Determination of Moisture Content and Basic Density of Poplar Wood Chips under Various Moisture Conditions by Near-Infrared Spectroscopy. Issue 5 (20th May 2019)

• Record Type: Journal Article
• Authors: Liang, Long; Fang, Guigan; Deng, Yongjun; Xiong, Zhixin; Wu, Ting
• Is Part Of: Forest science. Volume 65:Issue 5(2019)
• Page Start: 548
• Page End: 555
• Publication Date: 2019-05-20
• Subjects: basic wood density -- moisture content -- near-infrared spectroscopy -- poplar wood; Forests and forestry -- Periodicals; Forest management -- Periodicals; Forest policy -- United States -- Periodicals; Forest management; Forest policy; Forests and forestry; United States; Electronic journals; Periodicals; 634.9
• DOI: 10.1093/forsci/fxz007
• Languages: English
• ISSNs: 0015-749X

Abstract

Abstract: The potential of near-infrared (NIR) spectroscopy coupled with partial least-squares (PLS) regression was used to determine the moisture content and basic density of poplar wood chips. NIR spectra collected from the surface of wood chips were used to develop calibration models for moisture content and basic density predication, and various spectral preprocessing techniques were applied to improve the accuracy and robustness of the prediction models. The models were tested using totally independent sample sets and exhibited acceptable predictive performance for moisture content (coefficient of determination for prediction [ R 2 p ] = 0.98 and standard error of prediction [SEP] = 2.51 percent) and basic density ( R 2 p = 0.87 and SEP = 17.61 kg m –3 ). In addition, the effect of moisture variations on prediction of basic density was investigated based on NIR spectra from wood chips under various moisture levels. The results demonstrated that broad absorption bands from water molecules, especially when free water exists in the cell lumen, overlap with informative signals related to wood properties and weaken the calibration relation between spectral features and basic density. Thus, maintaining wood chips in a low and even moisture state would help achieve reliable estimates of wood density by NIR analysis models.