Revista Mexicana de Ingeniería Química
Vol. 13, No. CONTENIDO
3 (2014) 765-778
Volumen 8, número 3, 2009 / Volume 8, number 3, 2009
OPTIMIZATION OF ENZYMATIC SACCHARIFICATION OF WHEAT STRAW IN A
MICRO-SCALE SYSTEM BY RESPONSE SURFACE METHODOLOGY

´ 213 Derivation and application of the Stefan-Maxwell equations ´
´
OPTIMIZACION DE LA SACARIFICACION ENZIMATICA DE PAJA DE TRIGO EN
´
´
(Desarrollo y aplicación las ecuaciones de Stefan-Maxwell)
MICROESCALA A TRAVESdeDE LA METODOLOGIA DE SUPERFICIE DE
Stephen Whitaker
RESPUESTA
C. Molina1∗ , A. S´ nchez2 , A. Seraf´n-Mu˜ oz3 y J. Folch-Mallol4 a ı n de Guanajuato - Guanajuato, Depto. de Ingenier´a Qu´mica, Noria Alta s/n, 36050 Guanajuato, ı ı
245 Modelado de la biodegradaciónGto., M´ xico. lodos de hidrocarburos totales del petróleo en biorreactores de e 2 Centro de Investigaci´ n y de Estudios Avanzados del IPN, Unidad de Ingenier´a Avanzada. Av. del Bosque 1145, o intemperizados en suelos y sedimentos ı Colonia el Baj´o, Zapopan, 45019, Jalisco, M´ xico. ı e
(Biodegradation modeling of sludge bioreactors of total petroleum hydrocarbons weathering in soil
3 Universidad de Guanajuato - Guanajuato, Depto. de Ingenier´a Ambiental, Av. Ju´ rez 77, Zona Centro, 36000, ı a and sediments)
Guanajuato, Gto., M´ xico. e S.A. Medina-Moreno, S. Huerta-Ochoa,
L.
4 Universidad Aut´ noma del Estado de Morelos, CentroC.A. Lucho-Constantino, enAguilera-Vázquez,ıA. Jiménezo de Investigaci´ n Biotecnolog´a, Cuernavaca, Morelos, o González y M. Gutiérrez-Rojas
M´ xico. e 259 Crecimiento, sobrevivencia y adaptación de Bifidobacterium infantis a condiciones ácidas
Received October 31, 2013; Accepted July 2, 2014
1 Universidad

Biotecnología / Biotechnology

(Growth, survival and adaptation of Bifidobacterium infantis to acidic conditions)

Abstract

L. Mayorga-Reyes, P. Bustamante-Camilo, A. Gutiérrez-Nava, E. Barranco-Florido y A. Azaola-

Espinosa
This paper studies the combined effects of temperature, pH and enzyme-substrate ratio (E/S R ) on hydrolysis yield and
265 in a microscale system in order to maximize enzymatic hydrolysis of pretreated wheat straw specific reaction rate (S RV )Statistical approach to optimization of ethanol fermentation by Saccharomyces cerevisiae in the
(WS). The WS was pretreated by of Valfor® zeolite NaA Enzymatic complex Accellerase 1500T M was used for hydrolysis presence alkaline-peroxide. assays. Using response surface methodology, optimal parameter values were determined. A complete enzymatic kinetic
(Optimización estadística de la fermentación etanólica de Saccharomyces cerevisiae en presencia de of the hydrolysis reaction was obtained in 10 h. The optimal value of reducing sugars concentration (RSC ), given by the zeolita Valfor® zeolite NaA) model, was 5.97 mg/mL and the corresponding yield was 61.73%. The maximum yield for the WS hydrolysis was 61.73%
G. Inei-Shizukawa, H. A. Velasco-Bedrán, G. F. Gutiérrez-López and H. Hernández-Sánchez and was achieved at a temperature of 52.0°C, pH 4.6, and a E/S R of 2.1 mL of Accellerase 1500T M /g of cellulose. The
S RV was 4.80 U/mg and was obtained with the following conditions: pH 5.0, temperature of 48.5°C and an E/S R of 0.19
Ingeniería de procesos / Process engineering mL/g. A quadratic polynomial equation for predicting the hydrolysis yield was developed. The confirmation experiment
271 Localización de una planta industrial: Revisión crítica y adecuación de los criterios empleados en showed a final value for RS C of 5.98 ± 0.81 mg/mL. This result indicates a % error of 0.33. The experimental results were esta decisión in good agreement with predicted value.
(Plant site selection: Critical review and adequation criteria used in this decision)

Keywords: enzymatic saccharification,R.L. Romero y G.A. Pérez surface methodology, microscale system.
J.R. Medina, wheat straw, response

Resumen
El presente trabajo estudia la hidr´ lisis de paja de trigo utilizando un sistema de microreacci´ n. El M´ todo de Superficie o o e de Respuesta se utiliz´ para estudiar los efectos combinados de la temperatura, el pH y la relaci´ n enzima-sustrato (RE/S ) o o sobre la hidr´ lisis enzim´ tica y la velocidad espec´fica de reacci´ n VER . El sustrato fue paja de trigo pretratada de forma o a ı o alcalino-oxidativa. El extracto enzim´ tico utilizado fue Accellerase 1500T M . El tiempo de obtenci´ n de una cin´ tica de a o e ´ la hidr´ lisis enzim´ tica completa fue de 10 h. El valor optimo de la concentraci´ n de az´ cares reductores (C AR ) arrojado o a o u por el modelo fue de 5.97 mg/mL y el rendimiento correspondiente fue de 61.73%. Estos valores fueron obtenidos con una
´
temperatura de 52.0°C, pH 4.6 y una RE/S de 2.1 mL de Accellerase 1500/g de celulosa. La VER optima fue de 4.80 U/mg y fue obtenida con una temperatura de 48.5°C, pH 5.0 y una RE/S de 0.19 mL/g. Se realiz´ un ensayo de confirmaci´ n o o en el que el valor predicho de C AR por el modelo fue de 5.96 mg/mL y el valor obtenido experimentalmente fue de 5.98 ±
0.81 mg/mL, indicando un error de 0.33%.
Palabras clave: hidr´ lisis enzim´ tica, paja de trigo, metodolog´a de superficie de respuesta, micro-escala, accellerase o a ı 1500T M .
∗ Corresponding author. E-mail: carlosmolina0@hotmail.com

Publicado por la Academia Mexicana de Investigaci´ n y Docencia en Ingenier´a Qu´mica A.C. o ı ı 765

Molina et al./ Revista Mexicana de Ingenier´a Qu´mica Vol. 13, No. 3 (2014) 765-778 ı ı

1

Introduction

Lignocellullosic materials can be considered as suitable feedstock for the production of bioethanol of second generation (2G) due to their availability worldwide, whose estimated production is around 1015 billion tons per year (Alfaro et al., 2009). In addition, these resources are considered renewable with a low carbon footprint (Areque et al., 2008).
The production of 2G bioethanol using biochemical platforms is considered as a strong alternative for commercial production because the current maturity of process technologies (IEA Biofuels for transport,
2004).
A biochemical platform comprises four fundamental steps: a) pretreatment, b) enzymatic hydrolysis, c) fermentation and d) downstream processes (Poonam and Anoop, 2011).
Several
investigations have been conducted in the last decade to maximize 2G bioethanol production, and one of the stages in which the investigations have focused the attention is on the saccharification step. Many authors have reported the enzymatic hydrolysis of a variety of substrates as rice straw (Ma et al., 2009), wheat straw (Benkun et al., 2009), perennial grass
(Karthika et al., 2012), corn cobs (Primo et al., 1995) and stover (Chen et al., 2014), wheat bran (Lequart et al., 1999), eucalyptus (Mart´n-Sanpedro et al., 2012), ı cedar (Toyokazu et al., 2012), straw bean (Gonz´ leza
Renter´a et al., 2011) and even synthetic biomass ı which was formed by the three main components of lignocellulose (Lin et al., 2010) such as cellulose, hemicellulose and lignin using an specific enzyme or an enzyme complexes extracted from microorganisms
(Lin et al., 2010; Grande and De Maria, 2012; Kawai et al., 2012; Song et al., 2012).
Enzymatic hydrolysis of cellulose to glucose is carried out by cellulase enzymes which are highly specific catalysts. The increase of hydrolysis yield to reducing sugars (RS) is well accepted to be a central issue to achieve commercial 2G ethanol production. Considerable attention has been given to the enzymatic hydrolysis process in order to maximize the production of RS (Saha et al., 2005;
Benkun et al., 2009). Response surface methodology
(RSM) has been used by Lin et al., (2010) in order to assay the saccharification of a synthetic biomass composed of cellulose, hemicellulose and lignin in order to understand the different behaviors of three biomass components in hydrolysis and their potential interaction. Benkun et al., (2009), showed the optimization of the hydrolysis of pretreated WS by alkaline-peroxide using a RSM with a central
766

composite design (CCD) in order to develop a useful tool to predict and optimize the hydrolysis process of
WS. Furthermore, many reports have shown that the operating variables that affect the hydrolysis process are pH, enzyme loading, substrate concentration, incubation time, and agitation speed (Brudecki et al.,
2012; Jeya et al., 2012; Liu et al., 2010; Ma et al.,
2009).
All the works mentioned above have been carried out at laboratory scale with test volume of 20 mL or higher, nevertheless, only few works have shown microscale saccharification in volume smaller than
1 mL. Microscale methods represent a technical advance to select the most appropriate combinations since many different cellulase complexes can be evaluated rapidly (Berlin et al., 2005; Chundawast et al., 2008). Furthermore, when reducing the volume assay, the amount of enzyme required for the tests is very little. Since recombinant enzymes obtained at lab-scale are often produced in small quantities, micro-scale methods are appropriate to evaluate the enzymatic performance of novel enzyme mixtures (Kim et al., 2009). Also, a great quantity of experiments can be realized simultaneously in a controlled system. Moreover, shaking of microwell plates is the simplest and most efficient way of promoting liquid mixing, and a rapid and efficient mixing during liquid addition to individual wells underpins the reproducibility of all bioprocess studies, in addition the loss of heat and mass are minimized allowing study purely kinetic aspects (Micheletti and
Lye, 2006). Characterization of the engineering environment in micro-well systems will ultimately underpin their use in bioprocess studies, ensuring the generation of reproducible, quantitative and, above all, scalable bioprocess information (Micheletti and Lye,
2006). Enzymatic microscale have been developed to evaluate the performance of different enzymes on enzymatic hydrolysis of wheat straw and the results obtained in enzymatic microscale were comparable with those from standard procedures in shake flasks
(Alvira et al., 2010).
The main objective of this research is to maximize the reducing sugar production using a microscale system. Furthermore, an experimental design of microscale saccharification in a volume smaller than
1 mL was not reported before for the hydrolysis of wheat straw and this is the contribution of this study. A CCD was used for the analysis of hydrolysis of pretreated WS by alkaline-peroxide using an enzymatic complex Accellerase 1500T M .
This enzymatic complex has been used by other

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authors in the hydrolysis of a variety of substrates as rice straw, wheat straw, eucalyptus, cedar and even in a mix of the principal components of lignocellulosic as cellulose, hemicelulose and lignin (Grande and de
Maria 2012, Kawai et al., 2012, Lin et al., 2010,
Pessani et al., 2011, Song et al., 2012), obtaining good results. 2
2.1

Material and methods
Substrate and enzyme

WS was obtained from local farmers in San Francisco del Rinc´ n, Guanajuato, M´ xico. It was cut to 3 mm o e in length, washed with distilled water to remove some impurities, and then dried at 70°C in an oven (Gravity convection Oven, ThermoFisher Scientific, Waltham,
Massachusetts, USA).
The commercial enzymatic complex AccelleraseT M
1500 was employed in this research. AccelleraseT M
1500 was a gift from Genencor International
Incorporation. AccelleraseT M 1500 (referred to as
Cellulase) is an enzyme complex which contains a mixture of cellulase, hemicellulase and βglucosidase. The RS C , was performed using different substrates to determine single activities. Overall cellulase activity was determined using Avicel and
Carboximeticelullose (Ghose, 1987).
Xylanase
activity was determined on xylan birch and xylan oat (Bailey and Nevalainen, 1981). An experiment with WS whit out pretreatment was realized according to Ghose (1987), in order to compare the effect of enzymatic complex over this not pretreated substrate.

2.2

Pretreatment peroxide of

WS

by

alkaline

Before enzymatic hydrolysis, the WS was pretreated by an alkaline peroxide method according to Pattel and Bhatt (1992), with a modified concentration of
NaOH. The pretreatment was accomplished in a stirred

flask at 150 rpm using a stirred and hot plate (Stirring hot plate, Corning®, Model PC-420D, Tewksbury,
USA), with an alkaline-oxidative (AO) solution with a solid-liquid ratio of 1:20. The solution was prepared with distilled water; pH was adjusted to 11.5 with a 10 M NaOH solution. Then, the WS was added and mixed. Then, hydrogen peroxide was added to the suspension until a concentration of 2% (v/v) was reached. The suspension was stirred at a temperature of 60°C for 6 h. The solid residue was filtered under vacuum, and washed with distilled water until pH 8 was reached. The pH was adjusted with a diluted solution of acetic acid until pH 7 was reached. The solid was dried at 70°C in a gravity convection oven until the weight remained constant for subsequent enzymatic hydrolysis. The chemical composition of pretreated WS is shown in Table 1.

2.3

Enzymatic Hydrolysis

2.3.1. Microscale procedure
Microscale enzymatic hydrolysis experiments were performed in sample conical tubes of 1.5 mL, with an effective reaction volume of 1 mL containing
1% (v/v) of pretreated WS, AccelleraseT M 1500 and
50 mM citric acid/citric sodium buffer according to
Benkun et al., 2009. The tubes were incubated in a thermomixer at 700 rpm, and this was called microscale system.
Samples of 50 µL, were taken from the reaction mixture at different times during a period of 600 minutes.
All samples were heated to 100°C immediately for 5 min to denature the enzymatic complex and cooled to room temperature. The experimental conditions were established according to dosage guidelines described in the product information for AccelleraseT M 1500.
The ranges of the values for the three factors were pH
4 to 6, temperature from 45 to 65ºC, and 0.6 to 1.8 mL of Accellerase 1500T M per gram of cellulose as shown in Table 2.

Table 1. Cellulose, hemicellulose and lignin content before and after pretreatment of WS. % of dry biomass (% DB).
Wheat straw (Raw)
Wheat straw (pretreated)

Cellulose
54
60.9

Hemicellulose
18.2
21.6

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Lignin
15.17
5.37

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Table 2. Values of the Variables for the Central Composite Design
Variable
pH
T (°C)
E/S R (ml/g)

√
− 2
4
45
0.1

Actual values of natural levels
√
−1
0
1
2
4.3
5
5.7
6
48
55
62
65
0.33 0.9 1.46
1.8

2.3.2. Flask assay procedure
Experiments in 500 mL scale were performed in
500 mL flask (Proculture Spinner Flasks, 500 mL,
Corning®, Tewksbury, MA, USA) placed over a hot plate equipped whit a temperature controller (Stirring hot plate, Corning®, Model PC-420D, Tewksbury,
USA). A 50 mM citric acid/citric sodium buffer was used according to Benkun et al., 2009. The percentage of pretreated WS was 1%. Samples were withdrawn at different times (0, 2, 4, 6, 8, 10, 12, 24 and 48 h), and analyzed by DNS method (Miller, 1959).

2.4

Analytical methods

The composition of WS with respect to cellulose, hemicellulose and lignin was determined using the
Goering and Van Soest method (Goering and Van
Soest, 1970). Specific activity evaluation of the enzyme was based on the determination of the protein released by bovine serum albumin following the Folin-Lowry technique (Lowry, 1951).
The
RSC was determined using the 3, 5-dinitrosalycilic acid DNS (Sigma-Aldrich, 10 g L−1 ), following the Miller method (Miller, 1959). The yield of enzymatic hydrolysis was calculated following the procedure of (Delgado et al., 2009): Considering a complete reaction, where the molecular weight (MW) of cellulose is 162*n (where n is the number of molecules of glucose in a molecule of cellulose) and the n molecules of glucose release have a MW of
180, the ratio of stoichiometric factors is 180/162 of released glucose per gram of cellulose. Then, the maximum concentration of RS that can be obtained can be calculated as following:
MCRS =

180
XWS CWS
162

(1)

where MCRS is the maximum concentration of RS that can be obtained (mg/mL), CWS is dried WS concentration in the enzymatic hydrolysis media
(mg/mL), and XWS is the fraction of cellulose +
768

hemicellulose in the dried substrate. Then, the yield can be calculated as follows:
Enzimatic hydrolysis yield =

RS C
× 100
MCRS

(2)

where RS C is the RS concentration in a specific experiment. In our study, CWS was 10 mg/mL and
XWS was 0.825 mg/mg, consequently the maximum concentration of RS that can be obtained is 9.16 mg/mL. The specific reaction velocity (S RV ) is the amount of RS produced in micromoles per gram of protein per minute (U/mg).
RS P
S RV =
(3)
pt
Where RS P is the amount of RS production in one hour, P is the amount of protein in mg present in the enzymatic complex, and t is the time in minutes.

3

Theory/calculation

A CCD was used to study the effects of pH, T and
E/S R on the hydrolysis yield. The experiments were carried out in triplicate as independent experiments in order to take into account the non-adjustable data and allow the calculations of the analysis of variance
(ANOVA). The ranges and levels of independent input variables are shown in Table 2. The model was built with five central points; the design must include center runs to provide reasonably stable variance of the predicted response. Generally, three or five center runs are recommended (Montgomery, 2009). The
RSP curves were obtained over the time course of a batch experiment. Table 2 shows the experimental parameters and experimental CCD levels used.
Three significant independent variables pH, temperature, and E/S R were included in this study, the mathematical relationship between the response of these variables and the independent variables can be presented by second-degree quadratic polynomial equation (Montgomery, 2009):

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Table 3. Experimental design and summary of results for dependent variables
Experiment no.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19

Independent variables
X1 X2
X3
4.3
4.3
4.3
4.3
5.7
5.7
5.7
5.7
4
6
5
5
5
5
5
5
5
5
5

48
48
62
62
48
48
62
62
55
55
45
65
55
55
55
55
55
55
55

RSC (mg/ml)
6.02 ± 0.31
6.09 ± 0.80
2.11 ± 0.21
4.24 ± 0.42
4.99 ± 0.16
4.55 ± 0.47
0.54 ± 0.07
0.78 ± 0.06
2.98 ± 0.36
2.94 ± 0.12
2.64 ± 0.13
1.33 ± 0.07
5.06 ± 0.45
4.32 ± 0.12
5.44 ± 0.02
4.85 ± 0.61
4.52 ± 0.69
4.54 ± 0.46
4.71 ± 0.64

0.33
1.46
0.33
1.46
0.33
1.46
0.33
1.46
0.9
0.9
0.9
0.9
0.1
1.8
0.9
0.9
0.9
0.9
0.9

4

63.18 ± 2.57
65.52 ± 5.04
21.82 ± 2.19
43.89 ± 4.41
51.57 ± 1.69
61.12 ± 2.97
5.61 ± 0.78
8.11 ± 0.63
32.26 ± 1.23
30.41 ± 1.28
27.31 ± 1.30
14.17 ± 0.72
39.17 ± 2.66
48.29 ± 4.01
55.29 ± 2.45
54.40 ± 2.24
57.57 ± 5.53
59.82 ± 4.16
51.93 ± 6.17

5.37 ± 0.60
3.64 ± 0.72
9.95 ± 1.58
1.91 ± 0.17
8.67 ± 0.31
1.38 ± 0.36
0.58 ± 0.06
0.16 ± 0.03
4.04 ± 0.43
2.11 ± 0.33
1.98 ± 0.20
0.90 ± 0.04
0.07 ± 0.01
1.67 ± 0.09
4.12 ± 0.77
3.91 ± 0.59
4.39 ± 0.99
5.17 ± 1.51
4.36 ± 0.36

Results and discussions

(4)

Effect of enzymatic complex on pure substrates and not pretreated WS

where Z is the predicted value, in this case RS C or
S RV , β0 is the intersection term, X1 is the pH, X2 is the temperature, X3 is the enzyme substrate ratio, β1 , β2 and β3 are the linear coefficients, β11 , β22 and β33 are the quadratic coefficients, β12 , β13 and β23 are the interactive coefficients and ε is the total error. The accuracy and general ability of the above polynomial model were evaluated by the coefficient of determination R2 and the adjusted R2 . The optimal values were obtained solving the regression Eq. 4 by the standard least square method and analyzing the response surface contour. The analysis of the response surface, the ANOVA and the optimal conditions were obtained using JMP 10.0.2 software. The significant effects on dependent variables were determined by ttest with a probability value (p-value) smaller than
0.05.

The effect of enzymatic complex on pure substrate and WS without pretreatment after 40 minutes are shown in Figure 1 and it is possible observe that the quantity of RS is higher when the enzymatic complex was used on CMC, avicel, xylan of oat and xylan of birch compared with WS without pretreatment after 40 min of reaction. The result founded after
240 min of reaction is even much lower than that founded with pure substrates. Is worth noting that the trial realized with not pretreated WS contained 5 times more enzymatic complex than that done with pure substrates. This result showed the need of a pretreatment prior to enzymatic assay. Lin et al., 2010, realized experiments with different composition of the principal components of lignocellulose (cellulose, hemicellulose and lignin), the results shown that a less content of lignin increases the enzymatic hydrolysis yield. 2
2
2
Z =β0 + β1 X1 + β2 X2 + β3 X3 + β11 X1 + β22 X2 + β33 X3

+ β12 X1 X2 + β13 X1 X3 + β23 X2 X3 + ε

4.1

Dependent variables
Yield (%)
S RV (U/mg)

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Molina et al./ Revista Mexicana de Ingenier´a Qu´mica Vol. 13, No. 3 (2014) 765-778 ı ı

Fig.
2.
Representative 2.plot of the enzymatic
Figure
hydrolysis in microscale assay, treatment 15 to 19.

Representative plot of the enzymatic hydrolysis in microscale assay, treatment 15 to 19.

Figure 1.

Fig. 1. Reducing sugars production after 40 min of an increase in cellulose content in pretreated WS

Reducing sugars production after 40 min of hydrolysis reaction of pure substrates (CMC, hydrolysis reaction of pure substrates (CMC, Avicel,
Avicel, Xylan oat and birch) and WS without pretreatment. Assay temperature 50°C. The would increase the level of reducing sugars obtained

Xylan oat and birch) and WSfor WS without pretreatment. from enzymatic saccharification, while a decrease in enzymatic complex was 5 times higher without pretreatment.

Assay temperature 50°C. The enzymatic complex was hemicellulose and lignin content could improve the

5 times higher for WS without pretreatment. efficiency of enzymatic hydrolysis of lignocellulosic

materials (Mussatto et al., 2007).

4.2

Pretreatment peroxide. of

WS

by

alkaline

4.3

WS was analyzed for chemical components after

alkaline-peroxide pretreatment.
The cellulose,

hemicellulose and lignin before and after pretreatment

are shown in Table 1. As can be seen in Table 1, the percent cellulose and hemicellulose content of

pretreated WS were increased from 54% to 60.9% and from 18.9% to 21.6% respectively. In contrast, the percent lignin content after alkaline peroxide pretreatment decreased from 15.17% to 5.37% thus removing 64.60% of lignin from the raw material.
The percentage of delignification is similar to that obtained by Benkun et al., (2009), which reached a
65.97% of delignification with 1.50% (w/v) of NaOH, at 150 rpm, 50 °C, for 6 h, using a solid:liquid ratio of 1:25 of WS pretreated by alkaline peroxide.
Also, the work presented by Sun et al., (2000), showed that rye straw pretreated by alkaline peroxide
(2% H2 O2 at pH 11.5 and 50 °C for 12 h) showed dissolution of 83.1% of original lignin and 70.0% of original hemicelluloses, which is higher percentage of delignification compared whit this work, neverthelees, the time used in this research is low and the percentage of delignification is acceptable according whit Benkun et al., (2009). In addition, Patel et al., (1992), optimized alkaline peroxide pretreatment for the delignification of raw straw obtaining a
62% lignin solubilization which also, is according to our research. It is important to mention, that

770

Kinetic studies of enzymatic hydrolysis in microscale system

Table 2, shows the experimental data basis for the model fitting, which consists of the experimental design and the summary of the results.
The
experiments were conducted in a random order.
Experimental results are averages of three independent experiments and their respective standard deviation.
Figure 2 shows the kinetic behavior, with error bars, of the saccharification process for the five central points of the CCD (experiments 15 to 19), with a X1 = 5,
X2 = 55°C and X3 = 0.9 mL/g respectively. The average of RSC at 600 min was 4.81 ± 0.57 mg/mL, with the corresponding yield of 49.69%. The other treatments show similar behavior, although rates of the various parameters measured and their maximum concentrations were different in each case. Figure
2 shows, that was possible to obtain a complete hydrolysis kinetic in 10 h and not in 72 h like the conventional experiments developed by other authors
(Benkun et al., 2009, Fujii et al., 2009), which is advantages in order to obtain kinetic data for the study of the enzymatic hydrolysis in a relative short time. Alvira et al., 2010 obtained a hydrolysis time of 72 h for microscale system and flask assays using
Acellerase 1000. Our results showed that is possible obtained relative short time for enzymatic hydrolysis in micro assays. The difference in the hydrolysis time in this research can be attributed to the use of a different enzymatic complex.

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Table 4. Analysis of Variance (ANOVA) for the Quadratic Model
RS C
Source

DF

SS

MS

F value

Probability (P) > F

model
Error
Lack of fit pure error
C. Total

9
47
5
42
56

13190.3
6257.1
5306.0
951.0
19447.3

1465.6
133.1
1061.2
22.6

11.0

< 0.001*

46.8

Table 5. Significance of the coefficients of Regression for RS C
Model term

Standard error

F value

p-value

Model constant pH T
E/S R pH*T pH* E/S R
T* E/S R pH*pH T*T
E/S R * E/S R

4.4

Parameter estimate
-98.1
17.3
2.3
1.0
-0.09
-0.38
0.04
-1.3
-0.02
-0.30

21.76
5.19
0.55
4.45
0.05
0.57
0.06
0.45
0.01
0.64

-4.37
3.33
4.22
0.22
-1.91
-0.66
0.67
-2.87
-4.26
-0.47

F ( 0.05). It is also observed that the full trajectory of enzymatic hydrolysis for both scales was reached at 10 h of operation. This was confirmed considering that the RS C in the time of 48 h (8.02 mg of RS/mL) is only 4% higher than that found at 10 h (7.7 mg/mL). Alvira et al., 2010, showed a comparison between microscale and 20 mL scale. Found that the development of the trajectory of the enzymatic hydrolysis in two scales was similar, however, the complete enzymatic trajectory was only reached after 72 h of operation.

MW
RS
MCRS
WS
XWS
CWS
RS C
S RV
RS P
P
t
T
E/S R
RSM

molecular weight reducing sugars maximum concentration of RS wheat Straw fraction of cellulose + hemicellulose in the dried substrate dried WS concentration in the hydrolysis media
RS concentration specific reaction velocity
RS production in one hour protein time temperature enzyme substrate ratio response surface methodology

References
Conclusion

Articles:

The efficiency of pretreatment of WS by alkaline peroxide was similar to that showed in similar works, obtained a percentage of delignification of 64.60%.
The decrease in the content of lignin could facilitate the process of enzymatic hydrolysis. The RSM was performed to investigate the enzymatic hydrolysis of pretreated WS for production of reducing sugars. The analysis of variance showed that pH and temperature and the square value of pH and temperature have a significant effect on the enzymatic hydrolysis yield.
Specific reaction velocity was affected significantly by pH and temperature and the interaction between pH and temperature. The hydrolysis of pretreated WS can be studied in a short time, since the reaction time was just 10 h. The enzyme kinetic hydrolysis for microscale and 500 mL scale was similar until reached
4 h of reaction. The regression equation predicted properly the value of the confirmation experiment.
This reaction system enables one to carry out a large number of experiments at a controlled temperature in an economic way.

Alfaro, A., Rivera, A., Perez, A., Y´ nez, R., a˜ Garc´a, J. C., and L´ pez, F. (2009) Integral ı o valorization of two legumes by autohydrolysis and organosolv delignification. Bioresourse
Technology 100, 440-445.
Alvira, P., Negro, M. J., S´ ez, F., & Ballesteros, M. a (2010). Application of a microassay method to study enzymatic hydrolysis of pretreated wheat straw. Journal of Chemical Technology &
Biotechnology 85, 1291-1297.
Araque, E., Parra, C., Freer, J., Contreras, D.,
Rodriguez, J., Mendonca, R., Baeza, J. (2008).
Evaluation of organosolv pretreatment for the conversion of Pinus radiate D. Don to ethanol.
Enzyme Microbiology Technology 43, 214-219.
Bailey MJ, Biely P and Poutanen K, (1991).
Interlaboratory testing of methods for assay of xylanase activity. Journal of Biotechnology 23,
257-270.

www.rmiq.org

775

Molina et al./ Revista Mexicana de Ingenier´a Qu´mica Vol. 13, No. 3 (2014) 765-778 ı ı

Benkun Q., Xiangrong C., Fei S., Yinhua W.
(2009). Optimization of enzymatic hydrolysis of wheat straw pretreated by alkaline peroxide using response surface methodology. Industrial and Engineering Chemistry Research 48, 73467353.
Berlin A, Maximenko V, Bra R, Kamg KY, Gilkes
N and Saddler J, A rapid microassay to evaluate enzymatic hydrolysis of lignocellulosic substrates. Biotechnology and Bioengineering
93, 880-886 (2005).
Brudecki, G., I. Cybulska, K. Rosentrater & J. Julson.
(2012). Optimization of clean fractionation processing as a pre-treatment technology for prairie cordgrass. Bioresourse Technology 107,
494-504.
Chen J., Zhang W., Zhang H., Zhang Q., Huang
H. (2014). Screw extrude steam explosion:
A promising pretreatment of corn stover to enhance enzymatic hydrolysis. Bioresource
Technology 161, 230-235.
Chundawat SPS, Balan V and Dale BE, (2008)
High-throughput microplate technique for enzymatic hydrolysis of lignocellulosic biomass. Biotechnology and Bioengineering
99, 1281-1294.
Delgado R., Castro A.J., V´ zquez M. A. (2009). a Kinetic assessment of the enzymatic hydrolysis of potato (Solanum tuberosum). LWT - Food
Science and Technology 42, 797-804.
Fujii, T., X. Fang, H. Inoue, K. Murakami & S.
Sawayama. (2009). Enzymatic hydrolyzing performance of Acremonium cellulolyticus and
Trichoderma reesei against three lignocellulosic materials. Biotechnology for Biofuels 2, 24.
Ghose TK, Measurement of cellulase activities.
(1987). Pure and Applied Chemistry 59, 257268.
Gonz´ lez-Renter´a S., Soto-Cruz N., Rutiagaa ı Qui˜ ones O., Medrano-Rold´ n, Rutiagan a Qui˜ ones J. and L´ pez-Miranda J. (2011). n o
Optimization of the enzymatic hydrolysis process of four straw bean varieties. Revista
Mexicana de Ingenier´a Qu´mica 10, 17-28 ı ı
Grande, P. M. and de Mar´a P. D. (2012). Enzymatic ı hydrolysis of microcrystalline cellulose in
776

concentrated seawater. Bioresource Technology
104, 799-802.
Jeya, M., D. Kalyani, S. S. Dhiman, H. Kim,
S. Woo, D. Kim & J. K. Lee.
(2012).
Saccharification of woody biomass using glycoside hydrolases from Stereum hirsutum.
Bioresource Technology 117, 310-6.
Karthika K., Arun A.B., Rekha P.D. (2012).
Enzymatic hydrolysis and characterization of lignocellulosic biomass exposed to electron beam irradiation. Carbohydrate Polymers 90,
1038-1045
Kawai T., Nakazawa N., Ida H., Okada S., Tani
J., Sumitani T., Kawaguchi W., Ogasawara
Y., Kobayashi Y. (2012). Analysis of the saccharification capability of high-functional cellulase JN11 for various pretreated biomasses through a comparison with commercially available counterparts. Journal of Industrial
Microbiology and Biotechnology 39, 1741-9.
Kim ES, Lee HJ, Bang WG, Choi IG and
Kim KH, Functional characterization of a bacterial expansin from Bacillus subtilis for enhanced enzymatic hydrolysis of cellulose.
Biotechnology and Bioengineering 102, 13421353 (2009).
Lequart C., Nuzillard J., Kurek B., Debeire P.
(1999). Hydrolysis of wheat bran and straw by an endoxylanase: production and structural characterization of cinnamoyl-oligosaccharides.
Carbohydrate Research 319, 102-111
Li, Y., Cui, F., Liu, Z., Xu, Y., Zhao, H.
(2007). Improvement of xylanase production by Penicillium oxalicum ZH-30 using response surface methodology. Enzyme and Microbial
Technology 40, 1381.
Lin, L., Yan R., Liu Y., & Jiang W. (2010).
In-depth investigation of enzymatic hydrolysis of biomass wastes based on three major components: cellulose, hemicellulose and lignin. Bioresource Technology 101, 8217-23.
Liu, Q., Cheng K., Zhang J., Li J., Wang G.
(2010). Statistical optimization of recycledpaper enzymatic hydrolysis for simultaneous saccharification and fermentation via central composite design. Applied Biochemistry and
Biotechnology 160, 604-12.

www.rmiq.org

Molina et al./ Revista Mexicana de Ingenier´a Qu´mica Vol. 13, No. 3 (2014) 765-778 ı ı

Lowry, O., Rosebrough, N., Farr, A. Lewis and
Randall, Rose J. (1951). Protein measurement with the Folin phenol reagent. Journal of
Biological Chemistry 193, 265-275.

Saha BC, Iten LB, Cotta MA, Wu YV. (2005). Dilute acid pretreatment enzymatic saccharifiaction and fermentation of wheat Straw to etanol.
Process Biochemistry 40, 3693-700.

M.G. Tabka, I. Herpo¨ l-Gimbert, F. Monod, M. e Asther, J.C. Sigoillot, Ma, H., Liu W., Chen
X., Wu Y., Yu Z. (2009). Enhanced enzymatic saccharification of rice straw by microwave pretreatment. Bioresource Technology 100,
1279-84.

Song, L., Siguier B., Dumon C., Bozonnet
S., O’Donohue M. (2012).
Engineering
better biomass-degrading ability into a GH11 xylanase using a directed evolution strategy.
Biotechnology for Biofuels 5, 3.
Sun,

Mart´n-Sampedro R., Eugenio M.E., Garc´a J.C., ı ı
L´ pez F., Villar J.C. Diaz M.J. (2012). Steam o explosion and enzymatic pre-treatments as an approach to improve the enzymatic hydrolysis of Eucalyptus globulus. Biomass and Bioenergy
42, 97-106
Micheletti M., and Lye G. J. (2006). Microscale bioprocess optimization. Current Opinion in
Biotechnology 17, 611-618.
Miller, G.L. (1959). Use of dinitrosalicylic acid reagent for determination of reducing sugar.
Analytical Chemistry 31, 426-428.
Mu,

Y., Wang, G., Yu, H. Q. (2006).
Response surface methodological analysis on biohydrogen production by enriched anaerobic cultures. Enzyme and Microbial Technology 38,
905.

Mussatto, S. I., Fernandes, M., Milagres, A. M. F.,
Roberto, I. C. (2007). Effect of hemicellulose and lignin on enzymatic hydrolysis of cellulose from brewer’s spent grain.
Enzyme and
Microbial Technology 43, 124.
Patel, M., Bhatt, R. (1992).
Optimization
of the alkaline peroxide pretreatment for the delignification of rice straw and its applications. Journal of Chemical Technology and Biotechnology 53, 253.
Poonam S. and Anoop S. (2011).
Production
of liquid biofuels from renewable resources.
Progress in Energy and Combustion Science 37,
52-68.
Primo E., Gil C.I., Garc´a F.J. (1995). Hydrolysis ı of corn-cob lignocellulosic residue from pentose preparation. Bioresource Technology 52, 1-4.

R., Fang, J., Tomkinson, J. (2000).
Delignification of rye straw using hydrogen peroxide. Industrial Crops and Products 12,
71.

Sun, Y., Cheng, J. (2002).
Hydrolysis of lignocellulosic materials for ethanol production: a review. Bioresource Technology 83, 1.
Toyokazu M., Seung-Hwan L., Seiichi I., Takashi
E. (2012).
Combined pretreatment using ozonolysis and wet-disk milling to improve enzymatic saccharification of Japanese cedar.
Bioresource Technology 126, 182-186.
Xu, Z., Wang, Q., Jiang, Z., Yang, X.-X., Ji, Y.
(2007). Enzymatic hydrolysis of pretreated soybean straw. Biomass and Bioenergy 31, 162.
Books chapters:
Fogler Scott. (2001). Fundamentos de reacciones enzim´ ticas, en Elementos de Ingenier´a de las a ı
Reacciones Qu´micas. Prentice Hall, M´ xico. P. ı e
383.
Goering, H. K., Van Soest, P. J. (1970). Forage fiber analysis (apparatus, reagent, procedure and some applications). In Agricultural Handbook no. 379; US Department of Agriculture:
Washington, DC, p 1.
Haaland, P. D. (1989). Separating signals from the noise.
In Experimental Design in
Biotechnology. Marcel Dekker: New York, p
61.
Montgomery D.C. (2009).
Response surface methods and designs, in: Design and Analysis of Experiments, 7th ed., Wiley, USA. Pp. 417480.
Internet:

www.rmiq.org

777

Molina et al./ Revista Mexicana de Ingenier´a Qu´mica Vol. 13, No. 3 (2014) 765-778 ı ı

IEA

778

Biofuels for transport-an international perspective. International Energy Agency (IEA)
(2004) http://www.iea.org/textbase/nppdf/free/
2004/biofuels2004.pdf

Accellerse 1500T M . Product information (2014). http://accellerase.dupont.com/fileadmin/user upload/live/accellerase/documents/DUP00413 ProdSheet 1500 web.pdf

www.rmiq.org