Near-infrared spectroscopy prediction of southern pine No. 2 lumber physical and mechanical properties

2016 ◽  
Vol 51 (2) ◽  
pp. 309-322 ◽  
Author(s):  
Joseph Dahlen ◽  
Ignacio Diaz ◽  
Laurence Schimleck ◽  
P. David Jones
Keyword(s):  
Mechanical Properties ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Physical And Mechanical Properties ◽  
Southern Pine

scholarly journals Physical and Mechanical Properties of Poplar Clones and Rapid Prediction of the Properties by Near Infrared Spectroscopy

Forests ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 206
Author(s):  
Ru Jia ◽  
Yurong Wang ◽  
Rui Wang ◽  
Xu Chen
Keyword(s):  
Mechanical Properties ◽  
Compressive Strength ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Prediction Models ◽  
Physical And Mechanical Properties ◽  
Dry Density ◽  
Smoothing Methods ◽  
Poplar Clones

In order to understand the physical and mechanical properties of poplar clones, and explore a method for their quick evaluation, the air dry density, modulus of rupture (MOR), modulus of elasticity (MOE), and compressive strength parallel to grains of three new bred poplar clones were explored and the prediction models with the highest accuracy were established by near infrared spectroscopy (NIRs). Clone 50 (Populus deltoides CL. ‘55/65′) had the highest air dry density, MOR, MOE, and compressive strength parallel to grains in the three clones. For clone 50 and 108 (Populus euramericana cv. ‘Guariento’), the mechanical properties of sapwood were better than those of heartwood, and the sapwood of clone 50 also had a better air dry density than that of heartwood. There were significant positive correlations between the air dry density and mechanical properties, with correlation coefficients above 0.68. Prediction models with better effects could be obtained by using information on the cross section for the air dry density and mechanical properties. First derivative+ Savitzky–Golay (S-G) smoothing methods were employed for the air dry density and MOR, and multiple scattering correction (MSC)+ S-G smoothing methods were used when establishing prediction models of MOE and compressive strength parallel to grains.

scholarly journals Estimation of physical and mechanical properties of agro-based particleboards by near infrared spectroscopy

2010 ◽  
Vol 69 (3) ◽  
pp. 431-442 ◽  
Author(s):  
Paulo Ricardo Gherardi Hein ◽  
Ana Carolina Maioli Campos ◽  
Rafael Farinassi Mendes ◽  
Lourival Marin Mendes ◽  
Gilles Chaix
Keyword(s):  
Mechanical Properties ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Physical And Mechanical Properties

scholarly journals Near infrared spectroscopy for assessing mechanical properties of Castanea sativa wood samples

2019 ◽  
Vol 50 (4) ◽  
pp. 191-197 ◽  
Author(s):  
Manuela Mancini ◽  
Elena Leoni ◽  
Michela Nocetti ◽  
Carlo Urbinati ◽  
Daniele Duca ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Bending Strength ◽  
Prediction Models ◽  
Castanea Sativa ◽  
Modulus Of Rupture ◽  
Current Standard ◽  
Standard Samples

Near infrared spectroscopy (NIR) is a technique widely used for the prediction of different chemical-physical features of wood. In this study, the technique was used to assess its potential to predict the mechanical characteristics of wood. Castanea sativa samples of three different European provenances were collected and laboratory tests were performed to assess the mechanical properties of wood samples. Modulus of elasticity (MOE), load-deflection curve and modulus of rupture (MOR) were calculated by using INSTRON machine with three points bending strength with elastic modulus, while density (D) was calculated according to the current standard. Samples were then analysed by means of NIR spectroscopy. The raw spectra were pre-processed and regression models were developed. Variables selection techniques were used to improve the model performance. In detail, MOE regression model returned an error of 696.01 MPa (R2=0.78). Instead, MOR and D prediction models must be further investigated on a wider number of samples considering the high variability in physical characteristics of chestnut wood. The results demonstrated the possibility to use NIR technique for the prediction of the mechanical properties of wood providing useful indications in evaluation-screening processes. Indeed, the presence of the principal wood compounds (cellulose, hemicellulose and lignin) and their influence in the characterisation of mechanical stress reactions were confirmed.

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

2004 ◽  
Vol 38 (4) ◽  
Author(s):  
StephenS. Kelley ◽  
TimothyG. Rials ◽  
Rebecca Snell ◽  
LeslieH. Groom ◽  
Amie Sluiter
Keyword(s):  
Mechanical Properties ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Solid Wood

The Main Mechanical Properties of New Chinese Fir Clones and Their Rapid Prediction by Near-infrared Spectroscopy

2021 ◽  
Author(s):  
Ru Jia ◽  
Yurong Wang ◽  
Rui Wang ◽  
Haiyan Sun ◽  
Shengquan Liu ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Prediction Models ◽  
Wood Properties ◽  
Chinese Fir ◽  
Modulus Of Rupture ◽  
Tangential Section ◽  
Smoothing Methods

Due to rapidity and accuracy, near-infrared spectroscopy (NIRs) is powerful tool to establish appropriate prediction models with an innovative method for the evaluation of wood properties. In order to reveal mechanical qualities of clonal Chinese fir woods and determine sound prediction models of mechanical properties, four main mechanical properties of six Chinese fir clones (Yang 020, Yang 061, Kaihua 3, Kaihua 13, Daba 8, Kailin 24) were evaluated by NIRs. As a result, Kaihua 13, Kailin 24 and Yang 020 showed good mechanical properties. To estimate mechanical properties with NIRs, different methods should be adopted for different properties. The average spectra of radial section and tangential section combined with multiple scattering correction (MSC) and Savitzky-Golay (S-G) smoothing methods were used to predict the modulus of rupture (MOR) and modulus of elasticity (MOE). By adopting spectra of cross section and taking MSC and S-G smoothing methods for pretreatment, the models of compressive strength parallel to grain could deliver the best results. For wood hardness, the models established with average spectra of three sections and first derivative method were preferred. The correlation coefficients of the prediction models were between 0.84 and 0.90, and those of calibration models were between 0.75 and 0.96.

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