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Chen, K., Jing, X., and Liao, H. (2018). "Kinetic models and effects of Mn(II) ion on ethanol production from cornstalks," BioRes. 13(1), 954-966.


This paper presents a kinetic study of ethanol production by simultaneous saccharification and fermentation (SSF) from Mn(II)-catalyzed cornstalks. The optimal conditions of ethanol production were as follows: 1:2 inoculation proportion (ratio of Pachysolen tannophilus to Saccharomyces cerevisiae), 30 °C fermentation temperature, 15% inoculation quantity, 4 mg/g addition amount of Mn2+, and 10 U/g cellulase dosage. An optimal ethanol yield of 0.359 g/g was obtained from cornstalks under optimum conditions. A 38.5% increase in the yield was observed compared with the control group without the addition of Mn2+. The relationship between ethanol yield and fermentation time followed a Langmuir isotherm model. The relationship between the rate constant and fermentation time in the conversion of cornstalks to ethanol was fractal like. The findings elucidate the complex characteristics of ethanol production from cornstalks with Mn2+ catalysis and will be useful in improving production yield.

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Kinetic Models and Effects of Mn(II) Ion on Ethanol Production from Cornstalks

Kun Chen,a,b,* Xiaofei Jing,a and Hao Liao a

This paper presents a kinetic study of ethanol production by simultaneous saccharification and fermentation (SSF) from Mn(II)-catalyzed cornstalks. The optimal conditions of ethanol production were as follows: 1:2 inoculation proportion (ratio of Pachysolen tannophilus to Saccharomyces cerevisiae), 30 °C fermentation temperature, 15% inoculation quantity, 4 mg/g addition amount of Mn2+, and 10 U/g cellulase dosage. An optimal ethanol yield of 0.359 g/g was obtained from cornstalks under optimum conditions. A 38.5% increase in the yield was observed compared with the control group without the addition of Mn2+. The relationship between ethanol yield and fermentation time followed a Langmuir isotherm model. The relationship between the rate constant and fermentation time in the conversion of cornstalks to ethanol was fractal like. The findings elucidate the complex characteristics of ethanol production from cornstalks with Mn2+ catalysis and will be useful in improving production yield.

Keywords: Cornstalks; Manganese catalysis; Fractal-like; Kinetic; SSF; Fuel; Ethanol

Contact information: a: School of Safety Engineering, Chongqing University of Science and Technology, Chongqing 401331, China; b:Centre for Risk, Integrity and Safety Engineering (C-RISE), Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John’s A1B 3X5, Canada; *Corresponding author:


Lignocellulosic biomass is a high potential feedstock for bio-ethanol production; as such, it has the potential to reduce the pollution caused by the use of fossil fuels (Iqbal et al. 2012; Arevalo-Gallegos et al. 2017; Bilal et al. 2017a). Ethanol produced from lignocellulosic biomass could become the dominant global renewable fuel, and therefore there is a need for advanced development of ethanol fuel technology, such as determining the optimal factors of production (Asgher et al. 2014a). The optimal production of bioethanol requires efficient conversion in the three major steps of pretreatment, enzymatic hydrolysis, and fermentation (Gaur et al. 2016).

In previous work, the effects of several parameters on straw stalk used for ethanol fuel production were investigated, and the results showed that the optimal conditions were a fermentation temperature of 38 °C, a fermentation time of 72 h, a yeast inoculation quantity of 15%, a yeast inoculation proportion of 2:1, and a cellulose enzyme dosage of 20 U/g (Chen et al. 2013). Catalysts serve vital roles in lignocellulosic ethanol conversion. Acids and enzymes facilitate the hydrolysis of cellulose, and metal ions and biological catalysts can also improve the conversion rate (Hayes 2009; Asgher et al. 2014b; Bilal et al. 2017b).

Mn2+ catalytic ethanol production is a promising chemical approach (Ahmed and Lewis 2007; Liu et al. 2017). Liu et al. (2017) observed that Mn²⁺can improve the efficiency of conversion of lignocellulosic biomass to fermentable sugars for the production of bioethanol. Manganese (Mn2+) catalysts, which influence ethanol production, have been applied in the catalytic liquefaction of various biomasses (Chen et al. 2012; Lakkana et al. 2012). However, the addition of Mn2+ has no significant effect on sugar yield, and the saccharification yields for the samples with Mn2+ are the same or similar to those of the saccharification samples without added metal ions (Ramachandran et al. 2015). Ethanol production does not change considerably at higher concentrations of Mn2+ (Saxena and Tanner 2011). However, trace manganese enhances butyric acid production (Liu et al. 2015). Moreover, supplementation with Mn2+ and nitrogen coupled with a small amount of aeration improves ethanol production efficiency (Saxena and Tanner 2011; Deesuth et al. 2015). However, high concentration of Mn2+ may be toxic because it affects the permeability of membranes, causing a decrease in both yeast growth and fermentation activity (Stehlik-Tomas et al. 2004). Manganese ions can enhance cell growth (Xue et al. 2008; Pereira et al. 2010) and increase the activity of cellulase (Guerfali et al. 2011; El-Gindy et al. 2015). Cellulase enzyme production is relatively costly, which requires the enzyme to be used as fully as possible (Zhang et al. 2012). Therefore, further research on manganese supplementation is needed to optimize the process of manganese catalyzed ethanol production.

The study of fermentation kinetic parameters is important for understanding the impacts of process parameters on ethanol production (Wang and Feng 2010; Zhang et al. 2012). Moreover, a mathematical model is both an important tool for understanding the mechanism of a complex reaction and the base for largescale process model development (Wang and Feng 2010). The Langmuir equation has been utilized to describe the complex, fractal-like process of converting lignocellulosic materials to ethanol (Chen et al. 2014). Moreover, kinetic parameters can be used with mathematical models to predict the dynamics of the ethanol production rate (Yao et al. 2011; Zhang et al. 2012). The current understanding of the kinetic model of ethanol production is underdeveloped. Fractal kinetic analysis provides another point of view of heterogeneous chemical reactions to identify the optimal conditions of ethanol production from cornstalks (Chen et al. 2014; Nguyen et al. 2015).

The effects of enzyme loading, fermentation time, substrate concentration, fermentation temperature, and size distribution on cellulose hydrolysis have been examined in previously proposed kinetic models (Yao et al. 2011; Zhang et al. 2012; Chen et al. 2013; Chen et al. 2014), but few papers considered the effect of manganese catalyst on ethanol yield. Consequently, the kinetic models of ethanol production, the optimization of ethanol production from cornstalks, and productivity should be examined systemically. Kinetic models of ethanol production from Mn2+-catalyzed cornstalks will be helpful for scaling-up ethanol production plants.

In this study, the effects of MnSO4 (Mn2+) on the production of ethanol from cornstalks liquefaction pretreated via SSF were investigated. The aim was to identify the optimal conditions for the production of ethanol from cornstalks. Kinetic models were proposed to describe the effects of Mn2+ on the kinetic parameters of ethanol production, which should provide a better understanding of the effects of Mn2+ on the ethanol yield from cornstalks via SSF. Kinetic analysis of ethanol preparation from cornstalks catalyzed with the addition of different amounts of Mn2+ was considered and characterized. This information will be helpful for improving the energy utilization of cornstalks and the theoretical development of ethanol production.



The cornstalks used in this study were collected from a household in Bishan of Chongqing. Cellulase (filter paper activity, 15000 U/g) was purchased from Sinopharm Chemical Reagent Co., Ltd (Shanghai, China), and yeast (Pachysolen tannophilus 1770 and Saccharomyces cerevisiae 1001) were purchased from the China Center of Industrial Culture Collection (Beijing, China). Potassium dichromate, ethanol, sulfuric acid, glycol, MnSO4 (Mn2+), glucose, agar, wort, and peptone were purchased from Baimadang Chemical Storage (Chongqing, China). The oven (101-1), grinding mill (XQM-2L), portable steam sterilizer (YX280B), spectrophotometer (722), microscope (XSP-2CA) and hemocytometer (7108) were purchased from Shanghai CSOIF Company Limited (Shanghai, China).


Material pretreatment

The cornstalk material was placed in an oven at 40 °C for 25 h. It was sheared and milled until the entire sample passed through an 80-mesh sieve. The material was then dried to constant weight at 105 °C for 24 h. A total of 20 g of dried cornstalks powder and 120.0 g of glycol were put into a three-mouth flask with a magnetic rotor. The middle mouth of the three-mouth flask was connected to a condenser tube. The flask was placed in a water bath with magnetic stirring (90 °C, 100 rpm). The side mouth of the flask had a perforated rubber stopper, through which a thermometer was inserted into the reaction mixture. The other side of the mouth was a feed inlet (a loaded rubber plug without a hole). After 10 min of preheating, the rubber plug of the feed inlet was removed, and 25 m∙mol of concentrated sulfuric acid was added to the flask. A rubber plug was inserted, and the reaction solution was stirred for 75 min at 90 °C.

After completion of the reaction, the flask and condenser pipe were separated, and the stirrer was removed. The reaction mixture in the flask was diluted with hot water. The reaction was poured into the funnel of the vacuum suction filter and filtered. The reaction mixture was filtered twice more, with 20 mL of methanol added to the filtrate each time. This process was repeated twice with 20 mL of hot water. The final product containing the fermentation substrate was obtained by drying the filter cake for 1 h at 105 °C.

Preparation of the slant, seed, fermentation medium

The media were prepared as described by Li et al. (2013). Medium I was used for slant medium, and it was composed of 10% wort with 2% agar and 2% peptone. Medium II was used for seed culture, and it was composed of 10% wort with 2% peptone. Medium III was used for fermentation and was composed of fermentation substrate (10 g), 1.0% dilute sulfuric acid, 30% NH4HCO3, and had a solid-liquid ratio of 1:15 (m:m). All media were adjusted to pH 6 and sterilized for 30 min at 121 °C. The seed culture of the strains (P. tannophilus and S. cerevisiae) was grown aerobically in a 250 mL Erlenmeyer flask containing 30 mL of the seed medium and shaken at 160 rpm for 24 h at 30 °C.

Activation and dilution of yeast strains

P. tannophilus and S. cerevisiae were collected from the test tube slant and activated in liquid medium, respectively (30 °C, 24 h). The mixture was stirred (160 rpm, 2 h); samples were counted by hemocytometer and diluted to 10cell/mL with sterile water.

Design of ethanol optimization experiment and kinetic experiment

Pretreated cornstalks were used as raw material. The solid-to-liquid mass ratio was 1:15, and the fermentation time was 72 h. The orthogonal optimization experiment was designed with specific values of fermentation temperature, amounts of added Mn2+, inoculation quantity, inoculation proportions (ratio of P. tannophilus to S. cerevisiae), and cellulase dosage as factors. The results of the orthogonal experiment are listed in Table 1. Additionally, the control groups without the addition of Mn2+ are shown in Table 2.

Based on previous research results, using the optimized values (inoculation quantity, inoculation proportion, cellulase dosage, and fermentation temperature) obtained from the orthogonal experiment, the kinetics and effects of different concentrations of Mn2+ (4 mg/g, 6 mg/g, 8 mg/g, and 10 mg/g) on ethanol production via SSF of cornstalks were investigated.

Determination method

The contents of cellulose, hemicellulose, and lignin in the cornstalks were determined as previously described (Sluiter et al. 2012). Ethanol concentrations were determined as described in He et al. (2013). All experiments were performed in duplicate under the same conditions. Potassium dichromate spectrophotometry was used to determine the ethanol concentration at every 12 h. The standard curve is shown in Eq. 1,


where Y is the absorbance (g/L) and X is the ethanol concentration (g/L). The ethanol production rate was calculated according to the following equation,


where C is alcohol concentration that was obtained from contrasting with a standard curve (g/L), V is the total volume of liquid in the container (fermentation liquid volume + inoculation quantity) (L), M is the pretreated cornstalks (g), and Y is the ethanol yield (g/g).


Process Optimization of Ethanol Production from Cornstalks

The range analysis summarized in Table 1 showed that the order of importance of the five major influencing factors in ethanol preparation from cornstalks was inoculation quantity ˃ inoculation proportion ˃ addition amount of Mn2+ ˃ cellulase dosage ˃ fermentation temperature. Through orthogonal experiments and analysis, the optimum conditions were identified as follows: 1:2 inoculation proportion, 30 °C fermentation temperature, 15% inoculation quantity, 4 mg/g added Mn2+, and 10 U/g cellulase dosage. An analysis of variance showed that at F0.05, the effect of the five factors on ethanol production from cornstalks reached a significant level. The verification test was carried out under these optimized conditions. The ethanol yield was 0.359 g/g.

Table 1. Results of SSF Orthogonal Experiments in Addition of Mn2+ to Fermentation Broth

The experiments were performed in duplicate and the test results were expressed as mean ± SD. The value of K1K2K3K4, and R were calculated from the mean.

The range analysis summarized in Table 2 illustrates that the order of importance of the four major influencing factors in the preparation of ethanol from cornstalks were fermentation temperature ˃ inoculation quantity ˃ cellulase dosage ˃ inoculation proportion. By orthogonal experiment and analysis, the optimal conditions of the control groups were obtained as follows: the inoculation proportion was 2:1, the fermentation temperature was 32 °C, the inoculation quantity was 20%, and the cellulase dosage was 20 U/g. The verification experiment was carried out under the optimal conditions. The results showed that the ethanol yield was higher than that of the control orthogonal experiments group. The ethanol yield was 0.267 g/g. Accordingly, the optimal conditions of the control group were as follows: 2:1 inoculation proportion, 32 °C fermentation temperature, 20% inoculation quantity, and 20 U/g cellulase dosage. Under these conditions, the ethanol yield was 0.267 g/g.

Compared with the control group, ethanol yield in the group with added Mn2+ increased by 38.5% under optimal conditions. Furthermore, the addition of Mn2+ both initiated the anaerobic fermentation reaction at a lower temperature and decreased the cellulase dosage from 20 U/g to 10 U/g. Due to the reduced cellulose dosage and the reduced energy consumption allowed by the initiation of the anaerobic fermentation reaction at lower temperature (Yanase et al. 2010; Lupoi and Smith 2011), ethanol production costs in the group with the addition of Mn2+ were reduced. Table 3 shows that the hemicellulose content of cornstalks increased from 32.7% to 54.9%.

Lignin content was decreased from 16.8% to 11.2% by liquefaction pretreatment, increasing the binding sites between cellulase and substrate. Mn2+ is an essential trace element for microbial growth that improves the activity of cellulase and yeast (Saxena and Tanner 2011; Lakkana et al. 2012). The increase in activity and cellulose content is favorable for fermentation (Li et al. 2013; Deesuth et al. 2015). The results showed that the ethanol yield from cornstalks was improved by adding appropriate amounts of Mn2+, which was economically feasible.

Table 2. Results of SSF of Control Orthogonal Experiments

The experiments were performed in duplicate and the test results were expressed as mean ± SD. The value of K1K2, K3K4, and R were calculated from the mean.

Table 3. Composition of Corn Stalks (Percentage of Total Dry Weight)

Effects of Mn2+ Addition on Ethanol Yield

Based on the results of the optimization process, the effect of different Mn2+ concentrations (4 mg/g, 6 mg/g, 8 mg/g, and 10 mg/g) on ethanol fermentation was investigated. A comparison of the ethanol yield in the liquefaction of cornstalks with different quantities of Mn2+ added is given in Fig. 1. Ethanol yield, which reached 0.357 g/g, was the highest with a Mn2+ addition of 8 mg/g after 72 h of fermentation.

Fig. 1. Effect of the level of addition of MnSO4 on ethanol yield. The experiments were performed in duplicate and the test results were expressed as mean ± SD.

In a certain range of concentrations, there was a positive correlation between biological activity and the amount of Mn2+ added (Guerfali et al. 2011). However, a high content of Mn2+can lead to loss of activity in yeast and cellulose (Chen et al. 2008). If the amount of manganese ion is too high, it may lead to excessive activity in yeast and destroy the dynamic synergy between P. tannophilus and S. cerevisiae, causing a decrease in ethanol yield due to the assimilation of ethanol by Mn2+. In this study, low concentrations of Mn2+ (at 4 mg/g, 6 mg/g, 8 mg/g) improved ethanol yield from cornstalks. However, higher concentration additions of Mn2+ (at 10 mg/g) decreased ethanol yield from cornstalks. Therefore, the addition of Mn2+ increased the ethanol yield to a certain extent, as shown in Fig. 1. The results showed that the microorganism partially inhibits the biochemical reaction by adding Mn2+ under anaerobic conditions. The ethanol yield increased with the increase of the amount of Mn2+ (at the amount of Mn2+ 8 mg/g), and the ethanol yield declined at 10 mg/g.

Kinetic Analysis Based on Addition of Mn2+

Two-constant kinetics model

Kinetic modeling is important in designing and controlling bioprocess efficiency, and kinetics analysis improves product yield (Xu et al. 2008; Chen et al. 2014). As shown in Fig. 1, the ethanol yield (Y) gradually increased with increasing t values under different amounts of Mn2+ addition. The rate of ethanol preparation was faster at the starting stage, and the curve was similar to that of the Langmuir adsorption isotherm. Accordingly, Eq. 3 could be used to describe the relationship between Y and t,


where Y is the ethanol yield (g/g), a is the capacity for ethanol production by fermentation (g/g), b is the rate constant (h-1), and t is fermentation time (h). Equation 3 can also be expressed as Eq. 4.


The experimental data from Fig. 1 were fitted into Eq. 4 by one-dimensional nonlinear regression for each amount of Mn2+ addition. The values of a and b determined from the fit are shown in Table 4. The regression analysis results are also listed in Table 4.

Table 4. Calculation Results from the Two-Constant Experiential Model

The values were calculated from the mean.

Table 4 shows that the catalytic kinetics of Mn2+ in the process of preparing ethanol was well-described by a two-constant experiential model. Table 4 shows that parameter a decreased with an increasing initial addition of Mn2+ (except the addition of 8 mg/g of Mn2+). Moreover, ethanol peaked with the addition of 8 mg/g of Mn2+. Parameter b increased with the increasing addition of Mn2+. Parameter b, representing rate constant, reached the fastest level with the addition of 10 mg/g of Mn2+. The peak rate of ethanol fermentation was achieved with the addition of 10 mg/g of Mn2+. Taking into account the maximum yield, the addition of 8 mg/g of Mn2+ was selected as the optimal process factor. Thus, the two-constant Langmuir isotherm model adequately described the kinetics of Mn2+ in ethanol production from cornstalks. The reliability of the relative coefficient with different amounts of Mn2+addition exceeded 95.5%.

Fractal-like kinetics model

The rate constant of a reaction is independent of time in classical chemical kinetics. However, recent studies have shown that the rate of reaction is not proportional to the integral power of reaction time (t). The kinetics of most heterogeneous reactions do not follow the classical kinetics law, and the rate constant (k) was correlated with reaction time (Yao et al. 2011; Chen et al. 2014). The relationship can be expressed as Eq. 5,


where k is the time-dependent rate coefficient, h is the constant that measures the degree of local heterogeneity, and k1 is a constant that is not related to time.

Considering the first-order kinetic integral equation, the rate coefficient k at t (t1t2, t3etc. were different fermentation moments) can be calculated by using the change of ethanol yield from t1 to t2, and the k at t3 can be obtained by using the change of ethanol yield from tto t3 in the dynamic state. The others were deduced by analogy. The k values at t could be calculated using Eq. 6 (Liu et al. 2002); Table 5 lists the remaining k values.


As shown in Table 5, k decreased as fermentation time increased with different amounts of Mn2+. The kinetics of reaction of the fermentation process is fractal-like, and these k values appear to vary irregularly with different amounts of Mn2+ addition. The rate coefficient in this paper, which was time-dependent in the fractal kinetics, was different from the rate constant in classical kinetics. The time-dependent rate coefficient is related to the fractal exponent. The ethanol yield steadily decreased with increased addition of Mn2+ at the fermentation time of 72 h. Thus, these k values might increase or decrease as the addition of Mn2+ increases.

Table 5. Reaction Rate Coefficient k at Different Addition of Mn2+ in Reaction Time

The values were calculated from the mean.

To explore the quantitative relationship between the rate coefficient and time, Eq. 5 can also be expressed as follows:


The experimental data were regressed using Eq. 5, and the relationship between and was described with Eq. 7. The results are listed in Table 6. The reliability of the relative coefficient with various amounts of Mn2+ addition exceeded 96.9%. Thus, Eq. 5 and Eq. 7 were adapted to describe the quantitative relationship between the fermentation rate coefficient of cornstalks and time. Namely, the fermentation kinetics of cornstalks with different additions of Mn2+ are fractal-like. Although values of kand h appear to vary irregularly with the increase of the amount of Mn2+ added, k is concerned with h and t. Therefore, parameter h is relative to the fractal dimension. The fractal dimension and the order of reaction could not be obtained. However, as h was larger than 1, it is certain that the process of fermentation from cornstalks with different amounts of Mn2+ addition is fractal-like.

Table 6. Modeling Results for logk and logt

The values were calculated from the mean.


  1. Compared with the group without the addition of Mn2+ under the optimal conditions, ethanol yield increased by 38.5% in the group with added Mn2+. The addition of Mn2+ both initiated the anaerobic fermentation reaction at a lower temperature and decreased the cellulase dosage.
  2. The time course of the conversion of cornstalks to ethanol under different conditions of added Mn2+ was matched with the fractal-like kinetic model. The relationship between the ethanol yield and fermentation time could be described using the Langmuir isotherm model and inverse power function.
  3. The good fit of the experimental data confirmed the applicability of the kinetic model to describe the complex characteristics of ethanol production from cornstalks with Mn2+catalysis. This kinetic model provides a new way to analyze the complex kinetics of ethanol production from cornstalks with Mn2+ catalysis.


The authors are grateful for the financial support of the Scientific and Technological Research Program of Chongqing Municipal Education Commission (KJ1601337), the China Scholarship Council (201508505060), the National Natural Science Foundation of China (No.51404049), the Research Foundation of Chongqing University of Science & Technology (CK2015B14), and the Chongqing Administration of Work Safety (CQAWS2013Y-004).


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Article submitted: July 31, 2017; Peer review completed: October 21, 2017; Revised version received: November 30, 2017; Accepted: December 2, 2017; Published: December 7, 2017.

DOI: 10.15376/biores.13.1.954-966