Determination of Basic Density and Moisture Content of Merchantable Loblolly Pine Logs by near Infrared Spectroscopy

2011 ◽  
Vol 19 (5) ◽  
pp. 391-399 ◽  
Author(s):  
Christian R. Mora ◽  
Laurence R. Schimleck ◽  
Alexander Clark ◽  
Richard F. Daniels

2011 ◽  
Vol 19 (5) ◽  
pp. 401-409 ◽  
Author(s):  
Christian R. Mora ◽  
Laurence R. Schimleck ◽  
Seung-Chul Yoon ◽  
Chi N. Thai


2011 ◽  
Vol 65 (9) ◽  
pp. 1056-1061 ◽  
Author(s):  
Sharon L. P. Sakirkin ◽  
Cristine L. S. Morgan ◽  
James C. MacDonald ◽  
Brent W. Auvermann




CERNE ◽  
2013 ◽  
Vol 19 (4) ◽  
pp. 647-652 ◽  
Author(s):  
Silviana Rosso ◽  
Graciela Ines Bolzon de Muniz ◽  
Jorge Luis Monteiro de Matos ◽  
Clóvis Roberto Haselein ◽  
Paulo Ricardo Gherardi Hein ◽  
...  

This study aimed to analyze use of near infrared spectroscopy (NIRS) to estimate wood density of Eucalyptus grandis. For that, 66 27-year-old trees were logged and central planks were removed from each log. Test pieces 2.5 x 2.5 x 5.0 cm in size were removed from the base of each plank, in the pith-bark direction, and subjected to determination of bulk and basic density at 12% moisture (dry basis), followed by spectral readings in the radial, tangential and transverse directions using a Bruker Tensor 37 infrared spectrophotometer. The calibration to estimate wood density was developed based on the matrix of spectra obtained from the radial face, containing 216 samples. The partial least squares regression to estimate bulk wood density of Eucalyptus grandis provided a coefficient of determination of validation of 0.74 and a ratio performance deviation of 2.29. Statistics relating to the predictive models had adequate magnitudes for estimating wood density from unknown samples, indicating that the above technique has potential for use in replacement of conventional testing.





2011 ◽  
Vol 19 (3) ◽  
pp. 191-198 ◽  
Author(s):  
Cédric Camps ◽  
Marine Toussirot ◽  
Mélanie Quennoz ◽  
Xavier Simonnet


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