Volume 4 Issue 3
Sep.  2019
Article Contents
Turn off MathJax

Citation:

ZnCl2 Enhanced Acid Hydrolysis of Pretreated Corncob for Glucose Production: Kinetics, Thermodynamics and Optimization Analysis

  • Corresponding author: A I ADEOGUN, admin@gmail.com
  • Received Date: 2019-04-21
  • The biomass of agricultural wastes as a source of fermentable sugars for biofuels production will address the food security and environmental preservation issues. These wastes are rich in lignocellulosic materials which can be hydrolyzed into fermentable sugars. However, low sugar yield and high energy consumption are some of the challenges faced in the process of hydrolization. This study investigated the low-cost corncob substrate for glucose production by dilute sulphuric acid hydrolysis in the presence of ZnCl2 at temperatures below 100℃ after pretreatment with 10% NaOH. Time dependent hydrolysis data were analyzed by Saeman model, thermodynamic parameters were obtained using Erying and Arrhenius equations while Box-Behnken model (Design Expert 6.0 version) was used for experimental design. As the substrate concentration increased from 50 mg/L to 150 mg/L, glucose yield increased from 10.4 mg/g to 14.6 mg/g for pretreated corncob while an increase from 3.4 mg/g to 8.6 mg/g was noted for untreated corncob. The hydrolysis rate constant was two orders of magnitude higher than the degradation rate constant. Thermodynamic parameters revealed endothermic process with positive Gibb's free energy of hydrolysis having average values of 84.76 kJ/mol and 79.87 kJ/mol for pretreated and untreated samples respectively. The optimum yield from the model was found to be 177.44 mg/g with 3.94% H2SO4 and 0.43 mol/L ZnCl2 for 200 g/L compared with optimum yield of 46.37 mg/g obtainable without ZnCl2. The results of this study showed that the alkaline pretreatment of corncob increased the accessibility of cellulose from the solid fraction and increase glucose production.
  • 加载中
  • [1]

    Ali Z, Hussain M, Arshad M. 2014. Saccharification of corn cobs an agro-industrial waste by sulphuric acid for the production of monomeric sugars. International Journal of Biosciences (IJB), 5(3):204-213. DOI:10.12692/ijb/5.3.204-213.
    [2]

    Ayeni A O, Hymore F K, Mudliar S N, et al. 2013. Hydrogen peroxide and lime based oxidative pretreatment of wood waste to enhance enzymatic hydrolysis for a biorefinery:Process parameters optimization using response surface methodology. Fuel, 106:187-194. DOI:10.1016/j.fuel.2012.12.078.
    [3]

    Binder J B, Raines R T. 2010. Fermentable sugars by chemical hydrolysis of biomass. Proceedings of the National Academy of Sciences of the United States of America, 107(10):4516-4521. DOI:10.1073/pnas.0912073107.
    [4]

    Cao N J, Xu Q, Chen L F. 1995. Acid hydrolysis of cellulose in zinc chloride solution. Applied Biochemistry and Biotechnology, 51/52(1):21-28. DOI:10.1007/bf02933408.
    [5]

    Carey F A, Sundberg R J. 2007. Advanced organic chemistry. 5th ed. New York: Springer.
    [6]

    Chen H Z, Han Y J, Xu J. 2008. Simultaneous saccharification and fermentation of steam exploded wheat straw pretreated with alkaline peroxide. Process Biochemistry, 43(12):1462-1466. DOI:10.1016/j.procbio.2008.07.003.
    [7]

    Gámez S, González-Cabriales J J, Ramírez J A, et al. 2006. Study of the hydrolysis of sugar cane bagasse using phosphoric acid. Journal of Food Engineering, 74(1):78-88. DOI:10.1016/j.jfoodeng.2005.02.005.
    [8]

    Gurgel L V A, Marabezi K, Zanbom M D, et al. 2012. Dilute acid hydrolysis of sugar cane bagasse at high temperatures:A kinetic study of cellulose saccharification and glucose decomposition. part I:sulfuric acid as the catalyst. Industrial & Engineering Chemistry Research, 51(3):1173-1185. DOI:10.1021/ie2025739.
    [9]

    Le Troedec M, Sedan D, Peyratout C, et al. 2008. Influence of various chemical treatments on the composition and structure of hemp fibres. Composites Part A:Applied Science and Manufacturing, 39(3):514-522. DOI:10.1016/j.compositesa. 2007.12.001.
    [10]

    Li H J, Pu Y Q, Kumar R, et al. 2014. Investigation of lignin deposition on cellulose during hydrothermal pretreatment, its effect on cellulose hydrolysis, and underlying mechanisms. Biotechnology and Bioengineering, 111(3):485-492. DOI:10.1002/bit.25108.
    [11]

    Mathur S P. 1998. Composting processes. Bioconversion of waste materials to industrial products. Boston, MA: Springer US. 1998: 154-193. DOI: 10.1007/978-1-4615-5821-7_4
    [12]

    Mohlala L M, Bodunrin M O, Awosusi A A, et al. 2016. Beneficiation of corncob and sugarcane bagasse for energy generation and materials development in Nigeria and South Africa:a short overview. Alexandria Engineering Journal, 55(3):3025-3036. DOI:10.1016/j.aej.2016.05.014.
    [13]

    Mudzanani K E. 2017. Optimization and kinetics study of solvent pretreatment of South African corn cob for succinic acid production. Johannesburg, South Africa: University of the Witwatersrand.
    [14]

    Nwakaire J N, Ezeoha S L, Ugwuishiwu B O. 2013. Production of cellulosic ethanol from wood sawdust. Agricultural Engineering International:The CIGR e-Journal, 15(3):136-140.
    [15]

    Pedersen M, Meyer A S. 2010. Lignocellulose pretreatment severity-relating pH to biomatrix opening. New Biotechnology, 27(6):739-750. DOI:10.1016/j.nbt.2010.05.003.
    [16]

    Pointner M, Kuttner P, Obrlik T, et al. 2014. Composition of corncobs as a substrate for fermentation of biofuels. Agronomy Research, 12(2):391-396.
    [17]

    Saeman J F. 1945. Kinetics of wood saccharification-hydrolysis of cellulose and decomposition of sugars in dilute acid at high temperature. Industrial & Engineering Chemistry, 37(1):43-52. DOI:10.1021/ie50421a009.
    [18]

    Sorrell S. 2015. Reducing energy demand:a review of issues, challenges and approaches. Renewable and Sustainable Energy Reviews, 47:74-82. DOI:10.1016/j.rser.2015.03.002.
    [19]

    Sun Y, Cheng J Y. 2002. Hydrolysis of lignocellulosic materials for ethanol production:a review. Bioresource Technology, 83(1):1-11. DOI:10.1016/s0960-8524(01)00212-7.
    [20]

    UNEP (United Nations Environment Programme). 2009. Converting Waste Agricultural Biomass into a Reseource, Compedium of Technology, United Nations Environmental Programme, Japan.
    [21]

    Zheng Y, Pan Z, Zhang R. 2009. Overview of biomass pretreatment for cellulosic ethanol production. International Journal of Agricultural and Biological Engineering, 2:51-68.
  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Figures(10) / Tables(8)

Article Metrics

Article views(144) PDF downloads(17) Cited by()

Related
Proportional views

ZnCl2 Enhanced Acid Hydrolysis of Pretreated Corncob for Glucose Production: Kinetics, Thermodynamics and Optimization Analysis

    Corresponding author: A I ADEOGUN, admin@gmail.com
  • 1. Department of Chemistry, Federal University of Agriculture, Abeokuta
  • 2. Department of Food Science and Technology, Federal University of Agriculture, Abeokuta

Abstract: The biomass of agricultural wastes as a source of fermentable sugars for biofuels production will address the food security and environmental preservation issues. These wastes are rich in lignocellulosic materials which can be hydrolyzed into fermentable sugars. However, low sugar yield and high energy consumption are some of the challenges faced in the process of hydrolization. This study investigated the low-cost corncob substrate for glucose production by dilute sulphuric acid hydrolysis in the presence of ZnCl2 at temperatures below 100℃ after pretreatment with 10% NaOH. Time dependent hydrolysis data were analyzed by Saeman model, thermodynamic parameters were obtained using Erying and Arrhenius equations while Box-Behnken model (Design Expert 6.0 version) was used for experimental design. As the substrate concentration increased from 50 mg/L to 150 mg/L, glucose yield increased from 10.4 mg/g to 14.6 mg/g for pretreated corncob while an increase from 3.4 mg/g to 8.6 mg/g was noted for untreated corncob. The hydrolysis rate constant was two orders of magnitude higher than the degradation rate constant. Thermodynamic parameters revealed endothermic process with positive Gibb's free energy of hydrolysis having average values of 84.76 kJ/mol and 79.87 kJ/mol for pretreated and untreated samples respectively. The optimum yield from the model was found to be 177.44 mg/g with 3.94% H2SO4 and 0.43 mol/L ZnCl2 for 200 g/L compared with optimum yield of 46.37 mg/g obtainable without ZnCl2. The results of this study showed that the alkaline pretreatment of corncob increased the accessibility of cellulose from the solid fraction and increase glucose production.

1.   Introduction
  • Fossil fuels account for over 90% of world energy supply with consequence increase in atmospheric levels of greenhouse gases and other pollutants resulting in global warming, acid rains and various health disorders (Nwakaire, 2013). Dwindling in fossil fuel reserve, coupled with rising energy demand as a result of growth in industrial and transport systems has made energy prices be of major concern (Sorrell, 2015). Agricultural waste biomasses offer an alternative to conventional energy sources, and it is an effective measure to mitigate negative impacts of overreliance on fossil fuels. Food crops such as grains, sugarcane have been the source of ethanol and other chemicals, while they are not desirable in developing countries as a result of its implications on food security. Hence, attention is being shifted to production from nonfood biomass sources (mainly lignocellulosic biomass) as an essential source of renewable energy supply.

    Apart from the environmental problems, misuse of the biomass materials constitutes loss of potentially valuable resources (Ali et al., 2014). Annually, about 1.40×1011 t of waste biomasses are generated solely from agricultural activities globally, ineffective disposal of which constitutes huge problem, and their decompositions generate greenhouse gases that contribute to the global climate change (UNEP, 2009). The primary component of lignocellulosic biomass is cellulose, the most abundant organic compound on the earth with potential to be a renewable source of energy and chemicals (Binder et al., 2010). Nigeria is the 10th largest producer of corn in the world and one of Africa's major producers with average production of about 8.18×106 t in 2015 with 23% increase envisaged in 2017 (Mohlala et al., 2016). Corncob is a process residue, and it is one of the most abundant agricultural wastes, accounting for 16%–19% of the whole corn after different food products have been isolated. Proximate analysis of corncob revealed that it contains 32.3%–45.6% cellulose, 39.8% hemicelluloses and 6.7%–13.9% lignin (Sun et al., 2002), and it is a potential source of fermentable sugar and such a good choice for the production of biofuels such as ethanol.

    Acid or enzyme hydrolysis of cellulose ordinarily is an expensive procedure; acid hydrolysis for example is energy intensive. Glucose formation required acid hydrolysis at high temperature also favors its decomposition with formation of products that inhibited the fermentation process of microorganisms (Cao et al., 1995). Physico- chemical pretreatment is necessary to circumvent the drawbacks that characterized the hydrolysis processes. Various pretreatments and their effects had been reported in previous studies, including removal of the lignin and hemicellulose to improve the available cellulose and disruption of the crystalline structure of the cellulose (Chen et al., 2008; Zheng et al., 2009). Zinc chloride is an effective swelling agent of cellulose, and it dissolves native cellulose and reduces its crystallinity at high concentration, also hydrolysis of cellulose in the zinc chloride solution has been reported to have a higher rate with an increasing glucose yield (Cao et al., 1995).

    This study investigated the dilute acid hydrolysis of corncob for glucose production in solution containing ZnCl2. Sulphuric acid (H2SO4) was used due to its availability and the possibility of giving low yield of inhibitory products (Mudzanani, 2017). The effects of initial substrate quantity, acid concentration, time and temperature as well as ZnCl2 concentrations on the glucose production were analyzed. Kinetics of hydrolysis was analyzed using Saeman's model, while Erying and Arrhenius equations were used to determine the thermodynamic parameters. Box-Behnken experimental design was used for the optimization study on effects of the parameters.

2.   Materials and Methods
  • Concentrated sulphuric acid, sodium hydroxide, D(+)- Glucose, potassium sodium tartrate, were of analytical grade, products of British Drug House (BDH) Poole, England and 3, 5-Dinitrosalicylic acid were from Kem light laboratory, India.

  • The corncob was collected from Ile-Epo Market at Alimosho Local Government Area in Lagos. It was washed and oven dried for 6 h at 105℃. The dried corncob was pulverized, sieved (400 μm mesh sieve) and stored in a tightly caped container until required for hydrolysis. The pretreatment of the corncob was performed in an autoclave employing NaOH (10%) at 1꞉10 solid-liquid ratio in a 500 mL glass jar. The mixture was stirred and placed in the autoclave for 2 h at 121℃. After pretreatment, the resulting mixture was washed to neutrality, filtered and dried at 105℃ for 4 h and stored in an airtight container until needed.

  • Various amounts of substrate (2.5–15.0 g) in 50 mL water in a round bottom flask containing 10 mL of different amounts of ZnCl2 (0.0–0.5 mol/dm3) and 20 mL of various H2SO4 (0.5%–5.0%) were placed in a thermostatic water bath at preset temperatures. A flask containing the mixture was withdrawn at an interval and glucose concentration determined by dinitrosalicylic acid (DNS) method. Briefly, 3 mL of the DNS reagent was added to 3 mL of the glucose sample/filtrate in lightly capped test tube, and the mixture was heated at 90℃ for about 15 min in water bath until reddish-brown colour was developed. The content was cooled in a cold water bath and the absorbance was read at 540 nm.

  • The generalized form Saeman's model (Saeman, 1945) applied for the kinetic analysis in this study is as shown below:

    From this reaction model, the solutions to the resulting differential equation provide for determination of the concentrations of cellulose [C], glucose [G] and degradation products [H] as a function of time (t) and can be represented by the equations below:

    where C0 is the potential glucose concentration (g/L), k1 (min–1) and k2 (min–1) are rate constants, and under the condition of initial concentrations of products approximately zero.

    Kinetic data were analyzed for glucose production, and C0 and the rate constants (k1 and k2) were determined from the above equations (1)–(3) using the least square fit method with the aid Micro Math Scientist software (Salt Lake City, Utah). The pre-exponential values and activation energies were obtained by applying the Arrhenius equation (Equation (4)), similarly enthalpy changes (ΔH) were estimated using Equation (5), Eyring equation (Equation (6)), was used for entropy changes (ΔS) determination while Gibbs free energies (ΔG) were estimated using Equation (7) (Carey et al., 2007).

    where Ai is the pre-exponential factor, Eai is the activation energy, h is the Planck's constant, kB is the Boltzmann constant, R is the gas constant, T is thermodynamic temperature, k is reaction rate constant, RT is the product of gas constant and thermodynamic constant, and E is thermodynamic energy.

  • Box-Behnken experimental design model was used, in which the three variables: substrate concentration (40– 200 g/L), acid concentration (0.5%–5.0%, V/V) and ZnCl2 (0–0.5 mol/dm3) were evaluated at three levels each using Design Expert 6.0. The experiments were carried out for 1 h at 90℃. Analysis of variance (ANOVA) was used to estimate the statistical parameters.

  • The raw and pretreated corncob were characterized using scanning electron microscope (SEM), energy dispersive X-ray (EDX) and Fourier transform infrared (FT-IR) spectroscopy in order to determine the sample surface morphology, elemental composition and functional groups, respectively, before and after hydrolysis.

3.   Results and Discussion
  • The proximate analyses of the corncobs used in this study are shown in Table 1. The results show that larger parts of the biomass regarded as waste are made up of hydrolysable carbohydrates (i.e., cellulose and hemicelluloses) with proportion far above 50% of the dry sample, and this is in agreement with the previous result (Pointner et al., 2014).

    Component Proportion (wt%)
    Moisture 10.47
    Cellulose 31.30
    Hemicellulose 46.08
    Lignin 11.42
    Ash 2.73

    Table 1.  Proximate analysis of corncob used in this study

  • Substrate concentration is directly related to the amount of the available hydrolysable cellulosic materials, therefore glucose production depends on the quantity of the substrate available for hydrolysis. Figure 1 shows that more glucoses are produced at higher substrate quantity, the lower acid- substrate ratio may contribute to reducing degradation of glucose to 5-hydrometoxyfulfuran (5-HMF), therefore more glucoses are obtained at higher substrate concentration. The influence of treatment on the glucose yield can also be inferred by comparing Fig. 1a and Fig. 1b, and it is found that pretreated samples yielded more glucoses than untreated samples, and this is due to the fact that alkaline pretreatment exposed more of the samples and increased accessibility to hydrolysis (Mudzanani, 2017). In addition, the crystalline structure of the untreated sample would have crumble, thereby exposing more of the content to hydrolysis.

    Figure 1.  Effect of substrate quantity on glucose yield of pre-treated (a) and untreated (b) corncob ([H2SO4], 5% w/w; [ZnCl2], 0.5 mol/dm3; temperature, 90℃)

  • Increasing acid concentration led to the production of more glucose as shown in Fig. 2, and this could be attributed to the fact that glycosidic linkage catalyzed hydrolysis rate increased with increasing proton leading to increase glucose yield. Although there is rapid increase in the initial glucose production at higher acid concentration, degradation of the glucose is faster than that at lower acid concentration. It was noted that, when at higher acid concentration (1.5% and above), with the increase in reaction time, reduction in glucose production was noted; the trend observed in this study is similar to what has been reported (Gámez et al., 2006). Therefore, it is suggested that moderate acid concentration and lower reaction time could be observed during hydrolysis in the presence of ZnCl2 would forming maximum glucose yield.

    Figure 2.  Effect of acid concentration on glucose yield of pre-treated (a) and untreated (b) corncob (substrate quantity, 150 g/L; [ZnCl2], 0.5 mol/dm3; temperature, 90℃)

  • The rate of the hydrolysis depends on the acid concentration and the quantity of the substrate as presented in Fig. 1 and Fig. 2, and the parameters for kinetic fits are reported in Table 2. The kinetic profile of the hydrolysis data as obtained from equations (1)–(3) are presented in Fig. 3. As shown in Table 2, increase in the substrate concentration as well as treatment led to the increase of potential glucose concentration (C0). As the initial concentration of the substrate increased from 25 mg/L to 150 mg/L, the potential glucose concentration increased from 10.4 mg/g to 14.6 mg/g for treated sample while that of untreated sample was from 3.4 mg/g to 8.6 mg/g. The rate constant for glucose formation, k1 is two orders of magnitude higher than k2, the degradation rate constants, with higher rate observed for pretreated samples.

    Figure 3.  Kinetic profile for acid hydrolysis of pre-treated (a) and untreated (b) corncob

    Substrate concentration (g/L) Pre-treated corncob Untreated corncob
    C0 (mg/g) k1 (×102, min–1) k2 (×104, min–1) R2 C0 (mg/g) k1 (×102, min–1) k2 (×104, min–1) R2
    25 10.53 1.37 5.70 0.985 3.363 1.56 4.23 0.992
    50 13.31 1.35 2.33 0.995 4.119 0.97 2.59 0.982
    75 13.98 1.62 4.28 0.998 8.224 0.53 2.38 0.954
    100 13.72 1.67 1.55 0.999 5.618 1.63 4.20 0.988
    150 14.62 1.50 0.36 0.999 8.601 0.97 2.12 0.950

    Table 2.  Effect of substrate quantity on kinetics parameter

    The values of the rate constants obtained showed that the rate of production of glucose is in tandem with its degradation at lower substrate, however, when at higher substrate concentration, the rate of degradation is higher due to the reduced production of glucose as a result of percolation that reduces the acid access to the glycosidic linkage in the cellulose. The dependence of acid concentration on the hydrolysis rate is shown in Fig. 2 and the parameters used to obtain the fitting are shown in Table 3. The increased concentration led to the increased accessibility to available hydrolysable content as shown in the table. The value of hydrolysable cellulose is higher in the pretreated samples than the untreated sample. At high acid concentration, lower values of k1 is observed while k2 increases with the increase of acid concentration, and this is due to the degradation of produced glucose aided by increased acid concentration. Figure 3 shows the product profiles as analyzed with equations (1)–(3), and the results showed that treated sample (Fig. 3a) has higher hydrolysable cellulose than the untreated sample (Fig. 3b). As the hydrolysis progresses, the amount of the glucose increases, while the cellulose content decreases with attendant production of 5-HMF.

    Acid concentration (%, V/V) Pre-treated corncob Untreated corncob
    C0 (mg/g) k1 (×102, min–1) k2 (×104, min–1) R2 C0 (mg/g) k1 (×102, min–1) k2 (×104, min–1) R2
    0.5 0.973 1.52 0.36 0.999 0.366 2.09 0.14 0.986
    1.0 1.526 1.66 1.68 0.999 0.540 1.92 3.27 0.987
    1.5 2.012 1.69 3.04 0.998 0.696 1.28 1.36 0.903
    2.5 4.418 0.75 3.11 0.986 1.164 5.99 1.41 0.975
    5.0 4.179 1.49 5.57 0.982 1.360 1.52 4.62 0.992

    Table 3.  Effect of acid concentration on kinetics parameter

  • Hydrolysis temperature is one of the most significant factors affecting glucose yields (Pedersen et al., 2010), however hydrolysis at high temperature led to the creamelization of the substrate and increased inhibitory product (Mathur, 1998). The temperature dependence of the first order rate of hydrolysis of corncob is shown in Fig. 4, Fig. 5 shows the Arrhenius plot for the hydrolysis, and the parameters are shown in Table 4. From the table, the R2 values obtained indicated that the model fit the thermodynamic parameters. The lower activated energy obtained for the pretreated corncob compared with untreated sample demostrated the ease of hydrolysis of the sample.

    Figure 4.  Temperature dependence of the acid hydrolysis of pre-treated (a) and untreated (b) corncob

    Figure 5.  Arrhenius plot for acid hydrolysis of pre-treated (a) and untreated (b) corncob

    Temperature(K) Pre-treated corncob
    ln k1 Ea (kJ/mol) A (min–1) R2 ln k2 Ea (kJ/mol) A (min–1) R2
    343 –5.929 6.12 0.023 0.897 –6.122 10.16 0.077 0.992
    353 –5.863 –6.036
    363 –5.843 –5.941
    368 –5.763 –5.877
    Untreated corncob
    343 –4.449 19.19 9.721 0.996 –8.511 42.88 693.93 0.832
    353 –4.274 –7.944
    363 –4.098 –7.944
    368 –3.985 –7.295

    Table 4.  Arrhenius parameters for acid hydrolysis of pre-treated and untreated corncob

    The thermodynamic parameters for glucose formation and degradation are shown in Table 5. The values of enthalpy change for glucose formation were positive indicating endothermic nature which reduced slightly with increasing temperature, this could be attributed to the phase remained unchanged during the hydrolysis reaction. Higher values of enthalpy change were observed for glucose degradation indicating relatively higher energy requirement for glucose degradation, as compared with the formation. Similar trends were observed for the untreated sample with higher values than those of treated, implying that much more energy was required for the hydrolysis and degradation for the untreated sample. The negative entropy change values for glucose were negative, which corroborated stability of the products formed out of hydrolysis as a result of constant phase and volume during the reaction. The negative values showed that the glucose was a stable product of hydrolysis. Similarly, glucose degradation also had negative entropy change, indicating a stable 5-HMF formation. However, the more negative entropy value of formation than degradation showed that glucose was a relatively more stable product than 5-HMF formation. Positive values of Gibbs free energy of hydrolysis indicated that the reaction was non-spontaneous and endothermic nature. The ΔG values for degradation of glucose were higher than that of hydrolysis, implying that degradation was thermodynamically less favored process than the glucose formation, similar trends had also been reported (Gurgel et al., 2012).

    Pre-treated corncob
    ΔH343 (kJ/mol) ΔH353 (kJ/mol) ΔH363 (kJ/mol) ΔH368 (kJ/mol)
    Hydrolysis 3.264 3.181 3.098 3.056
    Degradation 16.342 16.259 16.176 16.134
    –ΔS343 (kJ/(mol·K–1)) –ΔS353 (kJ/(mol·K–1)) –ΔS363 (kJ/(mol·K–1)) –ΔS368 (kJ/(mol·K–1))
    Hydrolysis 0.228 0.229 0.229 0.229
    Degradation 0.192 0.193 0.194 0.194
    ΔG343 (kJ/mol) ΔG353 (kJ/mol) ΔG363 (kJ/mol) ΔG368 (kJ/mol)
    Hydrolysis 81.613 83.885 86.283 87.270
    Degradation 82.164 84.393 86.579 87.617
    Untreated corncob
    ΔH343 (kJ/mol) ΔH353 (kJ/mol) ΔH363 (kJ/mol) ΔH368 (kJ/mol)
    Hydrolysis 7.304 7.221 7.137 7.096
    Degradation 40.024 39.940 39.857 39.816
    –ΔS343 (kJ/(mol·K–1)) –ΔS353 (kJ/(mol·K–1)) –ΔS363 (kJ/(mol·K–1)) –ΔS368 (kJ/(mol·K–1))
    Hydrolysis 0.204 0.204 0.204 0.203
    Degradation 0.143 0.142 0.145 0.142
    ΔG343 (kJ/mol) ΔG353 (kJ/mol) ΔG363 (kJ/mol) ΔG368 (kJ/mol)
    Hydrolysis 77.393 79.220 81.019 81.829
    Degradation 88.977 89.992 92.625 91.957

    Table 5.  Thermodynamic parameters for acid hydrolysis of pre-treated and untreated corncob

  • The SEM images of the corncob samples are presented in Fig. 6. The SEM images of the untreated corncob before hydrolysis (Fig. 6a) revealed a rigid and compact fibrous morphology with thick-walled fiber cells. After pretreatment (Fig. 6b), the structure presented reduced particle size with pores, and the structure became more disorganized and the morphology was characterized by the separation with greater exposure of fibers as well as loosening of the fibrous network, which might be due to the solubilisation of cell wall components (Li et al., 2014). After hydrolysis, the structures of both untreated (Fig. 6c) and pretreated sample (Fig. 6d) witnessed an increase surface area and porosity (Ayeni, 2013).

    Figure 6.  The SEM analysis of untreated and pretreated corncob before and after hydrolysis

    The EDX analyses of the pretreated and untreated samples are presented in Fig. 7. The main elements presented at the surface were mainly C and O of the cellulose, and upon treatments the surface was more exposed, hence there were increases in intensity of the elemental peaks.

    Figure 7.  The EDX untreated (a) and pretreated (b) of corncob

    The FT-IR of raw corncob and pretreated corncob before and after hydrolysis are shown in Fig. 8 and Fig. 9. All the spectra have broad band in the region of 3400 cm–1, 2900 cm–1 and 1600 cm–1, corresponding to —OH group of cellulose, C—H stretching vibration and O—H bending of absorbed water molecule respectively, the band at 1400 cm–1 is associated with —CH2 scissors vibration of the cellulose (Le Troedec et al., 2008).

    Figure 8.  The FT-IR spectrum of untreated corncob before and after hydrolysis

    Figure 9.  The FT-IR spectrum of pretreated corncob before and after hydrolysis

    The reduction in intensities of absorption bands at 1735 cm–1 and 1300 cm–1 in the treated sample indicated reduction in lignin and hemicellulose content, which resurfaced after hydrolysis due to the consumption of cellulose during hydrolysis.

  • Box-Behnken experimental design gave 17 experimental run as shown in Table 6. The response, Y is the amount of glucose produced (mg/g). Equation (8) is the quadratic statistical model in terms of actual variables that were obtained from ANOVA for the surface response to the experimental data presented in Table 6.

    Run order Factor Response
    [Substrate] (g/L) [Acid] (%, V/V) ZnCl2(mol/dm3) Coded value Glucose yield (mg/g)
    x1 x2 x3 Observed Predicted
    1 40 2.75 0 –1 0 –1 8.18 –3.376
    2 120 0.5 0 0 –1 –1 11.29 –6.778
    3 120 5 0 0 1 –1 14.18 36.445
    4 200 2.75 0 1 0 –1 14.96 22.319
    5 40 0.5 0.25 –1 –1 0 38.18 67.804
    6 40 2.75 0.50 –1 0 1 65.73 58.371
    7 40 5 0.25 –1 1 0 68.18 57.471
    8 120 5 0.50 0 1 1 98.18 116.245
    9 200 0.5 0.25 1 –1 0 99.07 109.779
    10 120 2.75 0.25 0 0 0 106.18 127.956
    11 120 2.75 0.25 0 0 0 106.18 127.956
    12 120 2.75 0.25 0 0 0 106.18 127.956
    13 120 0.5 0.50 0 –1 1 147.07 124.805
    14 200 2.75 0.50 1 0 1 160.40 171.956
    15 120 2.75 0.25 0 0 0 160.62 127.956
    16 120 2.75 0.25 0 0 0 160.62 127.956
    17 200 5 0.25 1 1 0 184.40 154.776

    Table 6.  Composite design matrix for optimization of variable and response

    The substrate concentration is represented as x1, the acid concentrations is x2, and x3 is the ZnCl2. The results of ANOVA carried out to determine the fit of the statistical model are listed in Table 7 and Table 8.

    Item Value
    R2 0.865
    Adj. R2 0.695
    % (CV) 36.06
    Adequate precision 7.09

    Table 7.  Statistical information of response

    Source Sum of square Degree of freedom Mean square F P
    Model 48470.97 9 5385.66 4.99 0.0229 Significant
    x1 9699.15 1 9699.15 8.98 0.0200
    x2 600.89 1 600.89 0.56 0.4801
    x3 22342.63 1 22342.63 20.68 0.0026
    x12 1353.70 1 1353.70 1.25 0.2999
    x22 665.22 1 665.22 0.62 0.4583
    x32 9583.52 1 9583.52 8.87 0.0206
    x1x2 765.44 1 765.44 0.71 0.4277
    x1x3 1931.11 1 1931.11 1.79 0.2230
    x2x3 670.23 1 670.23 0.62 0.4567
    Residual 7561.46 7 1080.21
    Lack of fit 4004.42 3 1334.81 1.50 0.3427 Not significant
    Pure error 3557.04 4 889.26
    Cor. total 56032.43 16

    Table 8.  Analysis of variance for quadratic model

    The value CV of 36.06% obtained confirmed that the treatments were carried out with high precision and reliability. Adequate precision value of 7.09 obtained in the study showed that the suggested model is within the desirable and possesses adequate signal to navigate the design space (Mathur, 1998). The R2 indicated that 86.5% of variability fall within the explanation capacity of the model with only 13.5% could not be accounted for by the independent variable. The F value of 4.99 with significant P value showed that there was only 2.29% chance of it being a noise and the insignificant lack of fit obtained for the model from ANOVA indicated that the model was significant. Figure 10 (a–c) represents the response surface and contour plots for the optimization of acid hydrolysis of corncob. The results of Fig. 10a showed the response surface plots for glucose yield as a function of acid concentration and ZnCl2, an optimum value of 177.44 mg/g was obtained as the concentrations of the acid and ZnCl2 were increased to 3.94% and 0.94 mol/L respectively above which was found to be unfavorable for the glucose yield. Figure 10b depicted the variation of substrate concentration with [ZnCl2], as the substrate concentration increased to 200 mg/L with a steady increase in [ZnCl2] to 0.94 mol/L resulted in that an increase glucose yield up to about 177.44 mg/g was obtained. Similarly, Figure 10c showed the effect of the interaction between substrate concentration and [ZnCl2], with an optimum yield of 177.44 mg/g as the substrate concentration reached the maximum of 200 mg/L and [ZnCl2] of 0.94 mol/L. From the response surface analysis and the numerical optimization from the software, the final optimized hydrolysis conditions obtained with RSM were 3.94% (w/w) [H2SO4], 3.94 mol/L [ZnCl2] along with 200 mg/L substrate would lead to glucose yield of 177.44 mg/g. On the contrary, optimization in the absence of ZnCl2 resulted in the glucose yield of 46.37 mg/g at 5.0% (w/w) [H2SO4] and 179.5 g/L of substrate. These results showed that the presence of ZnCl2 would enhance glucose production with almost 4 fold under reduced acid concentration.

    Figure 10.  Response surface plots for effect of [ZnCl2] and [H2SO4] (a), [ZnCl2] and [Substrate] (b), [H2SO4] (c), and [Substrate]

4.   Conclusions
  • Dilute acid hydrolysis of the corncob derived substrate for glucose production was investigated in this study. The proximate analysis of the substrate revealed that corncob contain significant amount of cellulose and hemicelluloses. The increase in acid concentration in the presence of ZnCl2 showed that the glucose yield was time dependent for both alkaline pretreated and untreated substrate. When the substrate concentration increased from 50 mg/L to 150 mg/L, the amount of glucose produced increased from 10.4 mg/g to 14.6 mg/g and 3.4 mg/g to 8.6 mg/g for pretreated and untreated corncob respectively. Similar trends were observed under the influence of acid concentration and temperature increase. Thermodynamic parameters showed that the hydrolysis was endothermic, with stable products formation which was less favored than the hydrolysis for both pretreated and untreated sample. The optimization analyses revealed that the presence of ZnCl2 enhanced the utilizations of the substrate and acid led to a significant increase of glucose production from 46.37 mg/g to 177.44 mg/g.

Conflict of Interest
  • The authors have no conflict of interest.

Reference (21)

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return