Development of chemometric model for characterization of non-wood by FT-NIR data  

作　　者：Mohammad Nashir Uddin Taslima Ferdous Zahidul Islam M.Sarwar Jahan M.A.Quaiyyum 

机构地区：[1]BCSIR Laboratories,Dhaka,Bangladesh Council of Scientific and Industrial Research(BCSIR),Dhaka 1205,Bangladesh [2]Department of Applied Chemistry and Chemical Engineering,University of Dhaka,Dhaka 1000,Bangladesh

出　　处：《Journal of Bioresources and Bioproducts》2020年第3期196-203,共8页生物质资源与工程（英文）

摘　　要：In this study,a model for prediction of lignocellulose components of agricultural residues has been developed with Fourier Transformed Near Infrared(FT-NIR)spectroscopy data.Two calibration techniques(Principal Component Regression(PCR)and Partial Least Square Regression(PLSR))were assessed for prediction of lignin,holocellulose,α-cellulose,pentosan and ash,and found the PLSR better for lignin,holocellulose andα-cellulose.The PCR also produced better results for quantification of pentosan and ash.Spectral range(7000-5000 cm^(-1))showed more informative than other parts of the spectral data.The PLSR showed maximum value of R^(2)(R^(2)=0.91%)for prediction of holocellulose.For the prediction of pentosan,the PCR was better(R^(2)=0.68%).The PCR also showed better results(R^(2)=86%)for quantification of ash.To determine amount of lignin,the PLSR was the best(R^(2)=0.83%)when the spectral data were de-trained and smoothed with Savitzky-Golay(S-G)filtering simultaneously.For prediction ofα-cellulose,the PLSR was the best model(R^(2)=0.94%)when the data were pretreated with mean normalization.Considering the best alternatives inNear Infrared(NIR)data preprocessing and calibration techniques,methods for quantification of lignocellulose components of agricultural residues have been developed which is rapid,cost effective,and less chemical intensive and easily usable in pulp and paper industries and pulp testing laboratories.

关 键 词：Agricultural residue Multivariate modeling Lignocellulose component 

分 类 号：S781.4[农业科学—木材科学与技术]