Standard Procedures for Biomass Compositional Analysis
Capabilities in Biomass Analysis
NREL's Biomass Compositional Analysis Technologies team can work with you to characterize the chemical composition of biomass feedstocks, intermediates, and products.
NREL develops laboratory analytical procedures (LAPs) for standard biomass analysis. These procedures help scientists and analysts understand more about the chemical composition of raw biomass feedstocks and process intermediates for conversion to biofuels.
The American Society for Testing and Materials (ASTM) and the Technical Association of the Pulp and Paper Industry (TAPPI) may have adopted similar procedures, which may be ordered from those organizations. For more procedures, see the microalgal biofuels LAPs.
Reviewing and Integrating Laboratory Analytical Procedures
These documents provide crucial background information necessary for researchers and analysts to understand before using the biomass standard analytical procedures.
Summative Mass Closure for Feedstocks
Choosing the appropriate combinations of procedures allows for the summative mass closure of biomass feedstocks. Combining the appropriate procedures allows users to break down the biomass feedstock sample into constituents that sum to 100% by weight. There are several important points within the compositional analysis suite where decisions must be made to optimize the analysis. Some of these decisions are based on the type of biomass present, and some decisions must be made to obtain complete summative mass closure of all constituents.
Summative Mass Closure for Pretreated Slurries
This summary procedure includes a discussion of each LAP necessary to obtain complete compositional analysis of dilute-acid-pretreated biomass slurries. NREL has optimized these LAPs to provide compositional analysis for biomass feedstocks as well as for intermediary products of dilute acid pretreatment.
Laboratory Analytical Procedures
NREL wrote these analytical procedures to help the research community characterize biomass. Before performing these procedures, review the documents in the overview section. The analytical procedures are in order of logical use.
This procedure describes methods for sample drying and size reduction, obtaining samples with a uniform particle size, and representative sampling of biomass samples.
This procedure describes the methods used to determine the amount of solids or moisture present in a solid or slurry biomass sample. It also covers determining dissolved solids in a liquor sample. A traditional convection oven drying procedure is covered as well as determining solids using an automatic infrared moisture analyzer.
This test method covers determining ash expressed as the percentage of residue remaining after dry oxidation (oxidation at 550°C to 600°C). All results are reported relative to the 105°C oven-dried weight of the sample.
This procedure covers determining nitrogen-to-protein conversion factors to estimate the amount of protein in a biomass sample.
This procedure covers determining soluble, non-structural materials in a biomass sample. The results are reported on a dry-weight basis as a weight percentage of the biomass. Extractives percentages are measured and used to convert compositions from an extractives-free basis to an as-received basis. Determining the amount of water-extractable sucrose is also covered.
Use this LAP in conjunction with other assays to determine the total composition of biomass samples. This procedure should be performed before the Structural Carbohydrates and Lignin in Biomass procedure.
This procedure is for measuring carbohydrate and lignin content of samples without extractives. (For samples with extractives, see Extractives in Biomass.) This procedure uses a two-step acid hydrolysis to fractionate the biomass into forms that are more easily quantified.
The lignin fractionates into acid-insoluble and acid-soluble material. The acid-insoluble material also may include ash and protein, which must be accounted for during gravimetric analysis. The acid-soluble lignin is measured by UV-Vis spectroscopy. During hydrolysis, the polymeric carbohydrates are hydrolyzed into the monomeric forms, which are soluble in the hydrolysis liquid. They are then measured by high performance liquid chromatography (HPLC). Protein may also partition into the liquid fraction. Acetate is measured by HPLC.
Stirring at 30°C
This video shows the techniques used at NREL to stir during the first stage of hydrolysis (72% H2SO4 / 30°C water bath). Notice that the tubes are not removed from the bath during stirring and that care is taken to ensure no particles are deposited higher up the sides of the tube.
Filtration After Hydrolysis
This video shows the filtration of the acid insoluble residue (AIR) after the second stage of hydrolysis (4% H2SO4 / autoclave). In the first clip, notice the hydrolysate is initially decanted to prevent deposition of solids onto the filter. Also note the filtration rate is typically slow and will become slower after the solids are on the filter. In the second clip, notice that once most of the liquid has been filtered, the solids are transferred into the crucible with a quick motion to ensure maximum suspension of the slurry. This helps prevent multiple rinses.
In the third clip, a sample of the filtrate is taken prior to adding rinse water. The fourth clip shows the rinsing of the solids from the tubes with deionized water. This rinsing of the tube is typically enough to rinse the filtered solids free of entrained carbohydrates and acid.
This video shows the dilution of the 72% H2SO4 to 4% with deionized water. A Dosimat is used in this video but is not required. In the first clip, notice the stir rod is used to physically remove particles from the glass at the beginning of the rinse step. In the second clip, all particles are rinsed from the stir stick. Do not forget to invert the tube or mix the solution prior to autoclave.
The concentrations of monomeric sugars (soluble monosaccharides), cellobiose, total sugars (monosaccharides and oligosaccharides), carbohydrate degradation products, and sugar alcohols can be determined using this procedure. Monomeric sugars are quantified by HPLC with refractive index detection. Oligomeric sugars are converted into the monomeric form using acid hydrolysis and quantified by HPLC with refractive index detection. Byproducts and degradation products are quantified by HPLC with refractive index detection.
This procedure covers determining the percentage of water-insoluble solids in a pretreated biomass sample after extracting all soluble components with aggressive water washing.
This procedure describes the enzymatic saccharification of native or pretreated lignocellulosic biomass to glucose, cellobiose, and xylose in order to determine the comparative digestibility/conversion extent of the feedstock or the efficacy of various enzyme samples.
This LAP consists of two sub-procedures. The first is hydrolysis of lignocellulosic biomass. The second is simultaneous saccharification and fermentation of biomass. These procedures test a variety of lignocellulosic substrates and provide a consistent evaluation method. The procedures are for raw biomass substrates or washed, pretreated substrates only.
These Excel spreadsheets calculate compositional analysis and mass closure based on the equations in the relevant LAPs:
- Wood (hardwood or softwood)
- Corn stover (feedstock)
- Biomass hydrolyzate (liquid fraction produced from dilute-acid pretreatment)
- Corn stover intermediates (solid fraction produced from dilute-acid pretreatment of corn stover—may also be used for wood intermediates)
- Nitrogen-to-protein factor calculator.
These spreadsheets work best in conjunction with the appropriate LAPs. Each workbook combines the calculations for one or more LAPs to facilitate summative mass closure or summative analysis. The "Read Me" page of each workbook contains important instructions and legal information.
The following publications are related to NREL's standard procedures for biomass compositional analysis.
Degradation of Carbohydrates During Dilute Sulfuric Acid Pretreatment Can Interfere with Lignin Measurements in Solid Residues. Katahira, R., et al. (2013). Journal of Agricultural and Food Chemistry (61:13); 3286-3292.
Effect of Corn Stover Compositional Variability on Minimum Ethanol Selling Price (MESP). Tao, L.; Templeton, D.W.; Humbird, D.; Aden, A. (2013). Bioresource Technology (0).
Laboratory-Scale Pretreatment and Hydrolysis Assay for Determination of Reactivity in Cellulosic Biomass Feedstocks. Wolfrum, E.J.; Ness, R.M.; Nagle, N.J.; Peterson, D.J.; Scarlata, C.J. (2013). Biotechnology for Biofuels (6:162).
Methods for Biomass Compositional Analysis. Sluiter, A.; Sluiter, J.; Wolfrum, E. (2013). Behrens, M.; Datye, A., eds. Catalysis for the Conversion of Biomass and Its Derivatives. Max Planck Research Library for the History and Development of Knowledge, Proceedings 2. Berlin: Edition Open Access (ISBN 978-3-8442-4282-9).
Near Infrared Calibration Models for Pre-Treated Corn Stover Slurry Solids, Isolated and in Situ. Sluiter, A.; Wolfrum, E. (2013). Journal of Near Infrared Spectroscopy (21:4); 249-257.
Accurate and Reliable Quantification of Total Microalgal Fuel Potential as Fatty Acid Methyl Esters by in Situ Transesterification. Laurens, L.M.L.; Quinn, M.; Van Wychen, S.; Templeton, D.W.; Wolfrum, E.J. (2012). Analytical and Bioanalytical Chemistry (403:1); 167-178.
Algal Biomass Constituent Analysis: Method Uncertainties and Investigation of the Underlying Measuring Chemistries. Laurens, L.M.L.; Dempster, T.A.; Jones, H.D.T.; Wolfrum, E.J.; Van Wychen, S.; McAllister, J.S.P.; Rencenberger, M.; Parchert, K.J.; Gloe, L.M. (2012). Analytical Chemistry (84:4); 1879-1887.
Rapid Compositional Analysis of Microalgae by NIR Spectroscopy. Laurens, L.M.L.; Wolfrum, E.J. (2012). NIR News (23:2); 9-11.
Separation and Quantification of Microalgal Carbohydrates. Templeton, D.W.; Quinn, M.; Van Wychen, S.; Hyman, D.; Laurens, L.M.L. (2012). Journal of Chromatography A (1270); 225-234.
Uncertainty in Techno-Economic Estimates of Cellulosic Ethanol Production due to Experimental Measurement Uncertainty. Vicari, K.J.; Tallam, S.S.; Shatova, T.; Joo, K.K.; Scarlata, C.J.; Humbird, D.; Wolfrum, E.J.; Beckham, G.T. (2012). Biotechnology for Biofuels (5); 23-27.
Variation in Biomass Composition Components Among Forage, Biomass, Sorghum-Sudangrass, and Sweet Sorghum Types. Stefaniak, T.R.; Dahlberg, J.A.; Bean, B.W.; Dighe, N.; Wolfrum, E.J.; Rooney, W.L. (2012). Crop Science (52:4); 1949-1954.
Compositional and Agronomic Evaluation of Sorghum Biomass as a Potential Feedstock for Renewable Fuels. Dahlberg, J.; Wolfrum, E.; Bean, B.; Rooney,W.L. (2011). Journal of Biobased Materials and Bioenergy (5); 1-7.
Feasibility of Spectroscopic Characterization of Algal Lipids: Chemometric Correlation of NIR and FTIR Spectra with Exogenous Lipids in Algal Biomass. Laurens, L.M.L.; Wolfrum, E.(2011). BioEnergy Research (4); 22–35.
Compositional Analysis of Lignocellulosic Feedstocks 1: Review and Description of Methods. Sluiter, J.B., et al. (2010). Journal of Agricultural and Food Chemistry (58:16); 9043-9053.
Compositional Analysis of Lignocellulosic Feedstocks 2: Method Uncertainties. Templeton, D.W., et al. (2010). Journal of Agricultural and Food Chemistry (58:16); 9054-9062.
Development and Validation of a Fast High Pressure Liquid Chromatography Method for the Analysis of Lignocellulosic Biomass Hydrolysis and Fermentation Products. Scarlata, C.J.; Hyman, D.A. (2010). Journal of Chromatography A (1217:14); 2082-2087.
Life Cycle Environmental Impacts of Selected U.S. Ethanol Production and Use Pathways in 2022. Hsu, D.D.; Inman, D.; Heath, G.A.; Wolfrum, E.J.; Mann, M.K.; Aden, A. (2010). Environmental Science & Technology (44:13); 289–5297.
Assessing Corn Stover Composition and Sources of Variability via NIRS. Templeton, D.W.; Sluiter, A.D.; Hayward, T.K.; Hames, B.R.; Thomas, S.R. (2009). Cellulose (16:4); 621-639.
Characterization, Genetic Variation, and Combining Ability of Maize Traits Beneficial to the Production of Cellulosic Ethanol. Lorenz, A.; Coors, J.; deLeon, N.; Wolfrum, E.; Hames, B.; Sluiter, A.; Wiemer, P. (2009). Crop Science (49); 85-98.
Correlating Detergent Fiber Analysis and Dietary Fiber Analysis Data for Corn Stover. Wolfrum, E.; Lorenz, A.; DeLeon, N. (2009). Cellulose (16:5); 577-585.
Improved Multivariate Calibration Models for Corn Stover Feedstock and Dilute-Acid Pretreated Corn Stover. Wolfrum, E.; Sluiter, A. (2009). Cellulose (16:5); 567-576.
Process for the Conversion of Aqueous Biomass Hydrolysate into Fuels or Chemicals by the Selective Removal of Fermentation Inhibitors. Hames, B.R.; Sluiter, A.D.; Hayward, T.K.; Nagle, N.J. (2004). U.S. Patent. United States, Midwest Research Institute, Kansas City, MO.
Use of Near Infrared Spectroscopy to Measure the Chemical and Mechanical Properties of Solid Wood. Kelley, S.; Rials, T.; Snell, R.; Groom, L.; Sluiter, A. (2004). Wood Science and Technology (38:4); 257-276.
Rapid Biomass Analysis: New Tools for Compositional Analysis of Corn Stover Feedstocks and Process Intermediates from Ethanol Production. Hames, B.R.; Thomas, S.R.; Sluiter, A.D.; Roth, C.J.; Templeton, D.W. (2003). Applied Biochemistry and Biotechnology (105:1-3); 5-16.
Frequently Asked Questions
Find answers to frequently asked questions about NREL's standard procedures for biomass compositional analysis.
All current LAPs are in the procedures section. Some of the LAPs have new, descriptive titles instead of numbers. Several LAPs and versions of LAPs are no longer supported by NREL. NREL determined these LAPs were either outdated or incorrect, and we do not recommend using those procedures. All supported LAPs are in the section linked above.
NREL offers one-week training tailored to your needs. The price is the direct cost of NREL's time to prepare for and teach the class, which includes a combination of lectures and hands-on learning for up to four students. For more information, contact Justin Sluiter, 303-384-6347.
NREL routinely places agreements to perform compositional analysis. Costs range from $500 to $2,000 per sample, depending on sample type. We currently do not have a lab to recommend that fits within our data-quality parameters.
I have a limited quantity of sample or a large number of samples for NREL analysis. What are my options?
NREL developed a number of rapid calibration models to predict the composition of a variety of biomass feedstocks and feedstock intermediates by correlating near-infrared (NIR) spectroscopy with compositional data produced using traditional wet chemical analysis techniques. NIR is a non-destructive spectroscopic method that requires as little as 500 mg of sample. For more information, contact Amie Sluiter.
The biomass feedstock composition and property database provides a general idea of feedstock differences, but composition can vary widely based on factors such as cultivar, harvest time, harvest method, and ratio of anatomical fractions. This database is a good start for a general idea of compositional differences among feedstocks but should not be considered a true value for any individual feedstock sample.
How can I analyze a feedstock without a coefficient for acid soluble lignin (ASL) listed in the LAP?
The complex structure of lignin makes it difficult and time consuming to determine coefficients for UV-Vis peak maxima and extinction. The values listed in the "Determination of Structural Carbohydrates and Lignin in Biomass" LAP were based on a LAP that is no longer available and not supported by NREL. NREL suggests using the value of a similar biomass type as an estimate. NREL is working to improve lignin measurements and will update the LAP when more information is available. Issues with this measurement can be found in Degradation of Carbohydrates During Dilute Sulfuric Acid Pretreatment Can Interfere with Lignin Measurements in Solid Residues.
NREL uses the system pictured on the right. This consists of a vacuum flask with a rubber crucible holder and a filtration crucible attached to an in-house vacuum line. The vacuum attachment consists of vacuum-appropriate tubing and quick-connect coupling to an in-house vacuum line.
We have found that NDF and ADF methods report different values. NDF/ADF methods are designed for measuring animal feed; they do not translate well for biofuels conversion. For more information, see Correlating Detergent Fiber Analysis and Dietary Fiber Analysis Data for Corn Stover.
NREL does not calculate sugars based on cellulose and hemicellulose. NREL quantifies sugars based on a hypothetical oligomer form (e.g., glucan, xylan, galactan, arabinan, and mannan) by multiplying monomer values by the appropriate anhydro correction. Assigning them to cellulose and hemicellulose would require more detailed information about structural linkages than is provided by the hydrolysis method.
In general, cellulose is the sum of glucose molecules, and hemicellulose is the sum of the remaining sugars, but this underestimates the complexity of the biomass because many other components are present.
NREL does not recommend this column for carbohydrate analysis because the carbohydrate range has significant peak co-elution. For more information, see Development and Validation of a Fast High Pressure Liquid Chromatography Method for the Analysis of Lignocellulosic Biomass Hydrolysis and Fermentation Products.
Having polymeric carbohydrates in the hydrolysate indicates incomplete hydrolysis. Potential causes include high ash content in the feedstock and an autoclave not reaching temperature. Do not ignore oligomers; they are part of the carbohydrate content. Determine the cause of the incomplete hydrolysis and run the samples again.
Furfural, a degradation product of C5 sugars, is retained by the Pb column we use for carbohydrate analysis. This peak is regularly eluted in the area of oligomers in the following sample. UV detection can help identify a peak of furfural because it absorbs well, and oligomeric sugars do not. If UV detection is not possible, increase the time between sample injections to shift the peak away from the carbohydrates.
I don't have incomplete hydrolysis, but the HPLC is showing peaks in the oligomer region of the chromatogram. What can be done?
The presence of salts in the sample will give a false signal in the refractive index used for carbohydrate measurements (see the figure below where this signal is highlighted in pink). This false salt peak can be eliminated by installing a de-ashing cartridge. These de-ashing cartridges must be changed periodically when the salt peaks begin to appear. Their lifetime depends heavily on the amount of ash in the samples and the care taken during neutralization.
This chromatogram shows a typical analytical hydrolysate of a corn stover feedstock using the Pb column. The cellobiose peak is an artifact of the chromatogram but is of particular scrutiny. Any actual cellobiose, as indicated by peak shape and retention time stability, suggests incomplete hydrolysis. The peak at about 6 minutes is furfural present from the previous injection.
This chromatogram shows a typical analytical hydrolysate of a feedstock sample using the Biorad Aminex HPX-87H column. The acetic acid peak at about 15 minutes is small compared to the carbohydrates between 6 and 12 minutes.
NREL uses standard reference materials available on the NIST website that resemble the sample matrix. Any material can be used as a reference if enough data is available and the sample is homogenous over time.
For information about data reproducibility, see Compositional Analysis of Lignocellulosic Feedstocks 2: Method Uncertainties.
For a history of the methods, see Compositional Analysis of Lignocellulosic Feedstocks 1: Review and Description of Methods.
Analyzing samples for only glucan and xylan is possible, but determining the full composition takes little additional effort. The component mass closure information can help validate the results if the closure approaches 100%.
Milling the samples through a 2-mm screen allows for small enough particles for complete acid penetration and hydrolysis. This process is important to drive all the structural sugars into solution for analysis.
Water and ethanol extractives can interfere with the hydrolysis reaction by artificially adding to the lignin value or artificially adding soluble carbohydrates to the structural polymer calculation.
Some sugars degrade beyond monomeric forms during hydrolysis. This loss needs to be corrected. SRSs help correct results for carbohydrates lost to aldehydes and other products. This correction affects all carbohydrate concentrations and requires careful analysis. This is especially true for 5-carbon sugars such as xylose and galactose, which are more susceptible to degradation.
To clean the crucibles, place them in the furnace and then wash them with deionized water. If ash material is stuck to the crucible, gently scrub it with a thumb to dislodge the material. NREL does not recommend using acid baths or soaps, which might add to crucible tare weights.
Protein in whole biomass is diverse in nature and behavior. Some protein is solubilized during extraction of the raw feedstock and is indirectly measured as the difference between whole feedstock protein and structural or extracted feedstock protein. A limited study at NREL indicated that one-third to two-thirds of protein is solubilized and that the amount is not predictable.
Process intermediate samples washed free of non-structural carbohydrates are the same as extracted feedstocks, and the analysis is the same after the process intermediate is washed.
We prepared calculation spreadsheets that we use at NREL. They are available in the calculations section.
Descriptions of any acronyms or terms used in the calculation spreadsheets are identified in the first tab of the workbook entitled "Read me." TRB stands for "Technical Record Book" and is the notebook NREL uses to document laboratory experiments.
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The following team members work on NREL's standard procedures for biomass compositional analysis.
- Ed Wolfrum, Research Supervisor/Manager
- David Crocker, Research Scientist
- Jeanette Henry, Research Technician
- Glendon Hunsinger, Research Scientist
- Deb Hyman, Research Technician
- Stefanie Maletich, Research Technician
- William Michener, Research Technician
- Ryan Ness, Research Technician
- Courtney Payne, Research Scientist
- Darren Peterson, Research Technician
- Kailee Potter, Research Technician
- Kelsey Ramirez, Research Technician
- Michelle Reed, Research Technician
- Amie Sluiter, Research Scientist/Manager
- Justin Sluiter, Research Scientist
- David Templeton, Research Scientist
- Stefanie Van Wychen, Research Scientist
- Jeff Wolfe, Research Technician