Accepted Manuscript

High yield production of sugars from deproteinated palm kernel cake undermicrowave irradiation via dilute sulfuric acid hydrolysis

Suet-Pin Fan, Li-Qun Jiang, Chin-Hua Chia, Zhen Fang, Sarani Zakaria, Kah-Leong Chee

PII: S0960-8524(13)01771-9DOI: http://dx.doi.org/10.1016/j.biortech.2013.11.055Reference: BITE 12675

To appear in: Bioresource Technology

Received Date: 6 October 2013Revised Date: 16 November 2013Accepted Date: 20 November 2013

Please cite this article as: Fan, S-P., Jiang, L-Q., Chia, C-H., Fang, Z., Zakaria, S., Chee, K-L., High yield productionof sugars from deproteinated palm kernel cake under microwave irradiation via dilute sulfuric acid hydrolysis,Bioresource Technology (2013), doi: http://dx.doi.org/10.1016/j.biortech.2013.11.055

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High yield production of sugars from deproteinated palm kernel cake under microwave

irradiation via dilute sulfuric acid hydrolysis

Suet-Pin Fana, b, Li-Qun Jiangb, Chin-Hua Chiaa,*, Zhen Fangb,*, Sarani Zakariaa, Kah-

Leong Cheec

a School of Applied Physics, Faculty of Science and Technology, Universiti Kebangsaan

Malaysia, 43600 Bangi, Selangor, Malaysia

b Chinese Academy of Sciences, Biomass Group, Key Laboratory of Tropical Plant Resource and

Sustainable Use, Xishuangbanna Tropical Botanical Garden, 88 Xuefulu, Kunming, Yunnan

650223, China

c Faculty of Applied Sciences and Computing, Tunku Abdul Rahman University College, , Jalan

Genting Kelang, Setapak, 53300 Kuala Lumpur, Malaysia

*Corresponding authors:

Chin Hua Chia (chia@ukm.my); Zhen Fang (zhenfang@xtbg.ac.cn)

Revised for Bioresource Technology

(November 2013)

 

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Abstract

Recent years, great interest has been devoted to the conversion of biomass-derived carbohydrate

into sugars, such as glucose, mannose and fructose. These are important versatile intermediate

products that are easily processed into high value-added biofuels. In this work, microwave-

assisted dilute sulfuric acid hydrolysis of deproteinated palm kernel cake (DPKC) was

systematically studied using Response Surface Methodology. The highest mannose yield

(92.11%) was achieved at the optimized condition of 148 °C, 0.75 N H2SO4, 10 min 31 s and

substrate to solvent (SS) ratio (w/v) of 1:49.69. Besides that, total fermentable sugars yield

(77.11%), was obtained at 170 °C, 0.181 N H2SO4, 6 min 6 s and SS ratio (w/v) of 1:40. Ridge

analysis was employed to further verify the optimum conditions. Thus, this work provides

fundamental data of the practical use of DPKC as low cost, high yield and environmental-

friendly material for the production of mannose and other sugars.

Keywords: Mannose; Microwave-assisted hydrolysis; Palm kernel cake; ridge analysis; RSM

optimization

1. Introduction

Climate change and increasing concerns for energy security has imparted a trend shifting

from the use of fossil fuels to renewable energy sources. Globally, focus has been on

transforming the agricultural waste into high value-added products. Malaysia, one of the global

leading palm oil producers, actively seeking for the next catalyst to sustain their economic

growth since the palm oil production has reached a mature stage (MPOB, 2012). Palm kernel

cake (PKC), one of the main by-products from palm oil industry, is rich in protein (14.5 – 19.6%)

and mannan (35.2%) (Cerveró et al., 2010). It should be placed under the spotlight and

 

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revolutionize into a source of revenue for oil palm industry. PKC composes of high carbohydrate

contents, mainly hexoses such as mannose, glucose and galactose. These are promising

candidates for the production of bioethanol through fermentation by microorganism (Gírio et al.,

2010).

It is widely known that the hemicellulose is more easily to be hydrolyzed than cellulose due

to its lower crystallinity (Canettieri et al., 2007). Mannan possesses similar structure as cellulose

(Bradbury & Halliday, 1990), both are linear β-(1-4)-linked monosaccharide polymers exhibit

some crystalline polymorphism (Wyman et al., 2005). Mannan can be classified into two major

groups depending on the β-(1-4)-linked backbone whether it composed of only D-mannose

residues (mannans) or a combination of mannose and D-glucose residues (glucomannans) (van

Zyl et al., 2010). Essentially, a more rigorous hydrolysis condition is needed to effectively

catalyze the depolymerization of mannan into mannose. However, relatively little prior work has

been completed in the area of mannose production from lignocellulosic materials, especially

through acid hydrolysis (Bradbury & Halliday, 1990). In most of the reported studies, extraction

of mannose involves mannan-degrading enzyme (Cerveró et al., 2010; Zhang et al., 2009) which

possess several disadvantages, including high pretreatment cost of the raw material before the

enzymatic hydrolysis and the utilization of high priced enzyme.

Microwave-assisted green synthesis can be an alternative to accelerate the acid hydrolysis of

carbohydrate. In prior literatures, microwave heating can offer up to 85-folds energy saving

compared to the conventional heating (Yemiş & Mazza, 2012). It also shortens the reaction time

and reduces chemical consumption (Yoshida et al., 2010), thus making it more industrially

favorable. As interest is growing in the biofuel industry, dilute acid catalyzed hydrolysis has

been widely used for various lignocellulosic materials, such as corn stover (Liu & Cheng, 2010)

 

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and grass clippings (Orozco et al., 2011). Since microwave-assisted hydrolysis involves many

variables that affect the desired response, therefore response surface methodology (RSM), a

statistically designed experimental protocol possesses advantages for both the time requirements

and number of experiments reduction. In spite of that, RSM demonstrates a relationship between

variables and responses over a relatively broad factor domain, which is much practical and

professionally in determining the optimum conditions compare with classical method.

In previous studies, protein was successfully extracted from PKC by trypsin-assisted and

hexametaphosphate-assisted extraction (Chee & Ayob, 2013; Chee et al., 2012). Subsequently,

deproteinated PKC (DPKC) can be a suitable candidate to be further hydrolyzed into fermentable

sugars. On the plus side, these fermentable sugars are recognized as a precursor for platform

molecules in value-added chemicals and biofuels production. Hitherto, this is the first attempt on

systematic optimization of fermentable sugar production from DPKC via microwave-assisted

dilute sulfuric acid hydrolysis. This study elucidates different types of sugar production under

different hydrolysis conditions, and with the application of central composite rotatable design

(CCRD), it provides a more complete picture on the structural transformations of principal

DPKC components.

2. Materials and Methods

2.1. DPKC and Chemicals

PKC used in this study was supplied by FELDA Kernel Products Sdn. Bhd., Malaysia. It was

then deproteinated by sodium hydroxide and named as DPKC. The moisture content of DPKC

after deproteination was 5.25%. The DPKC was sieved into particle size ranging from 100-149

microns, and subsequently dried at 105 °C for 24 h before use. Sodium hydroxide, NaOH (purity

≥ 96%) and sulfuric acid, H2SO4 (purity 95-98%) were purchased from Xilong Chemical Co. Ltd

 

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(Guangzhou, China). Mannose, glucose, xylose and galactose (purity ≥ 99.5%) as standards were

purchased form Sigma Aldrich.

2.2. Chemical compositions of DPKC

The DPKC’s components were analyzed using National Renewable Energy Laboratory

(NREL) analytical methods (Sluiter et al., 2008a; Sluiter et al., 2008b). Before the determination

of structural carbohydrates and lignin in the DPKC, the content of extractives and ash were

determined. First, the sample was treated with 72% (w/w) H2SO4 at 30 °C for 1 h in an incubator

shaker at 100 rpm. The mixture was then diluted to 4% (w/w) H2SO4 by adding 84 ml deionized

water and autoclaved at 121 °C for 1 h. The hydrolysis solution was filtered and the sugar

content was analyzed by a High performance liquid chromatograph (HPLC; Shimadzu LC-20A

HPLC pump, Shimadzu, prominence oven CTO-20A, Kyoto) with an Aminex HP X-87P column

(300 ×7.8 mm, Bio-Rad, California) operated at 80 °C, flow rate 0.4 ml/min with Milli-Q water

as mobile phase, equipped with a refractive index detector (RID-10A, Shimadzu). Autoclaved

hydrolysis samples were filtered and acid-soluble lignin (ASL) determined using an ultraviolet–

visible (UV-Vis) spectrophotometer (UV 1800, Shimadzu) at wavelength 240 nm. Meanwhile,

the remaining autoclaved solid residue was dried overnight at 105 °C and ashed in a muffle

furnace at 575 °C for 24 h in order to determine the ash and acid-insoluble lignin contents. The

concentration of sugars (mannose, glucose, xylose and galactose) was quantitatively analyzed

using HPLC to calculate the percentage of the carbohydrate fractions in the DPKC. The protein

content of the DPKC was determined using the Kjeldahl method (AOAC, 2005), which was done

by UNIPEQ, Bangi, Malaysia.

2.3. Microwave-assisted hydrolysis

 

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All hydrolysis experiments were carried out in a well-controlled microwave synthesis reactor

(Monowave 300, Anton Paar, Graz, Austria) using a reactor vial made of borosilicate glass

sealed with a PTFE (Polytetrafluoroethylene)-coated silicone septum and closed with a snap cap

made of PEEK (Polyether ether ketone) at temperature up to 300 °C and pressure up to 3.2 MPa

(Fig. 1). The reaction temperature was measured by a built-in infrared (IR) sensor, which was

calibrated by a ruby sensor. Meanwhile, a non-invasive pressure sensor is located in the

swiveling cover of Monowave 300 for monitoring the pressure. The reaction was performed in

an airtight reaction vial. As such, before a reaction starts, the reaction vial was sealed by a

pneumatic system and then the deformation of the silicone septum was translated into reaction

pressure by a hydraulic piston throughout the experiment. The pressure was calibrated by the

saturated vapor pressures of water (1, 2, and 3 MPa) at three different temperatures (180, 212,

and 234 °C) which were measured by a ruby sensor. Both temperature and pressure vs. time were

recorded in a USB disk. Fig. 2 shows the temperature and pressure vs. time for the experimental

reaction at temperatures (120, 140, 160, 180, and 200 °C).

In a typical test, DPKC (0.1g) and sulfuric acid (5 ml) at a desired concentration were

charged into a reactor vial incorporated with a stir bar. The mixture was heated to the desired

temperature with heating rates 0.8-1.5 oC/s (Fig. 2) and stirred at 1000 rpm. The reaction was

maintained by a proportional-integral-derivative (PID) controller at the desired temperature for

different reaction time (0, 5, 10, 15, and 20 min), followed by a rapid cooling to 55 °C by

compressed air flushing to stop the reaction. After the reaction, the liquid hydrolysate was

separated from the product mixture using a centrifuge (3-30K, SIGMA, Osterode am Harz,

Germany). After neutralizing with NaOH, the liquid sample was filtered and the clear aqueous

phase was analyzed with HPLC.

 

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2.4. Experimental design and statistical analyses

In this study, RSM was employed to obtain the optimum conditions for microwave-assisted

hydrolysis of DPKC using H2SO4. The selection of variables was based on some preliminary

studies and then followed by a fractional factorial design (FFD) to identify the significant

variables for the production of sugars (data not shown). Hence, four independent variables

(temperature, acid concentration, reaction time, substrate: solvent (SS) ratio) with five levels

were set up according to the CCRD using Design Expert 6.0 (Stat-Ease Inc., Minneapolis, USA)

to obtain a quadratic model. The quadratic effects and central points were estimated with the

total monosaccharide yield (Ytm) and mannose yield (Ymy) as responses. The four independent

variables and the actual values at five levels (-2, -1, 0, +1, +2) were presented in Table 1. The

total number of experiments with four factor was 54 = [(2k + 2k) x 2] + 6, where k is the number

of factors. Forty eight experiments were augmented with six replications at the center points to

evaluate the pure error. The predictor variables were coded according to the following equation:

xi = (Xi – X0) / ∆Xi (1)

where, xi is the coded value of an independent variable, Xi is the actual values of the independent

variable i, X0 is the actual value of the independent variable at the center point, and ∆Xi is the

step change value corresponding to a unite variation of the dimensionless value.

The regression equation was fitted to the response resulted from the CCRD:

(2)

where, y is the predicted response, β0 is the intercept, βj, βjj, βjk are the linear, quadratic and

interactive coefficients, respectively.

 

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Ridge analysis was applied on a second-order fitted response to obtain a set of paths, a

maximum response, going outwards from the origin x' = (x1, x2,…,xq) = (0,0,…,0) of the factor

space. The basic ridge analysis method is as follows. Assume the fitted second-order surface is:

y = b0 + b1x1 + b2x2 + …+ bqxq + b11x12 + b22x2

2 + … + bqqxq2 + …

+ b12x1x2 + b13x1x3 + … + βq-1,q xq-1xq q = 1, 2, 3 (3)

where, y is the predicted response, b0 is the intercept, b’s are the regression coefficients.

Meanwhile Eq. (3) can be written in matrix form as:

y = b0 + x'b + x'Bx (4)

where, x' = (x1, x2, …, xq), b' = (b1, b2, …, bq).

(5)

where, B is a symmetric matrix containing all second-order coefficients.

The calculations to obtain the Eigen values and prediction points perform by using

MINITAB 16 (Minitab Inc., State College, Pennsylvania, USA). Then, actual experimental runs

at points along this path were conducted to achieve the optimum response values.

2.5. HPLC analysis

Sugars (mannose, glucose, xylose and galactose) were measured by HPLC (LC-20A,

Shimadzu). Each monosaccharide was calibrated by its standard sugar solutions with five

different concentrations (e.g., 0.1, 0.2, 0.3, 0.4 and 0.5 mg/ml). All the standard calibration

curves obtained with R2 > 0.998. Total monosaccharide yield (Ytm, wt. %) and mannose yield

(Ymy, wt. %) were calculated as follows:

Ytm (wt. %) = [total mass of monosaccharides (mannose + glucose + xylose + galactose) in the

liquid hydrolysate] / (total mass of monosacharides in DPKC) × 100%

 

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Ymy (wt. %) = (mass of mannose in the liquid hydrolysate) / (total mass of mannose in DPKC) ×

100%

3. Results and discussion

Fifty-four experiments were conducted under the conditions: temperature of 120-200 oC,

sulfuric acid concentration of 0-1.0 N, reaction time of 0-20 min and substrate (DPKC): solvent

ratio (g/ml) of 1:20-1:60 (Table 1) to optimize the sugar yields. The schematic representation of

microwave and reactor vial is displayed in Fig. 1. The chemical compositions and relative

monosaccharide composition of DPKC (wt. %) are listed in Table 2. Fig. 2 shows the

temperature-pressure profiles with respect to time at different reaction temperatures (120-200

°C). Three-dimensional (3D) response surface plots for the whole model of total monosaccharide

and mannose yields, presented in Fig. 3 and Fig. 4, showing the interaction effects of two

independent variables, where the other two variables were fixed at the center point. The

experimental responses values with CCRD are summarized in Table 3. As for the analysis of

variance (ANOVA) for the CCRD model of the total monosaccharide and mannose yields are

given in Tables 4 and 5. Lastly, ridge analysis of the total monosaccharide is stated in Table 6.

3.1. Components of DPKC

The components of the DPKC analyzed using NREL procedure are presented in Table 2.

Mannan and glucan account for 94.77% of the total carbohydrates in the DPKC. DPKC contains

substantially higher mannan fraction in the hemicellulose than other glucan, xylan and galactan.

3.2. Experimental design and statistical analysis

 

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The results of the responses (total monosaccharide and mannose yields) were summarized in

Table 3. The polynomial equations describing total monosaccharide yield (Ytm) and mannose

yield (Ymy) are given below:

Ytm = 76.7 - 4.22x1 - 1.69x2 - 1.35x3 + 0.63x4 - 10.74x1x2 -7.88x1x3 - 0.3x1x4 - 1.62x2x3

+ 1.11x2x4 + 0.4x3x4 -15.27x12 - 2.11x2

2 - 1.91x32 - 0.42x4

2 (6)

Ymy = 90.84 - 8.37x1 - 2.68x2 - 2.25x3 + 0.71x4 - 13.92x1x2 - 10.68x1x3 - 0.92x1x4 - 1.76x2x3

+ 1.64x2x4 + 0.47x3x4 - 20.93x12 - 1.88x2

2 - 3.05x32 - 0.52x4

2 (7)

where, x1, x2, x3, x4, are the coded values of independent variables of temperature, acid

concentration, reaction time and SS ratio, respectively. The models for total monosaccharide and

mannose yields evaluated by ANOVA are summarized in Table 4. For both responses, the

regression were statistically significant at the 95% confidence level, as denoted from the Fisher’s

F-test with the probability (P) value was less than 0.001.

The quality of the regression model was expressed by the coefficient of determination (R2).

The predicted R2 and adjusted R2 for the first (Ytm) were 0.9227 and 0.9505; second (Ymy) were

0.9392 and 0.9611, respectively, which suggested the design model was adequately

demonstrating the real relationships among the parameters chosen. The high value of the R2

indicates the good correlation between the model and the experimental results (Joglekar & May,

1987).

3.2.1. Effect of independent variables on responses

The response surfaces and contour plots, which described by the regression models for the

total monosaccharide and mannose yields were generated to illustrate the interactive effects

between each independent variable on the response variables. Fig. 3 and 4 are delineated by

imposing two independent variables at their zero level. Fig. 3a-f and 4a-f represent response

 

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surfaces and contour plots for responses, Ytm and Ymy, respectively. The significance level for

the interactions between variables can be depicted from the shape of the corresponding contour

plots. Elliptical contours can be achieved when there is a perfect interaction between independent

variables (Muralidhar et al., 2001). In Table 5, the greatest significant effect for the response, Ytm

was the quadratic term of temperature (x12), ensued by x1x2, x1x3, temperature (x1), x3

2, x22, acid

concentration (x2), reaction time (x3) and x2x3. While, the most significant effect for the response,

Ymy sequenced as: quadratic term of temperature (x12), x1x2, x1x3, temperature (x1), x3

2, reaction

time (x3) and acid concentration (x2). In present study, mannose was the main DPKC-derived

sugar from the hydrolysis.

3.2.1.1. Effect of temperature on total monosaccharide yield (Ytm) and mannose yield (Ymy)

First of all, temperature is a key parameter in determining the sugars recovery and degradation

during acid hydrolysis process. Temperature imparts disruption on the DPKC substrate structure,

the acid dissociation is also depending on the operating temperature (Marshall & Jones, 1966).

At normal temperature, the polysaccharide stays in a stable crystalline form. At high temperature,

the monosaccharide unit in the polysaccharide exists abundantly in open-chain form (less stable)

than the ring form (Nattorp et al., 1999). Thus, it is more susceptible to hydrolysis. As

temperature increases, molecules gain higher kinetic energy that leads to a greater collision rate

between the substrate and hydronium ions, which randomly attack on the glycosidic linkage to

surpass the activation energy barrier, and thereby resulting in the hydrolysis/degradation reaction

to occur. These scenarios can be seen in Figs. 3a and 4a, where both Ytm and Ymy increased when

temperature rose from 140 to 165 °C, but both declined as temperature increased further. A

similar trend can be found in Figs. 3b, 3c and 4b and 4c. Consequently, it is concluded that at

0.25 N H2SO4, the temperature increment (<165 °C) contributes a higher impact on DPKC

 

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hydrolysis reaction rate than secondary decomposition rate of the hydrolyzed sugars (Gurgel et

al., 2011). The highest Ytm achieved was 76.98% at 164 °C, 10 min, SS ratio of 1:40, and

concurrently 92.01% for Ymy at 163 °C. By comparing the results obtained (Fig. 3a), it can be

proposed that the DPKC-derived sugars decomposition begins to dominate at temperature higher

than 165 °C. Whereas, at fixed acid concentration 0.75 N H2SO4 and reaction time of 10 min, a

negative effect of temperature (>150 °C) observed on the DPKC-derived sugars. Ytm and Ymy

decreased from 150 °C onwards as shown in Figs. 3a and 4a, owing to the low pKa of H2SO4

with greater hydrolyzing power generating more hydronium ion which further catalyzed the

degradation of sugars into furfural (from C5-sugars) and 5-hydroxymethylfurfural (5-HMF, from

C6-sugar) (Jung et al., 2013; Mosier et al., 2002). In Fig. 3a, for acid concentration of 0.25 N

H2SO4, the steepness of the curve became more gradual in the direction of temperature range

(140-165 °C). Next, further processing of the data by numerical optimization function (Design

Expert Software) showed that Ytm, at temperature range (140-150 °C) was nearly 2.7-fold faster

than the temperature range (150-165 °C). These data suggested that, initially the diffusion rate of

hydrolyzed sugars into the bulk medium is equivalent to the penetration rate of the reacting

species into the DPKC substrate. As described previously, increasing temperature entailed a rise

on the kinetic energy of the reacting species, penetration rate and its collision probabilities with

substrate, thus the hydrolysis reaction occurred at a greater rate. Yet, up to a certain extent, the

increasing concentration of “released” sugars in the bulk medium (near the surface of substrate)

may slow-down the continuous releasing of sugars from the DPKC substrate as well as induced

an additional resistance for the penetration of the reacting species into the DPKC substrate.

These results are in accord with previous study by Torget et al. (2000), stated that the released

moieties tend to stay closed on the cellulose surface due to the hydrogen-bonding potential with

 

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the structure cellulose surface, and van der Waals attraction forces along with the resistance of

diffusion caused by the charged structural water layer (Torget et al., 2000).

In Table 5 (ANOVA), temperature demonstrated a significant quadratic effect on Ytm and Ymy,

evidently in surface plots (Fig. 3 and 4). This indicated that temperature is the most important

factor in determining the resultant degree of conversion of DPKC into sugars. Also, hydrolysis

shows stronger temperature dependency at acid concentration greater than 0.4 wt. % (Saeman,

1945; Torget et al., 2000). The interaction effect between temperature-acid concentration and

temperature-reaction time was positive (P < 0.001) towards Ytm and Ymy. By comparing the F

value between these two interaction pairs, the temperature-acid concentration was more

significant than the temperature-reaction time pair. By considering the interaction temperature-

acid concentration, it was found that at low temperature (140 °C), the sugars recovery rose with

increasing acid concentration (0.25-0.75 N). However, an inversely effect observed during

hydrolysis at high temperature (175 °C). An identical phenomenon showed by the temperature-

reaction time interaction pair in Figs. 3b and 4b. Apparently, hydrolysis at low temperature

requires a longer reaction time and vice versa in order to obtain a reasonable amount of sugars.

Furthermore, based on Fig. 3c and 4c, the SS ratio factor remains constant with respect to the

temperature factor from 140-180 °C. Therefore, it can be concluded that the interaction effect

between temperature and SS ratio has no significant influence on Ytm and Ymy.

According to the experimental data presented in Table 3, at given operational conditions (tests

21-24), Ytm dropped from average of 69.28% to 51.63% when temperature increased from 140 to

180 °C. In the same way, at given conditions with longer reaction time (tests 29-32) there is a

drastic reduction of Ytm from 76.14% to 29.70%, suggesting that the decomposition reaction

occurred. Likewise, it was found that a lower mannose yield (Ymy) was obtained with further

 

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increase in the temperature from 140 to 180 °C (tests 21-24, 29-32). It was recently reported that

the degradation stage is more temperature sentient than hydrolysis stage, evidently from the

relatively higher activation energy for degradation process than the hydrolysis reaction (Kim et

al., 2013). According to (Nattorp et al., 1999), the degradation of mannose had higher activation

energy (140 kJ/mol) than the mannan hydrolysis (113 kJ/mol). Hence, increasing temperature

gives negative effect on maximizing mannose yield (Ymy), because increase in temperature led to

mannose degradation more dominant than hydrolysis of mannan in DPKC.

3.2.1.2. Effect of acid concentration on total monosaccharide yield (Ytm) and mannose yield (Ymy)

Apart from temperature factor, acid concentration also plays a significant role in Ytm and Ymy,

as illustrated in Fig. 3a, 3d, 3e, 4a, 4d and 4e. In present study, the reacting species that catalyze

the hydrolysis were hydronium ion, sulfate and bisulfate anions (Lindstrom & Wirth, 1969).

With progressively higher acid concentration at 140 °C, the selectivity towards sugars was

higher, thus enhanced Ytm and Ymy as shown in Figs 3a and 4a. The rising of sugars with

increasing acid concentration could possibly due to the increased charge perturbation at the

boundary layer. The ionic disturbance caused by the increase hydronium ion concentration

facilitates sugars in “released” state (Torget et al., 2000). It is noted that at elevated temperature

(up to 180 °C), Ytm and Ymy decreased with increasing acid concentration. As depicted in Figs.

3a, 3d, 3e, 4a, 4d and 4e, at the acid concentration greater than its optimum point, it will

introduce an adverse effect on the selectivity of sugars, Ytm and Ymy. In essence, under

conditions of higher acid concentration (Fig. 4d), Ymy increased at the initial phase of reaction

and then decreased gradually with prolonged reaction time. These results could be attributed to

the severe action of acid with longer reaction time; mannose underwent secondary

decomposition to 5-HMF. It should be noted in Fig. 4d, the highest amount of Ytm obtained at

 

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160 °C, SS ratio 1:40 with acid concentration lower than 0.5 N H2SO4. Szabolcs and co-

researchers found that at above 0.5 N H2SO4, a higher yield of levulinic acid (simultaneously, the

amount of 5-HMF was lower) was observed and it reached the maximum at 1 N H2SO4 during

the microwave-assisted conversion of carbohydrates. It is well-known that the formation of 5-

HMF proceed from hexose (mannose, glucose and galactose) degradation, therefore this result is

in good agreement with a previous study (Szabolcs et al., 2013), reported that the formation of 5-

HMF (degradation product from hexose) is favorable at acid concentration higher than 0.5 N

H2SO4.

3.2.1.3. Effect of reaction time on total monosaccharide yield (Ytm) and mannose yield (Ymy)

In the point of time factor, at fixed temperature 160 °C with SS ratio 1:40 of and 0.25 N

H2SO4, longer reaction time contributes to a higher sugars recovery (Fig. 3d and Fig. 4d). These

are consistent with other report on the hydrolysis of sweet sorghum bagasse at moderate

temperature (100-121 °C) (Banerji et al., 2013). In contrast, at the same reaction conditions (160

°C, SS ratio 1:40) with higher acid concentration (0.75 N H2SO4), the degradation of the sugars

occurred with prolonged reaction time. Indeed, other study reported that extending the reaction

time at high acid concentration led to the decomposition of decrystallized cellulose and thus

reduced the sugar yield (Chin et al., 2011). Therefore, it can be summarized that the time factor

is dependent to the reaction temperature and acid concentration.

Table 3 (Tests 39 and 40) demonstrates the averages of total monosaccharide yield (Ytm)

16.34%, consisting mono-sugars (glucose, xylose and galactose). Although the experiments were

conducted at high temperature (200 °C), there is no great amount of DPKC-derived sugars

obtained in the hydrolysate, which could be attributed to the lower dissociation of H2SO4 at high

temperature (Lloyd & Wyman, 2004; Maki-Arvela et al., 2011).

 

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According to a study reported on the hydrolysis of cellulose, the highest cellulose conversion

using pure water was 70%, which can be achieved at 220 °C and 100 min (Kupiainen et al.,

2012). In the present work, the DPKC hydrolysis took place in the presence of deionized water,

160 °C, 10 min of reaction time and SS ratio 1:40, and yielded trace of xylose monomer 0.4% of

total monosaccharide, (Tests 41 and 42). The possible explanations could be the auto-ionization

of water at elevated temperature, generating hydronium ions (Kim et al., 2013) and leading to the

production of acetic acid from the hemicellulose. These would catalyze partial hydrolysis of

hemicellulose (xylan) to form xylose. It was found that the activation energy for the hydrolysis

of cellubiose (Mosier et al., 2002), mannan (Nattorp et al., 1999) and xylan (Canettieri et al.,

2007) was 110, 113, and 101 kJ/mol, respectively. The lowest energy barrier (activation energy)

for xylan hydrolysis could be the reason for this observation where xylose was the only detected

compound after the hydrolysis (Kim et al., 2013). Additionally, by applying “easy-to-hydrolyze”

and “hard-to-hydrolyze” concept of xylan, it can be postulated that these xylose monomer

released from the “easy-to-hydrolyze” fraction (Lavarack et al., 2002). The purpose of inserting

this parameter (160 °C, 0 N of acid concentration) was to evaluate the effect of the pure water on

the hydrolysis at high temperature. However, according to the Diagnostics function, these

response data fall outside the outlier T area between +3.50 and -3.50, thus it is considered as

outliers. Consequently, these outliers (tests 41 and 42) were then excluded in the CCRD model.

3.2.1.4. Effect of substrate: solvent ratio on total monosaccharide yield (Ytm) and mannose yield

(Ymy)

Higher substrate concentrations means that larger quantity of the raw material can be

processed which is an important aspect for industrial applications. To alleviate this concern, SS

ratio factor was incorporated in the experimental design as well, although the SS ratio was not a

 

17  

significant factor for both responses as the sugars formation are always lower at higher substrate

loading, if other parameters kept constant. Ytm and Ymy of the DPKC hydrolysis were affected

marginally with increased SS ratio at temperature range (140-180 °C) as displayed in Fig. 3d and

4d. From Table 5, it elucidates that during the hydrolysis of DPKC, SS ratio was an insignificant

factor (P > 0.05) for the responses Ytm and Ymy, where same phenomena reported by Yemiş and

Mazza in the hydrolysis wheat straws (Yemiş & Mazza, 2012). As can be seen, the mutual

interactions between SS and other pairs of independent (temperature-SS ratio, acid

concentration-SS ratio and reaction time-SS ratio) were not significant (P > 0.05) as well. In

current work, the instrument limitation on the highest SS ratio at 1:20, it caused restriction in the

chosen range SS ratio (1:20, 1:30, 1:40, 1:50 and 1:60), these intervals were too small to give a

barely noticeable changes on Ytm and Ymy that could be the reason for the insignificant effect of

SS ratio.

From the experimental results inferred that it may not be possible to optimize the reaction

conditions to obtain a maximum yield for all sugars simultaneously. It is noteworthy that,

mannose is the dominant hemicellulose sugar in the DPKC, thereby; achieving the maximum

mannose monomer concentration is preferentially than other monomer sugars. One of the

striking observations obtained in this study is the mannose yield is comparable with those

reported in the literature using mannan degrading enzyme (Cerveró et al., 2010; Zhang et al.,

2009). An important factor could be related to the microwaves interacted with the DPKC at a

molecular level, adsorbed deeply into the folding layers of cellulose to destroy the crystal

structure and enhance the mass transfer (Wu et al., 2010; Yemiş & Mazza, 2012).

3.2.2. Model verification, ridge analysis and optimum reaction conditions

 

18  

Model verification was carried out in triplicate under selected solutions given by Design

Expert software. The confirmation experiments for total monosaccharide yield (Ytm) were

conducted at operating parameters 153 °C, 0.72 N H2SO4, 9 min 42 s and SS ratio of 1:38.84.

This hydrolysis run gave a good result (76.15% of Ytm), which is in good agreement with the

predicted value, 78.02%.

From the analysis of the ANOVA data and the statistical parameters, after the removal of the

insignificant terms, the final deduced empirical model in terms of coded factors is shown below:

Ytm = 76.7 - 4.22x1 - 1.69x2 - 1.35x3 - 10.74x1x2 -7.88x1x3 - 1.62x2x3 - 15.27x12 - 2.11x2

2

- 1.91x32 (8)

The second order polynomial model [Eq. (8)] in present study was employed for response

optimization by using Minitab 16. As the center point value greater than the mean value

(58.57%), it can be assumed that the model reached the optimum region. However, the 3D

contour plot showed a saddle curve, therefore ridge analysis on the total monosaccharide was

further conducted (Table 6) to verify the optimum reaction conditions. As the three Eigen values

had different signs, hence it can be deduced that the stationary point for this model did not have a

unique optimum. Therefore, the predicted optimum values for the three key variables were

determined from the results of ridge analysis. Three hydrolysis conditions were selected and the

experiments were carried out based on the calculated actual value of the variables. It was

successfully found that, the optimum conditions for maximum Ytm were 170 °C, 0.181 N H2SO4

and 6 min 6 s. The predicted maximum Ytm was calculated to be 77.67%, and the actual yield of

Ytm obtained was 77.11% with 0.56% deviation from the predicted value. The criteria for the

optimization of the mannose yield (Ymy) by means of the Desirability function based on the

maximization of the mannose content were performed at 148 °C, 0.75 N H2SO4, 10 min 31 s and

 

19  

substrate to solvent (SS) ratio (w/v) of 1:49.69 to corroborate with the predicted value. The

average value of triplicate experiments for mannose yield was 92.11%, whereas the predicted

value was 94.63%.

4. Conclusions

The microwave-assisted hydrolysis of deproteinated palm kernel cake under operating

conditions (170 °C, 0.181 N H2SO4 and SS ratio of 1:40) offered a maximum yield, 77.11% of

total monosaccharide in a reaction time 6 min 6 s. Besides, high yield of mannose, 92.11% was

obtained at 148 °C, 0.75 N H2SO4, 10 min 31 s and SS ratio of 1:49.69. This work demonstrated

that the microwave-assisted process is an effective method for the acid-catalyzed conversion of

DPKC to monosaccharides. DPKC is an economically and environmentally benign source for the

mannose generation as it is a cheap and abundantly available resource.

Acknowledgements

The authors would like to acknowledge the financial support given by University Research Grant

(DIP-2012-34) and ERGS/1/2012/STG01/UKM/03/3. Fan acknowledges the Ministry of Higher

Education (KPT) for the disbursement of MyPhD scholarship.

References

1. Banerji, A., Balakrishnan, M., Kishore, V.V.N. 2013. Low severity dilute-acid hydrolysis of

sweet sorghum bagasse. Appl. Energy 104, 197-206.

2. Bradbury, A.G.W., Halliday, D.J. 1990. Chemical structures of green coffee bean

polysaccharides. J. Agric. Food. Chem. 38, 389-392.

3. Canettieri, E.V., Rocha, G.J.D.M., de Carvalho, J.A., Silva, J.B.D.A. 2007. Optimization of

acid hydrolysis from the hemicellulosic fraction of Eucalyptus grandis residue using response

surface methodology. Bioresour. Technol. 98, 422-428.

 

20  

4. Cerveró, J.M., Skovgaard, P.A., Felby, C., Sørensen, H.R., Jørgensen, H. 2010. Enzymatic

hydrolysis and fermentation of palm kernel press cake for production of bioethanol. Enzyme

Microb. Technol. 46, 177-184.

5. Chee, K.L., Ayob, M.K. 2013. Optimization of hexametaphosphate-assisted extraction and

functional characterization of palm kernel cake protein. Food Sci. Technol. Int. 19, 109-122.

6. Chee, K.L., Ling, H.K., Ayob, M.K. 2012. Optimization of trypsin-assisted extraction,

physico-chemical characterization, nutritional qualities and functionalities of palm kernel cake

protein. LWT Food Sci. Technol. 46, 419-427.

7. Chin, K.L., H’ng, P.S., Wong, L.J., Tey, B.T., Paridah, M.T. 2011. Production of glucose

from oil palm trunk and sawdust of rubberwood and mixed hardwood. Appl. Energy 88, 4222-

4228.

8. Gírio, F.M., Fonseca, C., Carvalheiro, F., Duarte, L.C., Marques, S., Bogel-Łukasik, R. 2010.

Hemicelluloses for fuel ethanol: A review. Bioresour. Technol. 101, 4775-4800.

9. Gurgel, L.V.A., Marabezi, K., Zanbom, M.D., Curvelo, A.A.D. 2011. Dilute acid hydrolysis

of sugar cane bagasse at high temperatures: A kinetic study of cellulose saccharification and

glucose decomposition. Part I: Sulfuric acid as the catalyst. Ind. Eng. Chem. Res. 51, 1173-1185.

10. Joglekar, A.M., May, A.T. 1987. Product excellence through design of experiment. Cereal

Foods World 32, 857-869.

11. Jung, Y.H., Kim, I.J., Kim, H.K., Kim, K.H. 2013. Dilute acid pretreatment of lignocellulose

for whole slurry ethanol fermentation. Bioresour. Technol. 132, 109-114.

12. Kim, Y., Kreke, T., Ladisch, M.R. 2013. Reaction mechanisms and kinetics of xylo-

oligosaccharide hydrolysis by dicarboxylic acids. AlChE J. 59, 188-199.

 

21  

13. Kupiainen, L., Ahola, J., Tanskanen, J. 2012. Distinct Effect of Formic and Sulfuric Acids

on Cellulose Hydrolysis at High Temperature. Ind. Eng. Chem. Res. 51, 3295-3300.

14. Lavarack, B.P., Griffin, G.J., Rodman, D. 2002. The acid hydrolysis of sugarcane bagasse

hemicellulose to produce xylose, arabinose, glucose and other products. Biomass Bioenergy 23,

367-380.

15. Lindstrom, R.E., Wirth, H.E. 1969. Estimation of the bisulfate ion dissociation in solutions

of sulfuric acid and sodium bisulfate. J. Phys. Chem. 73, 218-223.

16. Liu, C.Z., Cheng, X.Y. 2010. Improved hydrogen production via thermophilic fermentation

of corn stover by microwave-assisted acid pretreatment. Int. J. Hydrogen Energy 35, 8945-8952.

17. Lloyd, T., Wyman, C. 2004. Predicted effects of mineral neutralization and bisulfate

formation on hydrogen ion concentration for dilute sulfuric acid pretreatment. Appl. Biochem.

Biotechnol. 115, 1013-1022.

18. Maki-Arvela, P., Salmi, T., Holmbom, B., Willfor, S., Murzin, D.Y. 2011. Synthesis of

sugars by hydrolysis of hemicelluloses- A review. Chem. Rev. 111, 5638-5666.

19. Marshall, W.L., Jones, E.V. 1966. Second dissociation constant of sulfuric acid from 25 to

350° evaluated from solubilities of calcium sulfate in sulfuric acid solutions. J. Phys. Chem. 70,

4028-4040.

20. Mosier, N.S., Ladisch, C.M., Ladisch, M.R. 2002. Characterization of acid catalytic domains

for cellulose hydrolysis and glucose degradation. Biotechnol. Bioeng. 79, 610-618.

21. MPOB. 2012. Overview of the malaysian oil palm industry 2012.

22. Muralidhar, R.V., Chirumamila, R.R., Marchant, R., Nigam, P. 2001. A response surface

approach for the comparison of lipase production by Candida cylindracea using two different

carbon sources. Biochem. Eng. J. 9, 17-23.

 

22  

23. Nattorp, A., Graf, M., Spühler, C., Renken, A. 1999. Model for random hydrolysis and end

degradation of linear polysaccharides:  Application to the thermal treatment of mannan in

solution. Ind. Eng. Chem. Res. 38, 2919-2926.

24. Orozco, A.M., Al-Muhtaseb, A.H., Albadarin, A.B., Rooney, D., Walker, G.M., Ahmad,

M.N.M. 2011. Acid-catalyzed hydrolysis of cellulose and cellulosic waste using a microwave

reactor system. RSC Adv. 1, 839-846.

25. Saeman, J.F. 1945. Kinetics of Wood Saccharification - Hydrolysis of Cellulose and

Decomposition of Sugars in Dilute Acid at High Temperature. Ind. Eng. Chem. 37, 43-52.

26. Sluiter, A., Hames, B., Ruiz, R., Scarlata, C., Sluiter, J., Templeton, D., Crocker, D. 2008a.

Determination of structural carbohydrates and lignin in biomass. Technical Report NREL/TP-

510-42618.

27. Sluiter, A., Ruiz, R., Scarlata, C., Sluiter, J., Templeton, D. 2008b. Determination of

extractives in biomass. Technical report NREL/TP-510-42619.

28. Szabolcs, A., Molnar, M., Dibo, G., Mika, L.T. 2013. Microwave-assisted conversion of

carbohydrates to levulinic acid: an essential step in biomass conversion. Green Chem. 15, 439-

445.

29. Torget, R.W., Kim, J.S., Lee, Y.Y. 2000. Fundamental aspects of dilute acid

hydrolysis/fractionation kinetics of hardwood carbohydrates. 1. Cellulose hydrolysis. Ind. Eng.

Chem. Res. 39, 2817-2825.

30. van Zyl, W.H., Rose, S.H., Trollope, K., Görgens, J.F. 2010. Fungal β-mannanases: Mannan

hydrolysis, heterologous production and biotechnological applications. Process Biochem. 45,

1203-1213.

 

23  

31. Wu, Y., Fu, Z., Yin, D., Xu, Q., Liu, F., Lu, C., Mao, L. 2010. Microwave-assisted

hydrolysis of crystalline cellulose catalyzed by biomass char sulfonic acids. Green Chem. 12,

696-700.

32. Wyman, C.E., Decker, S.R., Himmel, M.E., Brady, J.W., Skopec, C.E., Viikari, L. 2005.

Hydrolysis of cellulose and hemicellulose, pp. 1-39.

33. Yemiş, O., Mazza, G. 2012. Optimization of furfural and 5-hydroxymethylfurfural

production from wheat straw by a microwave-assisted process. Bioresour. Technol. 109, 215-223.

34. Yoshida, T., Tsubaki, S., Teramoto, Y., Azuma, J. 2010. Optimization of microwave-

assisted extraction of carbohydrates from industrial waste of corn starch production using

response surface methodology. Bioresour. Technol. 101, 7820-7826.

35. Zhang, T., Pan, Z., Qian, C., Chen, X. 2009. Isolation and purification of D-mannose from

palm kernel. Carbohydr. Res. 344, 1687-1689.

 

24  

Figure Captions:

Fig. 1 Schematic representation of microwave and reactor vial.

Fig. 2 Temperature-pressure profiles with respect to time at different reaction temperatures

(120 °C, 140 °C, 160 °C, 180 °C and 200 °C).

Fig. 3 Three-dimensional (3D) response surface plots showing the interaction effects of two

independent variables on total monosaccharide yield (Ytm), while the other two variables

were fixed at the center point.

(a) Effect of temperature and sulfuric acid concentration at fixed reaction time (10 min)

and SS ratio (1: 40).

(b) Effect of temperature and reaction time at fixed sulfuric acid concentration (0.5 N)

and SS ratio (1: 40).

(c) Effect of temperature and SS ratio at fixed sulfuric acid concentration (0.5 N) and

reaction time (10 min).

(d) Effect of sulfuric acid concentration and reaction time at fixed temperature (160 °C)

and SS ratio (1: 40).

(e) Effect of sulfuric acid concentration and SS ratio at fixed temperature (160 °C) and

reaction time (10 min).

(f) Effect of reaction time and SS ratio at fixed temperature (160 °C) and sulfuric acid

concentration (0.5 N).

Fig. 4 Three-dimensional (3D) response surface plots showing the interaction effects of two

independent variables on mannose yield (Ymy), while the other two variables were fixed

at the center point.

 

25  

(a) Effect of temperature and sulfuric acid concentration at fixed reaction time (10 min)

and SS ratio (1: 40).

(b) Effect of temperature and reaction time at fixed sulfuric acid concentration (0.5 N)

and SS ratio (1: 40).

(c) Effect of temperature and SS ratio at fixed sulfuric acid concentration (0.5 N) and

reaction time (10 min).

(d) Effect of sulfuric acid concentration and reaction time at fixed temperature (160 °C)

and SS ratio (1: 40).

(e) Effect of sulfuric acid concentration and SS ratio at fixed temperature (160 °C) and

reaction time (10 min).

(f) Effect of reaction time and SS ratio at fixed temperature (160 °C) and sulfuric acid

concentration (0.5 N).

 

26  

Table Captions:

Table 1 Actual and coded variables at five levels in the CCRD constructed to optimize the

hydrolysis of DPKC by sulfuric acid.

Table 2 Chemical compositions of DPKC (wt. %).

Table 3 Central composite rotatable design with the experimental responses values of total

monosaccharide yield (Ytm), mannose yield (Ymy), mannose (man), glucose (glu),

xylose (xyl) and galactose (gal).

Table 4 ANOVA for regression models of total monosaccharide yield (Ytm) and mannose

yield (Ymy).

Table 5 ANOVA and regression coefficient for linear, quadratic and interactive terms of

total monosaccharide yield (Ytm) and mannose yield (Ymy).

Table 6 Ridge analysis on the total monosaccharide yield (Ytm).

 

27  

Table 1 Actual and coded variables at five levels in the CCRD constructed to optimize the

hydrolysis of DPKC by sulfuric acid.

Independent variables Coded Levels

-2 -1 0 1 2

Temperature (°C) x1 120 140 160 180 200

Acid concentration (N) x2 0 0.25 0.5 0.75 1.0

Reaction time (min) x3 0 5 10 15 20

Substrate : solvent ratio (g/ml) x4 1:20 1:30 1:40 1:50 1:60

 

28  

Table 2 Chemical compositions of DPKC (wt. %).

Components :

Protein 6.70 ± 0

Lignin

Acid-Insoluble Lignin 5.67 ± 0.42

Acid-Soluble Lignin 2.45 ± 0.35

Extractives

Water-Soluble 4.13 ± 0.18

Ethanol-Soluble 3.54 ± 0.08

Ash 3.50 ± 0.08

Monosaccharides after hydrolysis*

Glucose 13.66 ± 0.78

Mannose 55.71 ± 0.68

Xylose 1.84 ± 0.14

Arabinose 1.00 ± 0.24

Galactose 1.00 ± 0.06

* Measured by NREL analytical methods (Sluiter et al., 2008a; Sluiter et al., 2008b).

 

29  

Table 3 Central composite rotatable design with the experimental responses values of total monosaccharide yield (Ytm), mannose

yield (Ymy), mannose (man), glucose (glu), xylose (xyl) and galactose (gal).

Test Factors Monosaccharide in DPKC (g/g) Responses (%)

x1 x2 x3 x4 Man Glu Xyl Gal Ytm Ymy

(°C) (N) (min) (g/ml)

1 ‒1 ‒1 ‒1 ‒1 0.3189 0.0021 0.0143 0.0137 47.76 57.25

2 ‒1 ‒1 ‒1 ‒1 0.3054 0.0018 0.0146 0.0131 45.75 54.83

46.76 ± 1.42 a 56.04 ± 1.71 b

3 1 ‒1 ‒1 ‒1 0.4802 0.0175 0.0170 0.0153 72.42 86.20

4 1 ‒1 ‒1 ‒1 0.4928 0.0187 0.0187 0.0152 74.51 88.46

73.47 ± 1.48 a 87.33 ± 1.60 b

5 ‒1 1 ‒1 ‒1 0.4287 0.0198 0.0152 0.0070 64.31 76.95

6 ‒1 1 ‒1 ‒1 0.4484 0.1922 0.0181 0.0096 67.67 80.49

65.99 ± 2.38 a 78.72 ± 2.50 b

7 1 1 ‒1 ‒1 0.2826 0.0723 0.0033 0.0017 49.17 50.73

8 1 1 ‒1 ‒1 0.2903 0.0423 0.0061 0.0024 46.59 52.11

 

30  

47.88 ± 1.82 a 51.42 ± 0.98 b

9 ‒1 ‒1 1 ‒1 0.3927 0.0057 0.0179 0.0170 59.19 70.49

10 ‒1 ‒1 1 ‒1 0.3896 0.0060 0.0151 0.0152 58.19 69.94

58.69 ± 0.71 a 70.22 ± 0.39 b

11 1 ‒1 1 ‒1 0.3450 0.0415 0.0260 0.0107 57.80 61.93

12 1 ‒1 1 ‒1 0.3328 0.0335 0.0262 0.0076 54.66 59.74

56.23 ± 2.22 a 60.84 ± 1.55 b

13 ‒1 1 1 ‒1 0.5087 0.0188 0.0169 0.0149 76.41 91.32

14 ‒1 1 1 ‒1 0.5224 0.0137 0.0206 0.0097 77.38 93.77

76.90 ± 0.69 a 92.55 ± 1.73 b

15 1 1 1 ‒1 0.0997 0.0652 0.0103 0 23.94 17.90

16 1 1 1 ‒1 0.0946 0.0507 0 0 19.85 16.98

21.90 ± 2.89 a 17.44 ± 0.65 b

17 ‒1 ‒1 ‒1 1 0.3243 0.0019 0.0142 0.0138 48.40 58.22

18 ‒1 ‒1 ‒1 1 0.3101 0.0014 0.0137 0.0116 46.02 55.67

47.21 ± 1.68 a 56.95 ± 1.80 b

 

31  

19 1 ‒1 ‒1 1 0.4316 0.0369 0.0131 0.0153 67.88 77.47

20 1 ‒1 ‒1 1 0.4423 0.0272 0.0157 0.0138 68.16 79.39

68.02 ± 0.20 a 78.43 ± 1.36 b

21 ‒1 1 ‒1 1 0.4774 0.0068 0.0211 0.0083 70.17 85.70

22 ‒1 1 ‒1 1 0.4660 0.0104 0.0166 0.0076 68.38 83.65

69.28 ± 1.27 a 84.68 ± 1.45 b

23 1 1 ‒1 1 0.3182 0.0569 0.0039 0.0009 51.90 57.12

24 1 1 ‒1 1 0.3149 0.0573 0.0023 0.0013 51.35 56.53

51.63 ± 0.39 a 56.83 ± 0.42 b

25 ‒1 ‒1 1 1 0.4318 0.0049 0.0190 0.0150 64.30 77.51

26 ‒1 ‒1 1 1 0.4205 0.0047 0.0177 0.0140 62.43 75.49

63.37 ± 1.32 a 76.50 ± 1.43 b

27 1 ‒1 1 1 0.3195 0.0464 0.0145 0.0095 53.26 57.36

28 1 ‒1 1 1 0.3113 0.0505 0.0146 0.0085 52.57 55.88

52.92 ± 0.49 a 56.62 ± 1.05 b

29 ‒1 1 1 1 0.5193 0.0106 0.0199 0.0060 75.91 93.22

 

32  

30 ‒1 1 1 1 0.5269 0.0075 0.0198 0.0048 76.37 94.59

76.14 ± 0.33 a 93.91 ± 0.97 b

31 1 1 1 1 0.1434 0.0768 0.0018 0 30.32 25.74

32 1 1 1 1 0.1350 0.0758 0.0020 0 29.08 24.23

29.70 ± 0.88 a 24.99 ± 1.07 b

33 0 0 0 0 0.5054 0.0185 0.0188 0.0165 76.40 90.73

34 0 0 0 0 0.5033 0.0186 0.0182 0.0167 76.07 90.34

76.24 ± 0.23 a 90.54 ± 0.28 b

35 0 0 0 0 0.5081 0.0182 0.0185 0.0154 76.52 91.21

36 0 0 0 0 0.5114 0.0189 0.0185 0.0162 77.19 91.81

76.86 ± 0.47 a 91.51 ± 0.42 b

37 ‒2 0 0 0 0.0691 0.0058 0.0307 0 14.43 12.40

38 ‒2 0 0 0 0.0713 0.0080 0.0449 0 16.97 12.79

15.70 ± 1.80 a 12.60 ± 0.28 b

39 2 0 0 0 0 0.032 0.0206 0.0691 16.62 0.00

40 2 0 0 0 0 0.023 0.0171 0.0774 16.05 0.00

 

33  

16.34 ± 0.40 a 0 b

41* 0 ‒2 0 0 0 0 0.0036 0 0.49 0.00

42* 0 ‒2 0 0 0 0 0.0026 0 0.31 0.00

0.4 ± 0.13 a 0 b

43 0 2 0 0 0.4351 0.0299 0.0140 0.0045 66.05 78.10

44 0 2 0 0 0.4231 0.0353 0.0099 0.0044 64.57 75.94

65.31 ± 1.05 a 77.02 ± 1.53 b

45 0 0 ‒2 0 0.4335 0.0028 0.0726 0.0052 70.22 77.82

46 0 0 ‒2 0 0.4243 0.0022 0.0646 0.0042 67.67 76.17

68.95 ± 1.8 a 77.00 ± 1.17 b

47 0 0 2 0 0.4448 0.0429 0.0142 0.0148 70.58 79.84

48 0 0 2 0 0.4315 0.0544 0.0091 0.0130 69.40 77.47

69.99 ± 0.83 a 78.66 ± 1.68 b

49 0 0 0 ‒2 0.4827 0.0302 0.0224 0.0117 74.72 86.65

50 0 0 0 ‒2 0.4898 0.0172 0.0220 0.0111 73.77 87.92

74.25 ± 0.67 a 87.29 ± 0.90 b

 

34  

51 0 0 0 2 0.4894 0.0156 0.0559 0.0034 77.11 87.86

52 0 0 0 2 0.4979 0.0110 0.0430 0.0047 76.03 89.38

76.57 ± 0.76 a 88.62 ± 1.07 b

53 0 0 0 0 0.5094 0.0196 0.0185 0.0171 77.13 91.44

54 0 0 0 0 0.5063 0.0189 0.0177 0.0151 76.23 90.89

76.68 ± 0.64 a 91.17 ± 0.39 b

* Outliers which are not included in the RSM model.

a Values are expressed as mean ± standard deviation (n = 2) for the total monosaccharide yield (Ytm).

b Values are expressed as mean ± standard deviation (n = 2) for the mannose yield (Ymy).

 

35  

Table 4 ANOVA for regression models of total monosaccharide yield (Ytm) and mannose

yield (Ymy).

Source Sum of squares DF Mean square F-value p-Value

Total monosaccharide yield (Ytm)

Model 17866.63 14 1276.19 69.63 < 0.0001*

Residual 659.79 36 18.33

Pure Error 45.46 27 1.68

R2adj 0.9505

R2pred 0.9227

Mannose yield (Ymy)

Model 34479.65 14 2462.83 89.23 < 0.0001*

Residual 993.59 36 27.60

Pure Error 41.11 27 1.52

R2adj 0.9611

R2pred 0.9392

* Significant values.

 

36  

Table 5 ANOVA and regression coefficient for linear, quadratic and interactive terms of

total monosaccharide yield (Ytm) and mannose yield (Ymy).

Source Regression coefficient F-value p-Value

Total monosaccharide yield (Ytm)

Intercept 76.7

Linear

x1 (temperature) - 4.22 46.68 < 0.0001*

x2 (acid concentration) - 1.69 5.04 0.0310*

x3 (reaction time) - 1.53 4.75 0.0360*

x4 (substrate: solvent ratio) 0.63 1.04 0.3153

Quadratic

x12 - 15.27 528.47 < 0.0001*

x22 - 2.11 6.19 0.0176*

x32 - 1.91 8.24 0.0068*

x42 - 0.42 0.40 0.5294

Interaction

x1x2 - 10.74 201.36 < 0.0001*

x1x3 - 7.88 108.47 < 0.0001*

x1x4 - 0.3 0.16 0.6899

x2x3 - 1.62 4.57 0.0394*

x2x4 1.11 2.14 0.1521

 

37  

x3x4 0.4 0.28 0.6023

Mannose yield (Ymy)

Intercept 90.84

Linear

x1 (temperature) - 8.37 121.81 < 0.0001*

x2 (acid concentration) - 2.68 8.41 0.0063*

x3 (reaction time) - 2.25 8.81 0.0053*

x4 (substrate: solvent ratio) 0.71 0.87 0.3560

Quadratic

x12 - 20.93 659.46 < 0.0001*

x22 - 1.88 3.25 0.0797

x32 - 3.05 14.00 0.0006*

x42 - 0.52 0.40 0.5290

Interaction

x1x2 - 13.92 224.62 < 0.0001*

x1x3 - 10.68 132.29 < 0.0001*

x1x4 - 0.92 0.97 0.3303

x2x3 - 1.76 3.60 0.0657

x2x4 1.64 3.11 0.0865

x3x4 0.47 0.26 0.6124

* Significant variables.

 

39  

Table 6 Ridge analysis on the total monosaccharide yield (Ytm).

λ 

Radii Eigen value Predicted yield (%) Actual value Actual yield (%)

x1 x2 x3

ŷ

x1 x2 x3

ŷ

0.300 0.7169 0.1627 ‒0.5851 ‒0.3810 77.26 163.2539 0.3537 8.0948 66.35

0.185 1.5799 0.5061 ‒1.2771 ‒0.7803 77.70 170.1227 0.1807 6.0985 77.11

0.165 2.0090 0.6763 ‒1.6198 ‒0.9771 77.97 173.5253 0.0950 5.1146 10.20

 

 

40  

Figure 1  

 

 

41  

Figure 2  

 

 

42  

Figure 3(a)  

 

Figure 3(b)  

 

 

43  

Figure 3(c)  

Figure 3(d)  

 

 

44  

Figure 3(e)  

 

Figure 3(f)  

 

45  

Figure 4(a)  

 

Figure 4(b)  

 

 

46  

Figure 4(c)  

 

Figure 4(d)  

 

 

47  

Figure 4(e)  

 

Figure 4(f)  

 

48  

Graphical abstract: Microwave-assisted hydrolysis via dilute sulfuric acid is an effective method for the conversion of DPKC to fermentable sugars which potentially to be further transform into biofuels.

BiofuelsBiofuels

Fermentable sugars

 

 

 

49  

Highlights: 

 

Response Surface Methodology as optimization strategy for DPKC‐derived sugars.  Statistically optimized on total monosaccharide, 77.11% and mannose yield, 92.11%.  Ridge analysis was further conducted to verify the optimization parameters.  Established an effective microwave‐assisted hydrolysis on DPKC to sugars.