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Optimization of Alkaline and Dilute Acid Pretreatment of Agave Bagasse by Response Surface Methodology.

Ávila-Lara AI, Camberos-Flores JN, Mendoza-Pérez JA, Messina-Fernández SR, Saldaña-Duran CE, Jimenez-Ruiz EI, Sánchez-Herrera LM, Pérez-Pimienta JA - Front Bioeng Biotechnol (2015)

Bottom Line: Another important effect that need to be studied is the use of a high solids pretreatment (≥15%) since offers many advantaged over lower solids loadings, including increased sugar and ethanol concentrations (in combination with a high solids saccharification), which will be reflected in lower capital costs; however, this data is currently limited.Subsequently enzymatic hydrolysis was performed using Novozymes Cellic CTec2 and HTec2 presented as total reducing sugar (TRS) yield.The optimum conditions were determined for AL pretreatment: 1.87% NaOH concentration, 50.3 min and 13.1% solids loading, whereas DA pretreatment: 2.1% acid concentration, 33.8 min and 8.5% solids loading.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical Engineering, Universidad Autónoma de Nayarit , Tepic , Mexico.

ABSTRACT
Utilization of lignocellulosic materials for the production of value-added chemicals or biofuels generally requires a pretreatment process to overcome the recalcitrance of the plant biomass for further enzymatic hydrolysis and fermentation stages. Two of the most employed pretreatment processes are the ones that used dilute acid (DA) and alkaline (AL) catalyst providing specific effects on the physicochemical structure of the biomass, such as high xylan and lignin removal for DA and AL, respectively. Another important effect that need to be studied is the use of a high solids pretreatment (≥15%) since offers many advantaged over lower solids loadings, including increased sugar and ethanol concentrations (in combination with a high solids saccharification), which will be reflected in lower capital costs; however, this data is currently limited. In this study, several variables, such as catalyst loading, retention time, and solids loading, were studied using response surface methodology (RSM) based on a factorial central composite design of DA and AL pretreatment on agave bagasse using a range of solids from 3 to 30% (w/w) to obtain optimal process conditions for each pretreatment. Subsequently enzymatic hydrolysis was performed using Novozymes Cellic CTec2 and HTec2 presented as total reducing sugar (TRS) yield. Pretreated biomass was characterized by wet-chemistry techniques and selected samples were analyzed by calorimetric techniques, and scanning electron/confocal fluorescent microscopy. RSM was also used to optimize the pretreatment conditions for maximum TRS yield. The optimum conditions were determined for AL pretreatment: 1.87% NaOH concentration, 50.3 min and 13.1% solids loading, whereas DA pretreatment: 2.1% acid concentration, 33.8 min and 8.5% solids loading.

No MeSH data available.


(A) Predicted vs. actual TRS yield of alkaline-pretreated AGB. (B) Predicted vs. actual TRS yield of dilute acid pretreated AGB.
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Figure 1: (A) Predicted vs. actual TRS yield of alkaline-pretreated AGB. (B) Predicted vs. actual TRS yield of dilute acid pretreated AGB.

Mentions: In the same way, the final equations for DA pretreatment were as follows:(4)TRS yield=427.27−5.87×A+0.26×B−12.80×C−13.65×AB+2.19×AC+     2.92×BC−27.48×A2−11.45×B2−0.62∗C2(5)TRS yield=305.8687+137.0487×Acid+2.1816×Time−2.4166×Solids−     0.5917×Acid×Time+0.3231×Acid×Solids+0.0133×Time×Solids−384832×     Acid2−0.0154×Time2−0.0097×Solids2where A, B, and C are catalyst concentration (NaOH for AL and H2SO4 for DA), retention time and solids loading, respectively. An analysis of variance (ANOVA) was performed to test the significance of the developed model and the results are presented for AL and DA pretreatment in Tables 3 and 4, respectively. If a p-value (also known as the Prob > D-value) is lower than 0.05 a model in considered significant, indicating only a 5% chance that their respective model could occur due to noise. For both pretreatments, their models effectively describes the response nevertheless the AL pretreatment model have a lower p-value (0.0003) than the DA pretreatment model (0.0247). In addition, the Prob > F values for each model term in AL pretreatment suggest that A, C, and A2, meanwhile for DA pretreatment suggest that only A2 are the model terms that have significant effects on the TRS yield. To determine the suitability of the model, the lack of fit test was used, which indicated an insignificant lack of fit with an F-value of 0.1393 and 0.3009 for AL and DA pretreatment, respectively. The coefficient of determination (R2) of the pretreatment models was 0.9151 for AL and 0.7270 and for DA, implying a good and average correlation between the observed and predicted values of AL and DA respectively, as shown in Figures 1A,B. Finally, the quadratic models developed for AL and DA pretreatment are appropriate for predicting TRS yield under different pretreatment conditions within the range used in the present study.


Optimization of Alkaline and Dilute Acid Pretreatment of Agave Bagasse by Response Surface Methodology.

Ávila-Lara AI, Camberos-Flores JN, Mendoza-Pérez JA, Messina-Fernández SR, Saldaña-Duran CE, Jimenez-Ruiz EI, Sánchez-Herrera LM, Pérez-Pimienta JA - Front Bioeng Biotechnol (2015)

(A) Predicted vs. actual TRS yield of alkaline-pretreated AGB. (B) Predicted vs. actual TRS yield of dilute acid pretreated AGB.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4585156&req=5

Figure 1: (A) Predicted vs. actual TRS yield of alkaline-pretreated AGB. (B) Predicted vs. actual TRS yield of dilute acid pretreated AGB.
Mentions: In the same way, the final equations for DA pretreatment were as follows:(4)TRS yield=427.27−5.87×A+0.26×B−12.80×C−13.65×AB+2.19×AC+     2.92×BC−27.48×A2−11.45×B2−0.62∗C2(5)TRS yield=305.8687+137.0487×Acid+2.1816×Time−2.4166×Solids−     0.5917×Acid×Time+0.3231×Acid×Solids+0.0133×Time×Solids−384832×     Acid2−0.0154×Time2−0.0097×Solids2where A, B, and C are catalyst concentration (NaOH for AL and H2SO4 for DA), retention time and solids loading, respectively. An analysis of variance (ANOVA) was performed to test the significance of the developed model and the results are presented for AL and DA pretreatment in Tables 3 and 4, respectively. If a p-value (also known as the Prob > D-value) is lower than 0.05 a model in considered significant, indicating only a 5% chance that their respective model could occur due to noise. For both pretreatments, their models effectively describes the response nevertheless the AL pretreatment model have a lower p-value (0.0003) than the DA pretreatment model (0.0247). In addition, the Prob > F values for each model term in AL pretreatment suggest that A, C, and A2, meanwhile for DA pretreatment suggest that only A2 are the model terms that have significant effects on the TRS yield. To determine the suitability of the model, the lack of fit test was used, which indicated an insignificant lack of fit with an F-value of 0.1393 and 0.3009 for AL and DA pretreatment, respectively. The coefficient of determination (R2) of the pretreatment models was 0.9151 for AL and 0.7270 and for DA, implying a good and average correlation between the observed and predicted values of AL and DA respectively, as shown in Figures 1A,B. Finally, the quadratic models developed for AL and DA pretreatment are appropriate for predicting TRS yield under different pretreatment conditions within the range used in the present study.

Bottom Line: Another important effect that need to be studied is the use of a high solids pretreatment (≥15%) since offers many advantaged over lower solids loadings, including increased sugar and ethanol concentrations (in combination with a high solids saccharification), which will be reflected in lower capital costs; however, this data is currently limited.Subsequently enzymatic hydrolysis was performed using Novozymes Cellic CTec2 and HTec2 presented as total reducing sugar (TRS) yield.The optimum conditions were determined for AL pretreatment: 1.87% NaOH concentration, 50.3 min and 13.1% solids loading, whereas DA pretreatment: 2.1% acid concentration, 33.8 min and 8.5% solids loading.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical Engineering, Universidad Autónoma de Nayarit , Tepic , Mexico.

ABSTRACT
Utilization of lignocellulosic materials for the production of value-added chemicals or biofuels generally requires a pretreatment process to overcome the recalcitrance of the plant biomass for further enzymatic hydrolysis and fermentation stages. Two of the most employed pretreatment processes are the ones that used dilute acid (DA) and alkaline (AL) catalyst providing specific effects on the physicochemical structure of the biomass, such as high xylan and lignin removal for DA and AL, respectively. Another important effect that need to be studied is the use of a high solids pretreatment (≥15%) since offers many advantaged over lower solids loadings, including increased sugar and ethanol concentrations (in combination with a high solids saccharification), which will be reflected in lower capital costs; however, this data is currently limited. In this study, several variables, such as catalyst loading, retention time, and solids loading, were studied using response surface methodology (RSM) based on a factorial central composite design of DA and AL pretreatment on agave bagasse using a range of solids from 3 to 30% (w/w) to obtain optimal process conditions for each pretreatment. Subsequently enzymatic hydrolysis was performed using Novozymes Cellic CTec2 and HTec2 presented as total reducing sugar (TRS) yield. Pretreated biomass was characterized by wet-chemistry techniques and selected samples were analyzed by calorimetric techniques, and scanning electron/confocal fluorescent microscopy. RSM was also used to optimize the pretreatment conditions for maximum TRS yield. The optimum conditions were determined for AL pretreatment: 1.87% NaOH concentration, 50.3 min and 13.1% solids loading, whereas DA pretreatment: 2.1% acid concentration, 33.8 min and 8.5% solids loading.

No MeSH data available.