Christian R. Mora

Relationships between acoustic variables and different measures of stiffness in standing Pinus taeda trees

Acoustic tools are increasingly used to estimate standing-tree (dynamic) stiffness; however, such techniques overestimate static stiffness, the standard measurement for determining modulus of elasticity (MOE) of wood. This study aimed to identify correction methods for standing-tree estimates making dynamic and static stiffness comparable. Sixty Pi- nus taeda L. trees, ranging from 14 to 19 years old, obtained from genetic tests established in the southeastern United States, were analyzed. Standing-tree acoustic velocities were measured using the TreeSonic tool. Acoustic velocities were also recorded in butt logs cut from the same trees using the Director HM200. A strong but biased relationship between tree and log velocities was observed, with tree velocities 32% higher (on average) than the corresponding log velocities. Two correction methods, one for calibrating tree velocities and one for accounting for differences in wood moisture con- tent, were used to determine an adjusted MOE. After correction, adjusted MOE estimates were in good agreement with static longitudinal MOE values measured on clearwood specimens obtained from the trees, and no systematic bias was ob- served. The results of this study show that acoustic estimates of MOE on standing trees largely depend on how the data are processed and the reference method used.

Comparison of Pinus taeda L. wood property calibrations based on NIR spectra from the radial-longitudinal and radial-transverse faces of wooden strips

Abstract When a radial strip is cut from an increment core it can potentially be cut with two orientations: parallel to longitudinal tracheids, i.e., a radial-longitudinal (RL) strip (the orientation of SilviScan samples), or at an orientation of 90° to the tracheids, i.e., a radial-transverse (RT) strip. Both strips could be used for near-infrared (NIR) analysis, but it is unknown how calibrations based on RT-face NIR spectra compare with those based on RL-face NIR spectra. A total of 20 Pinus taeda L. (loblolly pine) RL strips were characterized in terms of air-dry density, microfibril angle (MFA), stiffness and several tracheid morphological characteristics. NIR spectra were collected in 10-mm increments from the RL and RT faces of matching strips and used to develop calibrations for each property. In general, RL-face NIR spectra gave calibrations that provided stronger relationships. Differences between the two sets of calibrations were small, indicating that either face could be used for NIR analysis.

Characterization of the wood quality of pernambuco (Caesalpinia echinata Lam) by measurements of density, extractives content, microfibril angle, stiffness, color, and NIR spectroscopy

Abstract A total of 30 Caesalpinia echinata (pernambuco) sticks were ranked based on their suitability for making high quality bows and were assigned to one of the three following categories: 0=very poor to poor, 1=good to very good, and 2=excellent. From the end of each stick a sample was cut for wood property and near infrared (NIR) spectroscopic analysis. Wood properties measured included air-dry density, extractives content, microfibril angle, stiffness and wood color. NIR spectra were evaluated by principal component analysis (PCA) and on the PC scores. Poor quality samples were discriminated from those of good to very good and excellent quality; however, samples from the two higher quality groups were mixed. Based on relationships observed between PC scores and wood properties, we suggest that, of the measured properties, density and stiffness were the most important in sample discrimination based on quality. Samples ranked in the excellent category had high average density (1119 kg m-3) and stiffness (25.2 GPa) and relatively low extractives content (21.2%) compared to samples in the very poor to poor category (density= 938 kg m-3, stiffness=18.9 GPa and extractives content=24.9%).

Modeling corewood–outerwood transition in loblolly pine using wood specific gravity

A modified logistic function was used for modeling specific-gravity profiles obtained from X-ray densitometry analysis in 675 loblolly pine (Pinus taeda L.) trees in four regeneration trials. Trees were 21 or 22 years old at the time of the study. The function was used for demarcating corewood, transitional, and outerwood zones. Site and silvicultural ef- fects were incorporated into the model. Heteroscedasticity and within-group correlation were accounted for by specifying the variance and serial-correlation structure, respectively. The estimated transition zone was located between rings 5 and 15, and the outerwood demarcation point varied from rings 12 to 15. No effects of treatments on the demarcation points were observed; however, site preparation and fertilization affected the lower asymptotes of the curves in all sites. A geo- graphical trend for the demarcation point was observed, with the northern site requiring more time to reach a plateau in specific gravity compared with the southern sites. The diameter of the juvenile core was increased as a result of the treat- ments. However, the amount of corewood was not statistically affected, ranging from 55% in the north to 75% in the south, except at one site where fertilization decreased the percentage of corewood.

On the selection of samples for multivariate regression analysis: application to near-infrared (NIR) calibration models for the prediction of pulp yield in Eucalyptus nitens

The effects of using reduced calibration sets on the development of near-infrared (NIR) calibration models for the prediction of kraft pulp yield in Eucalyptus nitens (Dean & Maiden) Maiden trees were explored. Three selection techniques based on NIR spectral data (CADEX (computer-aided design of experiments), DUPLEX, and SELECT algorithms) and one selection method based on a measured property (RANKING algorithm) were used for analysis and compared against a model using all data. The effect of using calibration sets of different sizes was also evaluated. All sample-selection methods resulted in models of similar performance compared with the model fitted using all samples. For calibration purposes, RANKING selection resulted in models with the lowest errors of cross-validation, followed by the DUPLEX, CADEX, and SELECT methods. In terms of validation, the SELECT and CADEX methods resulted in lower errors of prediction compared with the DUPLEX and RANKING algorithms. In general, cross-validation and predic...

Determination of basic density and moisture content of loblolly pine wood disks using a near infrared hyperspectral imaging system

The use of near infrared (NIR) hyperspectral imaging for the estimation of basic density (BD) and moisture content (MC) of loblolly pine (Pinus taeda L.) disks is reported. A total of 125 wood disks, ranging in age from 13 years to 19 years, were analysed. Hyperspectral images were collected using an imaging system composed of an InGaAs camera from Sensors Unlimited, Inc. (sensitive between 1000nm and 1700nm at 5nm increments) and a Liquid Crystal Tunable Filter from CRI, Inc., continuously tunable between 1000 nm and 1800 nm. Owing to noise, spectra were truncated to 1005–1645nm and smoothed using a five-point median filter prior to calibration development. Sixteen samples were detected as outliers, reducing the number of disks available for analysis to 109, which were subsequently split into calibration (85) and validation (24) sets. Successful models, based on the hyperspectral data, were obtained for disk basic density (R2c=0.81) and moisture content (R2c=0.77). The predictive ability of the calibrations was acceptable, with root mean square errors (RMSEP) of 23.6 kg m−3 for BD and 2.1% for MC. The calibrations were compared to those obtained using NIR spectra collected from the surface of the disks using a Foss XDS NIR System coupled with a Smart Probe Analyser using the same wavelength range and number of samples (each disk was represented by an average of eight spectra which had been divided into four quadrants with two spectra collected per quadrant). Probe-based calibrations were more successful; however, the hyperspectral-based calibrations were of sufficient strength to suggest that hyperspectral imaging could be used for the estimation of BD and MC of loblolly pine disks.

Near infrared calibration models for the estimation of wood density in Pinus taeda using repeated sample measurements

Near infrared (NIR) diffuse reflectance was used for the estimation of air-dry density and basic density in wood radial strip samples obtained at breast height (1.4 m) from 60 Pinus taeda trees established in three progeny tests in the south-eastern United States. NIR calibration models were fitted using raw spectra and pre-processed spectra with second derivative, multiplicative scatter correction and orthogonal signal correction. Successful calibrations were obtained for both wood properties using data collected in consecutive 10 mm sections from the samples. Data pre-processing did not result in model improvements compared to the models fitted using raw data. The effects of using repeated measures were evaluated by incorporating serial correlation into the partial least squares regression algorithm. The empirical autocorrelation of the normalised residuals showed that serial dependence among residuals was successfully removed by using an autoregressive correlation structure of second order. However, because the initial dependence among observations was not strong, the predictions were similar using the modified algorithm to those obtained with the traditional approach. These results indicate that the use of repeated measurements does not represent a serious problem for the development of NIR calibration models for the prediction of wood properties using radial samples measured in 10 mm sections and that the specification of the correlation structure may not be required when the models are used only for predictive purposes.

Determination of basic density and moisture content of merchantable loblolly pine logs by near infrared spectroscopy

The use of near infrared (NIR) diffuse reflectance spectroscopy for the estimation of basic density and moisture content of loblolly pine (Pinus taeda L.) logs was explored. A total of 219 wood disks representing the large and small ends of 146 merchantable logs 4.87 m in length, ranging in age from 13 years to 19 years, were analysed. NIR spectra were obtained from the transverse surface of the disks when the wood was green using a Foss XDS NIR System coupled with a Smart Probe Analyser. Each disk was divided into four quadrants and two spectra were collected per quadrant (one representing juvenile wood and one mature wood). NIR calibration models were fitted using pre-processed spectra with multiplicative scatter correction and the dimensionality of the models was kept constant for comparison purposes. Successful models based on an average of all spectra collected from both ends of the logs were obtained for basic density (R2c = 0.84) and moisture content (R2c = 0.85) using nine factors for both properties. The predictive ability of the calibrations was acceptable, with mean square errors of 22.8 kg m−3 for basic density and 2.1% for moisture content. It was found that the number of spectra per disk could be reduced to four readings but further reductions increased prediction errors considerably. Calibration models based only on spectra collected from one of the log ends were also examined. Using large-end diameter spectra only, the fit statistics for basic density models fell to R2 c =0.76 for (eight spectra) and R2c=0.71 (four spectra). Similarly, the fit statistics for moisture content calibrations dropped to R2c=0.76 for (eight spectra) and R2c=0.72 (four spectra). Calibrations based only on small-end diameter spectra were considerably weaker than those based on large-end diameter spectra.

Genetic variation in Pinus taeda wood properties predicted using non-destructive techniques

Abstract• BackgroundTree breeders have been reluctant to include wood traits in tree improvement programs owing to logistic difficulties and the cost associated with the assessing the traits.• MethodsWe aimed to evaluate the efficiency of two non-destructive techniques for genetic parameters estimation in three diallel test series of loblolly pine (Pinus taeda L.). The traits were measured by acoustics (velocity, stiffness) and predicted by calibration models based on near infrared (NIR) spectra (air-dry density, microfibril angle, modulus of elasticity, coarseness, wall thickness).• ResultsAcoustic and NIR-predicted traits were not correlated with diameter based on 30 full-sib family means of each diallel series. Correlations between traits were in accordance with previous published results. Additive genetic variation was considerable for all traits. Specific combining ability variances were not significant. The traits predicted by acoustic and NIR methods had high narrow-sense individual tree and family mean heritability values. Individual tree narrow sense heritability ranged from 0.14 (tracheid coarseness) to 0.92 (air-dry density). As expected, family mean heritability values of most traits exceeded 0.80.• Conclusions The high heritabilities suggest that acoustic and NIR-based methods can efficiently be used for screening loblolly pine progeny tests for surrogate wood traits. Such methods can save considerable resources in tree breeding programs that aim to improve wood quality.

Determination of specific gravity of green Pinus taeda samples by near infrared spectroscopy: comparison of pre-processing methods using multivariate figures of merit

Near infrared diffuse reflectance was used for the determination of specific gravity in green Pinus taeda L. wood samples representing simulated increment cores obtained at breast height and merchantable green logs. The effects of using three pre-processing methods (second derivative, multiplicative scatter correction, and orthogonal signal correction) to reduce the scatter observed in the original spectra were evaluated. The effectiveness of each method was assessed in terms of the average predictive ability of the models and in terms of multivariate figures of merit derived from net analyte signal theory. Specific gravity was successfully modeled using green wood samples. No differences in predictive ability among models were found, although more parsimonious regressions were obtained using transformed spectra. The incorporation of figures of merit for the characterization of calibration models proved to be a valuable tool for understanding the effects of the pre-processing alternatives on the final results.