Abstract
Previous results from this laboratory have shown that near infrared (NIR) spectroscopy, coupled with multivariate analysis, can be a powerful tool for the prediction of wood quality. While wood quality measurements are of utility, their determination can be both time and labor intensive, thus limiting their use where large sample sizes are concerned. This paper will demonstrate the applicability of the NIRVANA system to such studies, in particular the automated property assessment of increment cores. This system has been successfully applied to a set of longleaf cores obtained from a variety of sites within the Southeastern United States. Mechanical property models based on longleaf pine were applied to the NIR data, from which modulus of elasticity (MOE) and modulus of rupture (MOR) predictions were obtained for the cores. These initial results, while promising, did indicate the need for the inclusion of some of the new samples (from the various sites) into the calibration set to provide more robust models.
Parent Publication
Citation
So, Chi-Leung; Elder, Thomas; Groom, Leslie; Kush, John S.; Myszewski, Jennifer; Shupe, Todd. 2006. The application of nirvana to silvicultural studies. Gen. Tech. Rep. SRS-92. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. pp. 371-374