Application of NIR Reflectance Spectroscopy on Rapid Determination of Moisture Content of Wood Pellets

NIR spectroscopy was used to measure the moisture concentration of wood pellets. Pellets were conditioned to various moisture levels between 0.63% and 14.16% (wet basis) and the moisture concentration was verified using a standard oven method. Samples from various moisture levels were separated into two groups, as calibration and validation sets. NIR absorption spectral data from 400 nm to 2500 nm with 0.5 nm intervals were collected using pellets within the calibration and validation sample sets. Spectral wavelength ranges were taken as independent variables and the MC of the pellets as the dependent variable for the analysis. Measurements were obtained on 30 replicates within each moisture level. Partial Least Square (PLS) analysis was performed on both raw and preprocessed spectral data of calibration set to determine the best calibration model based on Standard Error of Calibration (SEC) and coefficient of multiple determinations (R2). The PLS model that yielded the best fit was used to predict the moisture concentration of validation group pellets. Relative Percent Deviation (RPD) and Standard Error of Prediction (SEP) were calculated to validate goodness of fit of the prediction model. Baseline and Multiple Scatter Corrected (MSC) reflectance spectra with 1st derivative model gave the highest RPD value of 4.46 and R2 of 0.95. Also it’s SEP (0.670) and RMSEP (0.782) were less than the other models those had RPD value more than 3.0 with less number of factors. Therefore, this model was selected as the best model for moisture content prediction of wood pellets.

[1]  R. Marchessault,et al.  The infrared spectrum of crystalline polysaccharides. IX. The near infrared spectrum of cellulose , 1963 .

[2]  L. Velasco,et al.  Analysis of total glucosinolate content and individual glucosinolates in Brassica spp. by near‐infrared reflectance spectroscopy , 1998 .

[3]  M. Ali,et al.  Spectroscopic studies of the ageing of cellulosic paper , 2001 .

[4]  Kevin McDonnell,et al.  Prediction of moisture, calorific value, ash and carbon content of two dedicated bioenergy crops using near-infrared spectroscopy. , 2011, Bioresource technology.

[5]  Bo Johnsson,et al.  NIR techniques create added values for the pellet and biofuel industry. , 2009, Bioresource technology.

[6]  Tatsuhiko Yamada,et al.  Rapid screening of wood chemical component variations using transmittance near-infrared spectroscopy. , 2005, Journal of agricultural and food chemistry.

[7]  K. Kojima,et al.  Near-infrared spectra of water and aqueous electrolyte solutions at high pressures , 1984 .

[8]  Elaine Duterte Delvo-Favre,et al.  Implementation of Near-Infrared Technology (AccuVein AV-400®) to Facilitate Successful PIV Cannulation , 2017 .

[9]  Phil Williams,et al.  Comparison of three whole seed near-infrared analyzers for measuring quality components of canola seed , 1994 .

[10]  M. Paulsen,et al.  Calibration of a Near-infrared Transmission Grain Analyser for Extractable Starch in Maize , 2004 .

[11]  T. Fearn.  Assessing Calibrations: SEP, RPD, RER and R2 , 2002 .

[12]  T. Lestander,et al.  Multivariate NIR spectroscopy models for moisture, ash and calorific content in biofuels using bi-orthogonal partial least squares regression. , 2005, The Analyst.

[13]  B. Pérez-Vich,et al.  Determination of seed oil content and fatty acid composition in sunflower through the analysis of intact seeds, husked seeds, meal and oil by near-infrared reflectance spectroscopy , 1998 .

[14]  I. Karaman,et al.  Determination of lignin and extractive content of Turkish Pine (Pinus brutia Ten.) trees using near infrared spectroscopy and multivariate calibration , 2010, Wood Science and Technology.

[15]  Thomas L. Eberhardt,et al.  Chemical and Calorific Characterisation of Longleaf Pine Using near Infrared Spectroscopy , 2010 .

[16]  H. Büning-Pfaue.  Analysis of water in food by near infrared spectroscopy , 2003 .

[17]  Carmen Hernando,et al.  Fast estimation of the calorific values of forest fuels by near infrared-reflectance spectroscopy , 1997 .

[18]  L. Schimleck,et al.  NIR spectroscopy of woods from Eucalyptus globulus , 1996 .

[19]  William R. Windham,et al.  APPLICATION OF NIR REFLECTANCE SPECTROSCOPY ON DETERMINATION OF MOISTURE CONTENT OF IN-SHELL PEANUTS: A NON-DESTRUCTIVE ANALYSIS , 2010 .

[20]  M Gishen,et al.  Analysis of elements in wine using near infrared spectroscopy and partial least squares regression. , 2008, Talanta.

[21]  Karin Fackler,et al.  A Review of Band Assignments in near Infrared Spectra of Wood and Wood Components , 2011 .

[22]  Tom Fearn,et al.  Practical Nir Spectroscopy With Applications in Food and Beverage Analysis , 1993 .

[23]  Junliang Liu,et al.  Application of FT-NIR-DR and FT-IR-ATR spectroscopy to estimate the chemical composition of bamboo (Neosinocalamus affinis Keng) , 2011 .

[24]  Emil W. Ciurczak,et al.  Handbook of Near-Infrared Analysis , 1992 .