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dc.contributorLori Eckhardt, eckhalg@auburn.eduen_US
dc.creatorVia, Brian K.
dc.creatorZhou, Chengfeng
dc.creatorAcquah, Gifty E.
dc.creatorJiang, Wei
dc.creatorEckhardt, Lori G.
dc.date.accessioned2019-08-02T16:27:27Z
dc.date.available2019-08-02T16:27:27Z
dc.date.created2014
dc.identifier10.3390/s140813532en_US
dc.identifier.urihttps://www.mdpi.com/1424-8220/14/8/13532en_US
dc.identifier.urihttp://hdl.handle.net/11200/49440
dc.description.abstractThis 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.en_US
dc.formatPDFen_US
dc.relation.ispartofSensorsen_US
dc.relation.ispartofseries1424-8220en_US
dc.rights© 2014. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.subjectNIRen_US
dc.subjectchemometricen_US
dc.subjectPLSen_US
dc.subjectPCRen_US
dc.subjectregressionen_US
dc.subjectloadingen_US
dc.subjectcoefficienten_US
dc.subjecterroren_US
dc.subjectwood chemistryen_US
dc.titleNear Infrared Spectroscopy Calibration for Wood Chemistry: Which Chemometric Technique Is Best for Prediction and Interpretation?en_US
dc.typeCollectionen_US
dc.type.genreJournal Article, Academic Journalen_US
dc.citation.volume14en_US
dc.citation.issue8en_US
dc.citation.spage13532en_US
dc.citation.epage13547en_US
dc.description.peerreviewYesen_US


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