The authors would like to thank intern Evelyn Von Neida who provided paramount insights regarding the preparation of biomass samples for both of the high-throughput pipelines discussed in this manuscript. Support for the development of this work and manuscript was provided by the BioEnergy Science Center. The BioEnergy Science Center is a U.S. Department of Energy Bioenergy Research Center supported by the Office of Biological and Environmental Research in the DOE Office of Science. The National Renewable Energy Laboratory (NREL) is a national laboratory of the US DOE Office of Energy Efficiency and Renewable Energy, operated for DOE by the Alliance for Sustainable Energy, LLC. This work was supported by the U.S. Department of Energy under Contract No. DE-AC36-08-GO28308 with the National Renewable Energy Laboratory.

1. High-throughput Determination of Glucose and Xylose Yields Following Enzymatic Saccharification9,29
<ol>
	<li>Sample Preparation (Grinding, De-starching, Extraction, Pretreatment)
	<ol>
		<li>Grind at least 300 mg of each biomass sample using a Wiley mill, such that the particles pass through a 20 mesh (850 &#181;m) screen. Transfer to anti-static zip-top bags (typically bar-coded) and record sample information to the barcode database.</li>
		<li>Add approximately 250 mg or more of the ground biomass from...

<ol>
	<li>Perlack, R. D., Stokes, B. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> U.S. Billion-Ton Update: Biomass Supply for a Bioenergy and Bioproducts Industry. , (2011).</li><li>Henry, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ch.+5.">Ch. 5.</a> Plant Resources for Food, Fuel and Conservation. , 53-80 (2009).</li><li>Henry, R. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+plant+biomass+resources+available+for+replacement+of+fossil+oil.">Evaluation of plant biomass resources available for replacement of fossil oil.</a> Plant Biotechnol. J. 8 (3), 288-293 (2010).</li><li>Furtado, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modifying+plants+for+biofuel+and+biomaterial+production.">Modifying plants for biofuel and biomaterial production.</a> Plant Biotechnol. J. 12 (9), 1246-1258 (2014).</li><li>Sluiter, J. B., Ruiz, R. O., Scarlata, C. J., Sluiter, A. D., Templeton, D. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Compositional+analysis+of+lignocellulosic+feedstocks.+1.+Review+and+description+of+methods.">Compositional analysis of lignocellulosic feedstocks. 1. Review and description of methods.</a> J. Agric. Food Chem. 58 (16), 9043-9053 (2010).</li><li>Lupoi, J. S., Singh, S., Simmons, B. A., Henry, R. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Assessment+of+Lignocellulosic+Biomass+Using+Analytical+Spectroscopy:+an+Evolution+to+High-Throughput+Techniques.">Assessment of Lignocellulosic Biomass Using Analytical Spectroscopy: an Evolution to High-Throughput Techniques.</a> Bioenerg. Res. 7 (1), 1-23 (2014).</li><li>Lapierre, C., Monties, B., Rolando, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Thioacidolysis+of+lignin:+comparison+with+acidolysis.">Thioacidolysis of lignin: comparison with acidolysis.</a> J. Wood Chem. Technol. 5 (2), 277-292 (1985).</li><li>DeMartini, J. D., Studer, M. H., Wyman, C. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Small-scale+and+automatable+high-throughput+compositional+analysis+of+biomass.">Small-scale and automatable high-throughput compositional analysis of biomass.</a> Biotechnol. Bioeng. 108 (2), 306-312 (2010).</li><li>Selig, M. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High+throughput+determination+of+glucan+and+xylan+fractions+in+lignocelluloses.">High throughput determination of glucan and xylan fractions in lignocelluloses.</a> Biotechnol. Lett. 33 (5), 961-967 (2011).</li><li>Selig, M. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Lignocellulose+recalcitrance+screening+by+integrated+high-throughput+hydrothermal+pretreatment+and+enzymatic+saccharification.">Lignocellulose recalcitrance screening by integrated high-throughput hydrothermal pretreatment and enzymatic saccharification.</a> Ind. Biotechnol. 6 (2), 104-111 (2010).</li><li>Studer, M. H., De Martini, J. D., Brethauer, S., McKenzie, H. L., Wyman, C. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Engineering+of+a+high-throughput+screening+system+to+identify+cellulosic+biomass,+pretreatments,+and+enzyme+formulations+that+enhance+sugar+release.">Engineering of a high-throughput screening system to identify cellulosic biomass, pretreatments, and enzyme formulations that enhance sugar release.</a> Biotechnol. Bioeng. 105 (2), 231-238 (2009).</li><li>Gjersing, E., Happs, R. M., Sykes, R. W., Doeppke, C., Davis, M. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rapid+determination+of+sugar+content+in+biomass+hydrolysates+using+nuclear+magnetic+resonance+spectroscopy.">Rapid determination of sugar content in biomass hydrolysates using nuclear magnetic resonance spectroscopy.</a> Biotechnol. Bioeng. 110 (3), 721-728 (2013).</li><li>Templeton, D. W., Sluiter, A. D., Hayward, T. K., Hames, B. R., Thomas, S. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Assessing+corn+stover+composition+and+sources+of+variability+via+NIRS.">Assessing corn stover composition and sources of variability via NIRS.</a> Cellulose (Dordrecht, Netherlands). 16 (4), 621-639 (2009).</li><li>Tucker, M. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fourier+transform+infrared+quantification+of+sugars+in+pretreated+biomass+liquors.">Fourier transform infrared quantification of sugars in pretreated biomass liquors.</a> Appl. Biochem. Biotechnol. 84-86, 39-50 (2000).</li><li>Wolfrum, E. J., Sluiter, A. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Improved+multivariate+calibration+models+for+corn+stover+feedstock+and+dilute-acid+pretreated+corn+stover.">Improved multivariate calibration models for corn stover feedstock and dilute-acid pretreated corn stover.</a> Cellulose (Dordrecht, Netherlands). 16 (4), 567-576 (2009).</li><li>Ona, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Non-destructive+determination+of+wood+constituents+by+Fourier-transform+Raman+spectroscopy.">Non-destructive determination of wood constituents by Fourier-transform Raman spectroscopy.</a> J. Wood Chem. Technol. 17 (4), 399-417 (1997).</li><li>Ona, T., Sonoda, T., Ohshima, J., Yokota, S., Yoshizawa, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+rapid+quantitative+method+to+assess+eucalyptus+wood+properties+for+kraft+pulp+production+by+FT-Raman+spectroscopy.">A rapid quantitative method to assess eucalyptus wood properties for kraft pulp production by FT-Raman spectroscopy.</a> J. Pulp Pap. Sci. 29 (1), 6-10 (2003).</li><li>Hames, B. R., Thomas, S. R., Sluiter, A. D., Roth, C. J., Templeton, D. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rapid+biomass+analysis.+New+tools+for+compositional+analysis+of+corn+stover+feedstocks+and+process+intermediates+from+ethanol+production.">Rapid biomass analysis. New tools for compositional analysis of corn stover feedstocks and process intermediates from ethanol production.</a> Appl. Biochem. Biotechnol. 105-108, 5-16 (2003).</li><li>Studer, M. H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Lignin+content+in+natural+Populus+variants+affects+sugar+release.">Lignin content in natural Populus variants affects sugar release.</a> Proc. Natl. Acad. Sci. U. S. A. 108 (15), 6300-6305 (2011).</li><li>Chen, M., Zhao, J., Xia, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+four+different+chemical+pretreatments+of+corn+stover+for+enhancing+enzymatic+digestibility.">Comparison of four different chemical pretreatments of corn stover for enhancing enzymatic digestibility.</a> Biomass Bioenergy. 33 (10), 1381-1385 (2009).</li><li>Davison, B. H., Drescher, S. R., Tuskan, G. A., Davis, M. F., Nghiem, N. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Variation+of+S/G+ratio+and+lignin+content+in+a+Populus.+family+influences+the+release+of+xylose+by+dilute+acid+hydrolysis.">Variation of S/G ratio and lignin content in a Populus. family influences the release of xylose by dilute acid hydrolysis.</a> Appl. Biochem. Biotechnol. 129-132, 427-435 (2006).</li><li>Li, X., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Lignin+monomer+composition+affects+Arabidopsis+cell-wall+degradability+after+liquid+hot+water+pretreatment.">Lignin monomer composition affects Arabidopsis cell-wall degradability after liquid hot water pretreatment.</a> Biotechnol. Biofuels. 3, 27-33 (2010).</li><li>Lupoi, J. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+prediction+of+eucalypt+lignin+syringyl/guaiacyl+content+using+multivariate+analysis:+a+comparison+between+mid-infrared,+near-infrared,+and+Raman+spectroscopies+for+model+development.">High-throughput prediction of eucalypt lignin syringyl/guaiacyl content using multivariate analysis: a comparison between mid-infrared, near-infrared, and Raman spectroscopies for model development.</a> Biotechnol. Biofuels. 7, 93 (2014).</li><li>Lupoi, J. S., Smith, E. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterization+of+woody+and+herbaceous+biomasses+lignin+composition+with+1064+nm+dispersive+multichannel+Raman+spectroscopy.">Characterization of woody and herbaceous biomasses lignin composition with 1064 nm dispersive multichannel Raman spectroscopy.</a> Appl. Spectro. 66 (8), 903-910 (2012).</li><li>Sun, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rapid+determination+of+syringyl:guaiacyl+ratios+using+FT-Raman+spectroscopy.">Rapid determination of syringyl:guaiacyl ratios using FT-Raman spectroscopy.</a> Biotechnol. Bioeng. 109 (3), 647-656 (2012).</li><li>Lupoi, J. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+prediction+of+Acacia+and+eucalypt+lignin+syringyl/guaiacyl+content+using+FT-Raman+spectroscopy+and+partial+least+squares+modeling.">High-throughput prediction of Acacia and eucalypt lignin syringyl/guaiacyl content using FT-Raman spectroscopy and partial least squares modeling.</a> Bioenerg. Res. in press, (2015).</li><li>Sykes, R., Kodrzycki, B., Tuskan, G., Foutz, K., Davis, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Within+tree+variability+of+lignin+composition+in+Populus.">Within tree variability of lignin composition in Populus.</a> Wood Sci. Technol. 42 (8), 649-661 (2008).</li><li>Sykes, R., Mielenz, J. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ch.+12.+High-Throughput+Screening+of+Plant+Cell-Wall+Composition+Using+Pyrolysis+Molecular+Beam+Mass+Spectroscopy.">Ch. 12. High-Throughput Screening of Plant Cell-Wall Composition Using Pyrolysis Molecular Beam Mass Spectroscopy.</a> Biofuels: Methods and Protocols. 581, 169-183 (2009).</li><li>Decker, S., Himmel, M. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ch.+17.+Reducing+the+effect+of+variable+starch+levels+in+biomass+recalcitrance+screening).">Ch. 17. Reducing the effect of variable starch levels in biomass recalcitrance screening).</a> Biomass Conversion. 908, 181-195 (2012).</li><li>Evans, R. J., Milne, T. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+characterization+of+the+pyrolysis+of+biomass.">Molecular characterization of the pyrolysis of biomass.</a> Energy Fuels. 1 (2), 123-137 (1987).</li></ol>

The key sample preparation steps for obtaining accurate and reproducible data when conducting high-throughput screening experiments are as follows:
Sugar Release Assay:
In general, samples are prepared in lots ranging from a few dozen to several thousand at a time. Each major step is typically carried out for all samples prior to moving forward in order to minimize variations in preparation between samples. De-starching was not originally part of the protocol and ca...

As the global supply of non-renewable fuels and their associated products declines, scientists have been challenged to create similar fuels and chemicals from plant-derived sources1. A key aspect of this work is determining which species of plants may be suitable for the production of biofuels and biomaterials2,3. Typically, these feedstocks are evaluated for lignin, cellulose, and hemicellulose content; as well as their susceptibility to deconstruction (recalcitrance) through thermal, mechanical, and/or chemical pretreatment with or without subsequent enzyme saccharification. More detailed analyses are used to determine the specific composition of the lignin and hemicellulose fractions as well as optimal enzyme activities needed. Transgenic modifications of plants that do not intrinsically possess ideal traits for biochemical or thermochemical conversion to desired commodities have provided researchers with a greatly expanded source of potential feedstocks4. The standard analytical methods for quantifying the chemical traits of a plant, while quite useful for small sample sets, are unsuited for the rapid screening of hundreds or thousands of samples5-7. The HTP methods described herein have been developed to rapidly and efficiently evaluate large numbers of biomass variants for changes in cell wall recalcitrance to thermochemical and/or enzymatic degradation.
It is critical to understand that the HTP screening assays described herein have not been designed to maximize conversion or yield. The objective is to determine relative differences in the intrinsic recalcitrance of related biomass samples. As a result, many of the analysis steps differ from the &#8220;typical&#8221; biomass conversion assays, where the objective is to obtain maximum conversion rate or extent. For example, lower pretreatment severities and shorter enzyme hydrolysis times are used to maximize differences between samples. In most cases, relatively high enzyme loadings are used to reduce differences due to experimental variation in enzyme activity, which could skew the results significantly.
Rapid techniques for determining the composition of plant cell-walls and the monomeric sugars liberated following enzymatic saccharification include robotics, customized, thermochemically compatible 96-well plates, and modifications of standard laboratory methods8-11 and instrumental protocols, such as vibrational spectroscopy (infrared (IR), near-infrared (NIR), or Raman) and nuclear magnetic resonance (NMR)12-17. These methodologies are key to isolating feedstocks with high cellulose or low lignin contents, or those expected to yield the highest glucose, xylose, ethanol, etc. These methods have enabled downscaled analyses that employ smaller quantities of biomass and consumables, leading to reductions in experimental expense18. Another feature of this methodological approach is that various experimental conditions can be rapidly, and in some cases simultaneously, evaluated. For example, a variety of different pretreatment strategies or enzyme cocktails can be tested, allowing the most optimal experimental parameters to be quickly identified and employed. Popular feedstocks, such as corn stover9, poplar8,10, sugarcane bagasse8, and switchgrass8 have been successfully evaluated using these HTP methods.
Total lignin and lignin monomeric composition are also commonly quantified biomass traits. Reductions in lignin content have been shown to increase the enzymatic digestibility of polysaccharides19,20. The role that the lignin monomeric ratio (often reported as syringyl/guaiacyl (S/G) content) plays in the deconstruction of the plant cell wall is still under investigation. Some reports have indicated that reductions in the S/G ratio led to increased glucose yields following hydrolysis21, while other studies unveil the opposite trend19,22. High throughput methods for evaluating lignin and its monomers include vibrational spectroscopy (IR, NIR, and Raman23-26) coupled with multivariate analysis, and pyrolysis molecular beam mass spectrometry (pyMBMS)27,28.
When developing HTP methods for screening biomass, several integral considerations need to be kept in mind. One key aspect is the complexity of the method. What is the required skill level for the technique? Chemometric analyses, for example, require specific skills for constructing, evaluating, and maintaining predictive models. The standard methods exhibit undesirable preparatory or data analysis steps or employ toxic reagents. Development of the models is an ongoing process where new data is incorporated into the model over time to increase the model&#8217;s robustness. Another consideration is the cost-savings and decreased experimental analysis times of the proposed high-throughput methods. If the method is quite rapid, but very costly, it may not be a feasible technique for many labs to adopt. The methods illustrated in this manuscript are variants of standardized techniques, modified to amplify the throughput capabilities. These protocols quantitatively measure the biomass traits of interest without necessitating the development of predictive models. This is a key attribute of these techniques, since predictive methods, while exhibiting strong correlations with the standard analyses used to develop the models, are not as accurate as actually measuring the quantity of interest for the samples. Whereas the methods used are essentially scaled down versions of standard bench-scale analytical methods, accuracy and precision are traded for speed and throughput. Mostly, this outcome is due to higher errors in small volume pipetting and weighing; as well as increased sample heterogeneity as sample size is decreased. While large sample sets can be screened and compared, great care must be exercised when making comparisons between separate campaigns and to bench-scale results.
The most time-consuming steps involve the physical manipulation of the biomass. Grinding samples may take several min per sample, including cleaning out the mill between samples. Manually loading, unloading, and cleaning hoppers and filling and emptying tea bags and sample bags is also very labor intensive. While each step may take a minute or more, doing thousands of samples may take many hours or even days. The robots can load a typical reactor plate with biomass in about 3 to 4 hr or 6 to 8 plates day-1 robot-1. This situation depends on the precision parameters used as well as the type and amount of biomass to be tested. Filling reactor plates with water, dilute acid, or enzyme is quickly done using a liquid handling robot. Pretreatment of a plate stack (1 to 20 reactor plates) takes between 1 and 3 hr when assembly, cool down, and disassembly is included. Enzyme hydrolysis takes 3 days and the sugar analysis requires about 1 hr of prep time plus 10 min per reactor plate to complete the assay and read the results. A weekly schedule of set pretreatment and analysis days accommodates a reasonable work schedule, minimizing odd-hour and weekend efforts for the human component of the assay and allows for processing ~800 to 1,000 samples per week on an ongoing basis. The maximum throughput depends on several factors, mainly how much hardware (robots, reactors plates, etc.) and how much &#8220;software&#8221; (i.e., staffing) are available to do the manual work. The practical upper limit is 2,500 to 3,000 samples/week; however, that output requires 7 day-a-week operation and multiple student interns and technicians. In comparison, 3,000 samples by HPLC would require approximately 125 days of sample analysis plus the additional labor of manually weighing samples into reactors and filtering samples prior to analysis.

<table border="0" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td>Wiley mill</td>
			<td>Thomas Scientific</td>
			<td>3375E15 (Model 4), or 3383L20 (Mini-mill)</td>
			<td></td>
		</tr>
		<tr>
			<td>anti-static bags</td>
			<td>Minigrip*</td>
			<td>MGST4P02503</td>
			<td>2.5x3&#34;, multiple suppliers available</td>
		</tr>
		<tr>
			<td>tin-coated copper wire</td>
			<td>McMaster-Carr</td>
			<td>8871K84</td>
			<td>0.016&#34; diameter, bend-and-stay wire</td>
		</tr>
		<tr>
			<td>tea-bags</td>
			<td>Herbco</td>
			<td>press n&#39; brew teabags</td>
			<td>3.5x5 inches</td>
		</tr>
		<tr>
			<td>gluco-amylase</td>
			<td>Novozymes</td>
			<td>Spirizyme Fuel&#160;</td>
			<td></td>
		</tr>
		<tr>
			<td>alpha-amylase</td>
			<td>Novozymes</td>
			<td>Liquozyme SC DS</td>
			<td></td>
		</tr>
		<tr>
			<td align="left">
			<table cellpadding="0" cellspacing="0">
				<tbody>
					<tr>
						<td>sodium acetate trihydrate</td>
					</tr>
				</tbody>
			</table>
			</td>
			<td>any chemical supplier</td>
			<td></td>
			<td>reagent grade</td>
		</tr>
		<tr>
			<td>acetic acid</td>
			<td>any chemical supplier</td>
			<td></td>
			<td>reagent grade</td>
		</tr>
		<tr>
			<td>190 proof (95%) ethanol</td>
			<td>any chemical supplier</td>
			<td></td>
			<td>reagent grade</td>
		</tr>
		<tr>
			<td>hoppers</td>
			<td>Freeslate</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>96-well C-276 Hastelloy plates</td>
			<td>Aspen Machining (Lafayette, Colorado)</td>
			<td>N/A (custom built)</td>
			<td></td>
		</tr>
		<tr>
			<td>1/8&#8221; soldering iron tip</td>
			<td>Sears</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>silicone-adhesive backed Teflon tape</td>
			<td>3M</td>
			<td>5180</td>
			<td>3&#34; wide (36-yard rolls)</td>
		</tr>
		<tr>
			<td>enzyme solution</td>
			<td>Novozymes</td>
			<td></td>
			<td>Cellic CTec2</td>
		</tr>
		<tr>
			<td>citric acid monohydrate</td>
			<td>any chemical supplier</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>trisodium citrate dihydrate</td>
			<td>any chemical supplier</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>disposable, polystyrene 96-well plates</td>
			<td>Greiner Bio-One</td>
			<td>655101</td>
			<td>or equivalent; multiple suppliers available</td>
		</tr>
		<tr>
			<td>glucose oxidase/peroxidase&#160;</td>
			<td>Megazyme</td>
			<td>K-Gluc</td>
			<td>Megazyme D-glucose assay kit</td>
		</tr>
		<tr>
			<td>xylose dehydrogenase</td>
			<td>Megazyme</td>
			<td>K-Xylose</td>
			<td>Megazyme D-xylose assay kit</td>
		</tr>
		<tr>
			<td>glucose standard solution</td>
			<td>Megazyme</td>
			<td>K-Gluc</td>
			<td>Megazyme D-glucose assay kit</td>
		</tr>
		<tr>
			<td>xylose standard solution</td>
			<td>Megazyme</td>
			<td>K-Xylose</td>
			<td>Megazyme D-xylose assay kit</td>
		</tr>
		<tr>
			<td>stainless steel sample cups</td>
			<td>Frontier Laboratories</td>
			<td>PY1-EC80F</td>
			<td></td>
		</tr>
		<tr>
			<td>glass fiber sheets</td>
			<td>Pall</td>
			<td>66227</td>
			<td>8x10&#34; sheets--circles punched with standard hole punch</td>
		</tr>
		<tr>
			<td>Sugarcane Bagasse Whole Biomass Feedstock</td>
			<td>NIST</td>
			<td>8491</td>
			<td></td>
		</tr>
		<tr>
			<td>Eastern Cottonwood (poplar) Whole Biomass Feedstock</td>
			<td>NIST</td>
			<td>8492</td>
			<td></td>
		</tr>
		<tr>
			<td>Monterey Pine Whole Biomass Feedstock</td>
			<td>NIST</td>
			<td>8493</td>
			<td></td>
		</tr>
		<tr>
			<td>Wheat Straw Whole Biomass Feedstock</td>
			<td>NIST</td>
			<td>8494</td>
			<td></td>
		</tr>
	</tbody>
</table>

high-throughput screening of recalcitrance variations in lignocellulosic biomass: total lignin, lignin monomers, and enzymatic sugar release

The conversion of lignocellulosic biomass to fuels, chemicals, and other commodities has been explored as one possible pathway toward reductions in the use of non-renewable energy sources. In order to identify which plants, out of a diverse pool, have the desired chemical traits for downstream applications, attributes, such as cellulose and lignin content, or monomeric sugar release following an enzymatic saccharification, must be compared. The experimental and data analysis protocols of the standard methods of analysis can be time-consuming, thereby limiting the number of samples that can be measured. High-throughput (HTP) methods alleviate the shortcomings of the standard methods, and permit the rapid screening of available samples to isolate those possessing the desired traits. This study illustrates the HTP sugar release and pyrolysis-molecular beam mass spectrometry pipelines employed at the National Renewable Energy Lab. These pipelines have enabled the efficient assessment of thousands of plants while decreasing experimental time and costs through reductions in labor and consumables.

The combined effect of the thermochemical pretreatment and subsequent enzyme saccharification is measured as a function of the mass of glucose and xylose released at the end of the assay. The results are reported in terms of milligrams of glucose and xylose released per gram of biomass. This is in stark contrast to data reported from bench-scale assays, which is usually reported as percent theoretical yield based on compositional analysis of the starting material. As it is not yet practical to carry out compositional ana...

Watch this Scientific Journal Video about High-throughput Screening of Recalcitrance Variations in Lignocellulosic Biomass: Total Lignin, Lignin Monomers, and Enzymatic Sugar Release at JoVE.com

High-throughput Screening of Recalcitrance Variations in Lignocellulosic Biomass: Total Lignin, Lignin Monomers, and Enzymatic Sugar Release

Plant cell wall structure and chemistry traits are evaluated to identify ideal feedstocks for biofuels and bio-materials. Standard methods have limitations when applied to large data sets. These high-throughput pretreatment, enzyme saccharification, and pyrolysis-molecular beam mass spectrometry methods compare large numbers of biomass samples with decreased experimental time and cost.

The conversion of lignocellulosic biomass to fuels, chemicals, and other commodities has been explored as one possible pathway toward reductions in the ...

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Research

JoVE Journal

Environment

9.9K Views.  National Renewable Energy Laboratory. Plant cell wall structure and chemistry traits are evaluated to identify ideal feedstocks for biofuels and bio-materials. Standard methods have limitations when applied to large data sets. These high-throughput pretreatment, enzyme saccharification, and pyrolysis-molecular beam mass spectrometry methods compare large numbers of biomass samples with decreased experimental time and cost.