Batch fermentative hydrogen production utilising sago (Metroxylon sp.) starch processing effluent by enriched sago sludge consortia

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Batch fermentative hydrogen production utilising sago (Metroxylon sp.) starch processing effluent by enriched sago sludge consortia Nurleyna Yunus a, Jamaliah Md Jahim b,c,*, Nurina Anuar b, Siti Rozaimah S. Abdullah b, Norhisham T. Kofli b a

Downstream Technology Division, CRAUN Research Sdn Bhd, 93055 Kuching, Sarawak, Malaysia Department of Chemical and Process Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 Bangi, Malaysia c Fuel Cell Institute, Universiti Kebangsaan Malaysia, 43600 Bangi, Malaysia b

article info

abstract

Article history:

Sago starch processing effluent (SSPE) is an ideal bio-resource that can be utilised as a

Received 11 August 2014

substrate for fermentative reactions due to its relatively high organic content. Annually in

Received in revised form

Malaysia, about 2.5 million tonnes of effluent are generated from the processing of sago

1 October 2014

starch. In this study, the potential use of SSPE as a substrate for fermentative hydrogen

Accepted 3 October 2014

production was confirmed under all the experimental conditions studied. The maximum

Available online 29 October 2014

hydrogen production and volumetric hydrogen production rate were 575 mL H2/L SSPE and

Keywords:

concentration of 11 g soluble carbohydrate/L SSPE. The final soluble metabolites were

Anaerobic fermentation

comprised mainly of acetate (24e43%), butyrate (4e20%), propionate (1e7%) and ethanol

Biohydrogen production

(44e66%), suggesting an acetic acid-ethanol type fermentation pathway.

Sago starch processing effluent

Copyright © 2014, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights

57.54 mL H2/hr.L SSPE, respectively, from cultures with an initial pH of 7 and substrate

Initial pH

reserved.

Initial substrate concentration

Introduction The sago palm (Metroxylon spp.) is an important food security crop in tropical Asia. Sago starch, which accumulates in the stem of the palm, is an important food resource and industrial raw material used throughout the world. Malaysia, is the largest exporter of sago starch to the world with an annual production of approximately 51,000 tonnes of dry starch. The sago starch processing effluent (SSPE), generated by this

industry, is a carbohydrate-rich liquid waste comprised mainly of macromolecules in the form of polysaccharides (starch and hemicelluloses). However, improper management of these wastes have resulted in vigorous research to solve the current predicament facing Malaysian sago industry. Past findings have shown the potential of SSPE as a substrate for the development of value-added products such as algae cultivation [1] and biomethane generation via anaerobic fermentation [2].

* Corresponding author. Department of Chemical and Process Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 Bangi, Malaysia. Tel.: þ60 3 8921 6427; fax: þ60 3 8921 6148. E-mail address: [email protected] (J.M. Jahim). http://dx.doi.org/10.1016/j.ijhydene.2014.10.015 0360-3199/Copyright © 2014, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

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An alternative prospect is to utilize the effluent as a substrate for fermentative hydrogen production; this was the purpose of this study. However, to effectively make use of this waste as a substrate for fermentation reactions, the effluent needs to be pre-treated by either acid or enzymatic hydrolysis to cleave the polysaccharides into simple sugar form. According to a review by Kapdan and Kargi [3], simple sugars such as glucose, sucrose and xylose are readily digestible and are the preferred substrates for hydrogen production. This is because bacterial metabolism of macromolecules (such as polysaccharides) differs from those of smaller molecular weight compounds (e.g. monosaccharides) as a consequence of physical and biological factors. Typically, compounds with molecular weights in excess of 1000 atomic mass units need to be hydrolysed into smaller polymers before they can be transported across the bacterial cell wall and used for energy production [4]. It has been claimed that Clostridia sp. has the ability to directly digest polysaccharides (starch particles) for biohydrogen production [5]. However, the process of digestion and rate of biohydrogen production is impeded due to the slow starch hydrolysis process [6]. To eliminate the ratelimiting starch hydrolysis step, Chen et al. [7] attempted to hydrolyse starch with amylase prior to utilising it as an energy source for biohydrogen production via dark fermentation. ~ o and Babel [8] were able to improve bioMeanwhile, Lean hydrogen production from cassava wastewater by pretreating the wastewater with commercial enzymes to increase the simple sugar concentration in the substrate. The production of biohydrogen from starch-containing synthetic wastewater has been reported extensively in the past [8e10]. However, studies on biohydrogen production from real starch processing wastewater using mixed cultures are limited, and most of these studies used cassava/tapioca wastewater [11e15]. No studies have documented the use of real sago starch processing wastewater/effluent for this purpose. The purpose of this study was to ascertain the feasibility of utilising SSPE as a substrate for fermentative hydrogen production through a series of batch assays. This was achieved by an initial attempt to increase the soluble carbohydrate concentration in the SSPE through in situ enzymatic treatment utilising a-amylase and g-amylase. Following to this, an investigation was conducted to study the effects of the initial substrate concentration and cultivation pH (over a pertinent range) on the hydrogen production potential seeded with heat-treated sago sludge inocula. The kinetics of hydrogen production were analysed using the modified Gompertz equation.

conditions in accordance with the traditional extraction method normally carried out by sago farmers in Sarawak. Sago logs, obtained from the Paya Paloh Sago Research Station in Kota Samarahan, Sarawak, Malaysia, were manually debarked and the pith was chopped into smaller pieces, bagged and stored frozen. When required, the chopped pith was thawed to room temperature and liquefied in a heavy duty blender with tap water, then filtered through muslin cloth followed by settling of the starch particles. The supernatant was then drawn off for another round of filtration and settling. This process was repeated three times. The final supernatant was then collected, kept in capped bottles and stored at 4  C to be used within 3 days. In order to obtain similar COD/soluble carbohydrate concentrations as effluents from a sago mill, a standard 1:4 ratio of pith to water was applied. Characterisation on the basic properties of SSPE was performed for SSPE sampled from a sago mill and from those prepared under laboratory conditions to compare the variability.

SSPE pre-treatment with a-amylase and g-amylase In order to naturally increase the soluble carbohydrate composition in SSPE, comparisons were made by pre-treating with a-amylase (Termamyl 120 L, Novo Nordisk, Denmark, with declared enzyme activity of 120 KNU/g) alone, and with a cocktail of a-amylase and g-amylase (AMG 300 L, Novo Nordisk, Denmark, with declared enzyme activity of 300 AGU/mL) at equal concentrations ranging from 0.2% to 1% (equivalent to 26.4e144 KNU/g and 60e300 AGU/mL for a-amylase and gamylase, respectively). Upon addition of the enzyme, the SSPE solution was stirred until it was homogeneous and its pH was adjusted to 6.0 with 1 M NaOH or 1 M HCl. The solution was then left to incubate at room temperature for 10 min. Additionally, further trials were also conducted to study the effect of increasing, in equal treatment concentrations, the enzyme cocktail of a-amylase and g-amylase ranging from 0.2% to 5% (equivalent to 26.4e739 KNU/g and 60e1500 AGU/ mL for a-amylase and g-amylase, respectively). The tested range of enzyme treatment concentration were aimed to sufficiently increase the soluble carbohydrate concentrations in the SSPE for a subsequent anaerobic fermentative reaction. Sampling was performed from each treatment for soluble carbohydrate analysis. To ascertain the storage stability of the SSPE after enzyme treatment, the mixtures were refrigerated at 4  C for 48 h and sampled every 24 h to determine the soluble carbohydrate concentration.

Hydrogen producing seed

Materials and methods SSPE preparation and pre-treatment SSPE is easily fermented during storage as a result of its carbohydrate content. For this reason, in addition to standardising the soluble carbohydrate concentration, all SSPE used throughout this study were processed under laboratory

Sago sludge consortia (sampled from the waste drain of a sago mill) that have been previously heat-treated in oven at 100  C for 1 h were used as inoculum source. The consortia were first adapted to an SSPE-based substrate. Preliminary analyses suggested that SSPE lacks the necessary nutrients for the growth of anaerobic microorganisms, specifically in terms of N, P and micronutrients (Table 1). Therefore, the Endo nutrient solution (adapted from the formulation by Endo et al. [16] as described by Lin and Lay [17]) was employed in this study to

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Table 1 e Comparison between sago starch processing effluents sampled from a sago mill and processed under laboratory conditions. Parameter

pH Total COD Soluble COD TS TSS VSS TKN Soluble carbohydrate Trace elements

mg/L

P K Cu Zn Ca Mg Mn Fe Na Ni Cr Al B

Mill

Lab

4.7 ± 0.3 12,409 ± 262 9530 ± 198 6542 ± 157 1516 ± 221 2340 ± 257 124 ± 6 683 ± 32 ND 331 ± 7.9 0.46 ± 0.01 0.83 ± 0.07 143 ± 6.2 58 ± 4.1 4 ± 0.12 1 ± 0.08 48 ± 0.89 0.09 ± 0.01 ND 1 ± 0.2 ND

4.2 ± 0.1 10,642 ± 157 8013 ± 112 6047 ± 109 1339 ± 197 1998 ± 91 114 ± 8 557 ± 13 ND 207 ± 3.8 0.37 ± 0.06 1 ± 0.01 119 ± 3.4 31 ± 2.2 5.4 ± 1.5 3 ± 0.57 55 ± 2.3 ND ND ND ND

provide sufficient nutrients to the SSPE for anaerobic bacterial growth. The Endo nutrient formulation has been widely used by researchers for fermentative biohydrogen production seeded with mixed microflora utilising synthetic and real waste materials/wastewater as the substrate [11,17,18]. The substrate was made up of enzyme-treated SSPE with an approximate concentration of 5 g/L soluble carbohydrate and supplemented with the Endo nutrient solution containing 5240 mg/L NH4HCO3, 125 mg/L K2HPO4, 15 mg/L MgCl2$6H2O, 25 mg/L FeSO4$7H2O, 5 mg/L CuSO4$5H2O, 0.125 mg/L CoCl2$5H2O and 6720 mg/L NaHCO3. Cultivation was conducted in 60 mL serum bottles with a 50 mL working volume at a 10% inoculant concentration. The incubation temperature was set at 37  C with a stirring rate of 100 RPM. Two successive transfers of 48 h cultures as the inoculum (10%) to a fresh substrate were made to obtain a stable hydrogen producing microbial consortium. The developed cultures were then used as hydrogen-producing seed stock in the following batch experiments.

Batch fermentative hydrogen production using SSPE as the substrate Experimental design Batch experiments were carried out to investigate the hydrogen production potential of SSPE as the main substrate component. However, due to the diverse organic components present in SSPE, it would be difficult to standardise the type of substrate used as the energy source for fermentation reactions. Therefore, throughout this study, the concentration of substrate for fermentation is generally identified by its soluble carbohydrate concentration. A fractional factorial central composite design and response surface methodology (RSM) [19] were employed to

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evaluate the effects of the independent variables (i.e. initial pH and substrate concentration) as well as any interaction between these two variables on the response variables. The hydrogen production rate (HPR) and hydrogen yield (HY) were defined as the response variables. The use of this experimental design had been similarly employed in the past [20e22] to study the effects of independent variables such as the initial pH and substrate concentration on biohydrogen production utilising substrates from various waste and wastewater sources. A thirteen trial design matrix was constructed to cover the two independent variables, each at five levels. All trials were done in triplicate to ensure the reproducibility of the results. The substrate concentrations, expressed in terms of soluble carbohydrate (SC), were varied from 3 to 11 g SC/L, with a central value of 7 g SC/L. The initial cultivation pH varied from 6.0 to 8.0 with a central value of 7.0.

Experimental apparatus and procedure The experiments were conducted in a series of 60 mL serum bottles with a 50 mL working volume. The substrate was made up of enzyme-treated SSPE and the Endo nutrient solution (as described in Section Hydrogen producing seed). A 10% inoculum concentration was employed throughout this study. Upon inoculation, the pH in each serum bottle was adjusted accordingly with 1 M NaOH or HCl. The bottles were then purged with nitrogen gas for 3 min (to create anaerobic conditions) and capped with a rubber septum. A hypodermic syringe (Terumo, Japan) was fitted to equilibrate the pressure inside each bottle to ambient pressure during the gas production phase. The cultures were then placed in a dark incubator shaker at 37  C and 100 RPM. During the course of the experiment, biogas samples were collected routinely for biogas composition analysis. Liquid samples from each serum bottle were drawn at the end of the trial and analysed for primary volatile fatty acids and related solvents, soluble carbohydrate and pH.

Analytical methods Biogas production was measured periodically throughout the duration of the experiments by logging the volume indicated on the fitted syringes. The biogas was also sampled from the headspace with a 500 mL gas-tight syringe (Hamilton, USA) and analysed for the gas composition using a gas chromatograph (GC; Hewlett Packard 5890) equipped with a thermal conductivity detector (TCD). The GC was fitted in series with a stainless steel molecular sieve column (10 ft 45/60) and Porapak Q packed column (9 ft 80/100). The injector, oven and detector temperatures were set at 90  C, 50  C and 200  C, respectively. Helium was used as the carrier gas with a flow rate of 18.7 mL/min. Primary volatile fatty acids (VFA) and related solvents were analysed using a GC (Hewlett Packard 5890) equipped with a flame ionisation detector (FID). An HP-FFAP column was used (50 m L  0.2 mm ID  0.33 mm film) with helium as the carrier gas. The injector and detector temperature were maintained at 270  C and 200  C, respectively. The total chemical oxygen demand (COD), total solids (TS), total suspended solids (TSS) and volatile suspended solids (VSS), total Kjeldahl nitrogen (TKN) and trace elements concentrations were analysed in accordance with standard

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methods [23]. Meanwhile, the determination of total carbohydrate was performed according to the method developed by Dubois et al. [24], while soluble carbohydrate analysis was carried out using the Nelson-Somogyi method as described by Refs. [25], with D-glucose (Sigma Aldrich, USA) as the standard.

Data analysis Cumulative hydrogen production curves were constructed according to the method described by Van Ginkel [26]. The gas composition in the headspace of the serum bottle and the total volume of the biogas produced at each time interval were measured and applied to the mass balance equation (Eq. (1)):

VH;i ¼ VH;i1 þ CH;i VG;i  VG;i1 þ VH CH;i  CH;i1

(1)

where VH,i and VH,i1 are cumulative hydrogen gas volumes at the current (i) and previous (i1) time interval; VG,i and VG,i1 are the total biogas volumes at the current (i) and previous (i1) time interval; CH,i and CH,i1 are the fraction of hydrogen gas in the headspace of the bottle as determined by gas chromatography in the current and previous interval; and VH is the total volume of headspace in the bottle. Each of the cumulative hydrogen production curves were fitted with the modified Gompertz equation (Eq. (2)) using Sigmaplot Software (Version 11, Systat Software Inc., USA).     Rm  e ðl  tÞ þ 1 H t ¼ Hmax  exp  exp: Hmax

(2)

where H(t) is the cumulative hydrogen production (mL); Hmax is the hydrogen production potential (mL); Rm is the maximum hydrogen production rate (mL H2/hr); l is the duration of the lag phase (h); e is 2.71828 and t is the incubation time (h). Each curve was best fitted using the MarquardteLevenberg algorithm by minimising the sum of square differences between the observed and predicted values of the dependent variable.The response variables (HPR and HY) were calculated from the data, followed by analysis using RSM to enhance the visual understanding of the type of trends that exist for the variables as a function of the experimental treatments. The response variables (HPR and HY) were fitted using a quadratic model to correlate each of the response variables to the independent variables (initial cultivation pH and substrate concentration). The mathematical form of each quadratic equation is as described in Eq. (3): Y ¼ A0 þ A1 X1 þ A2 X2 þ A1;2 X1 X2 þ A1;1 A21 þ A2;2 X22

(3)

where X1, X2 are the actual values of the independent variables, Y is the corresponding response variable, A0 is the constant of the model, A1 and A2 are the linear coefficient, A1,2 is the interactive coefficient and A1,1 and A1,2 are the quadratic coefficients. RSM analyses were performed using DesignExpert software (Version 6, Stat-Ease Inc. USA).

Results and discussion Characterisation of SSPE Comparisons on the characteristics of SSPE were made between those collected from a sago mill and those processed

under laboratory conditions (Table 1). The average percentage of variability obtained between the two sources of SSPE was 25% (for detectable data only). The highest percentage of variability was mainly attributed to trace element concentrations, particularly K, Mg, Mn and Fe, which respectively were well above 30%. Nevertheless, this finding revealed that the quality of the SSPE processed under laboratory conditions is sufficiently comparable with those processed in the mill. The basic properties of SSPE can be generally categorised as acidic with a pH range of 4.2e4.7. The total COD had an approximate range of 10,000 to 12,000 mg/L while the soluble carbohydrate concentration was relatively low at 500e700 mg/ L. This was attributed to the fact that most of the carbohydrate content in the effluent is in the form of starch particles and thin-walled parenchyma fibres/tissues which had penetrated the filter during the filtration process. These are macromolecules which need to be hydrolysed before they can be transported across the anaerobic bacteria cell wall. This hydrolysis step is rate-limiting and will impede the rate of biohydrogen production unless pre-treatment was conducted to facilitate in the breakdown of the carbohydrate components into simple sugar form prior to initiating the fermentation reaction.

Effect of in situ enzymatic treatment of SSPE on its soluble carbohydrate concentration Effect of a-amylase with and without g-amylase combination Comparisons were made in treating the SSPE with a-amylase alone and with a combination of a-amylase with g-amylase at different treatment concentrations (Fig. 1). From the results, the enzyme cocktail was found to be more effective in increasing the soluble carbohydrate concentration by approximately two-fold or higher in comparison to a-amylase alone. This increase could be attributed to the added advantage of g-amylase as it is able to act on available polysaccharides, dextrins and sugars by cleaving a-1, 4- and a-1, 6glycosidic linkages, thereby releasing stepwise from the end of the compound chain. Treatment with a-amylase alone will only hydrolyse the a-1,4 glycosidic linkages in polysaccharides to yield dextrins, oligosaccharides and monosaccharides [8]. Additionally, as the treatment concentration of the enzymes was increased, significant improvements (at a ¼ 0.05) in the soluble carbohydrate concentrations were observed, specifically with the cocktail of a-amylase and g-amylase at a 1% concentration, which achieved about 6000 mg/L soluble carbohydrate compared to about 3000 mg/L achieved by treatment with a-amylase alone.

Effect of the enzyme cocktail (a-amylase and g-amylase) at different treatment concentrations Additional comparisons were made to identify the effect of treating SSPE with a combination of a-amylase and g-amylase at various treatment concentrations from a low of 0.2% to a high of 5% (v/v). The results, as shown in Fig. 2, show that the soluble carbohydrate concentration in SSPE improved significantly (at a ¼ 0.05) with increasing enzyme treatment concentration. An increase from approximately 800 mg/L to 11,000 mg/L soluble carbohydrate was observed when SSPE was treated at the 0.2% and 2% treatment concentrations, respectively. Meanwhile, treatment at 2.5% achieved a

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Fig. 1 e Effect of treatment with and without g-amylase on the soluble carbohydrate concentration in SSPE.

marginal increase to approximately 12,000 mg/L as compared to the results obtained at 2%. A further trial at a high enzyme treatment concentration of 5% showed approximately a twofold increase to 24,000 mg/L in the soluble carbohydrate concentration.

Kinetic analysis of hydrogen production Examples of the cumulative hydrogen production curves obtained from each trial are presented in Fig. 3. Methane gas was not detected in the biogas produced in any of the experiments. Following a lag period that ranged from approximately 5 to 7 h, depending on the initial cultivation pH and substrate

concentration, biohydrogen production started at different rates and to different extent. Cultures with a lower initial cultivation pH (i.e. pH 6.0 and 6.5) were observed to have longer lag phase before gas production began as compared to those with a higher initial cultivation pH (i.e. pH 7.0e8.0). Similar observations have been reported in the past in studies utilising starch as the substrate in dark fermentation [27]. To further analyse the experimental data, the modified Gompertz model was used to fit the cumulative hydrogen production data from each experiment to obtain the parameters of interest, namely Hmax, Rm and l. The average results for all measured and calculated parameters are presented in Table 2. The coefficients of determination (R2) achieved for all

Fig. 2 e Effect of enzymatic (cocktail of amylase and g-amylase) treatment concentrations on the soluble carbohydrate concentration in SSPE.

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Fig. 3 e Cumulative hydrogen production curves reported at 25  C and 1 atm. Each curve represents one of the replicates from each trial run.

the fittings were more than 0.98, indicating that the modified Gompertz model could successfully describe the progress of cumulative hydrogen production in the batch trials in this study. Hydrogen yield (HY) was calculated by normalising Hmax with respect to mL H2 per litre SSPE, converted to H2 molar concentration and further fractionated with the molar concentration of substrate consumed (with the assumption that glucose was the sole carbohydrate present in the SSPE). Meanwhile the parameter Rm was normalised with respect to mL H2 per litre SSPE to attain the calculated values to hydrogen production rate (HPR). The highest hydrogen production (normalised per litre SSPE) recorded was at 575 mL H2/L SSPE with a corresponding

volumetric hydrogen production rate of 57 mL H2/hr.L SSPE attained from the cultures with an initial cultivation pH of 7.0 and a substrate concentration of 11 g SC/L. Meanwhile, cultures with an initial cultivation pH of 6.0 at 3 g SC/L substrate had the lowest hydrogen production at 201 mL H2/L SSPE with a corresponding volumetric hydrogen production rate of 23.6 mL H2/hr L SSSPE. Therefore, this study was able to demonstrate the ability of SSPE to be utilised as a substrate for fermentative biohydrogen production after successful biohydrogen production was achieved within the range of conditions studied. A comparison of biohydrogen production yield and rate achieved in the present study with literature on real starch-

Table 2 e Average values for measured and calculated kinetic parameters. Run

1 2 3 4 5 6 7 8 9 10 11 12 13

Initial pH

Substrate concentration

Modified Gompertz equation parameter values Hmax

Rmax

l

g SC/L SSPE

mL H2

mL H2/h

h

3 7 5 9 3 7 7 11 11 5 11 9 3

18.8 ± 0.3 15.8 ± 0.5 15.6 ± 0.8 19.3 ± 3.2 15.5 ± 2.3 22.7 ± 2.8 17.7 ± 0.5 23.9 ± 0.5 27.9 ± 1.2 18.0 ± 0.7 12.4 ± 0.5 25.1 ± 0.004 10.4 ± 0.5

8 6 6.5 6.5 7 8 7 8 7 7.5 6 7.5 6

SC, soluble carbohydrate.

1.8 ± 1.7 ± 1.8 ± 2.1 ± 1.3 ± 2.1 ± 2.7 ± 2.5 ± 2.8 ± 2.4 ± 1.9 ± 3.3 ± 1.2 ±

0.03 0.07 0.15 0.18 0.01 0.27 0.27 0.07 0.04 0.21 0.24 0.28 0.03

5.2 ± 7.2 ± 7.3 ± 7.3 ± 5.3 ± 5.7 ± 6.7 ± 5.8 ± 6.5 ± 5.8 ± 7.1 ± 6.2 ± 6.7 ±

0.046 0.112 0.049 0.137 0.173 0.365 0.175 0.242 0.069 0.181 0.055 0.153 0.129

HPR

HY

mL H2/h.L SSPE

mol H2/mol glucoseconsumed

R2

0.99 ± 0.002 0.99 ± 0.001 0.99 ± 0.0004 0.99 ± 0.003 0.99 ± 0.005 0.99 ± 0.002 0.99 ± 0.002 0.99 ± 0.002 0.99 ± 0.001 0.98 ± 0.0004 0.99 ± 0.002 0.99 ± 0.0004 0.99 ± 0.007

35.3 33.7 36.7 41.8 27.0 42.5 53.9 49.2 57.0 48.9 37.2 66.1 23.6

± 0.6 ± 1.4 ± 2.9 ± 3.6 ± 0.3 ± 5.4 ± 5.5 ± 1.5 ± 0.8 ± 4.2 ± 4.9 ± 5.5 ± 0.6

1.09 ± 0.39 ± 0.53 ± 0.34 ± 0.83 ± 0.62 ± 0.47 ± 0.39 ± 0.40 ± 0.61 ± 0.53 ± 0.44 ± 0.64 ±

0.03 0.01 0.02 0.07 0.13 0.12 0.01 0.02 0.02 0.04 0.16 0.02 0.01

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based wastewater as substrate is summarized in Table 3. The highest HY achieved in this study is found comparable with the results obtain for cassava starch processing wastewater [11], starch containing textile wastewater [20] and potato processing wastewater [26]. All of which were within the range of 0.94e1.09 mol H2/mol glucose. Meanwhile, data for highest HPR for SSPE at 502.5 mL H2/L SSPE was much lower compared to cassava starch processing wastewater at 1.25 L H2/L [12], starch-containing textile wastewater at 1.14 L H2/L [20], and potato processing wastewater at 2.8 L H2/L [26]. This was mainly attributed by the different loading rate applied in the respective studies.

Response surface analysis Effect of initial cultivation pH and substrate concentration on hydrogen yield (HY) In order to examine the relationship between the initial cultivation pH and substrate concentration on HY, the design matrix with the corresponding calculated results in Table 2 was subjected to stepwise regression and generated the following equation: HY ¼ 1:750:46X1 þ0:045X2 þ0:056X21 þ0:01X22 0:034X1 X2

(4)

where the response HY is in its original units and the X1, X2 are the actual values of the initial cultivation pH and substrate concentration, respectively. The analysis of variance (ANOVA) on the fitting model was considered to be a good representation of the HY data with a pvalue of the F test less than 0.0001, while the regression coefficient (R2) was 0.9780, indicating that the model was able to explain 97.8% of the variability in the response variable. These findings show that Eq. (4) could successfully describe the effect of the initial cultivation pH and substrate concentration on HY in this study.

The ANOVA results also indicated that most of the terms (i.e. the linear effect of the initial cultivation pH and substrate concentration, the quadratic effect of substrate concentration, and the interactive effect between the initial cultivation pH and substrate concentration) were highly significant, achieving p-values less than 0.05, thus suggesting that these terms have a great impact on the HY performance. Furthermore, a significant interaction between the two independent variables suggested that the heat-treated sago consortia favoured different initial cultivation pH levels when they were allowed to grow at different substrate concentrations during fermentative hydrogen production. Following to this, a two-dimensional contour plot was constructed using Eq. (4), as presented in Fig. 4. This plot clearly displays the tendency for HY to increase with increasing initial cultivation pH and decreasing substrate concentration. The highest HY obtained for this study was 1.09 mol H2/mol glucoseconsumed at an initial cultivation pH and substrate concentration of pH 8 and 3 g SC/L, respectively. The hydrogen yield was found to be lower at higher substrate concentrations (between 7 and 11 g SC/L) at all the pH levels tested. This trend is in agreement to a certain extent with those reported by Lay et al. [20] and Ginkel et al. [22]. The reason for this could be attributed to the fact that a higher substrate concentration resulted in a sharp decrease in the fermentation broth pH due to the higher accumulation of volatile fatty acids (VFA), which consequently led to the inhibition of the microorganisms involved in hydrogen production [22].

Effect of initial cultivation pH and substrate concentration on the hydrogen production rate (HPR) Stepwise regression analysis was also conducted for the data on HPR to evaluate its relationship with the initial cultivation pH and substrate concentration. The following quadratic equation was generated:

Table 3 e A comparison on biohydrogen yield and production rate from various starch-based wastewater via dark fermentation. Wastewater (WW) Sago (Cassava) starch processing WW Cassava WW Cassava processing WW Cassava starch processing WW Cassava Stillage Cassava WW Cassava starch manufacturing WW Cassava WW Starch containing textile WW Potato processing WW Sago (Metroxylon sp.) starch processing effluent Sago (Metroxylon sp.) starch processing effluent

Hydrogen yield (HY)a

Organism

Substrate concentration

MC

10.6 g COD/L

0.94 mol H2/mol glucose

e

Sen and Suttar (2012)

MC PC MC MC MC MC

32 g COD/L 5 g COD/L 5 g starch/L 60.1 g VS/L 30 g COD/L 22.6 g COD/L

847.71 mol H2/mol glucose 2.41 mol H2/mol glucose 0.18 mol H2/mol glucose 65.3 mL H2/g VS 3.29 mol H2/mol glucose 0.06 mol H2/mol glucose

e e 1246 mL/L e 524 mL H2/g VSS.d 4.42 mL H2/g VSS. hr

~ o and Babel (2012) Lean Cappelletti et al. (2011) O-Thong et al. (2011) Luo et al. (2010) Sreethawong et al. (2010) Sangyoka et al. (2007)

MC MC MC MC

20 g COD/L 20 g COD/L 21 g COD/L 3 g SC/L

1.20 mol 0.97 mol 1.06 mol 1.09 mol

glucose hexose glucose glucose

940.90 mL H2/g VSS 1.14 L H2/L WW/d 2.8 L H2/L 375 mL H2/L SSPE

Reungsang et al. (2007) Lay et al. (2012) Van Ginkel et al. (2005) This study

MC

9 g SC/L

0.44 mol H2/mol glucose

502.5 mL H2/L SSPE

This study

H2/mol H2/mol H2/mol H2/mol

Hydrogen production rate (HPR)

Reference

MC, mixed culture; PC, pure culture. a The published HY were standardised to mol H2/mol glucose with the assumption that 1 g/L COD ¼ 1.067 g/L glucose and 1 g starch ¼ 10.3 g/L COD [11].

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Fig. 4 e Response surface contour plot for hydrogen yield (HY).

HPR ¼ 569:1 þ 164:3X1 þ 2:45X2  11:2X21

(5)

where the response HPR is in its original units, while X1 and X2 represent the actual values of the initial pH and substrate concentration, respectively. The significance of Eq. (5) was estimated using the same statistical approach that was used for Eq. (4), achieving a pvalue of 0.008 and R2 of 0.7644. These findings indicate that the regression model was suitable to adequately represent the experimental data. Through analysis of variance, it was found that the linear and quadratic effect of the initial cultivation pH and the linear effect of the initial substrate concentration had a significant impact (p < 0.05) on HPR performance. Meanwhile, the quadratic term for the initial substrate concentration and the interaction between the two independent variables were found to be statistically insignificant (p > 0.05), indicating that these terms had little impact on HPR. In order to have a graphical understanding of the distribution of HPR based on the independent variables, a twodimensional contour plot was constructed using Eq. (5), as shown in Fig. 5. Generally, it can be observed that HPR was found to increase with an increasing substrate concentration. An increase in the initial cultivation pH also led to higher HPR with peak values obtained within the pH range of 7.0e7.5. At higher substrate concentrations, an improved HPR can be observed on the higher side of the pH range (i.e. pH 7.0e7.5). The optimal HPR predicted by Eq. (5) was 58.4 mL H2/hr.L SSPE obtained from the cultures with an initial cultivation pH of 7.0 and a substrate concentration of 11 g RS/L. Similar observations were also documented [20] where the optimal HPR was observed within the initial cultivation pH range of 6.5e7.5 and initial substrate concentration between 9 and 17 g COD/L,

utilising starch-containing textile wastewater as the substrate seeded with heat-treated cow dung.

Soluble metabolites distribution The results regarding the volatile fatty acids (VFA), alcohol concentrations, pH and percentage of substrate consumed after 48 h at various initial cultivation pH levels and substrate concentrations are presented in Table 4. Based on these results, acetic acid and ethanol were the major metabolites produced in all the trials, while butyric acid and propionic acid were also present but in smaller quantities. The concentrations of these soluble metabolites (acetic acid, butyric acid and ethanol) were also found to generally increase with an increase in the initial substrate concentration for all the initial cultivation pH levels trialled. Numerous studies have reported that the fermentation pathway of hydrogen production differs with the type of substrate used in addition to bacterial metabolism. A study conducted by OThong et al. [12] utilising cassava starch processing wastewater obtained a similar dominance of acetic acid and ethanol out of the total metabolites produced. In another study, Sen et al. [11] reported acetate and butyrate production fermentation pathways utilising cassava wastewater as the substrate seeded with heat-treated cow dung. Additionally, Luo et al. [28] documented butyrate/acetate and butyrate/propionate pathways for the fermentation of cassava stillage seeded with anaerobic sludge obtained from an ethanol-producing reactor. The findings obtained through this study suggest that the glycolysis of soluble carbohydrates present in SSPE are prone to the acetic acid/ethanol production fermentation pathway. According to studies by Li et al. [29] and Ren et al. [30], acetic acid/ethanol type fermentation occurs when the mass

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i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y 3 9 ( 2 0 1 4 ) 1 9 9 3 7 e1 9 9 4 6

Fig. 5 e Response surface contour plot for the hydrogen production rate (HPR).

percentage of acetic acid and ethanol are above 60% in the total fermentation end products. Meanwhile, from the data in Table 4, it was also observed that a higher initial cultivation pH level (between pH 6.5e8.0) allowed the fermentation reaction to continue thoroughly, thus improving on the percentage of substrate consumed. Additionally, the percentage of substrate consumed and the final pH were found to decrease with an increase in the initial substrate concentration at a lower initial pH. This could be attributed to the greater accumulation of volatile fatty acids which depleted the buffering capacity of the medium, leading to bacterial growth inhibition due to an acidic environment.

According to the findings of Dabrock et al. [31], a gradual decrease in pH inhibits hydrogen production due to the acidic environment which affects the activity of the iron-containing hydrogenase enzyme. Meanwhile, Roychowdhury [32] documented that hydrogen production by Clostridium sp. is inhibited in the pH range of 4.0e5.0.

Conclusion Preliminary trials have demonstrated the possibility of increasing the soluble carbohydrate concentration in SSPE via in

Table 4 e Soluble metabolites at the end of the batch experiments. Run

Initial pH

Substrate concentration

Volatile fatty acids AA

g SC/L SSPE 1 2 3a 4a 5 6 7 8 9a 10 11 12a 13 a

8 6 6.5 6.5 7 8 7 8 7 7.5 6 7.5 6

3 7 5 9 3 7 7 11 11 5 11 9 3

Propanol present at concentration 36 mg/L.

PA

BA

mg/L 669±25 1740±117 1315±284 981±6 1116±95 827±33 953±235 1034±40 1064±85 1078±56 1099±127 1449±160 705±8

30±1 37±6 190±30 186±31 153±13 30±1 173±63 33±0 145±34 55±17 31±3 64±44 27±0

397±11 820±69 371±8 551±106 343±21 287±14 407±35 331±16 241±51 317±11 300±16 403±28 253±12

Alcohols

Substrate consumed

Final pH

EtOH mg/L

%

900±39 1345±33 1437±108 2007±91 1130±136 1932±66 1427±125 2366±80 2946±270 1445±73 1184±109 2116±185 1089±18

92±5.4 99±0.7 99±0.7 98±0.1 97±0.3 96±1.6 97±0.2 86±2.4 98±0.9 97±0.5 34±7.8 99±0.3 85±0.5

6.43±0.03 5.08±0.15 5.93±0.03 4.91±0.31 5.20±0.27 6.14±0.06 6.13±0.01 4.99±0.04 5.07±0.33 6.45±0.01 4.88±0.01 6.28±0.03 5.50±0.01

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i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y 3 9 ( 2 0 1 4 ) 1 9 9 3 7 e1 9 9 4 6

situ enzymatic treatment without requiring a long incubation period. The experimental results utilising treated SSPE showed that biohydrogen production was achieved under all the conditions studied, thus confirming the potential use of SSPE for fermentative hydrogen production. Improved HY can be achieved by setting higher initial cultivation pH with low substrate concentration. On the contrary, to achieve higher HPR requires higher substrate concentration within initial cultivation pH of 7.0e7.5. The overall final soluble metabolite concentrations indicated that the digestion of SSPE by the mixed consortia lead to an acetic acid/ethanol type fermentation pathway.

[14]

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Acknowledgements

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The authors wish to thank the Sarawak State Government for financial support of this work through the grant provided under Sago Biomass Utilisation. [19]

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