3B); 403.1 mg GE/g ds. While for HA (1 h and 10% H2SO4) (Fig. 3A) the best results were obtained utilizing an enzymatic concentration of 15 and 30 FPU/g; 402.4 and 392 mg GE/g ds, respectively. Nevertheless, there was no significant difference between the concentrations of 15 and 30 FPU/g. This might be caused by the enzymes used in this study which contains endoglucanases. This enzyme might have triggered a negative effect by producing non-desirable sugars that accumulated during the process, mainly cellobiose; a potential inhibitor of the enzyme activity (Ask et al., 2012). The action of endoglucanases releasing glucose and cellobiose molecules could have attacked the regions of low crystallinity of the cellulose generating non-reducing free ends and cellubiohydrolases that act on the non-reducing ends, hence, the low yields (Sarkar et al., 2012). However, an enzymatic inhibition could be avoided recurring to what some authors have accomplished in previous studies; enzymatic cocktails that outperform those one-single enzymes in the hydrolysis (Balat, 2011; Soares et al., 2011). However, such preparations have an economic impact on the production of bioethanol. 3.5. Determination of inhibitors and fermentation The RS obtained after the pretreatments were applied also produced inhibitory compounds to the fermentation process such as acetic acid, furfural and phenolic compounds. In Table 4, the concentrations of these compounds after the pretreatments were done and their association with the structural composition of the biomass are shown. The acetic acid formed in the AH reached a concentration of 13.37 mg/mL, compared to SE (0.54 mg/mL). This compound is a consequence of the incomplete fractionation of the lignin-carbohydrate matrix by the action of vapor pressure (Table 1). This compound hinders rapid thermal expansion to penetrate the structure of the biomass making it difficult to hydrolyze the acetyl groups of this polysaccharide (El-Zawawy et al., 2011). Another inhibitory compound to the fermentation such as furfural
Fig. 4. Bioethanol obtained from pretreated bagasse samples, enzymatically saccharified and fermented from pretreatments (A) SE and (B) AH.
with concentrations of 0.44 mg/mL and 1.53 mg/mL in the SE and AH respectively was found. The highest concentration in AH is attributed to the dehydration of pentoses, specifically xylose, which boost its degradation to furfural when found in an acid medium (Chiaramonti et al., 2012). In like manner, the concentrations of phenolic compounds increased through the action of both pretreatments, showing 419
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Notwithstanding, a study carried out by Pereira et al. (2011), has shown that yields as high as 86% ethanol is technically feasible on biomass employing two different industrial isolated Saccharomyces Cerevisiae strains. Although, this study did not use this type of industrial isolates, the results are still valuable as it shows the effectiveness of the pretreatments applied with lower fermentation time (48 h) and a comercial Saccharomyces Cerevisiae strain. 4. Conclusions This study emphasizes the importance of applying pretreatments in lignocellulosic materials to foster further research and production of second-generation bioethanol in Colombia. As such, both pretreatments (SE and AH) proved that the initial composition of the lignin, hemicellulose and cellulose was in fact altered due to the pretreatments' action. This alteration of the cell structure allowed a better performance of the enzyme on the sample material due to a better exposure of the active sites. It was also observed that the SE pretreatment produced lower concentrations of inhibitory compounds prior the fermentation (acetic acid and furfural), producing more reducing sugars to obtain ethanol with regards to AH pretreatment. On balance, SE pretreatment seems to be practical to obtain ethanol as the reducing sugars (glucose) obtained outperform other pretreatments. Whereas, some scholars obtained higher fermentation yields, the yields presented in this study might perform better if other stages such as detoxification to remove inhibitory compounds are aggregated into the process.
Fig. 5. Concentrations of ethanol and glucose during the fermentation process with AH (10% H2SO4) and SE (t = 30 min) pretreatments.
concentrations of 2.13 mg GAE/mL for the no-pretreated material and 6.5 mg GAE/mL for both pretreatments. These concentrations are heavily related to the solubilization and partial degradation of lignin (Doherty et al., 2011). Fig. 4 shows the bioethanol content reached from pretreated, enzymatically saccharified and fermented (Saccharomyces cerevisiae) samples of sugarcane bagasse. The intensity of the electrical signal is expressed in peak amperes (pA). Each of the peaks shown in the two Fig. 4A (SE) and B (AH) are directly proportional to the concentration of ethanol obtained during the fermentation time (t = 0, 2, 4, 6, 8, 16, 24, 48 h). For this purpose, the area under the curve of each of the ethanol peaks was compared. The high concentrations of ethanol attained from the biomass pretreated with SE (t = 30 min) compared to those obtained with AH (t = 1 h, 10% H2SO4), presented a higher applicability potential in the ethanol production process. This result is linked to the effectiveness reached in the enzymatic saccharification that produced a modification in the hemicellulose and lignin with low concentrations of acetic acid and furfural (Table 4) (Fujitomi et al., 2012). Fig. 5 shows the relationship between ethanol and RS concentrations (mg GE/mL) during the 48 h of fermentation of the pretreated lignocellulosic material. The initial amount of substrate (glucose) attained by AH (t = 1 h and 10% H2SO4) along with subsequent enzymatic scarification was 203.89 mg GE/mL. On the other hand, the concentration reached by SE (t = 30 min) was higher (257.87 mg GE/ mL). For both cases, the highest rate of substrate consumption occurred in the first 24 h, after that the concentration of the reducing sugars remained stable until the process was completed. In fact, the highest production rate of ethanol was accomplished in the first 24 h, then the process displayed a steady state. At the end of the fermentation the concentration of ethanol obtained with SE (87.16 mg/mL) was higher than the one achieved with AH (58.7 mg/mL). The percentages of theoretical conversion yield for lignocellulosic biomass were calculated using the maximum concentration of ethanol produced (0.511 g ethanol/g glucose). The biomass pretreated with AH (t = 1 h, 10% H2SO4) and SE (t = 30 min) yielded 71% and 79%, respectively. Several scholars have reached different yields in the fermentation process on biomass pretreated; some studies had a lower theoretical percentage attained were compared to our study with values found between 65.5% and 61.1% on pre-treated straw with diluted acid (López-Linares et al., 2014). Other studies obtained similar yields as the ones reported in this study, where it was evidenced yields of 79.1% and 63.1% using fermented pretreated reed with hot water and fir chips pretreated with peroxide (Lu et al., 2012; Zhang et al., 2014).
Acknowledgements The authors acknowledge the support given by the Universidad del Tolima and its research groups; CEDAGRITOL, GIPRONUT and the Scientific Research and Development Office of the University of Tolima. References Aditiya, H.B., Mahlia, T.M.I., Chong, W.T., Nur, H., Sebayang, A.H., 2016. Second generation bioethanol production: a critical review. Renew. Sustain. Energy Rev. 66, 631–653. http://dx.doi.org/10.1016/j.rser.2016.07.015. Akgul, O., Shah, N., Papageorgiou, L.G., 2012. An optimisation framework for a hybrid first/second generation bioethanol supply chain. Comput. Chem. Eng. 42, 101–114. http://dx.doi.org/10.1016/j.compchemeng.2012.01.012. AOAC, 1984. Official Methods of Analysis of the Association of Official Analytical Chemists, 14th ed. Washington D.C. Ask, M., Bettiga, M., Mapelli, V., Olsson, L., 2013. The influence of HMF and furfural on redox-balance and energy-state of xylose-utilizing Saccharomyces cerevisiae. Biotechnol. Biofuels 6, 1–22. http://dx.doi.org/10.1186/1754-6834-6-22. Ask, M., Olofsson, K., Di Felice, T., Ruohonen, L., Penttilä, M., Lidén, G., Olsson, L., 2012. Challenges in enzymatic hydrolysis and fermentation of pretreated Arundo donax revealed by a comparison between SHF and SSF. Process Biochem. 47, 1452–1459. http://dx.doi.org/10.1016/j.procbio.2012.05.016. Balat, M., 2011. Production of bioethanol from lignocellulosic materials via the biochemical pathway: a review. Energy Convers. Manage. 52, 858–875. http://dx.doi. org/10.1016/j.enconman.2010.08.013. Benjamin, Y., Cheng, H., Görgens, J.F., 2014. Optimization of dilute sulfuric acid pretreatment to maximize combined sugar yield from sugarcane bagasse for ethanol production. Appl. Biochem. Biotechnol. 172, 610–630. http://dx.doi.org/10.1007/ s12010-013-0545-z. BID, Ministerio de minas y energia Colombia, CUE, C, 2012. Evaluación del ciclo de vida de la cadena de producción de biocombustibles en Colombia. Cai, J., He, Y., Yu, X., Banks, S.W., Yang, Y., Zhang, X., Yu, Y., Liu, R., Bridgwater, A.V., 2017. Review of physicochemical properties and analytical characterization of lignocellulosic biomass. Renew. Sustain. Energy Rev. 76, 309–322. http://dx.doi.org/ 10.1016/j.rser.2017.03.072. Cardona, E., Rios, J., Peña, J., Rios, L., 2014. Effects of the pretreatment method on enzymatic hydrolysis and ethanol fermentability of the cellulosic fraction from elephant grass. Fuel 118, 41–47. http://dx.doi.org/10.1016/j.fuel.2013.10.055. Chen, W.-H., Ye, S.-C., Sheen, H.-K., 2012. Hydrolysis characteristics of sugarcane bagasse pretreated by dilute acid solution in a microwave irradiation environment. Appl. Energy 93, 237–244. http://dx.doi.org/10.1016/j.apenergy.2011.12.014. Chen, Y., Zhang, X., Zhang, S., Qin, W., Guo, C., Guo, X., Xiao, D., 2014. Enhanced enzymatic xylose/cellulose fractionation from alkaline liquor-pretreated corn cob by surfactant addition and separate fermentation to bioethanol. Turk. J. Biol. http://dx. doi.org/10.3906/biy-1310-16. Cheng, K.-K., Cai, B.-Y., Zhang, J.-A., Ling, H.-Z., Zhou, Y.-J., Ge, J.-P., Xu, J.-M., 2008. Sugarcane bagasse hemicellulose hydrolysate for ethanol production by acid recovery
420
Industrial Crops & Products 122 (2018) 414–421
D.J. Bernier-Oviedo et al.
hydrolysis time courses. Bioresour. Technol. 200, 287–296. http://dx.doi.org/10. 1016/j.biortech.2015.10.020. Pereira, F.B., Guimarães, P.M.R., Teixeira, J.A., Domingues, L., 2011. Robust industrial Saccharomyces cerevisiae strains for very high gravity bio-ethanol fermentations. J. Biosci. Bioeng. 112, 130–136. http://dx.doi.org/10.1016/j.jbiosc.2011.03.022. Piñeros-Castro, Y., Velásquez-Lozano, M., 2014. Biodegradation kinetics of oil palm empty fruit bunches by white rot fungi. Int. Biodeterior. Biodegrad. 91, 24–28. http://dx.doi.org/10.1016/j.ibiod.2014.03.009. Quintero, J.A., Moncada, J., Cardona, C.A., 2013. Techno-economic analysis of bioethanol production from lignocellulosic residues in Colombia: a process simulation approach. Bioresour. Technol. 139, 300–307. http://dx.doi.org/10.1016/j.biortech. 2013.04.048. Saini, J.K., Saini, R., Tewari, L., 2015. Lignocellulosic agriculture wastes as biomass feedstocks for second-generation bioethanol production: concepts and recent developments. 3 Biotech 5, 337–353. http://dx.doi.org/10.1007/s13205-014-0246-5. Saqib, A.A.N., Whitney, P.J., 2011. Differential behaviour of the dinitrosalicylic acid (DNS) reagent towards mono- and di-saccharide sugars. Biomass Bioenergy 35, 4748–4750. http://dx.doi.org/10.1016/j.biombioe.2011.09.013. Sarkar, N., Ghosh, S.K., Bannerjee, S., Aikat, K., 2012. Bioethanol production from agricultural wastes: an overview. Renew. Energy 37, 19–27. http://dx.doi.org/10. 1016/j.renene.2011.06.045. Singh, R., Srivastava, M., Shukla, A., 2016. Environmental sustainability of bioethanol production from rice straw in India: a review. Renew. Sustain. Energy Rev. 54, 202–216. http://dx.doi.org/10.1016/j.rser.2015.10.005. Singleton, V.L., Orthofer, R., Lamuela-Raventós, R.M., 1999. Analysis of total phenols and other oxidation substrates and antioxidants by means of folin-ciocalteu reagent. Methods Enzymol. 152–178. http://dx.doi.org/10.1016/S0076-6879(99)99017-1. Soares, I.B., Travassos, J.A., Baudel, H.M., Benachour, M., Abreu, C.A.M., 2011. Effects of washing, milling and loading enzymes on the enzymatic hydrolysis of a steam pretreated sugarcane bagasse. Ind. Crops Prod. 33, 670–675. http://dx.doi.org/10.1016/ j.indcrop.2011.01.003. Tomás-Pejó, E., Alvira, P., Ballesteros, M., Negro, M.J., 2011. Chapter 7 – Pretreatment technologies for lignocellulose-to-bioethanol conversion. Biofuels. pp. 149–176. http://dx.doi.org/10.1016/B978-0-12-385099-7.00007-3. United Nations, 2015. Millennium Development Goals Indicators [WWW Document]. (accessed 4.4.18). http://mdgs.un.org/unsd/mdg/seriesdetail.aspx?srid=749. Van Soest, P.J., Robertson, J.B., Lewis, B.A., 1991. Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition. J. Dairy Sci. 74, 3583–3597. http://dx.doi.org/10.3168/jds.S0022-0302(91)78551-2. Villa-Vélez, H.A., Váquiro, H.A., Lopes-Filho, J.F., Telis, V.R.N., Telis-Romero, J., 2015. Study of the specific heat capacity of biomass from banana waste for application in the second-generation ethanol industry. Environ. Prog. Sustain. Energy 34, 1221–1228. http://dx.doi.org/10.1002/ep.12090. Viola, E., Zimbardi, F., Valerio, V., Nanna, F., Battafarano, A., 2013. Use of a twochamber reactor to improve enzymatic hydrolysis and fermentation of lignocellulosic materials. Appl. Energy 102, 198–203. http://dx.doi.org/10.1016/j.apenergy.2012. 04.044. Wang, M., Han, L., Liu, S., Zhao, X., Yang, J., Loh, S.K., Sun, X., Zhang, C., Fang, X., 2015a. A Weibull statistics-based lignocellulose saccharification model and a built-in parameter accurately predict lignocellulose hydrolysis performance. Biotechnol. J. 10, 1424–1433. http://dx.doi.org/10.1002/biot.201400723. Wang, P., Chang, J., Yin, Q., Wang, E., Zhu, Q., Song, A., Lu, F., 2015b. Effects of thermochemical pretreatment plus microbial fermentation and enzymatic hydrolysis on saccharification and lignocellulose degradation of corn straw. Bioresour. Technol. 194, 165–171. http://dx.doi.org/10.1016/j.biortech.2015.07.012. Xiao, L.-P., Sun, Z.-J., Shi, Z.-J., Xu, F., Sun, R.-C., 2011. Impact of hot compressed water pretreatment on the structural changes of woody biomass for bioethanol producti on. BioResources 6, 1576–1598. http://dx.doi.org/10.15376/biores.6.2.1576-1598. Yoon, S.-Y., Han, S.-H., Shin, S.-J., 2014. The effect of hemicelluloses and lignin on acid hydrolysis of cellulose. Energy 77, 19–24. http://dx.doi.org/10.1016/j.energy.2014. 01.104. Zabed, H., Sahu, J.N., Boyce, A.N., Faruq, G., 2016. Fuel ethanol production from lignocellulosic biomass: an overview on feedstocks and technological approaches. Renew. Sustain. Energy Rev. 66, 751–774. http://dx.doi.org/10.1016/j.rser.2016.08. 038. Zhang, L., You, T., Zhang, L., Yang, H., Xu, F., 2014. Enhanced fermentability of poplar by combination of alkaline peroxide pretreatment and semi-simultaneous saccharification and fermentation. Bioresour. Technol. 164, 292–298. http://dx.doi.org/10. 1016/j.biortech.2014.04.075. Zucaro, A., Forte, A., Basosi, R., Fagnano, M., Fierro, A., 2016. Life cycle assessment of second generation bioethanol produced from low-input dedicated crops of Arundo donax L. Bioresour. Technol. 219, 589–599. http://dx.doi.org/10.1016/j.biortech. 2016.08.022.
process. Biochem. Eng. J. 38, 105–109. http://dx.doi.org/10.1016/j.bej.2007.07. 012. Chiaramonti, D., Prussi, M., Ferrero, S., Oriani, L., Ottonello, P., Torre, P., Cherchi, F., 2012. Review of pretreatment processes for lignocellulosic ethanol production, and development of an innovative method. Biomass Bioenergy 46, 25–35. http://dx.doi. org/10.1016/j.biombioe.2012.04.020. Doherty, W.O.S., Mousavioun, P., Fellows, C.M., 2011. Value-adding to cellulosic ethanol: lignin polymers. Ind. Crops Prod. 33, 259–276. http://dx.doi.org/10.1016/j.indcrop. 2010.10.022. El-Zawawy, W.K., Ibrahim, M.M., Abdel-Fattah, Y.R., Soliman, N.A., Mahmoud, M.M., 2011. Acid and enzyme hydrolysis to convert pretreated lignocellulosic materials into glucose for ethanol production. Carbohydr. Polym. 84, 865–871. http://dx.doi.org/ 10.1016/j.carbpol.2010.12.022. Fedebiocombustibles, 2015. Federación Nacional de Biocombustibles de Colombia, Información Estadística Sector Biocombustibles [WWW Document]. (accessed 4.4.18). http://www.fedebiocombustibles.com/. Fujitomi, K., Sanda, T., Hasunuma, T., Kondo, A., 2012. Deletion of the PHO13 gene in Saccharomyces cerevisiae improves ethanol production from lignocellulosic hydrolysate in the presence of acetic and formic acids, and furfural. Bioresour. Technol. 111, 161–166. http://dx.doi.org/10.1016/j.biortech.2012.01.161. Ghose, T.K., 1987. Measurement of cellulase activities. Pure Appl. Chem. 59, 257–268. http://dx.doi.org/10.1351/pac198759020257. Hackmann, T.J., Keyser, B.L., Firkins, J.L., 2013. Evaluation of methods to detect changes in reserve carbohydrate for mixed rumen microbes. J. Microbiol. Methods 93, 284–291. http://dx.doi.org/10.1016/j.mimet.2013.03.025. Haghighi Mood, S., Hossein Golfeshan, A., Tabatabaei, M., Salehi Jouzani, G., Najafi, G.H., Gholami, M., Ardjmand, M., 2013. Lignocellulosic biomass to bioethanol, a comprehensive review with a focus on pretreatment. Renew. Sustain. Energy Rev. 27, 77–93. http://dx.doi.org/10.1016/j.rser.2013.06.033. Han, L., Feng, J., Zhang, S., Ma, Z., Wang, Y., Zhang, X., 2012. Alkali pretreated of wheat straw and its enzymatic hydrolysis. Braz. J. Microbiol. 43, 53–61. http://dx.doi.org/ 10.1590/S1517-83822012000100006. Ibrahim, M.M., El-Zawawy, W.K., Abdel-Fattah, Y.R., Soliman, N.A., Agblevor, F.A., 2011. Comparison of alkaline pulping with steam explosion for glucose production from rice straw. Carbohydr. Polym. 83, 720–726. http://dx.doi.org/10.1016/j.carbpol. 2010.08.046. Jackson de Moraes Rocha, G., Martin, C., Soares, I.B., Souto Maior, A.M., Baudel, H.M., Moraes de Abreu, C.A., 2011. Dilute mixed-acid pretreatment of sugarcane bagasse for ethanol production. Biomass Bioenergy 35, 663–670. http://dx.doi.org/10.1016/ j.biombioe.2010.10.018. Jonker, J.G.G., Junginger, H.M., Verstegen, J.A., Lin, T., Rodríguez, L.F., Ting, K.C., Faaij, A.P.C., van der Hilst, F., 2016. Supply chain optimization of sugarcane first generation and eucalyptus second generation ethanol production in Brazil. Appl. Energy 173, 494–510. http://dx.doi.org/10.1016/j.apenergy.2016.04.069. Kansou, K., Buléon, A., Gérard, C., Rolland-Sabaté, A., 2015. Multivariate model to characterise relations between maize mutant starches and hydrolysis kinetics. Carbohydr. Polym. 133, 497–506. http://dx.doi.org/10.1016/j.carbpol.2015.07.042. Kumar, S., Dheeran, P., Singh, S.P., Mishra, I.M., Adhikari, D.K., 2015. Kinetic studies of two-stage sulphuric acid hydrolysis of sugarcane bagasse. Renew. Energy 83, 850–858. http://dx.doi.org/10.1016/j.renene.2015.05.033. Larsen, J., Haven, M.Ø., Thirup, L., 2012. Inbicon makes lignocellulosic ethanol a commercial reality. Biomass Bioenergy 46, 36–45. http://dx.doi.org/10.1016/j. biombioe.2012.03.033. Leyva, A., Quintana, A., Sánchez, M., Rodríguez, E.N., Cremata, J., Sánchez, J.C., 2008. Rapid and sensitive anthrone–sulfuric acid assay in microplate format to quantify carbohydrate in biopharmaceutical products: method development and validation. Biologicals 36, 134–141. http://dx.doi.org/10.1016/j.biologicals.2007.09.001. López-Linares, J.C., Romero, I., Cara, C., Ruiz, E., Moya, M., Castro, E., 2014. Bioethanol production from rapeseed straw at high solids loading with different process configurations. Fuel 122, 112–118. http://dx.doi.org/10.1016/j.fuel.2014.01.024. Lu, J., Li, X., Zhao, J., Qu, Y., 2012. Enzymatic saccharification and ethanol fermentation of reed pretreated with liquid hot water. J. Biomed. Biotechnol. 2012, 1–9. http://dx. doi.org/10.1155/2012/276278. Matías, J., Encinar, J.M., González, J., González, J.F., 2015. Optimisation of ethanol fermentation of Jerusalem artichoke tuber juice using simple technology for a decentralised and sustainable ethanol production. Energy Sustain. Dev. 25, 34–39. http://dx.doi.org/10.1016/j.esd.2014.12.009. Miller, G.L., 1959. Use of dinitrosalicylic acid reagent for determination of reducing sugar. Anal. Chem. 31, 426–428. http://dx.doi.org/10.1021/ac60147a030. MINAMBIENTE, Ministry of Environment and Sustainable Development, C, Barrera, X., Gómez, R., Suarez, R., 2015. El ABC de los compromisos de Colombia para la COP21. Monschein, M., Nidetzky, B., 2016. Effect of pretreatment severity in continuous steam explosion on enzymatic conversion of wheat straw: evidence from kinetic analysis of
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