Use of near infrared spectroscopy to measure the chemical and mechanical properties of solid wood

By S. Kelley, T. Rials, R. Snell, L. Groom, Amie D. Sluiter. Wood Science and Technology, 2004

246 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Building and Construction, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/fe3e66018d768e0b7b30319caf8a78077350a179

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. Satoru Tsuchikawa
2. T. Rials
3. Helena Pereira
4. A. Lourenço

In Building and Construction

1. Satoru Tsuchikawa
2. J. Sugiyama
3. W. T. Tze
4. S. Kelley
5. Siqun Wang
6. C. Raymond
7. T. Rials
8. G. Pharr

In Nature and Landscape Conservation

1. Satoru Tsuchikawa

Citations in the corpus

• Qualitative and quantitative analysis of lignocellulosic biomass using infrared techniques: A mini-review (2013, methodology): “Other physical properties, such as mechanical properties, also could be investigated via NIRS, and a reduced spectral range (650–1150 nm) was used successfully for prediction [75].”
• Nanoindentation of wood cell walls: Continuous stiffness and hardness measurements (2007, background): “This tree was part of a study of the relationship between the Near Infrared spectra and the MFA (from Xray diffraction measurements), moduli of elasticity (MOE; from three-point bending experiments), and moduli of rupture (MOR; also from three-point bending) of wood [11].”
• Predicting Extractives, Lignin, and Cellulose Contents Using Near Infrared Spectroscopy on Solid Wood in Eucalyptus globulus (2006, methodology): “Kelley et al.([14]) developed good calibrations with high correlation coefficients for both lignin (0.”
• Identification of Pinus species related to historic architecture in Korea using NIR chemometric approaches (2016, background): “In previous studies, many researchers reported that this represents the most efficient classification performance in some specific spectral regions [12, 21, 23, 24], but the present study showed a clear classification in the spectral region of 8000–4000 cm.”
• A Review of Recent Near Infrared Research for Wood and Paper (2007, background): “(58) pointed out that the mechanical properties of wood could be predicted using a reduced spectral range (650 –1150 nm) that should allow for field measurements of these properties using handheld NIR spectrometers.”