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Line Monitoring By Near-infrared Chemometric Technique For Potential Ethanol Production From Hydrothermally Treated Eucalyptus Globulus

Yoshiki Horikawa, M. Imai, K. Kanai, T. Imai, T. Watanabe, Keiji Takabe, Y. Kobayashi, J. Sugiyama
Published 2015 · Chemistry

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Abstract This study reports a method that combines near-infrared (NIR) measurements with multivariate analysis to predict the saccharification efficiency of hydrothermally pretreated Eucalyptus globulus during ethanol conversion. Optimization of the NIR data with or without spectral treatment determined the best calibration model in the region 10000–4000 cm −1 of the original spectra, with an RMSEP of 2.08% and R p 2 of 0.99. By investigating the regression coefficient to understand the key regions and chemical components, for original and multiplicative scatter correction (MSC)-treated spectra, the water absorption and higher wavenumber regions were important. For the second derivative spectra, the regression model was constructed based on the CH overtone vibrations (6050–5500 cm −1 ). The regression coefficient demonstrated that the removal of hemicellulose resulted in higher lignin content, which might affect the biomass properties in terms of water absorption and enhanced enzymatic hydrolysis evaluated by dinitrosalicylic acid (DNS) method. For a higher throughput system, aqueous sample analysis was performed using an immersion probe equipped with an InGaAs detector, which generated an acceptable calibration model having RMSEP of 4.25% and R p 2 of 0.94. These results show the great potential of NIR spectroscopy for achieving fast, accurate, and nondestructive analysis, and its highly adaptability for maintaining an ethanol bioconversion system.TGS, triglycine sulfate
This paper references
10.1016/J.COMPAG.2012.07.013
A feasibility study of the classification of Alpaca (Lama pacos) wool samples from different ages, sex and color by means of visible and near infrared reflectance spectroscopy
A. W. Canaza-Cayo (2012)
10.1021/AC60319A045
Smoothing and Differentiation of Data by Simplified Least Squares Procedures.
A. Savitzky (1964)
Nearinfrared spectroscopic determination of acetate
J. W. Hall (1996)
10.1366/0003702963906726
Near-Infrared Spectroscopic Determination of Acetate, Ammonium, Biomass, and Glycerol in an Industrial Escherichia Coli Fermentation
J. W. Hall (1996)
10.1002/JCTB.4427
Fourier transformed near infrared (FT‐NIR) spectroscopy for the estimation of parameters in pretreated lignocellulosic materials for bioethanol production
Mariel Monrroy (2015)
10.15376/BIORES.5.4.2081-2096
CHARACTERIZATION OF KEY PARAMETERS FOR BIOTECHNOLOGICAL LIGNOCELLULOSE CONVERSION ASSESSED BY FT-NIR SPECTROSCOPY. PART II: QUANTITATIVE ANALYSIS BY PARTIAL LEAST SQUARES REGRESSION
Chularat Krongtaew (2010)
10.2166/wst.2010.070
Near-infrared spectroscopic assessment of contamination level of sewage.
T. Inagaki (2010)
10.1016/0003-2697(62)90098-2
Reducing power by the dinitrosalicylic acid method.
W. W. Luchsinger (1962)
10.1007/S10570-009-9320-2
Improved multivariate calibration models for corn stover feedstock and dilute-acid pretreated corn stover
E. Wolfrum (2009)
10.1016/j.biortech.2007.12.063
Fast classification and compositional analysis of cornstover fractions using Fourier transform near-infrared techniques.
X. Philip Ye (2008)
10.1007/s12010-011-9460-3
Chemometric Analysis with Near-Infrared Spectroscopy for Chemically Pretreated Erianthus toward Efficient Bioethanol Production
Yoshiki Horikawa (2011)
10.1007/s12010-010-9127-5
Near-Infrared Chemometric Approach to Exhaustive Analysis of Rice Straw Pretreated for Bioethanol Conversion
Yoshiki Horikawa (2011)
10.1016/J.ACA.2003.08.066
Prediction of phenolic compounds in red wine fermentations by visible and near infrared spectroscopy
D. Cozzolino (2004)
10.1002/9780470999714.CH10
Chapter 10. Near Infrared Spectroscopic Monitoring of the Diffusion Process of Deuterium-Labeled Molecules in Wood
S. Tsuchikawa (2008)
10.1255/jnirs.3
Comparison of Commercial near Infrared Transmittance and Reflectance Instruments for Analysis of Whole Grains and Seeds
P. Williams (1993)
10.1021/BM7008069
Monitoring of hydroxyl groups in wood during heat treatment using NIR spectroscopy.
K. Mitsui (2008)
10.1016/J.BIORTECH.2004.06.025
Features of promising technologies for pretreatment of lignocellulosic biomass.
N. Mosier (2005)
10.1366/000370203322005364
Near-Infrared Spectroscopic Monitoring of the Diffusion Process of Deuterium-Labeled Molecules in Wood. Part I: Softwood
S. Tsuchikawa (2003)
10.1007/s10295-012-1195-9
Analysis of the saccharification capability of high-functional cellulase JN11 for various pretreated biomasses through a comparison with commercially available counterparts
Tetsushi Kawai (2012)
10.1163/22941932-90000109
Estimation of Microfibril Angle and Stiffness by near infrared Spectroscopy using sample sets having Limited wood Density Variation
L. Schimleck (2005)
10.1016/J.BEJ.2010.08.006
Applicability of near-infrared spectroscopy for process monitoring in bioethanol production.
B. Liebmann (2010)
10.1039/B412759E
Near-infrared spectroscopic observation of the ageing process in archaeological wood using a deuterium exchange method.
S. Tsuchikawa (2005)
10.15376/BIORES.5.4.2063-2080
CHARACTERIZATION OF KEY PARAMETERS FOR BIOTECHNOLOGICAL LIGNOCELLULOSE CONVERSION ASSESSED BY FT-NIR SPECTROSCOPY. PART I: QUALITATIVE ANALYSIS OF PRETREATED STRAW
Chularat Krongtaew (2010)
10.1351/pac198759020257
Measurement of cellulase activities
T. Ghose (1987)
10.1016/S0008-6215(01)00244-0
Rapid analysis of sugars in fruit juices by FT-NIR spectroscopy.
L. Rodriguez-Saona (2001)
10.1016/S0961-9534(96)00039-6
Compositional analysis of biomass feedstocks by near infrared reflectance spectroscopy
M. Sanderson (1996)
10.1016/J.CARBPOL.2010.03.058
Variability of biomass chemical composition and rapid analysis using FT-NIR techniques
L. Liu (2010)
10.1021/IE00004A026
Uncatalyzed solvolysis of whole biomass hemicellulose by hot compressed liquid water
W. Mok (1992)
10.1016/j.aca.2008.10.069
Determination of glucose and ethanol in bioethanol production by near infrared spectroscopy and chemometrics.
B. Liebmann (2009)



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