Abstract
Attenuated total reflectance Fourier transform mid-infrared (ATR-FTIR) spectroscopy is widely applicable for the chemical analysis of biological materials, relatively inexpensive, requires only simple sample preparation, and is of comparatively high-throughput compared to traditional wet chemical or chromatographic methods. It is particularly well suited for the nondestructive analysis of dried and finely ground plant samples for the subsequent prediction of cell wall and other compositional or processing parameters using chemometric regression models. Furthermore, analysis of mid IR spectra by nonregression methods (e.g., principal component analysis) provides a straightforward approach for multivariate comparison of the effects of experimental, processing, and environmental treatments, and genotypic and temporal differences on chemical composition including changes in cell wall composition. There is thus great potential for using ATR-FTIR in the lignocellulosic biomass industry at a number of levels. Here we describe methods for cell wall sample preparation and generation of ATR-FTIR spectra, and suggest techniques for the statistical analysis and/or chemometric pattern recognition between the analyzed samples.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Pauly M, Keegstra K (2008) Cell-wall carbohydrates and their modification as a resource for biofuels. Plant J 54(4):559–568
Himmel ME et al (2007) Biomass recalcitrance: engineering plants and enzymes for biofuels production. Science 315:804–807
Torres AF et al (2016) Maize feedstocks with improved digestibility reduce the costs and environmental impacts of biomass pretreatment and saccharification. Biotechnol Biofuels 9(1):1–15
Allison GG (2011) Application of Fourier transform mid-infrared spectroscopy (FTIR) for research into biomass feed-stocks. In: Nokolic G (ed) Fourier transforms – new analytical approaches and FTIR strategies. Intech, London, pp 71–88
Stewart B (2005) Infrared spectroscopy: fundamentals and applications. John Wiley & Sons, Ltd, Hoboken, NJ
Smith BC (2011) Fundamentals of Fourier transform infrared spectroscopy, 2nd edn. CRC Press, Boca Raton, FL
Movasaghi Z, Rehman S, Rehman IU (2008) Fourier transform infrared (FTIR) spectroscopy of biological tissues. Appl Spectrosc Rev 43(2):134–179
Sills DL, Gossett JM (2012) Using FTIR to predict saccharification from enzymatic hydrolysis of alkali-pretreated biomasses. Biotechnol Bioeng 109(2):353–362
Zhou G, Taylor G, Polle A (2011) FTIR-ATR-based prediction and modelling of lignin and energy contents reveals independent intra-specific variation of these traits in bioenergy poplars. Plant Methods 7(1):9
Kumar R et al (2009) Physical and chemical characterizations of corn stover and poplar solids resulting from leading pretreatment technologies. Bioresour Technol 100:3948–3962
Allison GG et al (2009) Measurement of key compositional parameters in two species of energy grass by Fourier transform infrared spectroscopy. Bioresour Technol 100:2428–2433
da Costa RMF, Allison GG, Bosch M (2015) Cell wall biomass preparation and Fourier transform mid-infrared (FTIR) spectroscopy to study cell wall composition. Bioprotocol 5(11):1–7
Agger J, Meyer AS (2012) Alteration of biomass composition in response to changing substrate particle size and the consequences for enzymatic hydrolysis of corn bran. Bioresources 7:3378–3397
Bridgeman TG et al (2007) Influence of particle size on the analytical and chemical properties of two energy crops. Fuel 86(1–2):60–72
Hames B et al (2008) Preparation of samples for compositional analysis. In: Laboratory analytical procedure (LAP). National Renewable Energy Laboratory, Golden, CO
Allison GG et al (2010) Measurement of lignocellulose composition as a tool to understand how feed-stocks can be matched to conversion process. In: Bioten. CPL Press, Birmingham
Foster CE, Martin TM, Pauly M (2010) Comprehensive compositional analysis of plant cell walls (lignocellulosic biomass) part II: carbohydrates. J Vis Exp 37. http://www.jove.com/video/1837/comprehensive-compositional-analysis-plant-cell-walls-lignocellulosic
Persson S et al (2007) The Arabidopsis irregular xylem8 mutant Is deficient in glucuronoxylan and homogalacturonan, which are essential for secondary cell wall integrity. Plant Cell 19(1):237–255
Kong Y et al (2011) Molecular analysis of a family of Arabidopsis genes related to galacturonosyltransferases. Plant Physiol 155(4):1791–1805
Bro R, Smilde AK (2003) Centering and scaling in component analysis. J Chemom 17(1):16–33
Bro R et al (2008) Cross-validation of component models: a critical look at current methods. Anal Bioanal Chem 390(5):1241–1251
Kjeldahl K, Bro R (2010) Some common misunderstandings in chemometrics. J Chemom 24(7–8):558–564
Manly BFJ (2005) Multivariate statistical methods a primer. Chapman and Hall, London
Otto M (2007) Chemometrics. Wiley-VCH, Weinheim
Mur LAJ et al (2011) Exploiting the Brachypodium tool box in cereal and grass research. New Phytol 191(2):334–347
Allison GG et al (2009) Quantification of hydroxycinnamic acids and lignin in perennial forage and energy grasses by Fourier-transform infrared spectroscopy and partial least squares regression. Bioresour Technol 100:1252–1261
Belanche A et al (2013) Estimation of feed crude protein concentration and rumen degradability by Fourier-transform infrared spectroscopy. J Dairy Sci 96(12):7867–7880
Foster CE, Martin TM, Pauly M (2010) Comprehensive compositional analysis of plant cell walls (lignocellulosic biomass) part I: lignin. J Vis Exp 37. http://www.jove.com/video/1745/comprehensive-compositional-analysis-plant-cell-walls-lignocellulosic
Hatfield RD, Brei K, Grabber JH (1996) Revising the acetyl bromide assay to optimise lignin determinations in forage plants, in 1996 research summaries, ARS, USDA. USDA, Washington, DC
Hatfield RD et al (1999) Using the acetyl bromide assay to determine lignin concentrations in herbaceous plants: some cautionary notes. J Agric Food Chem 47(2):628–632
Yeniay Ö, Göktaş A (2002) A comparison of partial least squares regression with other prediction methods. Hacet J Math Stat 31:99–111
Zhang L, Garcia-Munoz S (2009) A comparison of different methods to estimate prediction uncertainty using partial least squares (PLS): a practitioner’s perspective. Chemom Intell Lab Syst 97(2):152–158
Allison GG et al (2011) Genotypic variation in cell wall composition in a diverse set of 244 accessions of miscanthus. Biomass Bioenergy 35(11):4740–4747
Norgaard L et al (2000) Interval partial least-squares regression (iPLS): a comparative chemometric study with an example from near-infrared spectroscopy. Appl Spectrosc 54(3):413–419
Leardi R, Nørgaard L (2004) Sequential application of backward interval partial least squares and genetic algorithms for the selection of relevant spectral regions. J Chemom 18(11):486–497
Acknowledgments
This work was supported by European Regional Development Funding through the Welsh Government for BEACON Grant number 8056; the Biotechnology and Biological Sciences Research Council (BBSRC) Institute Strategic Programme Grant on Energy Grasses & Biorefining (BBS/E/W/10963A01); and Supergen Bioenergy (EPSRC GR/S28204). Special thanks are also due to Prof. Luis Mur (IBERS, Aberystwyth University) for assistance with the Blumeria graminis/Brachypodium distachyon infection experiment which is used in this chapter to illustrate PCA .
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Science+Business Media, LLC, part of Springer Nature
About this protocol
Cite this protocol
da Costa, R.M.F., Barrett, W., Carli, J., Allison, G.G. (2020). Analysis of Plant Cell Walls by Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy. In: Popper, Z. (eds) The Plant Cell Wall. Methods in Molecular Biology, vol 2149. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0621-6_16
Download citation
DOI: https://doi.org/10.1007/978-1-0716-0621-6_16
Published:
Publisher Name: Humana, New York, NY
Print ISBN: 978-1-0716-0619-3
Online ISBN: 978-1-0716-0621-6
eBook Packages: Springer Protocols