Effects of Loblolly Pine Wood and Pulp Properties on Sheet Characteristics

White, David E.; Courchene, Charles E.; McDonough, Thomas Joseph; Schimleck, Laurie; Peter, Gary F.; Rakestraw, Jim; Goyal, Gopal

doi:10.32964/tj10.2.36

Cited by 7 publications

(1 citation statement)

References 6 publications

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“…1 However, such standardized methods are time-consuming and cannot be used to monitor the changes in MOE of standing trees, even though such information is important for end-use and silviculture prescription. 2 An additional property, fiber coarseness defined as weight per fiber length, has the greatest effect on paper sheet properties, 3 it can be measured using projection microscopy. 4 However, it is also a destructive and time-consuming approach.…”

Section: Introductionmentioning

confidence: 99%

Non-destructive evaluation of wood stiffness and fiber coarseness, derived from SilviScan data, via near infrared hyperspectral imaging

Inagaki

Tsuchikawa

2018

Journal of Near Infrared Spectroscopy

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Near infrared hyperspectral imaging combined with partial least squares regression analysis was used to evaluate wood stiffness (modulus of elasticity) and fiber coarseness. Five samples with normal wood and compression wood collected from two Japanese Cedar (Cryptomeria japonica) trees were analyzed. To achieve high reliability of the prediction values, a SilviScan system (X-ray densitometry, X-ray diffractometry, and optical microscopy) with the high spatial resolution was used for measuring reference data. The measurement interval for modulus of elasticity and fiber coarseness was 1 mm and 25 mm, respectively. After spectral pre-treatment and key wavelengths selection, partial least squares analysis was applied to calibrate near infrared data to reference values. The determination coefficient (R CV 2) of modulus of elasticity was 0.66 with a root mean square error of cross validation (RMSECV) of 1.80 GPa. For the constructed fiber coarseness calibration model, R CV 2 and RMSECV were 0.62 and 35.02 mm/g, respectively. Finally, modulus of elasticity and fiber coarseness mapping results show detailed information (156 mm/pixel) at the grown ring level. The differences among earlywood, latewood, and compression wood were all well identifiable.

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Section: Introductionmentioning

confidence: 99%

Non-destructive evaluation of wood stiffness and fiber coarseness, derived from SilviScan data, via near infrared hyperspectral imaging

Inagaki

Tsuchikawa

2018

Journal of Near Infrared Spectroscopy

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A review of recent application of near infrared spectroscopy to wood science and technology

2015

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This review article introduces recent scientific and technical reports due to near infrared spectroscopy (NIRS) at wood science and technology, most of which was published between 2006 and 2013. Many researchers reported that NIR technique was useful to detect multi traits of chemical, physical, mechanical and anatomical properties of wood materials although it was widely used in a state where characteristic cellular structure was retained. However, we should be sensitive and careful for application of NIRS, when spectra coupled with chemometrics presents unexpected good results (especially, for mechanical physical and anatomical properties). The real application for on-line or at-line monitoring in wood industry is desired as next step. Basic spectroscopic research for wooden material is also progressed. It should be a powerful and meaningful analytical spectroscopic tool.

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Comparison of whole-tree wood property maps based on near-infrared spectroscopic calibrations utilizing data at different spatial resolutions

Schimleck

Antony

Mora³

et al. 2019

Holzforschung

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Near-infrared (NIR) spectra or NIR-hyperspectral images obtained from radial strips or wood discs provide a cost-effective methodology for examining wood property variation within trees. The calibration used for wood property prediction is critical and can be obtained using two fundamentally different approaches. One involves using a spatial-specific model where wood property data and corresponding spectral data are measured at the same resolution for calibration and prediction, e.g. 10-mm radial increments. The other provides a spatial-interpolated model and involves measuring a property on a broad-scale, e.g. whole-tree, calibrating this data against NIR spectra representing the equivalent scale and then using the calibration to predict the property at higher resolution. To understand the impact of these approaches on subsequent patterns of within-tree variation, whole-tree air-dry density (ADD) and coarseness maps, based on data obtained using the two different approaches, were compared. Patterns of ADD and coarseness variation were comparable indicating that both approaches can be utilized to examine within-tree variation. Spatial-interpolated models have a distinct advantage; being based on whole-tree (or disc) samples, they greatly reduce the cost of wood property analysis and allow the development of maps for properties that are costly and difficult to measure, for example, pulp yield.

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Effects of Loblolly Pine Wood and Pulp Properties on Sheet Characteristics

Cited by 7 publications

References 6 publications

Non-destructive evaluation of wood stiffness and fiber coarseness, derived from SilviScan data, via near infrared hyperspectral imaging

Non-destructive evaluation of wood stiffness and fiber coarseness, derived from SilviScan data, via near infrared hyperspectral imaging

A review of recent application of near infrared spectroscopy to wood science and technology

Comparison of whole-tree wood property maps based on near-infrared spectroscopic calibrations utilizing data at different spatial resolutions

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