Near Infrared Spectroscopy Calibration for Wood Chemistry: Which Chemometric Technique Is Best for Prediction and Interpretation?

Via, Brian; Zhou, Chengfeng; Acquah, Gifty; Jiang, Wei; Eckhardt, Lori

doi:10.3390/s140813532

Title: Near Infrared Spectroscopy Calibration for Wood Chemistry: Which Chemometric Technique Is Best for Prediction and Interpretation?

Journal Article · Fri Jul 25 00:00:00 EDT 2014 · Sensors

DOI:https://doi.org/10.3390/s140813532· OSTI ID:1628544

Via, Brian ^[1]; Zhou, Chengfeng ^[2]; Acquah, Gifty ^[1]; Jiang, Wei ^[3]; Eckhardt, Lori ^[4]

Auburn Univ., AL (United States). School of Forestry and Wildlife Sciences. Forest Products Development Center
Auburn Univ., AL (United States). School of Forestry and Wildlife Sciences. Forest Products Development Center; Auburn Univ., AL (United States). Center for Bioenergy and Bioproducts, Biosystmes Engineering
Auburn Univ., AL (United States). School of Forestry and Wildlife Sciences. Forest Products Development Center; Qingdao Univ. (China). College of Textiles
Auburn Univ., AL (United States). School of Forestry and Wildlife Sciences. Forest Health Dynamics Lab.

This paper addresses the precision in factor loadings during partial least squares (PLS) and principal components regression (PCR) of wood chemistry content from near infrared reflectance (NIR) spectra. The precision of the loadings is considered important because these estimates are often utilized to interpret chemometric models or selection of meaningful wavenumbers. Standard laboratory chemistry methods were employed on a mixed genus/species hardwood sample set. PLS and PCR, before and after 1st derivative pretreatment, was utilized for model building and loadings investigation. As demonstrated by others, PLS was found to provide better predictive diagnostics. However, PCR exhibited a more precise estimate of loading peaks which makes PCR better for interpretation. Application of the 1st derivative appeared to assist in improving both PCR and PLS loading precision, but due to the small sample size, the two chemometric methods could not be compared statistically. This work is important because to date most research works have committed to PLS because it yields better predictive performance. But this research suggests there is a tradeoff between better prediction and model interpretation. Future work is needed to compare PLS and PCR for a suite of spectral pretreatment techniques.

View Accepted Manuscript (DOE)

Cite

Export

Save

Research Organization:: Auburn Univ., AL (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER); National Natural Science Foundation of China (NSFC); National Natural Science Foundation of Shandong Province; Special Foundation of Taishan Scholar Construction and National Science & Technology Pillar Program

Grant/Contract Number:: EE0001036

OSTI ID:: 1628544

Journal Information:: Sensors, Vol. 14, Issue 8; ISSN 1424-8220

Publisher:: MDPI AGCopyright Statement

Country of Publication:: United States

Language:: English

References (47)

Relationship between near-infrared (NIR) spectra and the geographical provenance of timber Sandak, Anna; Sandak, Jakub; Negri, Martino Wood Science and Technology, Vol. 45, Issue 1 https://doi.org/10.1007/s00226-010-0313-y	journal	March 2010
A Review of Band Assignments in near Infrared Spectra of Wood and Wood Components Schwanninger, Manfred; Rodrigues, José Carlos; Fackler, Karin Journal of Near Infrared Spectroscopy, Vol. 19, Issue 5 https://doi.org/10.1255/jnirs.955	journal	January 2011
Response of near Infrared Diffuse Reflectance Spectra to Blue Stain and Wood Age Via, Brian K.; So, Chi-Leung; Eckhardt, Lori G. Journal of Near Infrared Spectroscopy, Vol. 16, Issue 1 https://doi.org/10.1255/jnirs.756	journal	January 2008
A spectroscopic method for determining lignin content of softwood and hardwood kraft pulps Malkavaara, Petteri; Alén, Raimo Chemometrics and Intelligent Laboratory Systems, Vol. 44, Issue 1-2 https://doi.org/10.1016/s0169-7439(98)00068-9	journal	December 1998
Use of near infrared spectroscopy to measure the chemical and mechanical properties of solid wood Kelley, StephenS.; Rials, TimothyG.; Snell, Rebecca Wood Science and Technology, Vol. 38, Issue 4 https://doi.org/10.1007/s00226-003-0213-5	journal	May 2004
The Use of Principal Components in the Analysis of Near-Infrared Spectra Cowe, Ian A.; McNicol, James W. Applied Spectroscopy, Vol. 39, Issue 2 https://doi.org/10.1366/0003702854248944	journal	March 1985
Fast compositional analysis of ramie using near-infrared spectroscopy Jiang, Wei; Han, Guangting; Zhang, Yuanming Carbohydrate Polymers, Vol. 81, Issue 4 https://doi.org/10.1016/j.carbpol.2010.04.009	journal	July 2010
Carbon Content of Tree Tissues: A Synthesis Thomas, Sean C.; Martin, Adam R. Forests, Vol. 3, Issue 2 https://doi.org/10.3390/f3020332	journal	June 2012
Multivariate NIR spectroscopy models for moisture, ash and calorific content in biofuels using bi-orthogonal partial least squares regression Lestander, Torbjörn A.; Rhén, Christofer The Analyst, Vol. 130, Issue 8 https://doi.org/10.1039/b500103j	journal	January 2005
Soil carbon and nitrogen content and stabilization in mid-rotation, intensively managed sweetgum and loblolly pine stands Johnsen, Kurt H.; Samuelson, Lisa J.; Sanchez, Felipe G. Forest Ecology and Management, Vol. 302 https://doi.org/10.1016/j.foreco.2013.03.016	journal	August 2013
Simultaneously calibrating solids, sugars and acidity of tomato products using PLS2 and NIR spectroscopy Pedro, André M. K.; Ferreira, Márcia M. C. Analytica Chimica Acta, Vol. 595, Issue 1-2 https://doi.org/10.1016/j.aca.2007.03.036	journal	July 2007
Evaluation of density and strength of Norway spruce wood by near infrared reflectance spectroscopy Hoffmeyer, P.; Pedersen, J. G. Holz als Roh- und Werkstoff, Vol. 53, Issue 1 https://doi.org/10.1007/bf02716418	journal	January 1995
Characterization and evaluation of wood strand composite load capacity with near infrared spectroscopy Via, Brian Materials and Structures, Vol. 46, Issue 11 https://doi.org/10.1617/s11527-013-0018-4	journal	February 2013
Estimating the chemical composition of biodegraded pine and eucalyptus wood by DRIFT spectroscopy and multivariate analysis Ferraz, A. Bioresource Technology, Vol. 74, Issue 3 https://doi.org/10.1016/s0960-8524(00)00024-9	journal	September 2000
Developing and evaluating a multisite and multispecies NIR calibration for the prediction of Kraft pulp yield in eucalypts Downes, Gm; Meder, R.; Hicks, C. Southern Forests: a Journal of Forest Science, Vol. 71, Issue 2 https://doi.org/10.2989/sf.2009.71.2.11.826	journal	June 2009
Rapid analysis of poplar lignin monomer composition by a streamlined thioacidolysis procedure and near-infrared reflectance-based prediction modeling Robinson, Andrew R.; Mansfield, Shawn D. The Plant Journal, Vol. 58, Issue 4 https://doi.org/10.1111/j.1365-313X.2009.03808.x	journal	May 2009
Enhanced predictions of wood properties using hybrid models of PCR and PLS with high-dimensional NIR spectral data Fang, Yi; Park, Jong I.; Jeong, Young-Seon Annals of Operations Research, Vol. 190, Issue 1 https://doi.org/10.1007/s10479-009-0554-z	journal	June 2009
Chemical and Calorific Characterisation of Longleaf Pine Using near Infrared Spectroscopy So, Chi-Leung; Eberhardt, Thomas L. Journal of Near Infrared Spectroscopy, Vol. 18, Issue 6 https://doi.org/10.1255/jnirs.889	journal	January 2010
Development of near infrared reflectance analysis calibrations for estimating genetic parameters for cellulose content in Eucalyptus globulus Raymond, C. A.; Schimleck, L. R. Canadian Journal of Forest Research, Vol. 32, Issue 1 https://doi.org/10.1139/x01-174	journal	January 2002
Two-Dimensional Correlation Analysis and Waterfall Plots for Detecting Positional Fluctuations of Spectral Changes Ryu, Soo Ryeon; Noda, Isao; Lee, Chang-Hee Applied Spectroscopy, Vol. 65, Issue 4 https://doi.org/10.1366/10-06114	journal	April 2011
Micro Analytical Methods for Determination of Compression Wood Content in Loblolly Pine Chen, Qing‐min; Hu, Zhoujian; Chang, Hou‐min Journal of Wood Chemistry and Technology, Vol. 27, Issue 3-4 https://doi.org/10.1080/02773810701700810	journal	November 2007
Wood Quality and Growth Characterization across Intra- and Inter-Specific Hybrid Aspen Clones Hart, James; de Araujo, Francis; Thomas, Barb Forests, Vol. 4, Issue 4 https://doi.org/10.3390/f4040786	journal	September 2013
Near infrared analysis as a tool for rapid screening of some major wood characteristics in a eucalyptus breeding program Baill�res, Henri; Davrieux, Fabrice; Ham-Pichavant, Fr�d�rique Annals of Forest Science, Vol. 59, Issue 5-6 https://doi.org/10.1051/forest:2002032	journal	July 2002
Estimation of Microfibril Angle of Increment Cores by near Infrared Spectroscopy Schimleck, Laurence R.; Evans, Robert IAWA Journal, Vol. 23, Issue 3 https://doi.org/10.1163/22941932-90000300	journal	January 2002
Determination of lignin, holocellulose, and organic solvent extractives in fresh leaf, litterfall, and organic material on forest floor using near-infrared reflectance spectroscopy Ono, Kenji; Hiraide, Masakazu; Amari, Masahiro Journal of Forest Research, Vol. 8, Issue 3 https://doi.org/10.1007/s10310-003-0026-2	journal	August 2003
Rapid Determination of Heartwood Extractives in Larix sp. by Means of Fourier Transform near Infrared Spectroscopy Gierlinger, N.; Schwanninger, M.; Hinterstoisser, B. Journal of Near Infrared Spectroscopy, Vol. 10, Issue 3 https://doi.org/10.1255/jnirs.336	journal	June 2002
Comparison of Pyrolysis Mass Spectrometry and Near Infrared Spectroscopy for Genetic Analysis of Lignocellulose Chemical Composition in Populus Zhang, Jianxing; Novaes, Evandro; Kirst, Matias Forests, Vol. 5, Issue 3 https://doi.org/10.3390/f5030466	journal	March 2014
Rapid prediction of wood crystallinity in Pinus elliotii plantation wood by near-infrared spectroscopy Jiang, Ze-Hui; Yang, Zhong; So, Chi-Leung Journal of Wood Science, Vol. 53, Issue 5 https://doi.org/10.1007/s10086-007-0883-y	journal	October 2007
Mechanical response of longleaf pine to variation in microfibril angle, chemistry associated wavelengths, density, and radial position Via, B. K.; So, C. L.; Shupe, T. F. Composites Part A: Applied Science and Manufacturing, Vol. 40, Issue 1 https://doi.org/10.1016/j.compositesa.2008.10.007	journal	January 2009
Nonlinear multivariate modeling of strand density from near-infrared spectra Via, Brian; McDonald, Timothy; Fulton, John Wood Science and Technology, Vol. 46, Issue 6 https://doi.org/10.1007/s00226-012-0467-x	journal	January 2012
Relationships between climate, radial growth and wood properties of mature loblolly pine in Hawaii and a northern and southern site in the southeastern United States Samuelson, Lisa J.; Eberhardt, Thomas L.; Bartkowiak, Stan M. Forest Ecology and Management, Vol. 310 https://doi.org/10.1016/j.foreco.2013.09.025	journal	December 2013
Nondestructive estimation of wood chemical composition of sections of radial wood strips by diffuse reflectance near infrared spectroscopy Jones, P. David; Schimleck, Laurence R.; Peter, Gary F. Wood Science and Technology, Vol. 40, Issue 8 https://doi.org/10.1007/s00226-006-0085-6	journal	May 2006
Near-Infrared Spectroscopic Study of the Physical and Mechanical Properties of Wood with Meso- and Micro-Scale Anatomical Observation Tsuchikawa, Satoru; Hirashima, Yoshihiko; Sasaki, Yasutoshi Applied Spectroscopy, Vol. 59, Issue 1 https://doi.org/10.1366/0003702052940413	journal	January 2005
Within tree Variation of Lignin, Extractives, and Microfibril Angle Coupled with the Theoretical and near Infrared Modeling of Microfibril Angle Via, Brian K.; So, Chi L.; Groom, Leslie H. IAWA Journal, Vol. 28, Issue 2 https://doi.org/10.1163/22941932-90001633	journal	January 2007
Modeling for proximate analysis and heating value of torrefied biomass with vibration spectroscopy Via, Brian K.; Adhikari, Sushil; Taylor, Steve Bioresource Technology, Vol. 133 https://doi.org/10.1016/j.biortech.2013.01.108	journal	April 2013
Multivariate Modelling of Density, Strength and Stiffness from near Infrared Spectra for Mature, Juvenile and Pith Wood of Longleaf Pine ( Pinus Palustris ) Via, Brian K.; Shupe, Todd F.; Groom, Leslie H. Journal of Near Infrared Spectroscopy, Vol. 11, Issue 5 https://doi.org/10.1255/jnirs.388	journal	October 2003
Nonlinear multivariate modeling of strand mechanical properties with near-infrared spectroscopy Via, Brian K.; Jiang, W. The Forestry Chronicle, Vol. 89, Issue 05 https://doi.org/10.5558/tfc2013-113	journal	October 2013
A review of near-infrared spectroscopy for monitoring moisture content and density of solid wood Leblon, Brigitte; Adedipe, Oluwatosin; Hans, Guillaume The Forestry Chronicle, Vol. 89, Issue 05 https://doi.org/10.5558/tfc2013-111	journal	October 2013
Wood Quality and Growth Characterization across Intra- and Inter-Specific Hybrid Aspen Clones Hart, James F.; De Araujo, Francis; Thomas, Barb R. Multidisciplinary Digital Publishing Institute https://doi.org/10.14288/1.0378236	text	January 2019
A Review of Recent Near Infrared Research for Wood and Paper Tsuchikawa, Satoru Applied Spectroscopy Reviews, Vol. 42, Issue 1 https://doi.org/10.1080/05704920601036707	journal	February 2007
Rapid assessment of coniferous biomass lignin–carbohydrates with near-infrared spectroscopy Jiang, Wei; Han, Guangting; Via, Brian K. Wood Science and Technology, Vol. 48, Issue 1 https://doi.org/10.1007/s00226-013-0590-3	journal	October 2013
Non-destructive estimation of Pinus taeda L tracheid morphological characteristics for samples from a wide range of sites in Georgia Jones, P. D.; Schimleck, L. R.; Peter, G. F. Wood Science and Technology, Vol. 39, Issue 7 https://doi.org/10.1007/s00226-005-0021-1	journal	September 2005
NIR Measurement of Moisture Content in Wood under Unstable Temperature Conditions. Part 2. Handling Temperature Fluctuations Thygesen, Lisbeth G.; Lundqvist, Sven-Olof Journal of Near Infrared Spectroscopy, Vol. 8, Issue 3 https://doi.org/10.1255/jnirs.278	journal	June 2000
Determination of nitrogen, lignin, and cellulose content of decomposing leaf material by near infrared reflectance spectroscopy McLellan, Toni M.; Aber, John D.; Martin, Mary E. Canadian Journal of Forest Research, Vol. 21, Issue 11 https://doi.org/10.1139/x91-232	journal	November 1991
Near-infrared spectroscopy as a potential quality assurance tool for the wood preservation industry Stirling, Rod The Forestry Chronicle, Vol. 89, Issue 05 https://doi.org/10.5558/tfc2013-117	journal	October 2013
Comparison of Pinus taeda L. whole-tree wood property calibrations using diffuse reflectance near infrared spectra obtained using a variety of sampling options Jones, P. David; Schimleck, Laurence R.; Daniels, Richard F. Wood Science and Technology, Vol. 42, Issue 5 https://doi.org/10.1007/s00226-008-0178-5	journal	February 2008
Wood modification by heat treatment: A review Esteves, Bruno M.; Pereira, Helena M. BioResources, Vol. 4, Issue 1 https://doi.org/10.15376/biores.4.1.Esteves	journal	December 2008

Cited By (12)

Quantitative Analysis of Gas Phase IR Spectra Based on Extreme Learning Machine Regression Model Ouyang, Tinghui; Wang, Chongwu; Yu, Zhangjun Sensors, Vol. 19, Issue 24 https://doi.org/10.3390/s19245535	journal	December 2019
Assessing utility of handheld laser induced breakdown spectroscopy as a means of Dalbergia speciation Celani, Caelin P.; Lancaster, Cady A.; Jordan, James A. The Analyst, Vol. 144, Issue 17 https://doi.org/10.1039/c9an00984a	journal	January 2019
Detection of Vibrational Spectroscopic Biomarkers of the Effect of Gold Nanoparticles on Wheat Seedlings Using Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy Sharma, Sweta; Uttam, Rahul; Singh, Praveen Analytical Letters, Vol. 51, Issue 14 https://doi.org/10.1080/00032719.2017.1423077	journal	March 2018
Lifting Wavelet Transform De-noising for Model Optimization of Vis-NIR Spectroscopy to Predict Wood Tracheid Length in Trees Li, Ying; Via, Brian; Cheng, Qingzheng Sensors, Vol. 18, Issue 12 https://doi.org/10.3390/s18124306	journal	December 2018
Visible-Near Infrared Spectroscopy and Chemometric Methods for Wood Density Prediction and Origin/Species Identification Li, Ying; Via, Brian K.; Young, Tim Forests, Vol. 10, Issue 12 https://doi.org/10.3390/f10121078	journal	November 2019
Multivariate Calibration and Model Integrity for Wood Chemistry Using Fourier Transform Infrared Spectroscopy Zhou, Chengfeng; Jiang, Wei; Cheng, Qingzheng Journal of Analytical Methods in Chemistry, Vol. 2015 https://doi.org/10.1155/2015/429846	journal	January 2015
Potential of Near Infrared Spectroscopy for Classification of Different Delignificant Pre-Treatments on Banana Rachis Tamburini, Elena; Larenas Uria, Christian Fabricio Journal of Analytical & Bioanalytical Techniques, Vol. 7, Issue 3 https://doi.org/10.4172/2155-9872.1000311	journal	January 2016
Chemometric modeling of thermogravimetric data for the compositional analysis of forest biomass Acquah, Gifty E.; Via, Brian K.; Fasina, Oladiran O. PLOS ONE, Vol. 12, Issue 3 https://doi.org/10.1371/journal.pone.0172999	journal	March 2017
Potential use of nir and visible spectroscopy to analyze chemical properties of thermally treated wood Lengowski, Elaine Cristina; Muñiz, Graciela Inês Bolzon de; Klock, Umberto Maderas. Ciencia y tecnología, Issue ahead https://doi.org/10.4067/s0718-221x2018005041001	journal	January 2018
Quantitative analysis of gas phase IR spectra based on extreme learning machine regression model Ouyang, Tinghui; Wang, Chongwu; Yu, Zhangjun Universität Ulm https://doi.org/10.18725/oparu-40429	text	January 2019
Linkage Abundance and Molecular Weight Characteristics of Technical Lignins by Attenuated Total Reflection‐FTIR Spectroscopy Combined with Multivariate Analysis Lancefield, Christopher S.; Constant, Sandra; de Peinder, Peter ChemSusChem, Vol. 12, Issue 6 https://doi.org/10.1002/cssc.201802809	journal	February 2019
Linkage Abundance and Molecular Weight Characteristics of Technical Lignins by Attenuated Total Reflection‐FTIR Spectroscopy Combined with Multivariate Analysis Lancefield, Christopher S.; Constant, Sandra; de Peinder, Peter ChemSusChem, Vol. 12, Issue 6 https://doi.org/10.1002/cssc.201900636	journal	February 2019

Similar Records

Practical Guide to Chemometric Analysis of Optical Spectroscopic Data

Journal Article · Tue Jul 11 00:00:00 EDT 2023 · Journal of Chemical Education · OSTI ID:1628544

Lackey, Hope E.; Sell, Richard L.; Nelson, Gilbert L.; +3 more

Prediction of Cell Wall Properties and Response to Deconstruction Using Alkaline Pretreatment in Diverse Maize Genotypes Using Py-MBMS and NIR

Journal Article · Tue Oct 04 00:00:00 EDT 2016 · BioEnergy Research · OSTI ID:1628544

Li, Muyang; Williams, Daniel L.; Heckwolf, Marlies; +4 more

Quantification of Raman-Interfering Polyoxoanions for Process Analysis: Comparison of Different Chemometric Models and a Demonstration on Real Hanford Waste

Journal Article · Thu Sep 16 00:00:00 EDT 2021 · Environmental Science and Technology · OSTI ID:1628544

Tse, Poki; Shafer, Jenifer; Bryan, Samuel A.; +1 more

Related Subjects

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
09 BIOMASS FUELS
Chemistry
engineering
instruments & instrumentation
NIR
chemometric
PLS
PCR
regression
loading
coefficient
error
wood chemistry

Title: Near Infrared Spectroscopy Calibration for Wood Chemistry: Which Chemometric Technique Is Best for Prediction and Interpretation?

Citation Formats

References (47)

Cited By (12)

Similar Records

Related Subjects