Monomeric carbohydrates production from olive tree pruning biomass: Modeling of dilute acid hydrolysis

Bioresource Technology 149 (2013) 149–154

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Monomeric carbohydrates production from olive tree pruning biomass: Modeling of dilute acid hydrolysis Juan G. Puentes a, Soledad Mateo a, Bruno G. Fonseca b, Inês C. Roberto b, Sebastián Sánchez a, Alberto J. Moya a,⇑ a b

Department of Chemical, Environmental and Material Engineering, University of Jaén, 23071 Jaén, Spain Department of Biotechnology, College of Chemical Engineering of Lorena, P.O. Box 116, Lorena, São Paulo, Brazil

h i g h l i g h t s  Olive tree pruning was converted to monomers by a one-step hydrolysis reaction.  Response surface methodology was applied for statistical modeling and optimization.  D-Xylose recovery of 85% was achieved at optimized conditions, confirming the model.  Low concentration of toxic substances provided a high quality D-xylose substrate.

a r t i c l e

i n f o

Article history: Received 25 July 2013 Received in revised form 9 September 2013 Accepted 11 September 2013 Available online 20 September 2013 Keywords: Hemicellulose D-Xylose D-Glucose Statistical modeling Biorefinery

a b s t r a c t Statistical modeling and optimization of dilute sulfuric acid hydrolysis of olive tree pruning biomass has been performed using response surface methodology. Central composite rotatable design was applied to assess the effect of acid concentration, reaction time and temperature on efficiency and selectivity of hemicellulosic monomeric carbohydrates to D-xylose. Second-order polynomial model was fitted to experimental data to find the optimum reaction conditions by multiple regression analysis. The monomeric D-xylose recovery 85% (as predicted by the model) was achieved under optimized hydrolysis conditions (1.27% acid concentration, 96.5 °C and 138 min), confirming the high validity of the developed model. The content of D-glucose (8.3%) and monosaccharide degradation products (0.1% furfural and 0.04% 5-hydroxymethylfurfural) provided a high quality subtract, ready for subsequent biochemical conversion to value-added products. Ó 2013 Elsevier Ltd. All rights reserved.

1. Introduction Currently, due to the rapid depletion of fossil resources, researches of alternative renewable energy sources, such as biomass, is taking great interest. The conversion of different biomass feedstocks to fuel and other products, i.e., the biorefinery concept of biomass processing, is being considered now as a more potential way to guarantee sustainable bio-based economy (Kamm and Kamm, 2007). The agro-based lignocellulosic materials, such as industrial crop residues and various grasses represent an abundant and cheap feedstock for lignocellulosic feedstock biorefinery. Among the largest agricultural crop waste generation in Spain may be mentioned the wheat straw and especially the olive tree pruning for its high concentration in southern. The olive tree is one of the most important crops in Spain. The pruning, operation that is usually applied to the branches and leaves after harvest, ⇑ Corresponding author. Tel.: +34 953 212780; fax: +34 953 212140. E-mail address: [email protected] (A.J. Moya). 0960-8524/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.biortech.2013.09.046

generates 5:0  106  5:5  106 t/year of lignocellulosic biomass (Moya et al., 2008). The large volumes of waste generated, together with the great environmental damage caused by its uncontrolled burning has suggested the possibility of exploiting this biomass resource to produce oligosaccharides and monomeric carbohydrates (Mateo et al., 2013a). In agro-based biomass the proportion of xylan may amount to 95% of the total non-cellulosic polysaccharides (Hurter, 1988). The monomeric D-xylose can be used as substrate for a wide variety of products production, such as xylitol, a five-carbon sugar alcohol that has attracted much attention because of its potential use in food and pharmaceutics (as a natural food sweetener, dental caries reducer, sugar substitute for diabetics, thin coating of tablets) (Granstrom and Leisola, 2009). Xylan isolation and depolymerization to D-xylose can therefore be an important first step in the complex biorefinery scheme. The dilute sulfuric acid hydrolysis under moderate reaction conditions was proved to be a reliable and easily performed low cost method for quantitative conversion of hemicellulosic xylan

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to monomeric sugars. Hemicellulose hydrolysis of different lignocellulosic materials by dilute sulfuric acid solutions has been reported, rice straw (Karimi et al., 2006;Roberto et al., 2003), sugarcane bagasse (Rodrigues et al., 2010), sunflower stalks (Du et al., 2012), Eucaliptus wood (Gutsch et al., 2012), cauliflower mushroom (Lee et al., 2013), corn fiber (Noureddini and Byun, 2010) or triticale, barley, oats, canola and mustard straws (Pronyk and Mazza, 2012). The results showed that the amount of sugars released during the hydrolysis treatment is dependent on the type of raw material used and operational conditions (reaction time, temperature and acid concentration) applied for the hydrolysis reaction. The minimal monosaccharide decomposition to furans and cellulose degradation can be achieved under optimized conditions, providing high effectiveness and selectivity of the overall hydrolysis process. D-Xylose production from olive tree pruning biomass has been studied using a low temperature dilute sulfuric acid hydrolysis. The response surface methodology (RSM) was employed for process modeling and optimization to maximize effectiveness and selectivity of xylan conversion to monomeric D-xylose within one-step reaction. 2. Methods 2.1. Raw material and chemical The olive tree pruning biomass, collected during the pruning season, consisted of leaves, branches and pieces of trunks from olive trees and was collected in an olive grove situated in Jaén, Spain. The material was air-dried, milled, screened to select the fraction of particles with a diameter 0.425–0.60 mm and homogenized in a single lot.

2.5 as eluant, flow rate of 0.8 cm3 min1 and 20 lL sample volume. The samples were previously diluted with ultrapure water and filtered through membranes HAWP 04700 with 0.45 lm pores. The concentrations of these compounds were calculated from calibration curves obtained from standard solutions. To calculate the cellulose and hemicellulose percentage and Klason lignin, the methodology proposed by Irick et al. (1988) was utilized and moisture composition by the TAPPI norm T12 os-75. Furthermore, the concentration of acid-soluble lignin was determined by the method described in a previous work (Mateo et al., 2013b), and ash composition using the procedure established by Browning (1967). Extractives (nonstructural components such as pectins, fatty matters, terpenes, phenols, tannins, uronic acids, etc.) were determined gravimetrically using a two-step sequential extraction process by Soxhlet to remove water and ethanol soluble material according to a procedure adapted from Sluiter et al. (2008). 2.4. Statistical modeling Response surface methodology (RSM) was employed for statistical data treatment and optimization of hydrolysis conditions by multiple regression analysis, using Statistica 6.0 (Statsoft, USA) software. The 23 central composite rotatable design (CCRD) with three independent variables at five different levels, six star (axial) points and five central points (total 19 runs) was adopted to find linear, quadratic and interaction effects of independent process variables on experimental responses. A second-order polynomial model was fitted to each set of experimental data to predict optimal reaction conditions by the following equation:

Y z ¼ b0 þ

3 X i¼1

2.2. Dilute acid hydrolysis

bi X i þ

3 3 X X bii X 2i þ bij X i X j i¼1

ð1Þ

i
where Y is a predicted response (xylan conversion or D-xylose/ ratio), b0 is an interception coefficient (regression coefficient at central point), bi are the linear coefficients; bii are the quadratic coefficients, bij are the interaction coefficients, Xi and Xj are the independent variables (temperature, time and acid concentration). The statistical significance of regression coefficients and effects was checked by analysis of variance (ANOVA) using the software STATISTICA 6.0 (Statsoft, USA). D-glucose

Hydrolysis experiments (replicated for each condition set) were carried out in a discontinuous reactor (2 dm3 volume) heated with silicon V50 from a bath. For this study, the reactor was loaded with 100 g (on dry basis) of olive tree pruning residue and 1 dm3 of sulfuric acid solution. The process variables were reaction time (20–220 min), temperature (86–103 °C) and acid concentration (0.2–1.8 mass%). The heating-up period for each experiment was around 5 min. Solid residue after hydrolysis was separated from solution by vacuum-filtration. The collected hydrolyzate was examined on degree of monosaccharide recovery and degradation products formed. Xylan conversion after hydrolysis (Y1) was defined as a ratio of D-xylose content in hydrolyzate to hemicellulosic content in olive tree pruning raw biomass. Y2 was defined as a ratio of D-xylose to D-glucose in hydrolyzate. 2.3. Analytical methods The quantification of carbohydrates (D-glucose, D-xylose and Larabinose) as well as acetic acid concentrations (in order to estimate the acetyl groups content) were determined by high-performance liquid chromatography (HPLC) using a WATERS instrument, in the conditions: a BIO-RAD Aminex HPX-87H (300  7.8 mm) column at 45 °C, 0.005 M sulfuric acid as eluant, flow rate of 0.6 cm3 min1, refraction index (RI) detector and 20 lL sample volume. Furfural and HMF were analyzed by HPLC using a WATERS instrument with a UV detector (at 276 nm), in the following conditions: a Waters Resolve C18 5 lm (300  3.9 mm) column at ambient temperature, acetonitrile/water (1/8 with 1% of acetic acid) degassed with addition of phosphoric acid for pH correction to

3. Results and discussion 3.1. Compositional analysis of raw material Detailed chemical analysis of olive tree pruning biomass used in this study revealed some general features typical for other industrially important agro-crops and woody species. The hemicellulose content represent 18.63  0.27 % of dry matter. The content of cellulose, as the principal chemical constituent, accounting for 33.85  0.76 of dry residue, does not differ greatly from wheat straw (29–35%), bamboo (26–43%) and sugarcane bagasse (32–44%), but somewhat lower in comparison with woods (38–50%) (Hurter, 1988). However, it should be mentioned that cellulose and hemicellulose contents depend on the methods used for the determination of these components. Olive tree pruning has less lignin (23.13  0.04 % of dry matter, being 18.93  0.08 acid-insoluble and 4.20  0.03 acid soluble) and more extractives (19.20  0.39 % of dry matter), in relation to woods (25–30% and 1–5%, respectively) (Atchison, 1987). The particularly high proportion of water-soluble substances, (17.39  0.28 % of dry matter), indicates the high accessibility and therefore reactivity of this biomass during chemical processing. The minerals (ash) comprise

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J.G. Puentes et al. / Bioresource Technology 149 (2013) 149–154 Table 1 Experimental data on formation and decomposition of monomeric sugars during hydrolysis of olive tree pruning. T (°C)

90

t (min)

60

180

95

60

180

100

60

180

a

c (%)

Yield (% on dry material) Glua

Xyl

Ara

AcA

F

HMF

0.5 1.0 1.5 0.5 1.0 1.5

2.54 ± 0.08 4.03 ± 0.09 6.48 ± 0.14 5.58 ± 0.09 9.01 ± 0.18 10.12 ± 0.34

0.77 ± 0.03 3.66 ± 0.09 8.73 ± 0.11 7.04 ± 0.08 13.83 ± 0.21 15.99 ± 0.31

3.20 ± 0.07 3.54 ± 0.06 3.54 ± 0.07 3.50 ± 0.05 3.78 ± 0.04 3.92 ± 0.07

1.74 ± 0.07 2.61 ± 0.09 2.94 ± 0.12 2.77 ± 0.05 3.46 ± 0.07 3.59 ± 0.04

Traces Traces 0.01 ± 0.00 0.01 ± 0.00 0.06 ± 0.02 0.13 ± 0.04

Traces Traces Traces 0.01 ± 0.01 0.03 ± 0.01 0.04 ± 0.01

0.5 1.0 1.5 0.5 1.0

3.42 ± 0.07 6.88 ± 0.13 10.50 ± 0.21 7.49 ± 0.11 10.53 ± 0.30 12.75 ± 0.27

1.97 ± 0.04 9.13 ± 0.09 13.20 ± 0.17 10.88 ± 0.24 15.92 ± 0.26 16.03 ± 0.20

3.23 ± 0.03 3.13 ± 0.09 3.30 ± 0.06 3.65 ± 0.07 3.28 ± 0.05 3.40 ± 0.05

2.60 ± 0.07 3.21 ± 0.06 3.62 ± 0.08 3.42 ± 0.06 3.50 ± 0.06 3.57 ± 0.05

0.03 ± 0.01 0.03 ± 0.01 0.05 ± 0.01 0.03 ± 0.01 0.08 ± 0.03 0.16 ± 0.04

0.02 ± 0.00 0.03 ± 0.01 0.04 ± 0.01 0.03 ± 0.01 0.03 ± 0.01 0.05 ± 0.01

0.5 1.0 1.5 0.5 1.0 1.5

4.56 ± 0.04 8.77 ± 0.11 10.31 ± 0.19 11.80 ± 0.26 9.96 ± 0.16 10.76 ± 0.17

4.02 ± 0.05 12.07 ± 0.16 14.60 ± 0.37 16.17 ± 0.29 16.09 ± 0.27 16.10 ± 0.32

3.27 ± 0.06 3.21 ± 0.04 2.97 ± 0.02 3.28 ± 0.03 2.40 ± 0.06 2.36 ± 0.07

3.00 ± 0.07 3.37 ± 0.06 3.71 ± 0.05 3.63 ± 0.04 3.53 ± 0.07 3.52 ± 0.05

0.01 ± 0.00 0.02 ± 0.00 0.06 ± 0.00 0.11 ± 0.01 0.12 ± 0.02 0.13 ± 0.04

0.02 ± 0.00 0.03 ± 0.01 0.04 ± 0.01 0.05 ± 0.01 0.06 ± 0.02 0.06 ± 0.01

Glu, Xyl, Ara, AcA, F, HMF as D-glucose, D-xylose, L-arabinose, acetic acid, furfural and 5-hydroxymethylfurfural, respectively.

Table 2 Range and levels of independent process variables, (X1: time (min); X2: temperature (°C); X 3 : acid concentration (%)), used in experimental design. Variable

X1 X2 X3

Range and levels a

1

0

+1

+a

19 86.6 0.2

60 90 0.5

120 95 1.0

180 100 1.5

221 103.4 1.8

4.62  0.28 % of dry matter, similar to wheat straw (4–9%), flax (2– 5%), kenaf (2–5%) and substantially higher of wood species (Hurter, 1988). 3.2. Effect of hydrolysis conditions on D-xylose formation and degradation Some series of preliminary hydrolysis experiments have been carried out under variable conditions of sulfuric acid concentration, c (0.5, 1.0 and 1.5%), temperature, T (90, 95 and 100 °C) and reaction time, t (60 and 180 min) to define the current levels (settings) of the independent process variables to be used in statistical experimental design for process modeling and optimization. As can be seen from Table 1, although significant amount of monomeric D-xylose can be recovered in solution after dilute-acid hydrolysis, the xylose recovery (yield) is highly dependent of applied reaction conditions. In general, increase in process severity (i.e., increase in acid concentration, temperature and duration), while accelerates xylan hydrolysis to D-xylose, intensifies substantially the secondary degradation reactions of monomeric sugars, thereby decreasing the final yield of this pentose in solution. Some other sugars, such as L-arabinose and D-glucose, particularly, are formed during dilute hydrolysis. Whereas L-arabinose take a part of heteroxylan structure, the presence of D-glucose is a result of cellulose degradation, namely, of its less ordered (amorphous) portion having the same (or close) reactivity than hemicelluloses (Fengel and Wegener, 1989). Like the furans, D-glucose can have harmful effect on subsequent D-xylose bioconversion, e.g., to xylitol. Hydrolysis selectivity should therefore assure the minimal concentration of D-glucose units in the hydrolyzate as well as a rich D-xylose substrate. Obviously, the temperature of 90 °C provides

more preserving conditions for the formed monosaccharides and only traces of furfural can be detected in reaction solution, Table 1. Limited cellulose degradation and acetic acid formation (due to splitting out of acid-liable acetic groups of heteroxylan) was also observed. At the same time, the D-xylose recovery in solution (as a main objective) was low under this process temperature, pointing to incomplete xylan conversion. By contrast, the drastic conditions of 100 °C caused substantial monosaccharide (basically Dxylose) degradation and cellulose depolymerization (up to 5.3% of furfural and 4% of D-glucose in solution), decreasing substantially D-xylose recovery after hydrolysis and lowering substrate quality as a whole, particularly under elevated acid concentration. Maximum D-xylose recovery (ca. 16% of dry material, or 98% of total D-xylose) was observed when olive tree pruning was hydrolyzed at 95 °C for 180 min in 1.5% acid solution or at 100 °C for 180 min. Under these conditions, the contents of furfural, 5-hydroxymethylfurfural, acetic acid and D-glucose were found as 0.13% 0.02, 0.06% 0.01, 3.56% 0.05 and 11.3% 1.2, respectively, pointing to fairly good quality of D-xylose hydrolyzate with low concentration of inhibitors. Since high values of D-xylose recovery were achieved (90% and more), the tested ranges of the principal independent process variables were used later in the statistical experimental design, to maximize the reaction outputs. 3.3. Hydrolysis modeling and optimization Statistical modeling and optimization of dilute sulfuric acid hydrolysis of olive tree pruning biomass was done using response surface methodology (RSM) (Myers et al., 2009). To optimize the effect of the principal independent variables (reaction time (X1), temperature (X2) and acid concentration (X 3 )) on efficiency of xylan conversion to D-xylose (Y1) and D-xylose/D-glucose ratio (Y2), the 23 central composite rotatable design (CCRD) was employed. The current settings of process variables, Table 2 were defined based on results of the preliminary experiments, discussed above. According to CCRD, the RSM experimental design matrix for 3 coded independent variables at 5 levels each, with 6 star (axial) points and 5 replicates at the central point (total 19 runs) was developed (Table 3) and the significant effects having the greatest impact on reaction outputs (Y1 and Y2) were calculated using experimental data.

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Table 3 Central composite rotatable design (CCRD) applied for olive tree pruning hydrolysis and the corresponding experimental responses on xylan conversion (Y1) and D-xylose/ D-glucose ratio (Y2) used for RSM modeling. Run N°

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15(C) 16(C) 17(C) 18(C) 19(C)

Coded variables

Responses

X1

X2

X3

Y1

Y2

1 1 1 1 +1 +1 +1 +1 a +a 0 0 0 0 0 0 0 0 0

1 1 +1 +1 1 1 +1 +1 0 0 -a +a 0 0 0 0 0 0 0

1 +1 1 +1 1 +1 1 +1 0 0 0 0 -a +a 0 0 0 0 0

0.05 0.54 0.25 0.90 0.57 0.98 0.99 0.99 0.13 0.98 0.61 0.95 0.35 0.99 0.85 0.86 0.85 0.86 0.87

0.30 1.35 0.88 1.42 1.66 1.58 1.38 1.50 0.83 1.43 1.42 1.57 1.05 1.45 1.52 1.51 1.52 1.52 1.52

The Pareto charts of standardized linear, quadratic and interaction effects of the independent process variables, sorted by their absolute magnitude in relation to the statistical significance p-level of 0.05 shown that the effectiveness of xylan conversion to D-xylose was mainly affected by time and acid concentration (linear effects) and in a lesser degree by reaction temperature and interaction effect between time and acid concentration. The D-xylose/D-glucose ratio was also primarily controlled by time and acid concentration (linear and quadratic effects) having no significance effects the temperature and its interactions. The statistical significance of estimated effects was checked by analysis of variance (ANOVA), Table 4. The low p-values of the main effects (p < 0.01) indicated high statistical significance of the estimated relations between variables within a 99% confidence interval. To define the optimum levels (conditions) of the independent process variables, the second-order polynomial model (Eq. (1)) was fitted to experimental data and the regression coefficients were calculated by multiple regression analysis. Two model equations were obtained using more statistically significant regression coefficients (p<0.05):

Y 1 ¼ 0:8579 þ 0:2357X 1  0:1067X 21 þ 0:1144X 2 þ 0:1923X 3  0:0661X 23  0:0913X 1 X 3

ð2Þ

Y 2 ¼ 1:5187 þ 0:4656X 1  0:2825X 21 þ 0:0794X 2 þ 0:3372X 3  0:1977X 23  0:2525X 1 X 2  0:3875X 1 X 3

ð3Þ R2adj

2

The regression coefficients obtained (R = 0.97 and = 0.95 for Y1, and R2 = 0.94 and R2adj = 0.89 for Y2) and the sum of the squares of the differences between the values of Y i and the average Y i (Total SS) 1.756 for Y1 and 2.069 for Y2 confirm the goodness of the model. Fig. 1 shows the 3D response surfaces and the corresponding contour plots constructed on the basis of Eqs. (2) and (3) and illustrate the modeled effects of independent variables on reaction outputs. The response surfaces for xylan conversion (Fig. 1 top), having some maximum values (stationary points) near the center point of the experimental design, allow locating and characterizing the optimum responses. The effect of reaction temperature and time on xylan conversion is illustrated in Fig. 1(a) (top). At fixed acid concentration set at 1% as a center point of statistical experimental design, the maximum D-xylose yield can be obtained around the maximum values of this variables. The desirable ranges of acid concentration and reaction time at constant temperature of 95 °C set as a center point are particularly notable in Fig. 1(b) (top). It can be seen that a concentration range of 1.0–1.5% and time 120–180 min maximize the D-xylose recovery during hydrolysis. Finally, Fig. 1(c) (top) shows that maximum reaction temperature and acid concentration (100 °C and 1.5%, respectively), when the reaction time was kept constant at 120 min, were the best conditions to D-xylose recovery. The response surfaces for D-xylose/D-glucose ratio (Fig. 1 bottom) are similar to those for the xylan conversion, with maximum values encountered at various combinations of independent variables. As can be seen from Fig. 1(a) (bottom), keeping fixed acid concentration at 1% as a center point, the maximum D-xylose/Dglucose ratio is obtained during prolonged reaction time (180 min) decreasing lighting when more time is employed. Similarly, at fixed time of 120 min, the higher values of Y2 are obtained at 1.5% acid concentration, Fig. 1(c) (bottom). However, based on Fig. 1(b) (bottom) it can be seen a maximum Y2 zone at acid concentration range around 1.0% and time 120 min. This suggests the possibility of maximizing this response on the basis of ridge maximum and canonical analysis. Partial differentiation of the multivariate function described by Eq. 3 was done to find a critical value of the independent process variables for D-xylose/D-glucose ratio:

@Y 2 ¼ 0:4656  0:5651X 1  0:2525X 2  0:3875X 3 ¼ 0 @X 1

ð4Þ

@Y 2 ¼ 0:0794  0:2525X 1 ¼ 0 @X 2

ð5Þ

Table 4 ANOVA of estimated linear (L), quadratic (Q) and interaction effects for xylan conversion (Y1) and D-xylose/D-glucose ratio (Y2). Factor

(1) Temperature (L) Temperature (Q) (2) Time (L) Time (Q) (3) Concentration (L) Concentration (Q) 1L by 2L 1L by 3L 2L by 3L a

E. e. Estimated effect.

Y1

Y2

E. e.a

t-Test

F-test

p

E. e.a

t-Test

F-test

p

0.4715  0.2134 0.2287  0.0543 0.3846  0.1321  0.0325  0.1825  0.0625

12.2627  5.5498 5.9487  1.4128 10.0034  3.4353  0.6469  3.6329  1.2441

150.3751 30.7999 35.3874 1.9961 100.0684 11.8015 0.4185 13.1977 1.5479

0.0000 0.0004 0.0002 0.1913 0.0000 0.0074 0.5338 0.0055 0.2449

0.4143  0.2639 0.0282  0.0058 0.2860  0.1790  0.1650  0.3000 0.0100

11.3719  7.2413 0.7729  0.1588 7.8493  4.9128  3.4663  6.3023 0.2101

56.9628 20.9691 1.6574 0.1570 29.8862 10.2654 9.8151 23.1161 0.9246

0.0000 0.0000 0.4594 0.8773 0.0000 0.0008 0.0071 0.0001 0.8383

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Fig. 1. Response surfaces and contour plots of modeled xylan conversion to D-xylose (top) and D-xylose/D-glucose ratio (bottom) as a function of: (a) reaction time (t, min) and reaction temperature (T, °C) at fixed acid concentration of 1% set as a central point (b) reaction time and acid concentration (c, %) at fixed temperature of 95 °C set as a central point (c) reaction temperature and acid concentration at fixed reaction time of 120 min set as a central point.

Fig. 2. Mass balance flow diagram for acid hydrolysis of olive tree pruning biomass performed under optimized conditions designed for hydrolysis process.

@Y 2 ¼ 0:3372  0:3875X 1  0:3954X 3 ¼ 0 @X 3

ð6Þ

The following critical condition set was obtained after resolution of Eqs. (4)–(6): reaction time of 138.2 min, reaction temperature of 96.6 °C, sulfuric acid concentration of 1.27% and a maximum expected D-xylose/D-glucose ratio of 1.696 which correspond to a xylan conversion of 0.849 (85% of monomeric D-xylose recovery in solution). To validate the developed statistical model, the duplicated control experiments were performed under established optimal conditions. The obtained experimental data on xylan conversion (0.851  0.007, or 13.76 g D-xylose/100 g dry material) and D-xylose/ D-glucose ratio (1.7  0.4, with 8.32 g D-glucose/100 g dry material) were the same as predicted by the model. The resulting hydrolyzate revealed low concentration of toxic substances (furfural 0.11 g, 5-hydroxymethylfurfural 0.04 g, and acetic acid 3.78 g per 100 g of dry biomass) providing the highest quality of substrate for subsequent (bio)chemical processing.

The mass balance flow diagram, summarizing the yields of the principal structural components (cellulose, xylan and lignin) of olive tree pruning material during acid hydrolysis (performed under optimized conditions), is shown in Fig. 2. 4. Conclusions Low temperature dilute sulfuric acid hydrolysis was very effective to convert olive tree pruning biomass to monomeric sugars, providing a quality substrate for subsequent (bio)chemical processing. The statistical modeling, using RSM, made possible to identify the main factors of the hydrolysis process affecting efficiency and selectivity of xylan conversion to D-xylose and to define the critical set of reaction conditions for D-xylose/D-glucose ratio. Under these reaction conditions (time 138.2 min, temperature 96.6 °C and sulfuric acid concentration 1.27%), a xylan conversion of 0.85 and a D-xylose/D-glucose ratio of 1.7 was achieved, with limited inhibitors formation.

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