Composition Of Lignocellulosic Biomass Research Articles

Microbial cellulolytic enzymes: diversity and biotechnology with reference to lignocellulosic biomass degradation

Lignocellulosic biomass is the earth’s most abundant renewable feedstock alternative that comprises of cellulose, hemi-cellulose and lignin. The synergistic action of cellulolytic/xylanolytic enzymes produced by lignocellulolytic micro-organisms such as bacteria, algae and fungi are capable of robust cellulosic biomass deconstruction. Most of the microorganisms dwelling in extreme environmental habitats such as rumen environment, hot/cold springs, deep ocean trenches, acidic/alkaline pH environment have been considered as an attractive producers of hemi/cellulolytic lignocellulolytic and other biotechnological enzymes with enhanced bio-chemical properties essential for industrial bioconversion processes. However, the potential microbial sources of cellulolytic enzymes and the underlying mechanism to achieve this is not fully elucidated. In this review article, first we detail the composition of lignocellulosic biomass. Next, we describe the structure and functions of divergent hydrolytic enzymes (cellulolytic and xylanolytic enzymes) involved in cellulosic biomass degradation. Third, we analyze, outline and unveil the prospective source of microbes encoding exceptionally diverse set of biotechnologically relevant cellulolytic enzymes which are critical to answer the specific ecological question of by whom, where and how cellulosic biomass is degraded in the environment. Finally, this review article features the snapshot about the future developments and perspectives on microbial enzymes, high-throughput techniques and molecular tools that could be exploited to derive those enzymes from the potential sources.

Bioethanol production estimated from volatile compositions in hydrolysates of lignocellulosic biomass by deep learning

The cell growth and ethanol production from hydrolysates of various types were estimated from the volatile composition of lignocellulosic biomass by deep neural network (DNN) and the significant compositions estimated by asymmetric autoencoder-decoder (AAE). A six-layer DNN achieved good accuracy with learning and validation losses-0.033 and 0.507, respectively-and estimated overall time courses of yeast growth and ethanol fermentation. The AAE decoded the volatile compositions and represented the features of significant inhibitors via nonlinear dimensionality reduction, which was partly different from those using partial least squares regression reported previously. It revealed the significant features of hydrolysates for bioethanol production, which are lost in conventional approaches. The approach using DNN and AAE is, therefore, useful for bioethanol fermentation and other bioproductions using raw materials.

Prediction of fast pyrolysis products yields using lignocellulosic compounds and ash contents

The effects of lignocellulosic biomass composition on product yields and distributions were studied under high-temperature pyrolysis conditions (800–1250 °C) in a drop tube reactor. Several types of biomass were studied along with xylan, cellulose, and two types of lignin as model feeds. Among the model feeds, soot yields obtained from lignin pyrolysis were greater than those obtained from cellulose or xylan. Cellulose pyrolysis produced mostly gaseous products, along with small amounts of tars. Impregnation of lignin with alkali metals greatly reduced tar and soot formation, simultaneously increasing the hydrogen content of the syngas product. An empirical model predicted with reasonable accuracy trends in the product yields obtained from pyrolysis of whole biomass samples using as input data obtained from model feeds composition data and the pyrolysis temperature. Reaction temperature and ash content both have a strong influences on char yield, whereas gas yields were mostly affected by the reaction temperature.

Fermentative Conversion of Two-Step Pre-Treated Lignocellulosic Biomass to Hydrogen

Fermentative hydrogen production via dark fermentation with the application of lignocellulosic biomass requires a multistep pre-treatment procedure, due to the complexed structure of the raw material. Hence, the comparison of the hydrogen productivity potential of different lignocellulosic materials (LCMs) in relation to the lignocellulosic biomass composition is often considered as an interesting field of research. In this study, several types of biomass, representing woods, cereals and grass were processed by means of mechanical pre-treatment and alkaline and enzymatic hydrolysis. Hydrolysates were used in fermentative hydrogen production via dark fermentation process with Enterobacter aerogenes (model organism). The differences in the hydrogen productivity regarding different materials hydrolysates were analyzed using chemometric methods with respect to a wide dataset collected throughout this study. Hydrogen formation, as expected, was positively correlated with glucose concentration and total reducing sugars amount (YTRS) in enzymatic hydrolysates of LCMs, and negatively correlated with concentrations of enzymatic inhibitors i.e., HMF, furfural and total phenolic compounds in alkaline-hydrolysates LCMs, respectively. Interestingly, high hydrogen productivity was positively correlated with lignin content in raw LCMs and smaller mass loss of LCM after pre-treatment step. Besides results of chemometric analysis, the presented data analysis seems to confirm that the structure and chemical composition of lignin and hemicellulose present in the lignocellulosic material is more important to design the process of its bioconversion than the proportion between the cellulose, hemicellulose and lignin content in this material. For analyzed LCMs we found remarkable higher potential of hydrogen production via bioconversion process of woods i.e., beech (24.01 mL H2/g biomass), energetic poplar (23.41 mL H2/g biomass) or energetic willow (25.44 mL H2/g biomass) than for cereals i.e., triticale (17.82 mL H2/g biomass) and corn (14.37 mL H2/g biomass) or for meadow grass (7.22 mL H2/g biomass).

Characterization of Miscanthus cell wall polymers.

Efficient utilization of lignocellulosic Miscanthus biomass for the production of biochemicals, such as ethanol, is challenging due to its recalcitrance, which is influenced by the individual plant cell wall polymers and their interactions. Lignocellulosic biomass composition differs depending on several factors, such as plant age, harvest date, organ type, and genotype. Here, four selected Miscanthus genotypes (Miscanthus sinensis, Miscanthus sacchariflorus, Miscanthus × giganteus, Miscanthus sinensis × Miscanthus sacchariflorus hybrid) were grown and harvested, separated into stems and leaves, and characterized for their non‐starch polysaccharide composition and structures, lignin contents and structures, and hydroxycinnamate profiles (monomers and ferulic acid dehydrodimers). Polysaccharides of all genotypes are mainly composed of cellulose and low‐substituted arabinoxylans. Ratios of hemicelluloses to cellulose were comparable, with the exception of Miscanthus sinensis that showed a higher hemicellulose/cellulose ratio. Lignin contents of Miscanthus stems were higher than those of Miscanthus leaves. Considering the same organs, the four genotypes did not differ in their Klason lignin contents, but Miscanthus × giganteus showed the highest acetylbromide soluble lignin content. Lignin polymers isolated from stems varied in their S/G ratios and linkage type distributions across genotypes. p‐Coumaric acid was the most abundant ester‐bound hydroxycinnamte monomer in all samples. Ferulic acid dehydrodimers were analyzed as cell wall cross‐links, with 8‐5‐coupled diferulic acid being the main dimer, followed by 8‐O‐4‐, and 5‐5‐diferulic acid. Contents of p‐coumaric acid, ferulic acid, and ferulic acid dimers varied depending on genotype and organ type. The largest amount of cell wall cross‐links was analyzed for Miscanthus sinensis.

Plant cell wall composition and enzymatic deconstruction

Cellulosic ethanol is one the most prominent technologies capable of replacing the use of fossil fuels in an observable horizon of technological development. The complexity of plant biomass, however, continues to challenge our ability to convert it into biofuels efficiently. Highly complex and cross-linked polysaccharides, hydrophobic and protein adsorbent polymers, and crystalline supramolecular structures comprise some of the structures that shield the plant cell contents (and the shield structures themselves) against predators. In response, a sophisticated enzymatic weaponry, with its associated chemical and physical mechanisms, is necessary to overcome this recalcitrance. Here we describe basic information about chemical composition of lignocellulosic biomass and the enzymatic arsenal for lignocellulose deconstruction into fermentable sugars.

Biochar Gasification: An Experimental Study on Colombian Agroindustrial Biomass Residues in a Fluidized Bed

The effect of lignocellulosic biomass composition on gasification of biochar in a pilot-scale fluidized-bed reactor was studied. First, three biomass samples from agroindustrial sectors of Colombia were pyrolyzed. These biochars were then subjected to gasification. The biomasses, biochars, and gasification residues were subjected to various physicochemical and morphological analyses to study the evolution of the carbonaceous structure and syngas composition. In the case of sugar cane bagasse and rice husk, the high contents of cellulose and hemicellulose promoted the thermochemical conversion of the biochar into syngas; however, in the palm kernel shell, its high lignin content made thermochemical pyrolysis and gasification difficult as a result of the recalcitrance of the lignitic structure, which forms a more organized carbonaceous structure.

Chemometric modeling of thermogravimetric data for the compositional analysis of forest biomass.

The objective of this study was to investigated the use of chemometric modeling of thermogravimetric (TG) data as an alternative approach to estimate the chemical and proximate (i.e. volatile matter, fixed carbon and ash contents) composition of lignocellulosic biomass. Since these properties affect the conversion pathway, processing costs, yield and / or quality of products, a capability to rapidly determine these for biomass feedstock entering the process stream will be useful in the success and efficiency of bioconversion technologies. The 38-minute long methodology developed in this study enabled the simultaneous prediction of both the chemical and proximate properties of forest-derived biomass from the same TG data. Conventionally, two separate experiments had to be conducted to obtain such information. In addition, the chemometric models constructed with normalized TG data outperformed models developed via the traditional deconvolution of TG data. PLS and PCR models were especially robust in predicting the volatile matter (R2–0.92; RPD– 3.58) and lignin (R2–0.82; RPD– 2.40) contents of the biomass. The application of chemometrics to TG data also made it possible to predict some monomeric sugars in this study. Elucidation of PC loadings obtained from chemometric models also provided some insights into the thermal decomposition behavior of the chemical constituents of lignocellulosic biomass. For instance, similar loadings were noted for volatile matter and cellulose, and for fixed carbon and lignin. The findings indicate that common latent variables are shared between these chemical and thermal reactivity properties. Results from this study buttresses literature that have reported that the less thermally stable polysaccharides are responsible for the yield of volatiles whereas the more recalcitrant lignin with its higher percentage of elementary carbon contributes to the yield of fixed carbon.

Chemical composition of lignocellulosic biomass in the wood of Abies religiosa across an altitudinal gradient

Tree adaptation to environment has been extensively studied. However, little is known about the variations in structure and chemical composition of lignocellulosic biomass (LB) in relation to altitudinal gradient. We wonder, are there significant variations in the LB in the wood across an altitudinal gradient? To answer this, we carried out a study of Abies religiosa. Wood samples were collected from 36 trees, grown between 3000 and 3500 masl, and then subjected to gravimetric and FTIR (Fourier Transform Infrared) spectroscopic analyses. The gravimetric results showed a proportion of 54.81 ± 2.20 % cellulose, 12.37 ± 1.33 % hemicellulose and 24.68 ± 1.16 % of insoluble lignin. Using the principal components analysis with analysis of variance (ANOVA), significant differences were found at 3100 and 3200 masl in two independent components related to both hemicellulose and lignin, through gravimetry as well as the spectroscopic bands assigned to the carbonyl groups of these polymers, respectively. However, the observed changes in chemical composition of LB did not follow a linear relationship with respect to the altitudinal gradient, which suggests that complex environmental interactions could also be playing an important role. Also, there were significant differences (p < 0.05) in two of the empirical indexes calculated from the FTIR analysis.

Productive potential and quality of rice husk and straw for biorefineries

The use of lignocellulosic biomass to obtain high value-added products and biofuels has been highlighted in the last years, introducing the biorefinery concept. Among the types of lignocellulosics that can be used in biorefineries, there are rice husk and rice straw, byproducts of rice production usually treated as waste. Every year, 650–975 million tons of rice straw and 800 million tons of rice husk are generated during cultivation and processing of rice. This paper accomplishes a review of potential utilization of rice husk and rice straw in biorefineries approaching its chemical, biochemical, and thermochemical conversions in biofuels, biomaterials, biochemicals, bioenergy, and other high value-added products. The composition of lignocellulosic biomass, as well as the intra and intermolecular interactions among cellulose, hemicelluloses, and lignin in the biomass structure responsible for its recalcitrant characteristics are discussed. The need of performing a pretreatment prior to bioconversion due to biomass recalcitrance and different possible bioconversion processes are approached.

Robustness of two-step acid hydrolysis procedure for composition analysis of poplar

The NREL standard procedure for lignocellulosic biomass composition has two steps: primary hydrolysis in 72% wt sulfuric acid at 30°C for 1h followed by secondary hydrolysis of the slurry in 4wt% acid at 121°C for 1h. Although pointed out in the NREL procedure, the impact of particle size on composition has never been shown. In addition, the effects of primary hydrolysis time and separation of solids prior to secondary hydrolysis on composition have never been shown. Using poplar, it was found that particle sizes less than 0.250mm significantly lowered the glucan content and increased the Klason lignin but did not affect xylan, acetate, or acid soluble lignin contents. Composition was unaffected for primary hydrolysis time between 30 and 90min. Moreover, separating solids prior to secondary hydrolysis had negligible effect on composition suggesting that lignin and polysaccharides are completely separated in the primary hydrolysis stage.

Rapid determination of chemical composition and classification of bamboo fractions using visible-near infrared spectroscopy coupled with multivariate data analysis.

BackgroundDuring conversion of bamboo into biofuels and chemicals, it is necessary to efficiently predict the chemical composition and digestibility of biomass. However, traditional methods for determination of lignocellulosic biomass composition are expensive and time consuming. In this work, a novel and fast method for quantitative and qualitative analysis of chemical composition and enzymatic digestibilities of juvenile bamboo and mature bamboo fractions (bamboo green, bamboo timber, bamboo yellow, bamboo node, and bamboo branch) using visible–near infrared spectra was evaluated.ResultsThe developed partial least squares models yielded coefficients of determination in calibration of 0.88, 0.94, and 0.96, for cellulose, xylan, and lignin of bamboo fractions in raw spectra, respectively. After visible–near infrared spectra being pretreated, the corresponding coefficients of determination in calibration yielded by the developed partial least squares models are 0.994, 0.990, and 0.996, respectively. The score plots of principal component analysis of mature bamboo, juvenile bamboo, and different fractions of mature bamboo were obviously distinguished in raw spectra. Based on partial least squares discriminant analysis, the classification accuracies of mature bamboo, juvenile bamboo, and different fractions of bamboo (bamboo green, bamboo timber, bamboo yellow, and bamboo branch) all reached 100 %. In addition, high accuracies of evaluation of the enzymatic digestibilities of bamboo fractions after pretreatment with aqueous ammonia were also observed.ConclusionsThe results showed the potential of visible–near infrared spectroscopy in combination with multivariate analysis in efficiently analyzing the chemical composition and hydrolysabilities of lignocellulosic biomass, such as bamboo fractions.Electronic supplementary materialThe online version of this article (doi:10.1186/s13068-016-0443-z) contains supplementary material, which is available to authorized users.

Biomass Pre-treatment Methods and Their Economic Viability for Efficient Production of Biofuel

Development of sustainable technology for bioenergy/biofuel generation using lignocellulosic biomass is of prime importance in the present day research. An economically viable technology for production of ethanol from lignocellulosic biomass will certainly provide opportunity to the non-oil producing countries to refrain from deprivation of fuel and explore the concept of bio-refineries for complete utilization of the feedstock. Biomass feedstock is abundant in the form of network of cellulose, hemicelluloses and lignin and hence the name lignocellulose. The structure and composition of lignocellulosic biomass is a major hindrance in its complete digestibility into fermentable monomer sugars. Reports are in the literature indicating that pre-treatment of biomass from wood and grasses can increase the yield of sugars upto 90%. Here, we have reviewed various technologies and methods for the pre-treatment of biomass with emphasis on their advantages and disadvantages with respect to the production of biofuel. Also, capital expense (CAPEX) and operational expense (OPEX) is considered to assess the economic viability of the technology. Review Article Bhagwat et al.; BBJ, 8(2): 1-17, 2015; Article no.BBJ.18284 2

A gene stacking approach leads to engineered plants with highly increased galactan levels in Arabidopsis.

BackgroundEngineering of plants with a composition of lignocellulosic biomass that is more suitable for downstream processing is of high interest for next-generation biofuel production. Lignocellulosic biomass contains a high proportion of pentose residues, which are more difficult to convert into fuels than hexoses. Therefore, increasing the hexose/pentose ratio in biomass is one approach for biomass improvement. A genetic engineering approach was used to investigate whether the amount of pectic galactan can be specifically increased in cell walls of Arabidopsis fiber cells, which in turn could provide a potential source of readily fermentable galactose.ResultsFirst it was tested if overexpression of various plant UDP-glucose 4-epimerases (UGEs) could increase the availability of UDP-galactose and thereby increase the biosynthesis of galactan. Constitutive and tissue-specific expression of a poplar UGE and three Arabidopsis UGEs in Arabidopsis plants could not significantly increase the amount of cell wall bound galactose. We then investigated co-overexpression of AtUGE2 together with the β-1,4-galactan synthase GalS1. Co-overexpression of AtUGE2 and GalS1 led to over 80% increase in cell wall galactose levels in Arabidopsis stems, providing evidence that these proteins work synergistically. Furthermore, AtUGE2 and GalS1 overexpression in combination with overexpression of the NST1 master regulator for secondary cell wall biosynthesis resulted in increased thickness of fiber cell walls in addition to the high cell wall galactose levels. Immunofluorescence microscopy confirmed that the increased galactose was present as β-1,4-galactan in secondary cell walls.ConclusionsThis approach clearly indicates that simultaneous overexpression of AtUGE2 and GalS1 increases the cell wall galactose to much higher levels than can be achieved by overexpressing either one of these proteins alone. Moreover, the increased galactan content in fiber cells while improving the biomass composition had no impact on plant growth and development and hence on the overall biomass amount. Thus, we could show that the gene stacking approach described here is a promising method to engineer advanced feedstocks for biofuel production.

Lignocellulosic feedstock conversion, inhibitor detoxification and cellulosic hydrolysis – a review

The current review is an attempt to cover various pre-treatment strategies such as physical, chemical, organosolve and biological pre-treatment in order to change the crystallinity of lignocellulosic biomass along with methods and strategies for inhibitor detoxification for improving the cellulose hydrolysis and fermentation. The presence of lignin in lignocellulosic biomass is the biggest hurdle and therefore a judicial pre-treatment selection technique is important, based on lignocellulosic mass composition analysis for improving overall saccharification. The production of inhibitors during pre-treatment is another cause of low saccharification owing to deactivation of cellulase enzyme. In this review a comprehensive discussion has been made of the impact of various pre-treatment strategies on overall hydrolysis and saccharification in view of the varied composition of lignocellulosic biomass. Various detoxification approaches have also been discussed, along with the economical bioprocessing issue, and their advantages and disadvantages. Bio refinery approaches have been important in this regard to make bioethanol production more economical.

Statistical prediction of biomethane potentials based on the composition of lignocellulosic biomass

Mixture models are introduced as a new and stronger methodology for statistical prediction of biomethane potentials (BPM) from lignocellulosic biomass compared to the linear regression models previously used. A large dataset from literature combined with our own data were analysed using canonical linear and quadratic mixture models. The full model to predict BMP (R(2)>0.96), including the four biomass components cellulose (xC), hemicellulose (xH), lignin (xL) and residuals (xR=1-xC-xH-xL) had highly significant regression coefficients. It was possible to reduce the model without substantially affecting the quality of the prediction, as the regression coefficients for xC, xH and xR were not significantly different based on the dataset. The model was extended with an effect of different methods of analysing the biomass constituents content (DA) which had a significant impact. In conclusion, the best prediction of BMP is pBMP=347xC+H+R-438xL+63DA.

Effect of alkaline pretreatment on chemical composition of lignocellulosic biomass using radio frequency heating

The very nature of lignocellulosic biomass presents resistance and recalcitrance to biological and chemical degradation during enzymatic hydrolysis and the subsequent fermentation process. This leads to a very low conversion rate, which makes the process economically unfeasible. In this study, alkaline (NaOH) pretreatment was applied on barley straw, using radio-frequency-based dielectric heating to enhance accessibility and digestibility during the subsequent stage of enzymatic hydrolysis. Three levels of temperature (70, 80, and 90 °C), five levels of biomass:NaOH solution ratio (1:4, 1:5, 1:6, 1:7, and 1:8), 1 h equilibration time, screen size of 1.6 mm, 1% w/v NaOH concentration, and 20 min residence time were used for the pretreatment. The effect of the alkaline pretreatment was evaluated through chemical composition analysis of the pretreated and non-treated biomass samples. The use of NaOH solution and the biomass:NaOH solution ratio played a vital role in the breakdown of the lignified matrix. The ratio 1:6 at the four temperatures studied was determined to be the optimal treatment conditions. Radio frequency-assisted alkaline pretreatment resulted in lower acid insoluble lignin and higher total acid soluble lignin moieties. Based on the obtained data, we predict that this pretreatment will decrease the required amount and cost of enzymes by up to 64% compared to using non-treated biomass.

Substrate perturbation alters the glycoside hydrolase activities and community composition of switchgrass‐adapted bacterial consortia

Bacteria modulate glycoside hydrolase expression in response to the changes in the composition of lignocellulosic biomass. The response of switchgrass-adapted thermophilic bacterial consortia to perturbation with a variety of biomass substrates was characterized to determine if bacterial consortia also responded to changes in biomass composition. Incubation of the switchgrass-adapted consortia with these alternative substrates produced shifts in glycoside hydrolase activities and bacterial community composition. Substantially increased endoglucanase activity was observed upon incubation with microcrystalline cellulose and trifluororacetic acid-pretreated switchgrass. In contrast, culturing the microbial consortia with ionic liquid-pretreated switchgrass increased xylanase activity dramatically. Microbial community analyses of these cultures indicated that the increased endoglucanase activity correlated with an increase in bacteria related to Rhodothermus marinus. Inclusion of simple organic substrates in the culture medium abrogated glycoside hydrolase activity and enriched for bacteria related to Thermus thermophilus. These results demonstrate that the composition of biomass substrates influences the glycoside hydrolase activities and community composition of biomass-deconstructing bacterial consortia.

Carbohydrate composition of eucalyptus, bagasse and bamboo by a combination of methods

The carbohydrate composition of lignocellulosic biomass is normally obtained by the quantification of monomers after two stages of hydrolysis in H 2SO 4. A new two-stage hydrolysis protocol has recently been developed but so far only results for temperate hardwoods have been reported. In this investigation the new protocol was used in the analysis of depithed sugarcane bagasse, Eucalyptus grandis and bamboo. The results were compared to those from the traditional hydrolysis protocol. Sugar monomers were quantified by 1H NMR and high performance liquid chromatography (HPLC) and there were no significant differences between the two techniques. The new and traditional hydrolysis protocols gave nearly identical results for the bagasse and bamboo samples both of which contain <0.10 uronic acids per xylose unit. However, the new protocol gave a higher xylan yield (13.2% vs. 12.1%) for the E. grandis that contained >0.20 uronic acids per xylose units. For both hydrolysis protocols, summative analyses in the range of 97.5–101.0% were obtained for the three biomass samples. However, the range was narrower (98.6–99.5%) for the new hydrolysis protocol coupled with 1H NMR analysis.