Chi-Leung So

Multivariate Modelling of Density, Strength and Stiffness from near Infrared Spectra for Mature, Juvenile and Pith Wood of Longleaf Pine (Pinus Palustris)

In manufacturing, monitoring the mechanical properties of wood with near infrared spectroscopy (NIR) is an attractive alternative to more conventional methods. However, no attention has been given to see if models differ between juvenile and mature wood. Additionally, it would be convenient if multiple linear regression (MLR) could perform well in the place of more complicated multivariate models. Therefore, the purpose of this paper was to model the strength, stiffness and density of mature and juvenile longleaf pine to NIR spectra with MLR and principal component regression (PCR). MLR performed almost as well as PCR when predicting density, modulus of rupture (MOR) and modulus of elasticity (MOE). Choosing wavelengths associated with wood chemistry and developing principal components gave better predictive models (PCR2) than when all NIR wavelengths were used (PCR1). Models developed from mature wood did not predict wood properties from juvenile wood adequately, suggesting that separate models are needed. However, for density prediction, the area under the spectral curve appeared to be insensitive to mature and juvenile wood differences. Five of the six wavelengths associated with MOE were also associated with MOR, perhaps accounting for how MOE and MOR might be related. For pith wood, MOE and MOR were poorly related to NIR spectra, while density was strongly correlated. This inability to predict mechanical properties in the pith-wood zone warrants attention for those manufacturers interested in using near infrared to stress rate lumber within a mill.

Use of near infrared spectroscopy to predict the mechanical properties of six softwoods

Abstract The visible and near infrared (NIR) (500–2400 nm) spectra and mechanical properties of almost 1000 small clearwood samples from six softwood species: Pinus taeda L. (loblolly pine), Pinus palustris, Mill. (longleaf pine), Pinus elliottii Engelm. (slash pine), Pinus echinata Mill. (shortleaf pine), Pinus ponderosa Dougl. ex Laws (ponderosa pine), and Pseudotsuga menziesii (Mirb.) Franco (Douglas fir) were measured. Projection to Latent Structures (PLS) modeling showed that the NIR spectra of these softwoods could be used to predict the mechanical properties of the clear-wood samples. The correlation coefficients for most of these models were greater than 0.80. All six softwood species were combined into one data set and a PLS model was constructed that effectively predicted the strength properties of any of the individual softwoods. Reducing the spectral range to between 650 and 1050 nm only causes a slight decrease in the quality of the models. Using this narrow spectral range enables the use of smaller, faster, lighter, less expensive spectrometers that could be used either in the field or for process control applications.

Rapid prediction of wood crystallinity in Pinus elliotii plantation wood by near-infrared spectroscopy

Crystallinity is an important property of woody materials; it responds to tree growth traits, structure, and chemical composition, and has a significant effect on Young’s modulus, dimensional stability, density, and hardness, etc. The ability of near-infrared (NIR) spectroscopy coupled with multivariate analysis to rapidly predict the crystallinity of slash pine (Pinus elliotii) plantation wood was investigated. The results showed that the NIR data could be correlated with the X-ray diffraction (XRD)-determined crystallinity of slash pine wood by use of partial least squares (PLS) regression, producing excellent coefficients of determination, r2, and root mean square error of calibration, RMSEC. The use of either reduced spectral ranges or the selection of certain wavelengths consistent with known chemical absorptions did not have any detrimental effect on the quality of PLS models allowing the use of inexpensive, small, and portable spectrometers. These studies show that NIR spectroscopy can be used to rapidly predict the crystallinity of slash pine wood.

Genetic improvement of fiber length and coarseness based on paper product performance and material variability - a review

Improvement of specific gravity through tree breeding was an early choice made in the mid 20th century due to its ease of measurement and impact on pulp yield and lumber strength and stiffness. This was often the first, and in many cases, the only wood quality trait selected for. However, from a product standpoint, increased specific gravity has shown to lower many paper strength and stiffness properties and has been assumed to be directly attributable to increased fiber coarseness. As a result, it is currently not clear which fiber trait would best benefit a tree improvement program for paper products. This review found coarseness to be perhaps more important to paper strength and stiffness whereas tracheid length showed better promise from a breeding point of view due to its independence from specific gravity. However, both traits possessed strong heritability and influence on product performance and thus both would be beneficial to breed for depending on organizational goals and end product mix. The objective of this paper is to review and prioritize coarseness and tracheid length from both an end use and raw material perspective. To aid in prioritization, the variation, correlation, and heritability of both traits were reviewed along with significant genetic and phenotypic correlations. Variation trends within and between families as well as within a tree were reviewed.

Chemical and calorific characterisation of longleaf pine using near infrared spectroscopy.

Gross calorific value (GCV) has been predicted by building models based on near infrared (NIR) spectroscopy and multivariate analysis; however, to date, the impact of feedstock chemical composition on the models has not been directly assessed. In the present study, 20 longleaf pine trees were sampled at two positions (breast and mid-height) for calorimetric and spectroscopic analyses. The GCVs, which ranged from 20 MJ kg−1 to 24 MJ kg−1, showed a strong correlation with the wide-ranging values of acetone-soluble extractives content. After extraction of the samples with acetone, the range for the GCV was both lower and slightly narrower (19–21 MJ kg−1) and was poorly correlated to lignin content with its narrow range of values. Near infrared (NIR) spectroscopy coupled with multivariate analysis was applied to the samples and provided a strong coefficient of determination (R2) between the values predicted by NIR and those determined by calorimetry for the unextracted, but not the extracted, samples. Plotting the regression coefficients validated the results by showing very similar plots for GCV and extractives content, thereby indicating that the same molecular features are driving the models. NIR spectroscopy coupled with multivariate analysis can predict GCV for bioenergy feedstocks and also provide insight into chemical features with the greatest impact on fuel value.

Gadolinium chloride as a contrast agent for imaging wood composite components by magnetic resonance.

Abstract Although paramagnetic contrast agents have an established track record in medical uses of magnetic resonance imaging (MRI), only recently has a contrast agent been used for enhancing MRI images of solid wood specimens. Expanding on this concept, wood veneers were treated with a gadolinium-based contrast agent and used in a model system comprising three-ply plywood panels fabricated from two untreated veneers and one treated veneer. The limited degree of effect imparted by the contrast agent for specimens in a water-saturated state likely resulted from contrast agent losses due to leaching during the prerequisite water saturation process. Specimens were also analyzed in the air-dry state using a non-conventional MRI sequence. This allowed what appears to be the first reported visualization of earlywood and latewood bands in MR images for air-dry wood specimens. Observation of significant signal dropout for the gadolinium-treated veneer demonstrated the first successful use of a contrast agent to manipulate the signal intensity of a wood component within a composite structure. This technique shows promise for non-destructive two- and three-dimensional assessments of wood component (e.g., veneers, flakes, particles) distributions and orientations in wood composites.