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Success in Using NIR Spectroscopy to Estimate Wood Properties of Pinus Taeda Radial Strips Not Due to Autocorrelation

The Southern United States is one of the largest timber producing regions in the world, producing 60% of the wood used nationally and 15% of the wood consumed globally. It is expected that the Southern United States will remain a dominant wood producing region as private landowners expand the area of pine plantations into the future, with the plantation estate expected to be approximately 54 million acres by 2040. The major plantation species is loblolly pine (Pinus taeda L.) which has been favoured over other Pinus species native to the Southern United States because of its ability to grow well on a wide variety of sites. Loblolly pine has been subjected to genetic improvement that has greatly improved its growth and yield. It is expected that the inclusion of quality traits such as stem straightness and wood quality in loblolly pine breeding programmes will greatly increase genetic gains and the value of the trees. However, inclusion of basic wood properties in tree improvement programmes requires the development of cost-effective, rapid and reliable methods for screening progeny tests on a large scale. Near infrared (NIR) spectroscopy provides a rapid method for the nondestructive determination of many chemical and physical–mechanical properties of wood. In particular, we have used NIR spectroscopy to estimate the wood properties of increment cores, which have been removed from standing trees, facilitating non-destructive sampling. In these studies, NIR spectra have been collected in 10 mm sections from the radial longitudinal face of wooden strips or increment cores and calibrations for a range of wood properties obtained. Much of our work on increment cores has been made possible by the development of the SilviScan instruments which utilise a combination of scanning X-ray microdensitometry, X-ray diffractometry and image analysis to measure a range of wood properties including density, microfibril angle (MFA, the angle that the helical windings of cellulose chains, within the fibre wall, make with the fibre axis), stiffness (determined using SilviScan diffractometric data and measured density) and a range of tracheid morphological characteristics including coarseness, perimeter, radial diameter, tangential diameter, specific surface and wall thickness. A great challenge in all spectroscopic studies is obtaining accurate calibration data and a sufficiently large sample set to describe the variation that exists, and the SilviScan instruments have performed admirably in this regard making the development of Georgia-wide wood property calibrations possible. Almost all properties (apart from MFA and stiffness) are measured at 50 μm resolution providing an abundance of calibration data for relatively low cost. Strong relationships have consistently been found between NIR spectra and SilviScan measurements of air-dry density, MFA, stiffness and tracheid coarseness and wall thickness for loblolly pine. As the NIR spectra were collected from adjacent sections of the same wood core, the success of these calibrations could be explained by an autocorrelation that exists in wood cores. The autocorrelation exits partly because the cambial initial of each radial file is influenced by its previous growth history, and also because maturing wood cells experience common environmental conditions. Consequently we sought to investigate if it is possible to obtain strong calibration statistics for SilviScan measured wood properties using NIR spectra collected from independent samples. The samples utilised for this study were from earlier research that aimed to develop Georgia-wide calibrations for SilviScan measured wood properties. A detailed description of the origin of the samples and the measurement of wood properties by SilviScan are provided elsewhere. NIR diffuse reflectance spectra were obtained in consecutive 10 mm sections from the radial longitudinal face of each P. taeda strip using a NIRSystems Model 5000 scanning spectrophotometer (Silver Spring, Maryland, USA). For each strip the first spectrum was collected from the bark end. Fifty scans were accumulated for each 10-mm section and then averaged to give a single spectrum. All measurements were made in a conditioned atmosphere maintained at 40% RH and 20°C, this was done to ensure that the samples were tested under the same conditions as when they were subject to SilviScan analysis and to ensure that the dimensions of the samples had not changed. The number of spectra originally collected from the calibration set samples was 729, while 225 spectra were collected from the samples forming the prediction set. For each core in the calibration (89) and prediction sets (30) a single average NIR spectrum representing a 5 mm × 10 mm section of wood was selected. Spectra were selected to equally represent juvenile wood (close to pith), transition wood (zone between juvenile and mature wood) and mature wood (close to bark). Within each of these zones spectra were selected at random. Selection of a single spectrum per core ensured that samples used in the calibration and prediction sets were as unrelated as possible, in previous studies adjacent spectra were used for calibration development. Wood property calibrations were developed using the Unscrambler (version 8.0) software package (Camo AS, Norway). Partial Least Squares (PLS) regression with four cross-validation segments and a maximum of 10 factors was used. The Unscrambler software recommended the final number of factors to use for each calibration. Wood property calibrations were developed using NIR spectra collected from the selected wood samples and the corresponding SilviScan measured wood properties. The calibrations for MFA and stiffness provided the strongest calibration and prediction statistics. The calibration for stiffness is shown in Figure 1. Calibrations for air-dry density, tracheid coarseness, specific surface Success in using NIR spectroscopy to estimate wood properties of Pinus taeda radial strips not due to autocorrelation