Abstract
In this paper, the NaOH pretreatment of banana pseudo-stem fiber for biogas production was investigated using a statistically designed set of experiments. A central composite design was used to identify the optimum pretreatment condition for four factors, i.e., NaOH concentration, pretreatment temperature, pretreatment time, and fiber length, on biogas fermentation of banana pseudo-stem fiber. The best pretreatment condition was 7.8% NaOH, 0.2-cm fiber length, and a temperature of 48 °C for 3 days. NaOH pretreatment increased the biogas yield of banana pseudo-stem fiber. The highest biogas yield was 463.0 mL·g-1VSadded, which was 89.2% higher than that of the control, at 244.7 mL·g-1VSadded.
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Optimization of NaOH Pretreatment for Enhancement of Biogas Production of Banana Pseudo-Stem Fiber using Response Surface Methodology
Pei Pei,a,b Chengming Zhang,a,b Jihong Li,a,b Sandra Chang,b Shizhong Li,a,b,* Jianlong Wang,a Mingxing Zhao,c Li Jiang,a,b Menghui Yu,a,b and Xuelan Chen a,b
In this paper, the NaOH pretreatment of banana pseudo-stem fiber for biogas production was investigated using a statistically designed set of experiments. A central composite design was used to identify the optimum pretreatment condition for four factors, i.e., NaOH concentration, pretreatment temperature, pretreatment time, and fiber length, on biogas fermentation of banana pseudo-stem fiber. The best pretreatment condition was 7.8% NaOH, 0.2-cm fiber length, and a temperature of 48 °C for 3 days. NaOH pretreatment increased the biogas yield of banana pseudo-stem fiber. The highest biogas yield was 463.0 mL·g-1VSadded, which was 89.2% higher than that of the control, at 244.7 mL·g-1VSadded.
Keywords: Banana pseudo-stem fiber; NaOH pretreatment; Response surface methodology; Anaerobic fermentation; Biogas
Contact information: a: Institute of Nuclear and New Energy Technology, Tsinghua University, Tsinghua Garden, Beijing 100084, PR China; b: Beijing Engineering Research Center for Biofuels, Beijing 100084, PR China; c: School of Environment and Civil Engineering, Jiangnan University, Wuxi 214122, PR China; * Corresponding author: szli@tsinghua.edu.cn
INTRODUCTION
Banana is recognized as an important fruit crop in tropical and subtropical countries. During the production of bananas, a large amount of byproducts are produced, including pseudo-stem, leaves, inflorescence, and rhizomes. Banana pseudo-stem (BPS) constitutes the majority of the mass of byproducts, at 120 to 165 t per hectare produced annually. Usually, BPS are crushed and left to degrade in the soil to replenish the nutrients for the next growth season, or left whole without crushing to degrade on an empty lot after the harvesting of the bananas (Padam et al. 2012). However, both disposal methods generate a large amount of carbon dioxide, methane, hydrogen sulfide, and associated unpleasant odors. These disposal approaches could also lead to an outbreak of banana fusarium wilt caused by Fusarium oxysporum f. sp. cubense, one of the most serious fungal diseases affecting banana production (Getha and Vikineswary 2002; Xiao et al. 2013). It is therefore advantageous to make use of the BPS and at the same time prevent related environmental and ecological issues. Based on previous reports, BPS can be utilized in many different processes, such as compost, paper making, rope making, production of bags, feed, and biofuels (Tock et al. 2010; Wei and Zhou 2001; Zuluaga et al. 2009). Among these options, using BPS as raw material for biogas production by anaerobic digestion technology is a very promising strategy and addresses the serious need for alternative fuel sources worldwide.
Producing clean energy from agricultural wastes to partially substitute fossil fuels has aroused worldwide attention (Chandra et al. 2012a; Gunaseelan 2007; Binod et al. 2010). Presently, China is actively promoting the development of new resources to generate biogas. Ten thousand large-scale biogas plants using industrial and agricultural wastes as raw materials are projected to be built by 2020, with biogas production reaching 14 billion m3 annually (Zhang et al. 2013). With the support of the National Key Technology R&D Program, the Hainan Shenzhou New Energy Construction & Development Co., Ltd in Hainan province began building a plant in 2009 and started production at the end of 2013. The proposed biogas production ability of this plant was 30,000 m3 daily, and BPS was considered as one of the main raw materials used for fermentation. Therefore, research on biogas fermentation of BPS by anaerobic digestion is of practical significance and could provide the necessary data to support the stable operation of the plant. Most reports on biogas fermentation of banana byproducts have focused on using waste bananas and banana peels (Bardiya et al. 1996; Clarke et al. 2008). Only a few studies have been conducted on biogas fermentation of BPS and focused on the biological methane potential test or co-digestion with animal manure (Tian et al. 2013; Zhang et al.2013). The reported biogas yield for BPS is usually 221 to 325 mL·g-1 TS, and the methane content of the biogas is 59% to 79% (Kalia et al. 2000; Ou et al. 2006; Pei et al. 2014).
Compared with wheat straw and corn straw, the high water content (about 94%) of BPS greatly increased the transportation cost and limited industrial applications. Recently, to resolve this issue, Zhang et al. (2013) proposed reducing the water content before transportation by squeezing the BPS, thus reducing the cost and increasing the potential transport distance. Currently, two options exist after reducing the transportation cost (Fig. 1). One is the direct production of biogas through anaerobic digestion, utilizing BPS alone or with other feedstocks. The other option is, after extraction of banana pseudo-stem fiber (BPSF) for pulping (Daud and Law 2010; Liu et al. 2013), the residues, mostly parenchyma cells (Chen et al. 2000), could be used for biogas production. However, BPSF itself is suitable for biogas production. It is uncertain whether BPSF would be better used for pulping or biogas fermentation. No relevant research has been reported on the biogas production of BPSF. Therefore, the biogas fermentation performance of BPSF was investigated in this paper.
Pretreatment generally can improve the biogas yield of a lignocellulosic substrate to some extent (Chandra et al. 2012b; Wang et al. 2010; Zhang et al. 2011; Frigon et al. 2012; Quintero et al. 2012). Existing pretreatments for lignocellulosic substrates include physical, chemical, and biological methods. Among these methods, NaOH pretreatment is a promising approach for biogas production of lignocellulosic substrates from the point of industrial application (Salehian et al. 2013; Ward et al. 2008; Zhu et al. 2010). As a result, NaOH pretreatment was selected to improve the biogas yield of BPSF in this paper.
Fig. 1. Utilization options of banana pseudo-stem
The aim of this paper was to determine the biological biogas potential of BPSF with or without NaOH pretreatment, as well as the optimum NaOH pretreatment conditions. The optimal pretreatment conditions, including NaOH concentration, pretreatment temperature, time and fiber length, were determined by response surface methodology (RSM).
EXPERIMENTAL
Materials
Fresh BPS was provided by Hainan Shenzhou. BPS was cut and milled using a disc mill (BR30-300CB KRK, Kogyo). BPSF was sieved and cut to different lengths. The preparation process is shown in Fig. 2. Samples were stored at 4 °C before anaerobic digestion. Major components of BPSF were as follows (on dry basis): cellulose, 36.9 ± 0.3% to 44.9 ± 0.5%; hemicellulose, 17.7 ± 0.7% to 22.9 ± 1.1%; acid-soluble lignin, 1.7 ± 0.1% to 1.8 ± 0.1%; and acid-insoluble lignin, 13.0 ± 0.3% to 13.9 ± 0.8%.
Fig. 2. Preparation process of banana pseudo-stem fiber
Inoculum, anaerobic sludge, was collected from the Gaobeidian wastewater treatment plant. The total solids (TS, based on wet solid) and volatile solids (VS, based on dry matter) of the inoculums were 6.2 ± 0.1% and 32.0 ± 0.1%, respectively. The total nitrogen (TN) was 2.4% on dry basis. The pH value of inoculum was 7.0.
NaOH Pretreatment
Samples were pretreated in 50-mL plastic bottles. The pretreatment temperature was controlled by a water bath. Wet-state NaOH pretreatment was used. The moisture content was 90% (Chandra et al. 2012; Zheng et al. 2009). NaOH doses were calculated using the following equation:
(1)
The control sample was pretreated with water under the same conditions.
Biogas Fermentation
Alkali-pretreated BPSF was cooled to room temperature and used directly in fermentation without rinsing. The experiments were conducted in 500-mL glass bottles. The total mass and TS of the fermentation system were 400 g and 6% (w/v), respectively. The ratio of inoculum to substrate (both expressed in g of VS) was 1:1. The fermentation temperature was maintained at 37 ± 1 °C in a water bath. Urea and NaHCO3 were used to adjust the C/N and alkalinity of the system to 25:1 and 2500 mg CaCO3/L, respectively. Nitrogen was used before the fermentation to ensure an anaerobic environment. Reaction bottles were shaken 3 times daily to mix the samples. Biogas volume was measured using water replacement method with saturated salt solution. The daily and cumulative biogas production was recorded. The gas generation of inoculum was considered during the calculation of biogas production. The biogas yield could be calculated using the following equation:
(2)
Experimental Design and Data Analysis
The pretreatment conditions were optimized by central composite design (CCD) of RSM. In this study, four variables (concentration, time, temperature, and fiber length) were investigated. The range and levels of variables were selected based on the results of single-factor tests (Pei et al. 2014), results in the literature (Chandra et al. 2012; Sambusiti et al. 2013; Zheng et al. 2009), and real values from industrial-scale production. The CCD quadratic model of variables in the form of coded and actual values is given in Table 1. The value of α for this CCD was fixed at 2. The design was represented by a second-order polynomial regression model to generate contour plots,
(3)
where Y, xi, β0, βi, βii, βij, and ε are the biogas yield, process factors, offset coefficient, linear coefficients, quadratic coefficients, interaction coefficients, and residuals associated with the experiments, respectively.
The regression analysis of the experimental data was performed in Design-Expert software version 8.0 to determine the coefficients of the regression equation and estimate the response surface.
Table 1. Actual Alkali-Pretreatment Conditions and the Corresponding Encoding Levels of Central Composite Design
Analytical Method
TS and VS were measured by the weight loss method (Standard Methods for the Examination of Water & Wastewater 2005). The composition of hemicellulose, cellulose, and lignin were measured using the NREL method (Sluiter et al. 2008). The pH was measured with a pH meter (Mettler TOLEDO 6219, Mettler Toledo International Co., Ltd. Switzerland).
Biogas composition was measured using a gas chromatograph (SP-6890, Shandong southern shandong rainbow chemical equipment co., Ltd. China). The operational conditions for chromatography were the same as in Pei et al. (2014).
RESULTS AND DISCUSSION
NaOH Pretreatment Effect
pH variation of samples during the NaOH pretreatment
The pH values of the samples were measured during the NaOH pretreatment and are shown in Fig. 3. For all samples, the pH values actually declined with pretreatment time (Fig. 3a), likely due to the consumption of OH– (Chandra et al. 2012; Zheng et al. 2009). Furthermore, decreasing fiber length increased the speed of the pH decline under the same concentration of NaOH (Fig. 3b). For example, the pH value decreased faster for sample with shorter fiber length as seen for 3% and 6% NaOH respectively. The faster decline was probably due to better surface accessibility of the smaller fibers to the aqueous alkali solution. Results also suggested that the pH variation would lessen during the pretreatment with increasing concentration of NaOH (Fig. 3b). In samples pretreated with high doses of NaOH, the amount of OH– consumed during the pretreatment was too small to cause a significant pH variation.
During the NaOH pretreatment, the pH values of the samples declined for 2 to 3 days. For example, pH of samples treated by 3% NaOH declined to 7.0, and pH of samples treated by 6%, 9%, and 12% NaOH declined to 8.3 to 9.5. Although the pH variation could indirectly reflect the alkali treatment process (Chandra et al. 2012; Zheng et al. 2009), the optimum pretreatment conditions should be determined according to the biogas fermentation results.
Fig. 3. pH variation of samples during the NaOH pretreatment (a: pH variation of pretreated samples with various concentrations of NaOH; b: pH variation of samples with various fiber lengths under 3% and 6% NaOH)
NaOH pretreatment did not influence the pH of the fermentation system
The pH variations for the fermentation system before and after anaerobic digestion were also measured. Alkali-pretreated samples were directly used for biogas fermentation without further treatment. The initial pH of the fermentation systems was in the range of 7.0 to 8.5 because of the buffer capacity (2500 mg CaCO3/L) of the system. After fermentation, the final pH values remained in the range of 7.5 to 8.5. No sudden cease of daily gas production was observed for any of the pretreatment conditions (Fig. 4), which indicated that the fermentation system did not become acidified when pretreated samples for biogas fermentation were used without neutralization. This result could be attributed to the buffering capacity of the fermentation media and the relatively low substrate concentration (TS = 6%), which prevented the introduction of excess Na+ and OH–. Thus the alkali-pretreatment did not affect the pH stability of the overall fermentation process.
Fig. 4. Daily biogas production for representative samples
Pretreatment enhanced the degradation aspect of the fermentation process
The effect of alkali-pretreatment on anaerobic digestion was investigated. Results showed that alkali-pretreatment increased the degradation aspect of the fermentation process. After NaOH treatment, the TS and VS degradation increased from 13.3 ± 0.4% and 22.0 ± 0.3% to 16.7% and 32.9% (on average), respectively. The highest TS and VS degradation, 19.6 ± 0.6% and 47.3 ± 0.1%, was obtained with 6% NaOH, 0.2 cm fiber length, 40 °C and 3 days. Pretreatment enhanced the downstream fermentation process.
Modeling of Biogas Production
To optimize the pretreatment conditions, four variables (concentration of NaOH, time, temperature, and fiber length) were selected for testing by using the RSM. Table 2 lists the experimental conditions and the final biogas yield. From these data, the following polynomial equation was obtained using multiple regression analysis and was employed to factor in the role of each variable and their second-order interactions on the biogas yield generating the predicted values in the last column. The equation for the model as a function of the coded factors is given below:
(4)
ANOVA was used to determine the “goodness of fit” of the quadratic model. In this study, p-values less than 0.05 indicated that the corresponding coefficient terms were significant. The results of the simplified regression model after removing the insignificant factors are shown in Table 3.
The F value of the quadratic model was 18.77, which indicated that the developed quadratic model was highly significant (p < 0.0001). The regression model fitted the experimental data and could be used to appropriately explain the effects of the selected variables on biogas yield. There was a 11.50% chance that an F-value for “lack of fit” could occur due to noise. The fitness of the model was also confirmed by the regression correlation coefficient R2 value at 0.79. In this study, the adequate precision value was 18.49, which indicated an adequate signal. A low value for the coefficient of variation (CV = 8.97%) indicated that the experiments were precise and reliable. In short, the insignificant effect of lack of fit, the closeness of the R2 value to 1, the adequate precision greater than 4 and the lower CV value all indicated that the developed model was suitable and appropriate to used for predicting the final yield.
Table 2. Design and Experiment Results of CCD
Statistical analysis showed that alkali concentration (P < 0.0001) had a significant positive linear effect and a negative quadratic effect (P = 0.0001) on the biogas yield. Fiber length (P < 0.05) had a significant negative linear effect. Additionally, pretreatment time (P = 0.0071) had significant negative quadratic effects.
The most impactful factor was alkali concentration (F = 41.57), followed by fiber length (F = 9.44). The linear effect of pretreatment time and temperature, the quadratic effect of fiber length and temperature were insignificant. The interaction between each two variables was observed to be insignificant. The simplified second-order polynomial regression model after removing the insignificant factors is given below:
(5)
The coefficient estimates and P‑values of the simplified model were also presented in Table 3.
Table 3. ANOVA Analysis for the Fitted Quadratic Model and Simplified Modela
a R2 = 0.7964; adjusted R2 = 0.7540; predicted R2 = 0.5294; adequate precision = 18.496; CV% = 8.97.
b degree of freedom.
RSM analysis
The effects of the four variables on biogas yield were analyzed in detail using contour plots. Figure 5 represented the effects of two independent variables on the yield while the other two variables were held constant at the central point. In Fig. 5a, the pretreatment temperature and fiber length of BPSF were fixed at the center. Figure 5a showed that biogas yield increased with increasing alkali concentration from 0% to 7% when the pretreatment time was held at a constant level (3 days). However, further increasing the alkali concentration caused a slight decline in the biogas yield. A similar trend was observed in Fig. 5b when the temperature was held at a constant level (40 ºC). According to Fig. 5c, the biogas yield increased for all fiber lengths when alkali concentration increased from 3.0% to 9.0%. Also, according to the modeling results, alkali concentration was a significant factor (P < 0.0001) for biogas yield (Table 3). Generally, alkali concentration significantly affects the biogas yield of lignocellulosic materials (Salehian et al. 2013; Zhu et al. 2010). In this study, the highest biogas yield (522.7 mL· g-1VSadded) was obtained when the NaOH concentration was 6% (w/w).
There are many reasons for the enhancement of alkali-pretreatment. Alkali-pretreatment opened the bonds between cellulose, hemicelluloses, and lignin, thus weakening the complex lignocellulosic structure allowing easier access (Zuluaga et al. 2009). Pretreatment most likely dissolved a portion of the lignin and hemicellulose components, producing a soluble substance and allowing more access for the hydrolysis process (Triolo et al. 2011; Zuluaga et al. 2009). The substrate porosity for pretreated material increased after alkali-pretreatment, which could improve contact between substrate and microorganism, and thus facilitated the hydrolysis, which is the first phase of biogas fermentation (Mosier et al. 2005; Sindhu et al. 2014; Yao et al. 2013). On the contrary, a higher concentration of alkali might result in a decline in biogas yield (Ward et al. 2008). Concentrations of NaOH investigated in this paper include 0%, 3%, 6%, 9% and 12%. Without considering the effects of the other pretreatment factors, the average biogas yield obtained was 220.4, 302.5, 409.1, 401.6, and 348.9 mL·g-1VSadded, respectively. This suggested that the biogas yield would not be significantly decreased with NaOH concentrations between 6% and 9%. However, the biogas yield for 12% NaOH was 348 mL·g-1VSadded (Table 2), which was 33.4% lower than the highest sample. The negative effect of higher alkali concentration on lignocellulosic material may result from a more alkaline pH range of the fermentation system. Also extra Na+ ions were introduced into the fermentation system, along with the possible production of toxic compounds. In this study, pretreated samples were directly used for fermentation without rinsing. However, the pH values for all tests were between 7.0 and 8.5 because of the buffering capacity of the fermentation system, which should not cause a decline in biogas yield. In addition, the pH remained stable in the appropriate range for anaerobic digestion. Extra induction of Na+ would inhibit the activity of anaerobic microbes and thus cause a decline in biogas yield. The specific inhibitory concentration of Na+ for microbes would be affected by the different types of sludge, salts and nutrients in the medium (Feijoo et al. 1995). Usually, the inhibitory concentration of Na+ was between 3 and 16 g·L-1 (Feijoo et al. 1995). In this study, the highest Na+ concentration of the fermentation system was only 1.8 g·L-1, including the Na+ from NaHCO3 loading (2.5 g·L-1NaHCO3, Na+, 0.68 g·L-1) and alkali pretreatment (12% of NaOH, Na+, 1.14 g·L-1). This concentration was relatively low and had no obvious negative effect on biogas production process. Therefore, the reason for the decline in biogas yield under high alkali concentrations may be the generation of toxic substances (Lagerkvist and Morgan-Sagastume 2012). Further experiments need to be conducted to determine the influence of the formation of toxic substances on the biogas yield.
Fiber length was the other significant factor for biogas yield (P < 0.05). Figure 5d shows that the biogas yield continuously increased with decreasing fiber length when pretreatment time ranged from 2 to 4 days. A similar trend was observed in Fig. 5e with pretreatment temperatures ranging from 35 to 45 ºC. Shorter fiber lengths resulted in larger contact areas between fiber and aqueous alkali, higher treatment efficiency, and higher biogas yield.
The biogas yield was not significantly affected by pretreatment time (P > 0.05). Figure 5f shows that the biogas yield increased only slightly with increasing pretreatment time. However, increasing the pretreatment time past 3 days caused a slight decline in the biogas yield. It was previously reported that 3 days is sufficient for wet-state pretreatment to guarantee the complete chemical reaction between the substrates and NaOH (Chandra et al. 2012; Zheng et al. 2009). However, further increasing the pretreatment time might result in a decline in biogas yield, which may result from the production of toxic substances (Lagerkvist and Morgan-Sagastume 2012).
Fig. 5. Contour plots for the effects of two variables on the biogas production, holding the other two variables constant
Pretreatment temperature (35 to 50 ºC) had an insignificant effect on biogas yield in this experiment (P > 0.05), which was in agreement with the results of previous reports (Salehian et al. 2013). It had been reported that the difference in biogas yield for NaOH-pretreated fibers at temperatures between 0 ºC and 100 ºC is negligible. In the subtropical and tropical zones, the temperature is usually around 30 ºC to 35 ºC or even higher during the harvest season of banana. Therefore, for the industrial scale production, the alkali-pretreatment could be conducted in ambient temperature without heating, which could reduce the energy consumption for the pretreatment.
Anaerobic Fermentation under Optimized Pretreatment Conditions
Using Eq. 5, the model predicted a maximum biogas yield of 472.1 mL·g-1VSadded under the optimum parameters of NaOH concentration at 7.8%, pretreatment for 3 days, temperature of 48 ºC, and fiber length of 0.2 cm. To confirm the result predicted from the model, repeated BPSF biogas fermentation experiments under the optimum pretreatment conditions were conducted (Fig. 6a). The biogas yield under the optimum pretreatment condition was 463.0 mL·g-1VSadded, similar to the predicted value, and was 89.2% higher than that from the control, untreated sample. It should be pointed out that the biogas yield (522.7 mL·g-1VSadded) obtained (6% NaOH, 3 days, 40 °C and 0.2 cm, Table 2) was unusually high, which could be attributed to the experimental variation. In the early stage of anaerobic digestion, the biogas production for the pretreated sample was much faster than the control. This increased rate was likely caused by the digestion of easily digestible molecules in the pretreated BPSF. This result agreed with existing studies on the alkali-pretreatment of lignocellulose materials (Chandra et al. 2012; Taherdanak and Zilouei 2014).
In addition, the gaseous components were measured in the biogas fermentation process (Fig. 6b). The methane content for the alkali-pretreated sample remained stable between 55.5% and 63.9% after fermenting for 3 to 4 days which was slightly higher than that of the control (50.9% -56.23%).
Fig. 6. Biogas yield and methane content of BPSF under optimized pretreatment condition. (a)The biogas yield of pretreated and unpretreated samples; (b)The methane content of pretreated and unpretreated samples
NaOH pretreatment can improve the biodegradability and biogas yield of biomass material (Raposo et al. 2006; Salehian et al. 2013; Ward et al. 2008; Zhu et al. 2010). Studies have shown that pretreatment of lignocellulosic substrates, such as corn stover and rice straw, with NaOH increased biogas production by 32% to 87.5% (Chandra et al. 2012; Zheng et al. 2009). In this paper, the highest biogas yield for the optimal pretreatment condition was 89.2% higher than that from the control. This result was higher than previous reports on biogas production from BPS (Kalia et al. 2000; Ou et al. 2006). Compared with other existing reports on the alkali-pretreatment of biomass materials, the biogas yield discussed in this paper was relatively high (Chandra et al. 2012; Zheng et al. 2009).
BPS has much potential to be a biomass material for biogas production. Further efforts still need be made to improve the availability of BPS for industrial application after reducing the transportation cost. Extract BPSF for pulping and using the residues for biogas production could be another choice (Fig. 1). Data obtained from this paper provided a better understanding of the biogas yield and pretreatment of BPSF. These data can be used along with data on pulping to determine the best utilization of BPSF. Further work still needs to be done to optimize the technological route of BPS for industrial applications.
CONCLUSIONS
- Banana pseudo-stem fiber (BPSF) could be considered as a potential substrate for the biogas production for its favorable biogas fermentation performance. NaOH pretreatment was successfully used to increase the biogas yield of BPSF to 463.0 mL· g-1VSadded, which was 89.2% higher than that of the control.
- Among the pretreatment factors within the test ranges in this paper, only NaOH concentration and fiber length had significant effect on the biogas yield. Based on the climate condition of subtropical and tropical zones, and consideration of industrial application, ambient temperature and 3 days are recommended for the NaOH pretreatment.
ACKNOWLEDGMENTS
This research was funded by the Ministry of Science and Technology of China, National Key Technologies R&D Program (Grant No. 2012BAC18B01), Science and Technology Program for Public Wellbeing (Grant No. 2013GS460202-3) and the International S&T Cooperation Program (Grant No.2010DFB64040). We would like to thank Ruitao Zha for his analytical and technical help.
REFERENCES CITED
Bardiya, N., Somayaji, D., and Khanna, S. (1996). “Biomethanation of banana peel and pineapple waste,” Bioresource Technology 58(1), 73-76.
Binod, P., Sindhu, R., Singhania, R. R., Vikram, S., Devi, L., Nagalakshmi, S., and Pandey, A. (2010). “Bioethanol production from rice straw: An overview,” Bioresource Technology 101(13), 4767-4774.
Clarke, W. P., Radnidge, P., Lai, T. E., Jensen, P. D., and Hardin, M. T. (2008). “Digestion of waste bananas to generate energy in Australia,” Waste Management 28(3), 527-533.
Chandra, R., Takeuchi, H., and Hasegawa, T. (2012a). “Hydrothermal pretreatment of rice straw biomass: A potential and promising method for enhanced methane production,” Applied Energy 94, 129-140.
Chandra, R., Takeuchi, H., Hasegawa, T., and Kumar, R. (2012b). “Improving biodegradability and biogas production of wheat straw substrates using sodium hydroxide and hydrothermal pretreatments,” Energy 43(1), 273-282.
Chen, H., Zhou, J., and Qi, Y. (2000). “Biogas fermentation of parenchyma cell from nonwood plant fiber,” China Biogas 19(3), 15-19.
Daud, W. R. W., and Law, K. N. (2010). “Oil palm fibers as papermaking material: Potentials and challenges,” BioResources 6(1), 901-917.
Feijoo, G., Soto, M., Mendez, R., and Lema, J. M. (1995). “Sodium inhibition in the anaerobic digestion process: Antagonism and adaptation phenomena,” Enzyme and Microbial Technology 17(2), 180-188.
Frigon, J. C., Mehta, P., and Guiot, S. R. (2012). “Impact of mechanical, chemical and enzymatic pre-treatments on the methane yield from the anaerobic digestion of switchgrass,” Biomass and Bioenergy36, 1-11.
Getha, K., and Vikineswary, S. (2002). “Antagonistic effects of Streptomyces violaceusniger strain G10 on Fusarium oxysporum f. sp. cubense race 4: Indirect evidence for the role of antibiosis in the antagonistic process,” Journal of Industrial Microbiology and Biotechnology 28(6), 303-310.
Gunaseelan, V. N. (2007). “Regression models of ultimate methane yields of fruits and vegetable solid wastes, sorghum and napiergrass on chemical composition,” Bioresource Technology 98(6), 1270-1277.
Kalia, V. C., Sonakya, V., and Raizada, N. (2000). “Anaerobic digestion of banana stem waste,” Bioresource Technology 73(2), 191-193.
Lagerkvist, A., and Morgan-Sagastume, F. (2012). “The effects of substrate pre-treatment on anaerobic digestion systems: A review,” Waste Management 32(9), 1634-1650.
Li, L., Yang, X., Li, X., Zheng, M., Chen, J., and Zhang, Z. (2010). “The influence of inoculum sources on anaerobic biogasification of NaOH-treated corn stover,” Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 33(2), 138-144.
Liu, H., Li, N., Fu, S., and Chen, S. (2013). “Integrated pulping and biorefining of palm residues based on semichemical cooking and fiber fractionation,” Bioresource Technology 136, 230-236.
Mosier, N., Wyman, C., Dale, B., Elander, R., Lee, Y. Y., Holtzapple, M., and Ladisch, M. (2005). “Features of promising technologies for pretreatment of lignocellulosic biomass,” Bioresource Technology 96(6), 673-686.
Ou, Z., Zhang, J., and Deng, G. (2006). “Biogas production test for banana stem,” China Tropical Agriculture 5, 35-36.
Padam, B. S., Tin, H. S., Chye, F. Y., and Abdullah, M. I. (2012). “Banana by-products: An under-utilized renewable food biomass with great potential,” Journal of Food Science and Technology , 1-19.
Pei, P., Zhang, C., and Li, J. (2014). “The influence of physical treatment on biogas production potential of BPS,” Food and Fermentation Industries 40(1), 8-13.
Quintero, M., Castro, L., Ortiz, C., Guzmán, C., and Escalante, H. (2012). “Enhancement of starting up anaerobic digestion of lignocellulosic substrate: Fique’s bagasse as an example,” Bioresource Technology 108, 8-13.
Raposo, F., Banks, C. J., Siegert, I., Heaven, S., and Borja, R. (2006). “Influence of inoculum to substrate ratio on the biochemical methane potential of maize in batch tests,” Process Biochemistry41(6), 1444-1450.
Salehian, P., Karimi, K., Zilouei, H., and Jeihanipour, A. (2013). “Improvement of biogas production from pine wood by alkali pretreatment,” Fuel 106, 484-489.
Sambusiti, C., Monlau, F., Ficara, E., Carrère, H., and Malpei, F. (2013). “A comparison of different pre-treatments to increase methane production from two agricultural substrates,” Applied Energy 104, 62-70.
Sindhu, R., Kuttiraja, M., Binod, P., Sukumaran, R. K., and Pandey, A. (2014). “Physicochemical characterization of alkali pretreated sugarcane tops and optimization of enzymatic saccharification using response surface methodology,” Renewable Energy 62, 362-368.
Sluiter, A., Hames, B., Ruiz, R., Scarlata, C., Sluiter, J., Templeton, D., and Crocker, D. (2008). “Determination of structural carbohydrates and lignin in biomass,” Laboratory Analytical Procedure, National Renewable Energy Laboratory.
Taherdanak, M., and Zilouei, H. (2014). “Improving biogas production from wheat plant using alkaline pretreatment,” Fuel 115, 714-719.
Tian, M., Liu, X., Li, S., Liu, J., and Zhao, Y. (2013). “Biogas production characteristics of solid-state anaerobic co-digestion of banana stalks and manure,” Transactions of the Chinese Society of Agricultural Engineering 29(7), 177-184.
Tock, J. Y., Lai, C. L., Lee, K. T., Tan, K. T., and Bhatia, S. (2010). “Banana biomass as potential renewable energy resource: A Malaysian case study,” Renewable and Sustainable Energy Reviews14(2), 798-805.
Triolo, J. M., Sommer, S. G., Møller, H. B., Weisbjerg, M. R., and Jiang, X. Y. (2011). “A new algorithm to characterize biodegradability of biomass during anaerobic digestion: Influence of lignin concentration on methane production potential,” Bioresource Technology 102(20), 9395-9402.
Wang, J., Yue, Z. B., Chen, T. H., Peng, S. C., Yu, H. Q., and Chen, H. Z. (2010). “Anaerobic digestibility and fiber composition of bulrush in response to steam explosion,” Bioresource Technology101(17), 6610-6614.
Ward, A. J., Hobbs, P. J., Holliman, P. J., and Jones, D. L. (2008). “Optimisation of the anaerobic digestion of agricultural resources,” Bioresource Technology 99(17), 7928-7940.
Wei, Y., and Zhou, L. (2001). “Test in feeding milking cattle with banana leaf and stem,” Journal of Guangxi Agriculture and Biological Science 1(20), 34-36.
Xiao, R. F., Zhu, Y. J., Li, Y. D., and Liu, B. (2013). “Studies on vascular infection of Fusarium oxysporum f.sp. cubense race 4 in banana by field survey and green fluorescent protenin reporter,” ESci Journal of Plant Pathology 2(1), 44-51.
Yao, Y., He, M., Ren, Y., Ma, L., Luo, Y., Sheng, H., and An, L. (2013). “Anaerobic digestion of poplar processing residues for methane production after alkaline treatment,” Bioresource Technology134, 347-352.
Zhang, Q., Tang, L., Zhang, J., Mao, Z., and Jiang, L. (2011). “Optimization of thermal-dilute sulfuric acid pretreatment for enhancement of methane production from cassava residues,” Bioresource Technology 102(4), 3958-3965.
Zhang, C., Li, J., Liu, C., Liu, X., Wang, J., Li, S., and Zhang, L. (2013). “Alkaline pretreatment for enhancement of biogas production from banana stem and swine manure by anaerobic codigestion,” Bioresource Technology 149, 353-358.
Zheng, M., Li, X., Li, L., Yang, X., and He, Y. (2009). “Enhancing anaerobic biogasification of corn stover through wet state NaOH pretreatment,” Bioresource Technology 100(21), 5140-5145.
Zhu, J., Wan, C., and Li, Y. (2010). “Enhanced solid-state anaerobic digestion of corn stover by alkaline pretreatment,” Bioresource Technology 101(19), 7523-7528.
Zuluaga, R., Putaux, J. L., Cruz, J., Vélez, J., Mondragon, I., and Gañán, P. (2009). “Cellulose microfibrils from banana rachis: Effect of alkaline treatments on structural and morphological features,” Carbohydrate Polymers 76(1), 51-59.
Article submitted: April 8, 2014; Peer review completed: June 1, 2014; Revised version received: June 15, 2014; Accepted: June 18, 2014; Published: July 10, 2014.