Fast Determination of the Composition of Pretreated Sugarcane Bagasse Using Near-Infrared Spectroscopy

被引:0
作者
Ursula Fabiola Rodríguez-Zúñiga
Cristiane Sanchez Farinas
Renato Lajarim Carneiro
Gislene Mota da Silva
Antonio Jose Gonçalves Cruz
Raquel de Lima Camargo Giordano
Roberto de Campos Giordano
Marcelo Perencin de Arruda Ribeiro
机构
[1] Federal University of São Carlos,Department of Chemical Engineering
[2] Embrapa Instrumentation,Department of Chemistry
[3] Federal University of São Carlos,undefined
来源
BioEnergy Research | 2014年 / 7卷
关键词
Near-infrared spectroscopy; Partial least squares; Pretreated sugarcane bagasse; Lignocellulose composition;
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中图分类号
学科分类号
摘要
The chemical composition of pretreated sugarcane bagasse (SCB), in terms of cellulose, hemicellulose and lignin, was analyzed using a fast near-infrared spectroscopy (NIR) technique. Spectra of four types of SCB, prepared using ammonia, hydrothermal, organosolv, and sodium hydroxide pretreatments, were correlated with results of classical chemical analyses using partial least squares (PLS) regression. In a novel approach, isolation of the components used to prepare synthetic samples of SCB permitted assessment of their influence on the model. Inclusion of the synthetic samples did not improve the performance of the model, due to structural differences such as chemical bonding and physical interactions between the components. For natural pretreated samples, the PLS technique showed good predictive capacity in the ranges (%, w/w) of 47.2–89.4 (cellulose), 0.2–27.0 (hemicellulose), and 2.1–30.0 (lignin) with low root-mean-square error values of 4.1, 3.8, and 3.5, respectively, and coefficient of determination higher than 0.80, demonstrating the suitability of using different pretreated samples in the same calibration model.
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页码:1441 / 1453
页数:12
相关论文
共 101 条
[1]  
Sluiter JB(2010)Compositional analysis of lignocellulosic feedstocks. 1. Review and description of methods J Agr Food Chem 58 9043-9053
[2]  
Ruiz RO(2013)Qualitative and quantitative analysis of lignocellulosic biomass using infrared techniques: a mini-review Appl Energ 104 801-809
[3]  
Scarlata CJ(2010)Near infrared spectroscopy as a screening tool for sugar release and chemical composition of wheat straw J Biobased Mat Bioenerg 4 378-383
[4]  
Sluiter AD(2013)A review of recent near-infrared research for wood and paper (part 2) Appl Spectrosc Rev 48 560-587
[5]  
Templeton DW(2011)A review of band assignments in near infrared spectra of wood and wood components J Near Infrared Spec 19 287-308
[6]  
Xu F(2010)Global near infrared models to predict lignin and cellulose content of pine wood J Near Infrared Spec 18 367-380
[7]  
Yu J(2009)Review of the most common pre-processing techniques for near-infrared spectra TRAC-Trend Anal Chem 28 1201-1222
[8]  
Tesso T(2003)Rapid biomass analysis: new tools for compositional analysis of corn stover feedstocks and process intermediates from ethanol production Appl Biochem Biotech—Part A Enzym Eng Biotechnol 105 5-16
[9]  
Dowell F(2009)Measurement of key compositional parameters in two species of energy grass by Fourier transform infrared spectroscopy Bioresource Technol 100 6428-6433
[10]  
Wang D(2008)Fast classification and compositional analysis of cornstover fractions using Fourier transform near-infrared techniques Bioresource Technol 99 7323-7332