Eucalyptus globulus wood was subjected to autohydrolysis pretreatment at different severity factors. The pretreated materials were enzymatically saccharified at a substrate load of 10% (w/v) using a cellulase enzyme complex. Around 82-95% of original glucans were retained in the pretreated material, and the enzymatic hydrolysis yields ranged from 58% to 90%. The chemical and structural changes in the pretreated materials were investigated by microscopic (SEM, LSCM) and spectroscopic (2D-HSQC NMR and FT-IR) techniques. 2D-NMR results showed a reduction in the amounts of β-O-4 aryl-ether linkages and suggested the presence of newly condensed structures of lignin in the biomass pretreated at the more severe conditions. Furthermore, the microscopic analysis showed that lignin migrates out of the cell wall and re-deposits in certain regions of the fibers at the more severe conditions to form droplet-like structures and expose the cellulose surface. These changes improved the glucose yield up to 69%, on dry wood basis.

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In order to understand the relation between chemical composition, microscopic structure and enzymatic digestibility, different Eucalyptus globulus wood pretreated samples were examined. Pretreated materials obtained by steam explosion and autohydrolysis were compared with those obtained by organosolv and kraft processes. Chemical analyses of pretreated materials showed a decrease in the content of xylans, except in the kraft pulp. FT-IR spectra showed that the residual lignin in autohydrolysis pulp had experienced greater changes compared to those in steam explosion and organosolv pulps, whereas minor changes in lignin kraft pulp were observed. The fiber morphology indicated that autohydrolysis pretreatment was the most aggressive treatment. Reduction in the content of lignin and its redistribution on the fiber wall were confirmed through confocal laser microscopy. The formation of discrete lignin droplets deposited on the surface of the fibers was observed in all pretreatments, with a higher frequency in organosolv followed by steam explosion. A significant increase in enzymatic accessibility was achieved in organosolv, autohydrolysis and steam explosion pulps, due to xylans removal combined with lignin redistribution. Homogeneous lignin distribution and higher xylan content may be related to the low enzymatic hydrolysis efficiency in kraft pulp.

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Eucalyptus globulus wood chips were subjected to autohydrolysis pretreatment at 175ºC at three different residence times. Part of the recovered solids were submitted to alkaline extraction with NaOH solution to remove leachable lignin. The chemical composition of the fibrous material was analyzed by HPLC, Py-GCMS and 2D-NMR HSQC, while morphological changes were evaluated by SEM and LSCM. The pretreated materials were hydrolyzed with cellulases at a substrate loading of 10% (w/v) for up to 72 h. Glucose yields (based on dry wood) obtained in the enzymatic hydrolysis ranged between 38% and 65%, depending on reaction time in the autohydrolysis pretreatment. After the alkaline extraction, no significant change was observed in the yields in the enzymatic hydrolysis at 72 h, but at the lower severities, the initial rates of saccharification increased. The main effect of the hydrothermal pretreatment was removal of hemicelluloses, resulting in enriched cellulose pulps. SEM and LSCM images of the hydrothermal pretreated samples showed a disruption of the fiber surface, mainly in those samples obtained at the higher severity. Py-GC/MS and HSQC analysis showed that no major changes in the lignin structure occurred in the samples obtained by autohydrolysis and further alkaline extraction. By autohydrolysis at the higher severity (So=4.02), the lateral chains in lignin were cleaved and the formation of lignin droplets was observed. Hemicelluloses removal and lignin redeposition as droplets in certain regions of the fiber surface was associated with the higher accessibility of cellulose and the yield increase of the enzymatic hydrolysis.

BACKGROUND In the bioethanol production process it is necessary to know the physical and chemical characteristics of pretreated material which may affect the enzymatic hydrolysis as well as the carbohydrates potential for fermentation. In the present study, prediction models were developed with Fourier transformed near infrared (FT‐NIR) spectroscopy and multivariate analysis for the cellulose crystallinity index (CrI), saccharification and ethanol yield, and glucan, hemicellulose and lignin content. Prediction models were generated using Eucalyptus globulus and Pinus radiata samples from different pretreatments such as bio pretreatment, kraft process, steam explosion, organosolv and biorganosolv process. RESULTS The calibration models obtained by partial least‐squares (PLS), presented high coefficients of calibration and validation determination. The predictive ability of the calibration models developed was evaluated in a set of external samples. The properties were predicted with a prediction error (RMSEP) of 0.02, 1.4 g L−1, 2.0%, 0.9%, 1.0% and 1.9% for CrI, ethanol yield, saccharification, lignin, hemicellulose and glucan content, respectively. CONCLUSION These results suggest that it is possible to construct models for these properties with a database involving pulps from different pretreatments. NIR spectroscopy predictions provide useful and economic tools for rapid analysis of the large number of samples required in the assessment of bioethanol production processes. © 2014 Society of Chemical Industry

Lignocellulosic biomass (LB) has been recognized as potential raw for bioethanol production. To facility LB bioconversion a pretreatment is applied, followed by simultaneous or separated saccharification and fermentation (SSF or SHF, respectively) steps. Characterization of pretreated materials, needed to evaluate their ethanol yields, involves laborious and destructive methodologies. Therefore, saccharification is also time consuming and expensive step and some pretreated samples have not suitable characteristics to obtain high ethanol yields. Since bioethanol production aims to be a multivariable process respect to lignocellulosic resources, this work attempts to use NIR spectroscopy as alternative to wet chemical analysis to characterize samples from multiple pretreatments and lignocellulosic resources simultaneously and estimate their ethanol yield after a SSF process using multivariate calibration. Selection of suitable samples to obtain high ethanol yields using a classification method is also evaluated. Partial least squares (PLS) and discriminant partial least squares (PLS-DA) were used as calibration and classification techniques, respectively. Results showed ability of NIR spectroscopy to predict the chemical composition of samples and their ethanol yields, even if different lignocellulosic materials were used in the models, with low prediction errors and high correlation coefficients with reference methods (r>0,96) in PLS models and low misclassification rates (20-30%) in classification models. Use of these models could facility the fast selection of high number of samples with suitable characteristics to obtain high ethanol yields and as predictive tool of these ethanol yields after a SSF process under controlled conditions.