Skip to main content

Advertisement

SpringerLink
Log in

Quantifying Actual and Theoretical Ethanol Yields for Switchgrass Strains Using NIRS Analyses

  • Published:
BioEnergy Research Aims and scope Submit manuscript

Abstract

Quantifying actual and theoretical ethanol yields from biomass conversion processes such as simultanteous saccharification and fermentation (SSF) requires expensive, complex fermentation assays, and extensive compositional analyses of the biomass sample. Near-infrared reflectance spectroscopy (NIRS) is a non-destructive technology that can be used to obtain rapid, low-cost, high-throughput, and accurate estimates of agricultural product composition. In this study, broad-based NIRS calibrations were developed for switchgrass biomass that can be used to estimate over 20 components including cell wall and soluble sugars and also ethanol production and pentose sugars released as measured using a laboratory SSF procedure. With this information, an additional 13 complex feedstock traits can be determined including theoretical and actual ethanol yields from hexose fermentation. The NIRS calibrations were used to estimate feedstock composition and conversion information for biomass samples from a multi-year switchgrass (Panicum virgatum L.) biomass cultivar evaluation trial. There were significant differences among switchgrass strains for all biomass conversion and composition traits including actual ethanol yields, ETOHL (L Mg−1) and theoretical ethanol yields, ETOHTL (L Mg−1), based on cell wall and non-cell wall composition NIRS analyses. ETOHL means ranged from 98 to 115 L Mg−1 while ETOHTL means ranged from 203 to 222 L Mg−1. Because of differences in both biomass yields and conversion efficiency, there were significant differences among strains for both actual (2,534–3,720 L ha−1) and theoretical (4,878–7,888 L ha−1) ethanol production per hectare. It should be feasible to improve ethanol yields per hectare by improving both biomass yield and conversion efficiency by using NIRS analyses to quantify differences among cultivars and management practices.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Vogel KP, Jung HG (2001) Genetic modification of herbaceous plants for feed and fuel. Crit Rev Plant Sci 20:15–49

    Google Scholar 

  2. Roberts CA, Workman, J Jr, Reeves JB III (eds.) (2004) Near-infrared spectroscopy in agriculture. Agron Monog 44. ASA, CSSA, and SSSA, Madison, WI.

  3. Westerhaus M, Workman J, Reeves JB III, Mark H (2004). Quantitative analysis. In: Roberts CA, Workman J. Jr., Reeves JB (eds) Near-infrared spectroscopy in agriculture. Agron. Monog. 44. ASA, CSSA, and SSSA, Madison, WI, p 133–174

  4. Shenk JS, Westerhaus MO (1991) Population definition, sample selection, and calibration procedures for near-infrared reflectance spectroscopy. Crop Sci 31:469–474

    Article  Google Scholar 

  5. Wold S, Geladi P, Esbensen K, Öhman J (1987) Multi-way principal components and PLS analysis. J Chemom 1:41–56

    Article  CAS  Google Scholar 

  6. Wold S, Kettanehwold N, Skagerberg B (1989) Nonlinear PLS modeling. Chemom Intell Lab Syst 7:53–65

    Article  CAS  Google Scholar 

  7. Himmel ME (2007) Biomass recalcitrance: engineering plants and enzymes for biofuels production. Science 306:982

    Google Scholar 

  8. Yanase H, Yamamoto K, Matsuda S, Yamamoto S, Okamoto K (2007) Genetic engineering of Zymobacter palmae for production of ethanol from xylose. Appl Environ Microbiol 73:2592–2599

    Article  PubMed  CAS  Google Scholar 

  9. Sanderson MA, Agblevor F, Collins M, Johnson DK (1966) Compositional analysis of biomass feedstocks by near infrared reflectance spectroscopy. Biomass and Bioenergy 111:365–370

    Google Scholar 

  10. Maranan MC, Laborie MPG (2007) Analysis of energy traits of Populus spp. clones by near-infrared spectroscopy. J Biobased Mater Bioenergy 1:155–165

    Google Scholar 

  11. Hames BR, Thomas SR, Sluiter AD, Roth CJ, Templeton DW (2003) Rapid biomass analysis—new tools for compositional analysis of corn stover feedstocks and process intermediates from ethanol production. Appl Biochem Biotechnol 105:5–16

    Article  PubMed  Google Scholar 

  12. Lamb JFS, Jung HG, Sheaffer CC, Samac DA (2007) Alfalfa leaf protein and stem cell wall polysaccharide yields under hay and biomass management systems. Crop Sci 47:1407–1415

    Article  CAS  Google Scholar 

  13. Lorenz AJ, Coors JG, de Loen N, Wolfurm EJ, Hames BR, Sluiter AD, Weimer PJ (2009) Characterization, genetic variation, and combining ability of maize traits relevant to the production of cellulosic ethanol. Crop Sci 59:85–98

    Article  Google Scholar 

  14. Lorenzana RE, Lewis MF, Jung HG, Bernardo R (2010) Quantitative trait loci and trait correlations for maize stover cell wall composition and glucose release for cellulosic ethanol. Crop Sci 50:541–555

    Article  Google Scholar 

  15. Vogel KP, Brejda JJ, Walters DT, Buxton DR (2002) Switchgrass biomass production in the Midwest USA: harvest and nitrogen management. Agron J 94:413–420

    Article  Google Scholar 

  16. Casler MD, Vogel KP, Taliaferro CM, Wynia RE (2004) Latitudinal adaptation of switchgrass populations. Crop Sci 44:293–403

    Google Scholar 

  17. Moore KJ, Moser LE, Vogel KP, Waller SS, Johnson BE, Pedersen JF (1991) Describing and quantifying growth stages of perennial forage grasses. Agron J 83:1073–1077

    Article  Google Scholar 

  18. Varvel GE, Vogel KP, Mitchell RB, Follett RF, Kimble JM (2008) Comparison of corn and switchgrass on marginal soils for bioenergy. Biomass and Bioenergy 32:18–21

    Article  CAS  Google Scholar 

  19. Vogel KP, Mitchell RB (2008) Heterosis in switchgrass: biomass yield in swards. Crop Sci 48:2159–2164

    Article  Google Scholar 

  20. Murray I, Cowe, I (2004) Sample preparation. In: Roberts CA, Workman J Jr, Reeves JB III (eds) Near-infrared spectroscopy in agriculture. Agron Monog 44. ASA, CSSA, and SSSA, Madison, WI, p 75–112

  21. Dien BS (2010) Mass balances and analytical methods for biomass pre-treatment experiments. In: Vertes A, Qureshi N, Yukawa H, Blaschek H (eds) Biomass to biofuels: strategies for global industries. Wiley, United Kingdom, pp 213–231

    Chapter  Google Scholar 

  22. Bremner JM (1996) Nitrogen - Total. p. 1085–1121. In Sparks DL et al. (ed.) Methods of soil analysis. Part 3. Chemical methods. SSSA Book Ser. 5. SSSA and ASA, Madison, WI.

  23. Watson M E, Issac RA (1990) Analytical instruments for soil and plant analysis. In Westerman R (ed) Soil testing and plant analysis. (3rd Ed.). SSSA Book Ser. 3. SSSA, Madison, WI, p 691–704

  24. Padmore JM (1990a) Fat (crude) or ether extract in animal feed. Method 920.39. In: Herlich K (ed). Official methods of analysis of Association of Official Analytical Chemists. 15th ed. Arlington, VA.

  25. Dien BS, Jung HG, Vogel KP, Casler MD, Lamb JFS, Weimer PJ, Iten L, Mitchell RB, Sarath G (2006) Chemical composition and response to dilute-acid pretreatment and enzymatic saccharification of alfalfa, reed canarygrass, and switchgrass. Biomass Bioenergy 30:880–891

    Article  CAS  Google Scholar 

  26. Smith D (1973) The nonstructural carbohydrates. In: Butler GW, Bailey RW (eds) Chemistry and biochemistry of herbage, vol 1. Academic, New York, pp 105–155

    Google Scholar 

  27. Theander O, Aman P, Westerlund E, Andersson R, Pettersson D (1995) Total dietary fiber determined as neutral sugar residues, uronic acid residues, and Klason lignin (the Uppsala method): collaborative study. J AOAC Int 78:1030–1044

    PubMed  CAS  Google Scholar 

  28. Ahmed AER, Labavitch JM (1977) A simplified method for accurate determination of cell wall uronide content. J Food Biochem 1:361–365

    Article  CAS  Google Scholar 

  29. Iiyama K, Lam TBT, Stone BA (1990) Phenolic acid bridges between olysaccharides and lignin in wheat internodes. Phytochemistry 29:733–737

    Article  CAS  Google Scholar 

  30. Jung HG, Shalita-Jones SC (1990) Variation in the extractability of esterified p-coumaric and ferulic acids from forage cell walls. J Agric Food Chem 38:397–402

    Article  CAS  Google Scholar 

  31. Dowe N, McMillan J (2001) SSF Experimental Protocols—Lignocellulosic Biomass Hydrolysis and Fermentation; Laboratory Analytical Procedure (LAP). National Renewable Energy Laboratory, NREL/TP-510-42630. Available at http://www.nrel.gov/biomass/pdfs/42630.pdf. Accessed 08 Jan 09.

  32. Dien BS, Nagle N, Hicks KB, Singh V, Moreau RA, Tucker MP et al (2004) Fermentation of "Quick Fiber" produced from a modified corn-milling process into ethanol and recovery of corn fiber. Appl Biochem Biotechnol 113–116:937–949

    Article  PubMed  Google Scholar 

  33. Padmore JM (1990b) Protein (crude) in animal feed Dumas method. Method 968.06. In: Herlich K (eds) Official methods of analysis of Association of Official Analytical Chemists. 15th ed. Arlington, VA

  34. Vogel KP, Pedersen JF, Masterson SD, Toy JJ (1999) Evaluation of a filter bag system for NDF, ADF, and IVDMD forage analysis. Crop Sci 39:276–279

    Article  Google Scholar 

  35. SAS (2000-2004) SAS 9.1.3 help and documentation. SAS Institute Inc, Cary

    Google Scholar 

  36. Williams PC (1987) Variables affecting near-infrared reflectance spectroscopic analysis. In: Williams P, Norris K (eds) Near-infrared technology in the agriculture and food industries. 1st Ed. Am Cereal Assoc Cereal Chem, St. Paul, MN. p 143–167

Download references

Author information

Authors and Affiliations

  1. Grain, Forage, and Bioenergy Research Unit, Agricultural Research Service, US Department of Agriculture (USDA-ARS), University of Nebraska, 137 Keim Hall, P.O. Box 830937, Lincoln, NE, 68583-0937, USA

    Kenneth P. Vogel, Steven D. Masterson & Robert B. Mitchell

  2. Fermentation Biotechnology Research Unit, National Center for Agricultural Utilization Research, USDA-ARS, 1815 N. University Street, Peoria, IL, 61604, USA

    Bruce S. Dien

  3. Plant Science Research Unit, USDA-ARS, 411 Borlaug Hall, 1991 Upper Buford Circle, St. Paul, MN, 55108-6026, USA

    Hans G. Jung

  4. US Dairy Forage Research Center, 1925 Linden Dr. West, Madison, WI, 53706-1108, USA

    Michael D. Casler

Authors
  1. Kenneth P. Vogel
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bruce S. Dien
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hans G. Jung
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Michael D. Casler
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Steven D. Masterson
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Robert B. Mitchell
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kenneth P. Vogel.

Additional information

For abbreviations used in this paper, please refer to Table 1.

USDA neither guarantees nor warrants the standard of the product, and the use of the name by USDA implies no approval of the product to the exclusion of others that may also be suitable.

Ms. Patricia O’Bryan and Mr. Ted Joe are acknowledged for their excellent technical support in conducting the laboratory fermentation and composition experiments.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Vogel, K.P., Dien, B.S., Jung, H.G. et al. Quantifying Actual and Theoretical Ethanol Yields for Switchgrass Strains Using NIRS Analyses. Bioenerg. Res. 4, 96–110 (2011). https://doi.org/10.1007/s12155-010-9104-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12155-010-9104-4

Keywords

Search

Navigation