Abstract
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.
Similar content being viewed by others
References
Akima H, Gebhardt A (2016) akima: Interpolation of irregularly and regularly spaced data. R package version 0.6-2. https://CRAN.R-project.org/package=akima
Burdon RD, Kibblewhite RP, Walker JCF, Megraw RA, Evans R, Cown DJ (2004) Juvenile versus mature wood: a new concept, orthogonal to corewood versus outerwood, with special reference to Pinus radiata and P. taeda. For Sci 50:399–415
Dahlen J, Auty D, Eberhardt TL (2018) Models for predicting specific gravity and ring width for loblolly pine from intensively managed plantations, and implications for wood utilization. Forests 9:292
Dahlen J, Nabavi M, Auty D, Schimleck LR, Eberhardt TL (2020) Models for predicting the within-tree and regional variation of tracheid length and width for loblolly pine. Forestry (in press)
Defo M, Goodison A, Uy N (2009) A method to map within-tree distribution of fibre properties using SilviScan-3 data. For Chron 85:409–414
Evans R (1994) Rapid measurement of the transverse dimensions of tracheids in radial wood sections from Pinus radiata. Holzforschung 48:168–172
Evans R (1999) A variance approach to the X-ray diffractometric estimation of microfibril angle in wood. Appita J 52(283–289):294
Evans R (2006) Wood stiffness by X-ray diffractometry. In: Stokke DD, Groom LH (eds) Characterization of the cellulosic cell wall. Blackwell Publishing, Ames, pp 138–146
Evans R, Downes G, Menz D, Stringer S (1995) Rapid measurement of variation in tracheid transverse dimensions in a radiata pine tree. Appita J 48:134–138
Fernandes A, Lousada J, Morais J, Xavier J, Pereira J, Melo-Pinto P (2013) Measurement of intra-ring wood density by means of imaging VIS/NIR spectroscopy (hyperspectral imaging). Holzforschung 67:59–65
Ikonen VP, Peltola H, Wilhelmsson L, Kilpeläinen A, Väisänen H, Nuutinen T, Kellomäki S (2008) Modelling the distribution of wood properties along the stems of Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.) as affected by silvicultural management. For Ecol Manag 256:1356–1371
Jones PD, Schimleck LR, Peter GF, Daniels RF, Clark A (2005) Non-destructive estimation of Pinus taeda L. tracheid morphological characteristics for samples from a wide range of sites in Georgia. Wood Sci Technol 39:529–545
Jordan L, Clark A, Schimleck LR, Hall DB, Daniels RF (2008) Regional variation in wood specific gravity of planted loblolly pine in the United States. Can J For Res 38:698–710
Kellogg RM, Sastry CBR, Wellwood RW (1975) Relationships between cell-wall composition and cell-wall density. Wood Fiber Sci 7(3):170–177
Li XG, Evans R, Gapare W, Yang X, Wu HX (2014) Characterizing compression wood formed in radiata pine branches. IAWA J 35:385–394
Lundqvist SO, Ekenstedt F, Hedenberg Ö, Twaddle A (2005) Wood and fibre properties of loblolly pine in southeast USA variations and prediction models. In: IUFRO fifth workshop wood quality modelling: 22–27 Nov 2005, Auckland, New Zealand
Ma T, Inagaki T, Tsuchikawa S (2017) Calibration of SilviScan data of Cryptomeria japonica wood concerning density and microfibril angles with NIR hyperspectral imaging with high spatial resolution. Holzforschung 71:341–347
Mäkinen H, Jaakkola T, Piispanen R, Saranpää P (2007) Predicting wood and tracheid properties of Norway spruce. For Ecol Manag 241:175–188
Megraw R (1985) Wood quality factors in loblolly pine. TAPPI Press, Atlanta
Mitchell MD, Denne MP (1997) Variation in density of Picea sitchensis in relation to within-tree trends in tracheid diameter and wall thickness. Forestry 70:47–60
Mora CR, Schimleck LR (2009) Determination of within-tree variation of Pinus taeda wood properties by near infrared spectroscopy. Part 2: whole-tree wood property maps. Appita J 62:232–238
Nabavi M, Dahlen J, Schimleck L, Eberhardt TL, Montes C (2018) Regional calibration models for predicting loblolly pine tracheid properties using near-infrares spectroscopy. Wood Sci Technol 52:445–463
Nychka D, Furrer R, Paige J, Sain S (2015) fields: tools for spatial data. R package version 8.10. http://CRAN.R-project.org/package=fields
R Core Team (2018) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Available from http://www.R-project.org/
RStudio (2018) RStudio: integrated development environment for R. RStudio, Boston, Mass. Available from https://www.rstudio.com/
Sarkar D (2008) Lattice: multivariate data visualization with R. Springer, New York. ISBN 978-0-387-75968-5
Schimleck LR, Evans R (2004) Estimation of Pinus radiata D. Don tracheid morphological characteristics by near infrared spectroscopy. Holzforschung 58:66–73
Schimleck LR, Stürzenbecher R, Mora C, Jones PD, Daniels RF (2005) Comparison of Pinus taeda L. wood property calibrations based on NIR spectra from the radial-longitudinal and radial-transverse faces of wooden strips. Holzforschung 59:214–218
Schimleck LR, Mora CR, Jordan L, White DE, Courchene CE, Purnell RC (2009) Determination of within-tree variation of Pinus taeda wood properties by near infrared spectroscopy. Part 1: development of multiple height calibrations. Appita J 62:130–136
Schimleck L, Antony F, Mora C, Dahlen J (2018) Comparison of whole-tree wood property maps for 13- and 22-year-old loblolly pine. Forests 9:287
Wickham H, Francois R (2016) dplyr: a grammar of data manipulation. R package version 0.4.3. https://CRAN.R-project.org/package=dplyr
Williams PC, Sobering DC (1993) Comparison of commercial near infrared transmittance and reflectance instruments for analysis of whole grains and seed. J Near Infrared Spec 1:8
Acknowledgements
Support for this work was provided by the Georgia TIP3 program and is gratefully acknowledged. The authors thank the UGA Wood Quality Consortium for collecting the P. taeda samples and for sample preparation.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Schimleck, L.R., Antony, F., Mora, C. et al. Whole-tree tracheid property maps for loblolly pine at different ages. Wood Sci Technol 54, 683–701 (2020). https://doi.org/10.1007/s00226-020-01180-7
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00226-020-01180-7