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North American conifers exhibit three radial specific gravity (SG) patterns (Type 1, 2, and 3), which balance hydraulic and mechanical requirements. Type 1 and 2 patterns (Pinaceae) have low SG and high microfibril angle (MFA) corewood ensuring compliance, whereas in outerwood high SG/low MFA provide stiffness and strength resisting bending. Hydraulically, corewood, especially in Type 2 species, is resistant to embolism, whereas outerwood has higher specific conductivity. Cupressaceae (Type 3) have hydraulically very efficient, low SG outerwood, facilitating rapid growth. Corewood is flexible, whereas outerwood is mechanically weak and compensated for by more conical stems and durable heartwood (which prevents Brazier buckling). Radially earlywood (EW) decreases, and latewood (LW) increases for all types, whereas %latewood (%LW) increases (Type 1), decreases, then increases (Type 2) and decreases (Type 3). Ring SG increases when increasing LW SG and %LW are sufficient to counteract decreasing EW SG. Shade tolerance, crown recession, hormone gradients, and environmental variation affect patterns. Auxin concentration decreases with increasing distance from juvenile foliage slowing cell division, concomitantly gibberellin concentration (lignification) and carbohydrates (cell wall thickening) increase, producing higher %LW. Across a species range regions receiving relatively high summer rainfall have trees with higher %LW (by ring). [ABSTRACT FROM AUTHOR]

A chemistry-based explainable machine learning (ML) approach was used to predict wood properties using near infrared (NIR) spectral data collected from rough and smooth surfaces, and to provide better understanding of the role of important NIR wavelengths (features) in the performance of ML models. NIR spectra collected from western hemlock (Tsuga heterophylla) and coastal Douglas-fir (Pseudotsuga menziesii) boards with rough and smooth surfaces were fed into random forest and TreeNet; a gradient boosting machine algorithm, for predicting wood density, modulus of elasticity (MOE) and modulus of rupture (MOR). The TreeNet model could predict the MOE, MOR, and density with R2 of 0.66, 0.64, and 0.64 using spectra collected from rough surface and R2 of 0.54, 0.46, and 0.46 using spectra collected from smooth surface. TreeNet outperformed the random forest, and for both ML algorithms higher R2 and lower error were obtained using NIR data collected from rough surfaces. This suggested that for Douglass fir and western hemlock, NIR spectra could be collected on a sawn surface prior to surface planing. However, it is difficult to generalize the impact of surface roughness on the performance of predictive model as different factors (e.g. what constitutes a smooth or rough surface, variability of data set in terms of wood properties) impact the success of predictive models. NIR features having the greatest influence on TreeNet models were examined and consistently had wood chemistry specific band assignments. The most important features occurred in the O-H first overtone, and C–H second overtone regions and a narrow zone (approximately 2400–2500 nm) of the C–H stretch C–C stretch combination region. Important features also differed by property and with surface roughness. Explaining ML model performance using the relative importance of the NIR features showed the importance of wood chemistry related information when developing models, however MOE and MOR TreeNet models based on smooth surface NIR spectra showed an increased importance of water related features. Overall, the chemistry-based explainable machine learning model approach allows for identification of important NIR features, and regions, and aids in understanding how they contribute to the performance of NIR-based wood property predictive models. [ABSTRACT FROM AUTHOR]

The quality control of thermally modified wood and identifying heat treatment intensity using nondestructive testing methods are critical tasks. This study used near-infrared (NIR) spectroscopy and machine learning modeling to classify thermally modified wood. NIR spectra were collected from the surfaces of untreated and thermally treated (at 170 °C, 212 °C, and 230 °C) western hemlock samples. An explainable machine learning approach was practiced using a TreeNet gradient boosting machine. No dimensionality reduction was performed to better explain the feature ranking results obtained from the model and provide insight into the critical wavelengths contributing to the performance of classification models. NIR spectra in the ranges of 1100–2500 nm, 1400–2500 nm, and 1700–2500 nm were fed into the TreeNet model, which resulted in classification accuracy values (test data) of 94.35%, 89.29%, and 84.52%, respectively. Feature ranking analysis revealed that when using the range of 1100–2500 nm, the changes in wood color resulted in the highest variation in NIR reflectance amongst treatments. As a result, associated features were given higher importance by TreeNet. Limiting the wavelength range increased the significance of features related to water or wood chemistry; however, these predictive models were not as accurate as the one benefiting from the impact of wood color change on the NIR spectra. The developed framework could be applied to different applications in which NIR spectra are used for wood characterization and quality control to provide improved insights into selected NIR wavelengths when developing a machine learning model. [ABSTRACT FROM AUTHOR]

Hyperspectral imaging is a technique that combines spectroscopy and imaging. Originally utilized in the 1980's by the remote sensing community it is now utilized in a wide variety of applications. Spectral imaging was first used for the detection of compression wood in the late 1990's and since that time research focused on wood and wood products has steadily increased with a variety of applications reported. While there are several reviews of wood related research utilizing near infrared spectrometers a comprehensive summary of wood—hyperspectral imaging research is lacking. Near infrared hyperspectral imaging systems (NIR-HSI) typically have a wavelength range of 900–1700 nm, whereas short-wave infrared hyperspectral imaging (SWIR-HSI) systems range from 1000 to 2500 nm. We provide a detailed account of the various studies that have been published utilizing both camera types. [ABSTRACT FROM AUTHOR]

Wood stiffness (modulus of elasticity, MOE) is an important property for conifer wood, with the variability in MOE largely being a function of both the specific gravity (SG) (wood density) and the angle of the microfibrils within the S2 layer of longitudinal tracheids. Rapid analysis techniques can be used together to quantify MOE; while SG can be determined with relative ease, this is not the case for microfibril angle, requiring expensive X-ray diffraction equipment. An alternative to microfibril angle is to measure longitudinal acoustic velocity. The objective of this study was to measure and then model the within tree variation in dynamic MOE (MOEdyn) by developing the methodology to measure ultrasonic velocity (USV) in radial samples from pith to bark using ultrasonic frequencies (>20 kHz). A total of 419 pith-to-bark radial strips, collected from multiple height levels in 92 loblolly pine (Pinus taeda) trees, were processed to obtain matching SG (2mm longitudinal) and USV (8.2-mm longitudinal) samples. Ring-by-ring SG was measured using X-ray densitometry and time-of-flight USV was measured at a 10-mm radial resolution from pith to bark. A subset of samples was sent to SilviScan to determine microfibril angle using X-ray diffraction. The relationship between microfibril angle and USV was strong (R 2 = 0.91, RMSE = 2.6°). Nonlinear mixed-effects models were then developed to predict radial variation in SG, USV and MOEdyn. Fixed effects for the models, which included cambial age and height of disk within tree, had pseudo R 2 values of 0.67 for SG (RMSE = 0.051), 0.71 for USV (RMSE = 316 m/s) and 0.69 for MOEdyn (RMSE = 1.9 GPa). When combined with SG measurements from X-ray densitometry, USV measurements from pith to bark are a powerful tool for assessing variability in wood stiffness. [ABSTRACT FROM AUTHOR]

Rubberwood (Hevea brasiliensis Muell. Arg) is underutilized in most developing countries but has potential to be a solution to the shortage of wood for pulp, paper and wood composite products at the end of its production cycle. Determining and understanding its fibre properties (fibre dimensions and morphology) is key in its utilization for pulp and paper as well as composites. This study assessed the effect of age on the fibre properties of rubberwood. Samples of wood at four ages (10, 15, 20 and 25 years) were obtained at both the axial (base and top of merchantable length) and radial direction (innerwood, middlewood and outerwood). Slivers were obtained from the samples and macerated to provide individual fibres for optical measurement. Fibre dimensions at the four ages were measured, and their morphology was determined. Fibre properties and morphology were significantly affected by age at p = 0.05. Average fibre length was 1.47 ± 0.12 mm, with non-constant variation observed across the different ages, and from pith to bark. Average lumen width was 16.87 µm, and fibre diameter ranged from 25.02 µm to 27.23 µm. The fibre properties of rubberwood potentially make it suitable for pulp and paper production as well as wood composite boards. [ABSTRACT FROM AUTHOR]

There is a growing interest in improving wood properties through the appropriate selection of seed provenances within species. In this study, wood density and mechanical properties were investigated for Acacia mangium trees from six different provenances, planted in Quang Tri, Vietnam. Radial and among provenance variation in stress wave velocity (SWV), wood density (WD), dynamic modulus of elasticity (MOEd), modulus of rupture (MOR), and modulus of elasticity (MOE) were determined on a total of 480 small clear specimens (20 × 20 × 300 mm) cut from 30 trees (five per provenance). SWV and selected wood properties near the pith were significantly lower than those near the bark. Differences in all selected mechanical properties among provenances were significant. The highest static properties (MOR and MOE) were found for the Long Thanh provenance indicating its potential suitability for breeding programs in Vietnam focused on improving A. mangium wood quality. A high positive correlation coefficient was found between MOEd and MOE (r = 0.93, P < 0.001) and our results indicate that the stiffness of A. mangium can be predicted using stress wave method provided the density of measured element is known. [ABSTRACT FROM AUTHOR]

Prediction of pulp yield of Eucalyptus globulus wood samples based on partial least squares (PLS) regression can be optimized by utilizing specific near infrared (NIR) wavelengths. A critical feature of this approach is the weighting of constraint conditions. Equal weighting balances optimization in terms of calibration and prediction; however, there is a lack of knowledge regarding prediction performance of wood property models when different weight factors are used. In this study, pulp yield models were developed using two E. globulus data sets characterized by narrow (5%) and extreme (22.6%) yield ranges and represented by untreated and second derivative NIR spectra. The global optimization solver pySOT was used to optimize the performance of a PLS regression model in terms of wavelengths selected and number of latent variables. A linear function of R-squares for calibration ( R c 2 ) and prediction ( R p 2 ) sets was utilized as the objective function with the aim of maximizing α R c 2 + 1 - α R p 2 for all values of α between 0 (maximizing R p 2 without concern for R c 2 ) and 1 (only maximizing R c 2 ). Values of α ≤ 0.8 provided good predictive performance, whereas α ≥ 0.9 tended to overfit the calibration data indicating that models are robust for values of α from 0 to 0.8. Representative wavelengths for each data set were identified and assigned to corresponding wood components through a band assignment process. Strong agreement was observed for α ≤ 0.8 ; however, for α ≥ 0.9 , identified wavelengths generally occurred in regions unrelated to vibrations arising from specific wood components. [ABSTRACT FROM AUTHOR]

In this study, we used both nondestructive and destructive methods for assessing solid wood properties in six Vietnamese grown Eucalyptus clones at 6 years after planting. We measured stress wave velocity in standing sample trees (SWVT), logs (SWVL), and small clear specimens (SWVS) obtained from the trees and logs, and to measure static properties, we used MOE—modulus of elasticity and MOR—modulus of rupture. The highest average MOE and MOR were detected in clones 3 and 5, suggesting that these clones might be more appropriate for breeding programs focused on improving wood quality of Eucalyptus grown in Vietnam. Mean MOE and MOR of the lumber had significant (p < 0.001) relationships with SWVT (r = 0.61 and 0.53, respectively) and SWVL (r = 0.76 and 0.71, respectively). Stress wave velocity measurements of both standing trees and logs can be useful for further segregating Vietnam's Eucalyptus timber resource based on MOE and MOR. For the small clear specimens, the best prediction of stiffness (dynamic modulus of elasticity (MOEd)) was obtained when both SWVS and air-dry density (AD) were used. The coefficient of correlation between MOE and MOEd was 0.93. [ABSTRACT FROM AUTHOR]

Near-infrared spectroscopy (NIRS) allows for the rapid estimation of a wide range of wood properties. Typically, NIRS studies on wood have utilized benchtop spectrometers, but efforts to utilize NIR hyperspectral imaging to examine wood and wood products have increased. Compared to benchtop NIR systems, hyperspectral imaging has several advantages (speed, visualization of spatial variability), but the data typically have a lower signal-to-noise ratio as well as fewer wavelengths saved; thus, hyperspectral imaging systems have a larger spectral sampling interval (SSI). Furthermore, the SSI and wavelength range varies considerably among different HSI cameras. NIR-HSI systems based on indium gallium arsenide (InGaAs) detectors have a wavelength range typically from 900 to 1700 nm, while short-wave infrared hyperspectral imaging (SWIR-HSI) systems based on mercury cadmium telluride (MCT) detectors have the 'full' NIR wavelength range from 1000 to 2500 nm. These factors may influence the performance of wood property calibrations. We compared one NIR-HSI (900–1700 nm) and three SWIR-HSI (1000–2500 nm) commercially available cameras with an NIRS benchtop spectrometer (1100–2500 nm). The performance of specific gravity (SG) and stiffness (MOE) calibration models was compared with one-hundred Douglas-fir (Pseudotsuga menziesii) samples. The limited wavelength range of an NIR-HSI camera provided the best models for MOE, whereas the NIR-HSI and two SWIR-HSI cameras provided similar SG results. SWIR-HSI models heavily favored wavelengths greater than 1900 nm. [ABSTRACT FROM AUTHOR]

Near-infrared wavelengths selected by genetic algorithm were used to optimize partial least squares (PLS) regression models for loblolly pine (Pinus taeda L.) from the southeastern United States. Wood properties examined included density (D), microfibril angle, modulus of elasticity and tracheid coarseness (C), radial diameter (R), tangential diameter (T), and wall thickness (w)—measured by SilviScan. The optimization process was run for each property with Agenda 2020 samples utilized for PLS model development and the other sets used for prediction. The number of variables (i.e. wavelengths) varied from 10 to 100 with an optimum number identified by genetic algorithm. When compared to a full data set model (based on 700 wavelengths), calibration and prediction performance of optimized PLS regression models were superior for all properties. Importantly, representative wavelengths for each property were consistently related to recognized bond vibrations observed in specific wood components demonstrating that optimization targets wavelengths directly related to changes in wood chemistry within the examined loblolly pine samples. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Forest Research is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Radial and between-clone variations in stress-wave velocity, air-dry density (AD), and mechanical properties in six clones of 5-year-old Acacia auriculiformis trees planted in Vietnam were investigated. The potential to predict modulus of elasticity (MOE) and modulus of rupture (MOR) using stress-wave velocity of standing trees (SWVT) or small specimens (SWVS) was also examined. The examined SWVT, SWVS, and wood properties differed significantly among clones, particularly with two (clones 1 and 6) well suited for A. auriculiformis tree breeding programs focusing on lumber production, as they had the highest static bending values and no significant difference in AD between positions near pith and bark. At the specimen level, the best prediction of static bending properties could be achieved when both SWVS and AD were used in a model for calculation of dynamic modulus of elasticity (MOEd) in air-dry conditions. Significant correlations between SWVT and average MOE (r = 0.83) and MOR (r = 0.61) of test specimens indicated that the use of stress-wave technique for assessing MOE and MOR for selecting the best A. auriculiformis clones in terms of lumber performance was possible. [ABSTRACT FROM AUTHOR]

The moisture content (MC) of felled trees has a direct impact on transportation costs and efficiency. Transpirational (or field) drying of fallen trees, to reduce MC and subsequently improve the economics of transport can be employed; however, an understanding of seasonal drying rates is required. Typically load cells have been used to track moisture changes in bundles of logs but where access is limited this approach is impractical. Time-domain reflectometry (TDR) provides an alternative approach and was used to monitor seasonal changes in transpirational drying rates for felled loblolly and slash pine at a Lower Coastal Plain site in Florida and loblolly pine at a Piedmont site in Georgia on a weekly basis for approximately one year. Different transpirational drying rates and minimum MC's were observed by season. Drying rates observed during summer, fall and spring, at both test locations, indicate that after three weeks an equilibrium (or minimum) MC is achieved. Winter drying is slower, and up to 5 weeks in the field (or even longer) may be required. Post equilibrium felled log moisture content continued to vary during most seasons with rainfall events the most probable cause. TDR provides a viable approach for monitoring transpirational drying and subsequent MC changes in felled trees. [ABSTRACT FROM AUTHOR]

Within-tree variation of four handsheet properties (burst index, sheet density, STFI short-span compression strength (STFI) and tensile index) was mapped for loblolly pine trees aged 13 and 22 years using NIR predicted handsheet property data (representing an average of 18 trees for each age). All within-tree maps were similar demonstrating a radial decrease in handsheet properties at all heights, with sheet density and tensile index having the greatest within-tree variation. The corewood zone had the highest values for all properties, while the lowest values were observed in a region consistent with juvenile and transitional outerwood as defined by Burdon et al. (2004). The maps are also similar to, but the inverse of, maps reported in prior studies for density and tracheid coarseness and wall thickness. Relationships amongst the examined handsheet properties and wood and tracheid properties explains the overall similarities of the different maps. The maps provide a representation of within-tree variation of important paper properties at two different ages. An understanding of how these properties vary within loblolly pine trees can aid in better utilization of forest resources. [ABSTRACT FROM AUTHOR]

An optimization problem was developed by using a genetic algorithm to select wavelengths for establishing multivariate calibration models based on partial least squares (PLS) regression. Two near infrared (NIR) data sets represented by untreated and second derivative spectra were used to predict Eucalyptus globulus pulp yield. The optimization process was run with the number of variables (i.e., wavelengths) varied from 10 to 100 to determine the optimum wavelengths and number of latent variables for PLS regression model. A linear function of R-squares for calibration and prediction sets was utilized as the objective function of the optimization problem. The optimum wavelengths selected by genetic algorithm helped to considerably improve the performance of the PLS regression model, not only for the calibration sets but also for the prediction sets. The optimum number of latent variables varied over a wide range, from the maximum allowed (20) to a lower limit of six. Representative wavelengths for each data set were also statistically determined and assigned to corresponding wood components through a band assignment process, which showed strong agreement. [ABSTRACT FROM AUTHOR]

The objective of this work was to provide a rapid and nondestructive imaging method for evaluating the hygroscopic behavior of thermally modified lignocellulosic materials (softwood and hardwood). The difference in the hygroscopic behavior was explained by moisture content (MC) mapping results and molecular association characteristics of absorbed water (i.e. weakly, moderately, and strongly hydrogen-bonded water molecules) with wood at various relative humidities (RH). To achieve this goal, near-infrared (NIR) spectral images in the wavelength range 1816–2130 nm (covering the combination of stretching and deformation vibrations for OH) were used to visualize MC distributions over the surface of Japanese cedar and European beech samples which had been thermally treated at different temperatures. A curve fitting method was utilized to explore changes in water-wood structure characteristics based on shifts to longer wavelength in spectral signals caused by increasing MC. The curve fitting results support the recent nuclear magnetic resonance (NMR) studies that different bound water stabilities may pool in different compartments of the wood cell wall. Furthermore, water was firmly bound to wood at low RHs and H-bonds gained mobility as the number of absorbed molecules increased. It is concluded that NIR hyperspectral imaging also has the potential to be a complementary methodology for studying the transient changes of wood-water interactions before equilibrium. [ABSTRACT FROM AUTHOR]

The radial variation in cell morphology of ten-year-old Melia azedarach trees planted in northern Vietnam was experimentally investigated. The earlywood fiber lumen diameter and latewood fiber lumen diameter were almost unchanged from pith to 6th ring before significantly decreasing and remaining constant from 7th ring outwards. In contrast, fiber cell wall thickness in both earlywood and latewood increased from pith to 7th ring before becoming stable towards the bark. The maturation age of earlywood vessel lumen diameter estimated by segmented regression analysis indicated that wood of the Melia azedarach could be classified into core wood and outer wood, and the boundary between core and outer wood may be located at 7th ring from pith. This should be taken into account in wood processing using M. azedarach grown in northern Vietnam. [ABSTRACT FROM AUTHOR]

Loblolly pine is a major fibre source for the pulp and paper industry. Here we developed the first nonlinear models to predict the within-tree and regional variation of tracheid length and width for planted loblolly pine. Data were obtained from macerated tracheids and near-infrared spectroscopy calibration models from trees sampled in 109 stands across the southeastern United States. The fixed effects for the final tracheid length model, which included cambial age, height of disk within tree, and physiographic region, explained 71 percent of the variation with root mean square error (RMSE) of 0.28 mm, while the fixed effects for the final tracheid width model explained 57 percent of the variation with RMSE of 1.4 μm. There was significant variation in tracheid properties across the growing regions. Tree maps showing within-tree variability in tracheid properties were produced. Five simulated scenarios were compared using the models developed, with mean tracheid dimensions calculated on a whole-tree basis at a first and second thinnings, and at final harvest. Also from the final harvest, the tops of trees, and outerwood chips produced during lumber manufacturing were also simulated. For the whole tree scenarios, both mean tracheid length and width increased with age, increasing from 2.24 mm and 40.5 μm (age 12), to 2.51 mm and 41.3 μm (age 18), and to 2.73 and 41.8 μm at age 25, respectively. The tops of the trees at age 25 had a mean tracheid length of 2.46 mm and a mean width of 41.0 μm, while the chips had a mean tracheid length of 3.13 mm and a mean width of 42.5 μm. Due to the models representing samples collected from across the southeastern United States, and their relatively high precision, they are suitable for incorporation into growth and yield systems allowing for prediction of tracheid properties. [ABSTRACT FROM AUTHOR]

Maps developed using Akima's interpolation method, and representing average data for trees aged 13 and 22 years, were used to compare patterns of within-tree variation for Pinus taeda L. (loblolly pine) tracheid properties: coarseness (C), specific surface (S), radial (R) and tangential (T) diameter and wall thickness (w). SilviScan-calibrated near-infrared (NIR) spectroscopy provided data for the analysis with C (Rc2 = 0.85, Rp2 = 0.85), S (Rc2 = 0.83, Rp2 = 0.76), and w (Rc2 = 0.89, Rp2 = 0.93) models having very good calibration / prediction statistics, while those for T and R diameter were moderate (Rc2 = 0.79, Rp2 = 0.57) and poor (Rc2 = 0.64, Rp2 = 0.19), respectively. C, S, and w maps were similar to the density maps for P. taeda and indicate the properties increase radially at all heights. The T diameter map was similar to maps reported for microfibril angle except that T diameter increased radially and with height whereas microfibril angle decreased radially and with height. The map for R diameter increased with height and was unlike the other properties examined; caution is recommended regarding any interpretations based on the R diameter map owing to the weak statistics observed for the NIR model. Changes observed between the two ages are consistent with the asymptotic progression of properties associated with maturation. [ABSTRACT FROM AUTHOR]

Wood extractives are considered the major factor determining the natural durability of wood. Attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy was assessed for rapid determination of western juniper (Juniperus occidentalis Hook. var. occidentalis) durability based on extractives in heartwood, sapwood-heartwood and sapwood regions. Durability was assessed by exposing samples to brown-rot decay fungi [Gloeophyllum trabeum (Pers.) Murrill and Rhodonia placenta (Fr.) Niemelä, K.H. Larss. & Schigel] or eastern subterranean termite (Reticulitermes flavipes Kollar). Durability classifications were compared to their extractive contents, along with ATR-FTIR spectra of extracted and unextracted blocks to establish relationships using hierarchical cluster analysis (HCA) and principal component analysis (PCA). Western juniper durability varied with test organisms, but the majority of samples had high fungal and termite resistance. Moderate to weak connections were observed between durability and extractive content, but HCA and PCA analysis were unable to classify durability with accuracy. The absence of non-resistant samples may have influenced the ability of the chemometric methods to accurately categorize durability. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Extractives, such as carvacrol, play a major role in the durability of Alaska yellow cedar (Callitropsis nootkatensis) heartwood. However, it is a slow and complicated process to identify the levels of these compounds in individual timbers. This study investigated the feasibility of attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy and near-infrared (NIR) spectroscopy, coupled with hierarchical cluster analysis (HCA) and principal component analysis (PCA), for detecting carvacrol in wood. Alaska yellow cedar was extracted using sequential Soxhlet extraction with toluene-ethanol, followed by ethanol and hot water. The extracted samples were milled, and the powders were treated with different concentrations of carvacrol. The spectral analysis of the wood that contained carvacrol was conducted using ATR-FTIR and NIR spectroscopy, and the peaks indicative of carvacrol were identified. The chemometric analysis on the spectral data using PCA and HCA distinguished the wood with high (> 34%) and low (< 3.5%) carvacrol concentrations. The results suggest that infrared spectroscopy can be a non-destructive tool for the qualitative and quantitative evaluation of extractives, and possibly for the rapid assessment of Alaska yellow cedar durability. [ABSTRACT FROM AUTHOR]

Seasonal variation in the moisture content (MC) of standing trees can have a significant impact on wood (and when harvested) log weight; however, its variation is poorly understood owing to the destructive nature of sampling methodologies. To improve our understanding of temporal moisture variation, low cost systems that continuously monitor MC of standing trees are required. Time domain reflectometry (TDR) was explored as an option to estimate standing tree MC. TDR data was collected from ten loblolly and ten slash pine trees growing on the Lower Coastal Plain of Florida and ten loblolly pine from the Piedmont of Georgia on a weekly basis for approximately 1 year. Site specific calibrations were used to predict MC, but owing to a pronounced wound response it was not possible to accurately track temporal changes in whole-tree MC. If calibrations more oriented toward living trees can be obtained, it may be possible to use TDR to monitor temporal changes in standing tree MC. [ABSTRACT FROM AUTHOR]

Featured Application: Hyperspectral imaging may provide lumber mills with a cost-effective method to efficiently identify areas of high and low stiffness within logs prior to sawing, and thus allow mills to make more informed decisions on a log-by-log basis for sawing solutions. Near-infrared (NIR) spectroscopy and NIR hyperspectral imaging (NIR-HSI) were compared for the rapid estimation of physical and mechanical properties of No. 2 visual grade 2 × 4 (38.1 mm by 88.9 mm) Douglas-fir structural lumber. In total, 390 lumber samples were acquired from four mills in North America and destructively tested through bending. From each piece of lumber, a 25-mm length block was cut to collect diffuse reflectance NIR spectra and hyperspectral images. Calibrations for the specific gravity (SG) of both the lumber (SGlumber) and 25-mm block (SGblock) and the lumber modulus of elasticity (MOE) and modulus of rupture (MOR) were created using partial least squares (PLS) regression and their performance checked with a prediction set. The strongest calibrations were based on NIR spectra; however, the NIR-HSI data provided stronger predictions for all properties. In terms of fit statistics, SGblock gave the best results, followed by SGlumber, MOE, and MOR. The NIR-HSI SGlumber, MOE, and MOR calibrations were used to predict these properties for each pixel across the transverse surface of the scanned samples, allowing SG, MOE, and MOR variation within and among rings to be observed. [ABSTRACT FROM AUTHOR]

This study developed regional calibration models for the prediction of loblolly pine (Pinus taeda) tracheid properties using near-infrared (NIR) spectroscopy. A total of 1842 pith-to-bark radial strips, aged 19–31 years, were acquired from 268 trees from 109 stands across the southeastern USA. Diffuse reflectance NIR spectra were collected at 10-mm increments from the radial face of pith-to-bark strips using a FOSS 5000 scanning spectrometer. A subset of the 10-mm samples was selected based on the NIR spectra uniqueness and placed in calibration (N = 1020) and validation (N = 998) test sets. The samples were macerated and the tracheid properties measured using an optical analyzer (Techpap MorFi Fiber and Shive Analyzer). Models were created using partial least squares (PLS) regression using the calibration samples, and their performance checked using the validation set. Prediction PLS models for tracheid length were strong when checked with the validation set [Rp2 = 0.87, standard error of prediction (SEP) = 0.23 mm, ratio of performance to deviation (RPD) = 2.8]. Prediction models for tracheid width had moderate fit statistics (R2 = 0.61, SEP = 1.6 μm, RPD = 1.6), but the SEP was similar to the measurement error of the camera (± 2 μm). The NIR wavelengths of importance were largely attributed to cellulose. The 1542 nm wavelength explained 77% of the variation in tracheid length (RMSE = 0.31 mm). These results demonstrate that NIR spectroscopy models for tracheid length and width can be developed from a diverse set of samples and still maintain prediction accuracy. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Forest Research is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study investigated near-infrared spectroscopy (NIRS) to rapidly estimate physical and mechanical properties of No. 2 2 × 4 southern pine lumber. A total of 718 lumber samples were acquired from six mills across the Southeast and destructively tested in bending. From each piece of lumber, a 25-mm-length block was cut and diffuse reflectance NIR spectra were collected from the transverse face using a FOSS 5000 scanning spectrometer. Calibrations were created using partial least squares (PLS) regression and their performance checked with a prediction set. Overall moderate predictive ability was found between NIRS and the properties for the calibration and prediction sets: block specific gravity (SG) ( R = 0.66 and R = 0.63), lumber SG (0.54 and 0.53), modulus of elasticity (MOE) (0.54 and 0.58), and modulus of rupture (MOR) (0.5 and 0.4). Model performance for MOE ( R = 0.70) and MOR ( R = 0.50) improved when performing PLS regression on a matrix containing lumber SG and NIR spectra. Overall NIRS predicted MOE better than linear models using lumber SG ( R = 0.46), whereas lumber SG ( R = 0.51) predicted MOR better than NIRS. Overall NIRS has reasonably good predictive ability considering the small volume of wood that is scanned with the instrument. [ABSTRACT FROM AUTHOR]

Caesalpinia echinata Lam. (pernambuco or pau-brasil) is recognized as the premier raw material for manufacturing stringed instrument bows. Several studies have identified properties considered important in determining the suitability of pernambuco wood for bow manufacture including density, modulus of elasticity (MOE), and, possibly, microfibril angle (MFA). No research has been conducted on how these properties vary within individual trees; however, an understanding of how pernambuco wood properties vary within trees is important as it may assist in the identification of trees or provenances most suited for the establishment of plantations, aid in developing an understanding of management practices on wood property variation for plantation-grown pernambuco and also facilitate the identification of regions within trees that possess optimal properties for bow manufacture. Radial variation in density, MFA and MOE was examined using SilviScan for three radial strips representing differing levels of wood quality in terms of perceived suitability for making high-quality bows. The lowest quality sample showed considerable radial variation compared to the higher quality samples for all properties and it also had the lowest average density. It was not possible to identify a strong pith to bark trend for any of the wood properties examined. [ABSTRACT FROM AUTHOR]

Time-domain reflectometry (TDR) can be used to predict the moisture content in porous materials, including soil, and is an exciting tool that could be used to measure the moisture content in wet-stored wood. Three-rod probes with 127 mm- or 152 mm-long rods were inserted into 62 loblolly pine and 34 sweetgum saturated bolts. The bolts were air dried over a span of five weeks. TDR waveforms and moisture content were periodically recorded. In total, 534 and 482 readings were taken for the loblolly pine and sweetgum bolts, respectively. An algorithm in R was written to automatically analyze the apparent length of the TDR rods. Calibration models were developed between moisture content and X (apparent length/actual rod length). A three-parameter logistic model was developed for loblolly pine (R2=0.64) and sweetgum (R²=0.84). The process was repeated using shorter bolts and 152 mm-long rods, resulting in improved models for loblolly pine (R²=0.99) and sweetgum (R²=0.97). Overall, TDR and the algorithm written to analyze the waveforms were accurate in predicting moisture content and could be used to monitor moisture in wet-decks. [ABSTRACT FROM AUTHOR]

A study was conducted to identify geographical variation in loblolly pine bark and wood properties at the whole-tree level and to quantify the responses in whole-tree bark and wood properties following contrasting silvicultural practices that included planting density, weed control, and fertilization. Trees were destructively sampled from both conventionally managed stands and various designed experimental trials established across the southern United States by various research cooperatives and forest product industries to quantify the bark and wood properties of loblolly pine. Bark (percentage bark, specific gravity [SG], and moisture content [MC]) and wood (SG, MC, green weight of wood/m3, and green weight of wood and bark/m3 of volume) properties were measured from disks collected at multiple heights from sampled trees and used to compute the whole-tree bark and wood properties. Significant regional variation was observed for whole-tree bark and wood properties. Bark and wood SG showed an increasing trend from inland to coastal regions and vice versa for bark and wood MC. The effect of different silvicultural treatments on bark and wood properties were generally absent; but a significant effect on bark percentage, MC, and green weight of wood and bark/m3 was observed for trees that received intensive treatments such as early age competition control plus multiple fertilizations. [ABSTRACT FROM AUTHOR]

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Context: Modulus of elasticity (MOE) is an important mechanical property determining the end-use and value of loblolly pine ( Pinus taeda L.) lumber. Aim: In this study, a model was developed to predict the within tree variation of MOE, from pith-to-bark and stump-to-tip, using data collected from a 21-year-old unthinned stand where trees were planted under seven initial stand density levels (746-2,243 trees/hectare). Methods: The study was laid out in a randomized complete block design, with seven levels of initial planting density, replicated three times. Seven trees were destructively sampled from each plot, and bolts were cut from each tree at heights of 2.4, 7.3, and 12.2 m. Static bending samples (of dimension 2.5 × 2.5 × 40.6 cm) representing pith-to-bark variation were cut from each bolt and MOE measured. A three-parameter logistic function was used to model the pith-to-bark variation in stiffness with distance from pith as an explanatory variable. Results: Based on the final fitted model, it was found that the asymptotic parameter (maximum outerwood MOE = 13.48 GPa) was not influenced by sampling height, initial planting density, and stem slenderness. However, the inflection and scale parameters were significantly influenced by these variables. Conclusions: In summary, we found that initial planting density had a significant influence on the amount of corewood produced with higher initial planting densities producing a lower proportion of corewood as indicated by a linear decrease in inflection point with an increase in planting density. [ABSTRACT FROM AUTHOR]

The use of near infrared (NIR) spectroscopy to predict levels of white-rot degradation in Populus deltoides (cottonwood) by Trametes versicolor over the couse of 1-8 days was investigated. NIR spectra were collected from cross-sectional faces following laboratory soil block decay tests. Spectra in the range of 1100-2400 nm were calibrated in terms of mass loss, compression strength and exposure period based on data of standard methods. The first and second derivatives of NIR spectra were also included into the calibration, which was done by partial least squares regression. The best calibrations with the strongest R2 values were obtained in terms of exposure period (R2 0.92, second derivative), mass loss (R2 0.89, first derivative) and compression strength (R2 0.51, second derivative). As far as the validation (prediction) statistics are concerned, the following data were obtained: exposure period (R2=0.71; RPDp 1.81, second derivative), mass loss prediction (R2=0.43; RPDp=0.67, first derivative) and compression strength R2=0.28; RPDp=1.14 (second derivative). The weak statistical data can be interpreted only in a way that the data are not robust and thus an early prediction of fungal attack by NIR spectroscopy is not yet reliable. [ABSTRACT FROM AUTHOR]

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Growth and wood properties were measured on breast height cores collected from two stands, New Bern and Bertie, located in the lower Coastal Plain of North Carolina. The New Bern site was thinned before fertilizer application, and the Bertie site was not. The study was laid out in a randomized complete block design with each treatment replicated in four blocks at New Bern and two blocks at Bertie. The treatments were different levels of nitrogen fertilization: control (no nitrogen) and 112, 224, and 336 kg/ha. In addition, 28 kg/ha of phosphorus was included with each treatment. The objective of this study was to examine the response in growth and wood properties to midrotation fertilization in a thinned versus an unthinned stand. A significant decrease in latewood specific gravity was observed following nitrogen fertilization in the thinned stand but not in the unthinned stand. Whole ring width, latewood width, and earlywood width significantly increased following nitrogen fertilization at New Bern but not at Bertie. Whole ring specific gravity, earlywood specific gravity, latewood percentage, and earlywood:latewood ratio did not show any change due to fertilization in either stand. Responses in both growth and wood characteristics lasted for 2-3 years following fertilization and depended on the amount of fertilizer applied and whether or not the site was thinned. The response to nitrogen application was significant for the thinned stand only. [ABSTRACT FROM AUTHOR]

The use of calibrated near infrared (NIR) spectroscopy for measuring and predicting the advancement of wood decay in Pinus spp. sapwood wafers that were subjected to Gloeophyllum trabeum for periods ranging from 1 to 10 days was investigated. NIR spectra were obtained from the center of the cross-sectional face of each sample before and after decay tests. Mass loss and compression tests were also used to measure the progression of decay. Calibrations were created from NIR spectra, mass loss, and compression strength data using untreated and mathematically treated (multiplicative scatter correction and first and second derivative) spectra. Strong relationships were derived from the calibrations with the strongest R values being 0.98 (mass loss) and 0.97 (compression strength). Calibrations for mass loss showed the strongest statistics for predicting wood decay of a separate test set (0.85 raw, second derivative to 0.76 multiplicative scatter correction (MSC), while predictions for compression strength of the decayed samples resulted in R of 0.69 (raw) to 0.54 (MSC). Calibrations created from the amount of time the samples were decayed showed strong statistics, indicating that NIR spectroscopy can predict the early stages of wood decay. [ABSTRACT FROM AUTHOR]

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Ring specific gravity, earlywood and latewood specific gravity, and percent latewood were measured on cores collected at breast height from a thinned and fertilized midrotation loblolly pine (Pinus taeda L.) plantation in the lower Coastal Plain of North Carolina. The study was laid out in a randomized complete block design receiving four levels of nitrogen (N) fertilizer in 1984: 000 (control), 112, 224, and 336 kg/ha plus 28 kg/ha of phosphorus with each treatment. A consistent pattern of response was observed in latewood specific gravity (LWSG) after the application of different levels of fertilizer and used as a variable for modeling. The LWSG profiles of unfertilized trees followed a nonlinear relation with ring number from pith. A three-parameter asymptotic function was used to explain the LWSG profile of unfertilized trees with ring number as a covariate, Application of N reduced LWSG and was modeled using a two-parameter response function with year since fertilization as a covariate and separate parameter estimates for each fertilization level. On the basis of the model, the magnitude of maximum cumulative response was -0.025, -0.049, and -0.074 attained at 3.7, 1 .9, and 0.8 years after fertilization for the 112, 224, and 336 kg/ha treatments, respectively. [ABSTRACT FROM AUTHOR]

The effects of two treatments, irrigation and fertilization, were examined on specific gravity (SG)-related wood properties of loblolly pine trees (Pinus taeda L.) grown in Scotland County, North Carolina. The effects on the core as a whole, on the juvenile core, on the mature core, and from year to year were all analyzed. The results indicate that fertilization significantly lowered latewood SG, overall SG, and percent latewood and did so consistently throughout the period of study. Irrigation significantly lowered earlywood SG during the phase of juvenile wood production but significantly raised latewood SG during the period of mature wood production. Significant interaction between fertilization and irrigation indicated that irrigation helped overall SG and percent latewood of fertilized trees to increase to the level of untreated trees. Therefore, this study provides evidence that although fertilization significantly affects several SG-related properties, water availability is beneficial to the fertilization process; over time, an adequate water supply may help fertilized trees to maintain SG levels similar to those of unfertilized trees. [ABSTRACT FROM AUTHOR]

Near infrared diffuse reflectance spectra collected in 10-mm sections were used for the estimation of air-dry density (AD), microfibril angle (MFA), stiffness (MOE), tracheid coarseness (COARS), and tracheid wall thickness (WTHICK) in wood radial strip samples obtained at breast height (1.4 m) from 60 Pinus taeda trees. Calibration models were developed using traditional partial least squares (PLS) and kernel regression. The kernel methods included radial basis functions-partial least squares (RBF-PLS) and least-squares support vector machines (LS-SVM). RBF-PLS and LS-SVM models outperformed PLS-CV calibrations in terms of fit statistics. MFA and MOE, two properties that exhibited nonlinearity, showed the most significant improvements compared to PLS. In terms of predictive ability RBF-PLS performed better than PLS for the prediction of MFA, MOE, and COARS. LS-SVM showed better prediction statistics in all cases, except for WTHICK that gave similar statistics compared to PLS and was superior to RBF-PLS. By adding statistically significant factors to the PLS regressions, it was possible to capture some of the nonlinear features of the data and improve the predictive ability of the PLS models. [ABSTRACT FROM AUTHOR]

Near-infrared (NIR) spectroscopy provides a rapid method for estimating pulp carbohydrate content. Previous studies have used a variety of sample preparation methods; however, the influence of preparation method on calibration performance has not been examined. This study compares carbohydrate content calibrations for four sample preparation methods (coarse, fine, and milled pulp, and handsheets). Fifty-nine unbleached pulps (52 single-tree, 7 mill composite) with known carbohydrate composition (arabinose, fructose, galactose, glucose, rhamnose, and xylose) were prepared using the four methods. NIR spectra were collected from the samples, which were divided into calibration (40 samples) and prediction sets (19 samples). Calibrations were created for each combination of preparation method and carbohydrate, and tested on the prediction set. Calibration statistics were good for rhamnose and xylose but weaker for other carbohydrates. Coarse and fine pulp produced the best calibrations, but they were not significantly different from calibrations for handsheets; milled pulp provided the weakest calibrations. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Forest Research is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Forest Research is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

New approaches for assessing wood durability are needed to help categorize decay resistance as timber utilization shifts towards plantations or native forest regrowth that may be less durable than original native forest resources. This study evaluated attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy combined with principal component analysis (PCA) for distinguishing between groups of Alaska yellow cedar (Cupressus nootkatensis) wood for susceptibility to two decay fungi (Gloeophyllum trabeum and Rhodonia placenta) and the eastern subterranean termite (Reticulitermes flavipes). Alaska yellow cedar durability varied with test organisms, but the majority of samples were highly resistant to fungal and termite attack. Weight losses and extractives yield using sequential extractions (toluene:ethanol > ethanol > hot water) showed moderate to weak relationships. PCA analysis revealed limited ability to distinguish amongst levels of wood durability to all tested organisms. The absence of non-resistant samples may have influenced the ability of the chemometric methods to accurately categorize durability. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Forest Research is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Forest Research is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Forest Research is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The use of calibrated near infrared (NIR) spectroscopy for predicting the chemical composition of Pinus taeda L. (loblolly pine) wood samples is investigated. Seventeen P. taeda radial strips, representing seven different sites were selected and NIR spectra were obtained from the radial longitudinal face of each strip. The spectra were obtained in 12.5 mm sections from pre-determined positions that represented juvenile wood (close to pith), transition wood (zone between juvenile and mature wood), and mature wood (close to bark). For these sections, cellulose, hemicellulose, lignin (acid soluble and insoluble), arabinan, galactan, glucan, mannan, and xylan contents were determined by standard analytical chemistry methods. Calibrations were developed for each chemical constituent using the NIR spectra, wood chemistry data and partial least squares (PLS) regression. Relationships were variable with the best results being obtained for cellulose, glucan, xylan, mannan, and lignin. Prediction errors were high and may be a consequence of the diverse origins of the samples in the test set. Further research with a larger number of samples is required to determine if prediction errors can be reduced. [ABSTRACT FROM AUTHOR]

Recently, we demonstrated that the accuracy of pulp yield predictions for wood samples from a site (Gog) new to their calibration (Tasmania‐wide Eucalyptus nitens) was greatly improved by adding five Gog samples to the calibration set. In this study we investigated the addition of Gog samples to the Tasmania‐wide E. nitens set, with the aim of further improving predictive accuracy. It was demonstrated that the addition of a single Gog sample to the Tasmania‐wide calibration set was sufficient to greatly reduce predictive errors and that the inclusion of at least 3 Gog samples in the Tasmania‐wide set was sufficient to give relatively stable predictive errors. The addition of different sets of 5 Gog samples to the Tasmania‐wide calibration, however, caused predictive errors to vary between sets. The standard deviation of pulp yield for the prediction set (20 Gog samples) was important, with sets having the largest standard deviations giving the best predictive statistics. Finally, the Tasmania‐wide E. nitens calibration was enhanced using samples from a different species (Eucalyptus globulus) and applied successfully to other E. globulus samples. [ABSTRACT FROM AUTHOR]