Determination of moisture content and density of fresh-sawn red oak lumber by near infrared spectroscopy
Rapid, nondestructive prediction of green moisture content (MC) and density can improve wood processing, for example by allowing presorting of lumber into different classes for optimal drying. Near infrared (NIR) spectroscopy, coupled with multivariate analytic statistical techniques, has been used...
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| Veröffentlicht in: | Forest products journal 2007-05, Vol.57 (5), p.68-72 |
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| description | Rapid, nondestructive prediction of green moisture content (MC) and density can improve wood processing, for example by allowing presorting of lumber into different classes for optimal drying. Near infrared (NIR) spectroscopy, coupled with multivariate analytic statistical techniques, has been used to predict the MC and basic density of solid red oak (Quercus spp.) wood. Samples were prepared from fresh-sawn lumber purchased from a sawmill in east Tennessee. NIR spectra were collected from tangential, radial and transverse surfaces of the samples. Each property was correlated with spectra from 1000 to 2300 nm using projection to latent structures (PLS) models. PLS models were then validated using an independent test set. In general, spectra collected from transverse and radial surfaces gave better predictions than the ones collected from tangential surfaces. Good predictions were obtained for spectra collected from transverse or radial surfaces, with root mean square of errors of prediction (RMSEP) of less than 3.6 percent for MC and 19.8 kg/m3 for basic density when using 8 principal components. NIR has the potential to be used for rapid in-line measurement of green MC and basic density of red oak lumber. |
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Near infrared (NIR) spectroscopy, coupled with multivariate analytic statistical techniques, has been used to predict the MC and basic density of solid red oak (Quercus spp.) wood. Samples were prepared from fresh-sawn lumber purchased from a sawmill in east Tennessee. NIR spectra were collected from tangential, radial and transverse surfaces of the samples. Each property was correlated with spectra from 1000 to 2300 nm using projection to latent structures (PLS) models. PLS models were then validated using an independent test set. In general, spectra collected from transverse and radial surfaces gave better predictions than the ones collected from tangential surfaces. Good predictions were obtained for spectra collected from transverse or radial surfaces, with root mean square of errors of prediction (RMSEP) of less than 3.6 percent for MC and 19.8 kg/m3 for basic density when using 8 principal components. NIR has the potential to be used for rapid in-line measurement of green MC and basic density of red oak lumber.</description><identifier>ISSN: 0015-7473</identifier><identifier>EISSN: 2376-9637</identifier><identifier>CODEN: FPJOAB</identifier><language>eng</language><publisher>Madison, WI: Forest Products Society</publisher><subject>Applied sciences ; Calibration ; Degradation and preservation ; Density ; Exact sciences and technology ; Forest products industry ; Gamma rays ; Laboratories ; Lumber ; Mechanical woodworking and drying ; Moisture content ; Near infrared spectroscopy ; Polymer industry, paints, wood ; Properties and testing ; Quercus ; Spectrum analysis ; Studies ; Trees ; water content ; Wood ; wood density ; wood moisture ; Wood. Paper. Non wovens</subject><ispartof>Forest products journal, 2007-05, Vol.57 (5), p.68-72</ispartof><rights>2008 INIST-CNRS</rights><rights>COPYRIGHT 2007 Forest Products Society</rights><rights>Copyright Forest Products Society May 2007</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=18799737$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Defo, M</creatorcontrib><creatorcontrib>Taylor, A.M</creatorcontrib><creatorcontrib>Bond, B</creatorcontrib><title>Determination of moisture content and density of fresh-sawn red oak lumber by near infrared spectroscopy</title><title>Forest products journal</title><description>Rapid, nondestructive prediction of green moisture content (MC) and density can improve wood processing, for example by allowing presorting of lumber into different classes for optimal drying. Near infrared (NIR) spectroscopy, coupled with multivariate analytic statistical techniques, has been used to predict the MC and basic density of solid red oak (Quercus spp.) wood. Samples were prepared from fresh-sawn lumber purchased from a sawmill in east Tennessee. NIR spectra were collected from tangential, radial and transverse surfaces of the samples. Each property was correlated with spectra from 1000 to 2300 nm using projection to latent structures (PLS) models. PLS models were then validated using an independent test set. In general, spectra collected from transverse and radial surfaces gave better predictions than the ones collected from tangential surfaces. Good predictions were obtained for spectra collected from transverse or radial surfaces, with root mean square of errors of prediction (RMSEP) of less than 3.6 percent for MC and 19.8 kg/m3 for basic density when using 8 principal components. NIR has the potential to be used for rapid in-line measurement of green MC and basic density of red oak lumber.</description><subject>Applied sciences</subject><subject>Calibration</subject><subject>Degradation and preservation</subject><subject>Density</subject><subject>Exact sciences and technology</subject><subject>Forest products industry</subject><subject>Gamma rays</subject><subject>Laboratories</subject><subject>Lumber</subject><subject>Mechanical woodworking and drying</subject><subject>Moisture content</subject><subject>Near infrared spectroscopy</subject><subject>Polymer industry, paints, wood</subject><subject>Properties and testing</subject><subject>Quercus</subject><subject>Spectrum analysis</subject><subject>Studies</subject><subject>Trees</subject><subject>water content</subject><subject>Wood</subject><subject>wood density</subject><subject>wood moisture</subject><subject>Wood. Paper. Non wovens</subject><issn>0015-7473</issn><issn>2376-9637</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNptkU1v2zAMho1iA5q1-w0VCuzoQpRkyz4G2VeBAjusPRu0TKVKbSmTFAz591WQHAseCJAPX74gr6qVkLqt-1bqT9WKc2hqrbS8rr6ktOOc66YVq-r1O2WKi_OYXfAsWLYEl_IhEjPBZ_KZoZ_YRD65fDz1baT0Wif871mkiQV8Y_NhGSmy8cg8YWTO24inXtqTyTEkE_bH2-qzxTnR10u-qV5-_nje_K6f_vx63KyfaitB5noiLdHottdICpXlUoAqTqHpAXBEbZpOiU6OSo1ccIJGiWbkMILVHXRC3lT3Z919DP8OlPKwC4foy8qhKLUAwHWB6jO0xZmG4jfkiGZLniLOwZN1pbyGVknRKg6Ff_iALzHR4syHA98uLjAZnMs9vHFp2Ee3YDwO0Om-1_Jk5O7MWQwDbmNhXv6KIlD-00kozDuiMYk9</recordid><startdate>20070501</startdate><enddate>20070501</enddate><creator>Defo, M</creator><creator>Taylor, A.M</creator><creator>Bond, B</creator><general>Forest Products Society</general><scope>FBQ</scope><scope>IQODW</scope><scope>0U~</scope><scope>1-H</scope><scope>3V.</scope><scope>4T-</scope><scope>4U-</scope><scope>7ST</scope><scope>7WY</scope><scope>7WZ</scope><scope>7X2</scope><scope>7XB</scope><scope>87Z</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FK</scope><scope>8FL</scope><scope>8G5</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>K60</scope><scope>K6~</scope><scope>L.-</scope><scope>L.0</scope><scope>L6V</scope><scope>M0C</scope><scope>M0K</scope><scope>M2O</scope><scope>M7S</scope><scope>MBDVC</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>S0X</scope><scope>SOI</scope></search><sort><creationdate>20070501</creationdate><title>Determination of moisture content and density of fresh-sawn red oak lumber by near infrared spectroscopy</title><author>Defo, M ; Taylor, A.M ; Bond, B</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-f313t-de73ac7697ae4a4f0321456215911aba7c584283b44b020e15425b01b1f781823</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Applied sciences</topic><topic>Calibration</topic><topic>Degradation and preservation</topic><topic>Density</topic><topic>Exact sciences and technology</topic><topic>Forest products industry</topic><topic>Gamma rays</topic><topic>Laboratories</topic><topic>Lumber</topic><topic>Mechanical woodworking and drying</topic><topic>Moisture content</topic><topic>Near infrared spectroscopy</topic><topic>Polymer industry, paints, wood</topic><topic>Properties and testing</topic><topic>Quercus</topic><topic>Spectrum analysis</topic><topic>Studies</topic><topic>Trees</topic><topic>water content</topic><topic>Wood</topic><topic>wood density</topic><topic>wood moisture</topic><topic>Wood. Paper. Non wovens</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Defo, M</creatorcontrib><creatorcontrib>Taylor, A.M</creatorcontrib><creatorcontrib>Bond, B</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>Global News & ABI/Inform Professional</collection><collection>Trade PRO</collection><collection>ProQuest Central (Corporate)</collection><collection>Docstoc</collection><collection>University Readers</collection><collection>Environment Abstracts</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>Agricultural Science Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Research Library (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Professional Standard</collection><collection>ProQuest Engineering Collection</collection><collection>ABI/INFORM Global</collection><collection>Agricultural Science Database</collection><collection>Research Library</collection><collection>Engineering Database</collection><collection>Research Library (Corporate)</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>SIRS Editorial</collection><collection>Environment Abstracts</collection><jtitle>Forest products journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Defo, M</au><au>Taylor, A.M</au><au>Bond, B</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Determination of moisture content and density of fresh-sawn red oak lumber by near infrared spectroscopy</atitle><jtitle>Forest products journal</jtitle><date>2007-05-01</date><risdate>2007</risdate><volume>57</volume><issue>5</issue><spage>68</spage><epage>72</epage><pages>68-72</pages><issn>0015-7473</issn><eissn>2376-9637</eissn><coden>FPJOAB</coden><abstract>Rapid, nondestructive prediction of green moisture content (MC) and density can improve wood processing, for example by allowing presorting of lumber into different classes for optimal drying. Near infrared (NIR) spectroscopy, coupled with multivariate analytic statistical techniques, has been used to predict the MC and basic density of solid red oak (Quercus spp.) wood. Samples were prepared from fresh-sawn lumber purchased from a sawmill in east Tennessee. NIR spectra were collected from tangential, radial and transverse surfaces of the samples. Each property was correlated with spectra from 1000 to 2300 nm using projection to latent structures (PLS) models. PLS models were then validated using an independent test set. In general, spectra collected from transverse and radial surfaces gave better predictions than the ones collected from tangential surfaces. Good predictions were obtained for spectra collected from transverse or radial surfaces, with root mean square of errors of prediction (RMSEP) of less than 3.6 percent for MC and 19.8 kg/m3 for basic density when using 8 principal components. NIR has the potential to be used for rapid in-line measurement of green MC and basic density of red oak lumber.</abstract><cop>Madison, WI</cop><pub>Forest Products Society</pub><tpages>5</tpages></addata></record> |
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| subjects | Applied sciences Calibration Degradation and preservation Density Exact sciences and technology Forest products industry Gamma rays Laboratories Lumber Mechanical woodworking and drying Moisture content Near infrared spectroscopy Polymer industry, paints, wood Properties and testing Quercus Spectrum analysis Studies Trees water content Wood wood density wood moisture Wood. Paper. Non wovens |
| title | Determination of moisture content and density of fresh-sawn red oak lumber by near infrared spectroscopy |
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