Bruno Godin

Composition of structural carbohydrates in biomass: precision of a liquid chromatography method using a neutral detergent extraction and a charged aerosol detector.

We adapted and optimized a method to quantify the cellulose, hemicellulose, xylan, arabinan, mannan, galactan contents in lignocellulosic biomass. This method is based on a neutral detergent extraction (NDE) of the interfering biomass components, followed by a sulfuric acid hydrolysis (SAH) of the structural polysaccharides, and a liquid chromatography with charged aerosol detection (LC-CAD) to analyze the released monosaccharides. The first step of this NDE-SAH-LC-CAD method aims at removing all compounds that interfere with the subsequent sulphuric acid hydrolysis or with the subsequent chromatographic quantification of the cellulosic and hemicellulosic monosaccharides. This step includes starch hydrolysis with an analytical thermostable α-amylase followed by an extraction of soluble compounds by a Van Soest neutral detergent solution (NDE). The aim of this paper was to assess the precision of this method when choosing fiber sorghum (Sorghum bicolor (L.) Moench), tall fescue (Festuca arundinacea Schreb.) and fiber hemp (Cannabis sativa L.) as representative lignocellulosic biomass. The cellulose content of fiber sorghum, tall fescue and fiber hemp determined by the NDE-SAH-LC-CAD method were 28.7 ± 1.0, 29.7 ± 1.0 and 43.6 ± 1.2g/100g dry matter, respectively, and their hemicellulose content were 18.6 ± 0.5, 16.5 ± 0.5 and 14.5 ± 0.2g/100g dry matter, respectively. Cellulose, mannan and galactan contents were higher in fiber hemp (dicotyledon) as compared to tall fescue and fiber sorghum (monocotyledons). The xylan, arabinan and total hemicellulose contents were higher in tall fescue and fiber sorghum as compared to fiber hemp. The precision of the NDE-SAH-LC-CAD method was better for polysaccharide concentration levels above 1g/100g dry matter. Galactan analysis offered a lower precision, due to a lower CAD response intensity to galactose as compared to the other monosaccharides. The dispersions of the results (expanded uncertainty) of the NDE-SAH-LC-CAD method were smaller as compared to the Van Soest (VS) method. In addition, the NDE-SAH-LC-CAD method was able to provide additional information on the composition of the hemicellulose (xylan, arabinan, mannan and galactan content) that is not provided by the Van Soest method. The NDE-SAH-LC-CAD method offers also the advantage of a better specificity for hemicellulose and cellulose, as compared to the NREL and Uppsala methods.

Chemical characteristics and biofuels potentials of various plant biomasses: influence of the harvesting date.

BACKGROUNDnAn optimal valorization of plant biomasses to produce biofuels requires a good knowledge of the available contents and molecular composition of the main chemical components, which changes with the harvesting date. Therefore, we assessed the influence of harvesting date on the chemical characteristics of various energy crops in the context of their conversion to biofuels.nnnRESULTSnWe showed that the biomass chemical composition, enzymatic digestible organic matter, bioethanol and thermal energy production potential for each species are impacted by the harvesting date. The proportion of enzymatically digestible organic matter decreases as the harvesting date is delayed. This is related to the increase in cellulose and lignin contents. The suitability of the biomasses for bioethanol production increases with harvest stage, as the total carbohydrates content increases. The suitability of the biomasses as a source of thermal energy increases according to the harvesting date as the proportion of organic matter increases and the content of mineral compounds decreases. For all investigated energy conversions, the best harvesting period is autumn, because the significantly higher crop dry matter yield largely compensates for the sometimes slightly less favorable chemical characteristics.nnnCONCLUSIONnWhile the biomass composition of energy crops changes with harvest stage, the dry biomass yield per unit area is the main factor that controls the total amount of chemical components, digestible organic matter, bioethanol and thermal energy that can be expected to be harvested per unit area. The biomass compositions presented in this paper are essential to investigate their suitability for bioenergy conversion.

Biochemical methane potential prediction of plant biomasses: Comparing chemical composition versus near infrared methods and linear versus non-linear models

The reliability of different models to predict the biochemical methane potential (BMP) of various plant biomasses using a multispecies dataset was compared. The most reliable prediction models of the BMP were those based on the near infrared (NIR) spectrum compared to those based on the chemical composition. The NIR predictions of local (specific regression and non-linear) models were able to estimate quantitatively, rapidly, cheaply and easily the BMP. Such a model could be further used for biomethanation plant management and optimization. The predictions of non-linear models were more reliable compared to those of linear models. The presentation form (green-dried, silage-dried and silage-wet form) of biomasses to the NIR spectrometer did not influence the performances of the NIR prediction models. The accuracy of the BMP method should be improved to enhance further the BMP prediction models.

Structural carbohydrates in a plant biomass: correlations between the detergent fiber and dietary fiber methods.

We compared the detergent fiber and dietary fiber methods to analyze the cellulose and hemicellulose contents of commelinid and non-commelinid magnoliophyta biomass. A good linear correlation was found between both methods. Compared to the more accurate dietary fiber method, the detergent fiber method overestimates the content of cellulose, whereas the detergent fiber method, as compared to the dietary fiber method, overestimates and underestimates the hemicellulose content in commelinid and non-commelinid magnoliophyta biomass, respectively. Because of the good linear correlations, conversion factors were determined to predict the cellulose, hemicellulose, and xylan contents to be expected from the dietary fiber method, on the basis of analyses made by the faster, cheaper, and more commonly practiced detergent fiber method. Nevertheless, the dietary fiber method offers the advantage of providing the detailed composition of the hemicelluloses (xylan, arabinan, hemicellulosic glucan, galactan, and mannan), and that is of interest for biorefining purposes.

Prediction of chemical characteristics of fibrous plant biomasses from their near infrared spectrum: comparing local versus partial least square models and cross- validation versus independent validations

The reliability of local and partial least square (PLS) near infrared (NIR) models to predict the chemical characteristics of fibrous plant biomasses was compared. Validations with different degrees of independence were used. The developed NIR models were reliable for the prediction of different main chemical characteristics of various fibrous plant species using multispecies datasets. The local models were more reliable in terms of prediction error compared with the PLS models because the local method appears to cope with the nonlinearity and non-homogeneity associated with a large multispecies dataset. The degree of independence of samples in the validation set relative to samples used in the calibration set had a major impact on the prediction performance, especially for the local method. It affected the local method more because of the lower number of samples used in its specific regressions. There was a decrease in the reliability of local and PLS models according to the increase in the degree of independence of the validation set (i.e. the similarity of the predicted samples in regard to the calibration samples). The additions of a few independent samples of the predicted plant-species group to their calibration set that did not contain samples of the predicted plant-species group improved the prediction performance of multispecies models, especially for the local method. The type of NIR models developed in the present study can be used for screening, ranking and quantitative analyses of the main chemical components contents in fibrous biomasses, and for the assessment of their suitability to be converted into biofuels.

Lignin in plant biomasses: comparative metrological assessment of the detergent fiber and the insoluble dietary fiber methods

The detergent fiber and the insoluble dietary fiber methods were compared to quantitate lignin in commelinid and non-commelinid magnoliophyta biomasses. This comparison was based on the precision of these methods and on the correlation between these methods. The present study showed that the insoluble dietary fiber method was more reliable to quantitate lignin because of its higher precision and smaller bias, as compared to the detergent fiber method. Nevertheless, the less tedious and resource consuming detergent fiber method can reliably be used to predict the results of the insoluble dietary fiber method with the correction factors determined in this paper. These correction factors of commelinid biomasses are distinctive of those of non-commelinid magnoliophyta biomasses. The lignin content should be corrected for protein-like compounds, otherwise lignin is significantly overestimated. Owing to these correction factors, the biofuel (e.g. cellulosic ethanol and biomethanation production), bio-based chemicals and feed sectors can use the detergent fiber method to rapidly and reliably estimate the available amounts of lignin of plant biomasses and rank them according to their suitability to be converted based on their lignin content.

Evolution of Main Chemical Components Content and Monosaccharidic Content of Hemicelluloses in Several Lignocellulosic Grass Crops Grown under Different Crop Husbandry Conditions

Cellulose and hemicelluloses are the most abundant structural polysaccharide in nature. Their optimal valorization in lignocellulose-based biorefineries requires a good knowledge of the contents available in various biomasses, and of their molecular composition. The composition and more specifically the monosaccharidic content (cellulosic glucan, xylan, arabinan, mannan, galactan and hemicellulosic glucan) were analyzed in several lignocellulosic grass crops: switchgrass (Panicum virgatum L.), tall fescue (Festuca arundinacea Schreb.), cocksfoot-alfalfa association (Dactylis glomerata L.-Medicago sativa L.). Cellulose and hemicelluloses contents were in the range 20.8-33.3 and 14.5-32.6 g (100gDM)-1, respectively, with lignin, total soluble sugars, proteins, and ash contents around 2.9-7.8, 2.0-21.7, 5.7-17.2 and 4.3-16.3 g (100gDM)-1, respectively. The main hemicellulosic components were, by order of decreasing importance, xylan 8.3-23.2 g (100gDM)-1, arabinan 2.12-4.10 g (100gDM)-1, hemicellulosic glucan 1.36-3.42 g (100gDM)-1, galactan 0.63-2.31 g (100gDM)-1 and mannan 0.27-1.08 g (100gDM)-1. Plant species and harvest cycle has the most significant influence on the structural polysaccharide composition, while the influences of cultivar and nitrogen fertilization were only rarely significant.