Resonance and near Infrared Spectroscopy for Evaluating Dynamic Wood Properties

2010 ◽  
Vol 18 (6) ◽  
pp. 443-454 ◽  
Author(s):  
Paulo Ricardo Gherardi Hein ◽  
Loïc Brancheriau ◽  
Paulo Fernando Trugilho ◽  
José Tarcísio Lima ◽  
Gilles Chaix
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Wood Properties

Near Infrared Spectroscopy: A Tool for the Rapid Estimation of Wood Properties

2004 ◽  
pp. 8-17
Author(s):  
Laurence Schimleck ◽  
Robert Evans ◽  
David Jones ◽  
Richard Daniels ◽  
Gary Peter ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Wood Properties ◽  
Rapid Estimation

scholarly journals OTIMIZAÇÃO DE CALIBRAÇÕES BASEADAS EM ESPECTROSCOPIA NO INFRAVERMELHO PRÓXIMO PARA ESTIMATIVA DE PROPRIEDADES DA MADEIRA DE Eucalyptus

FLORESTA ◽  
2010 ◽  
Vol 40 (3) ◽  
Author(s):  
Paulo Ricardo Gherardi Hein ◽  
José Tarcísio Lima ◽  
Gilles Chaix Gilles Chaix
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Laboratory Data ◽  
Wood Properties ◽  
Coefficient Of Determination ◽  
Mathematical Treatment ◽  
Least Squares Regression ◽  
Eucalyptus Wood ◽  
Prediction Density

A espectroscopia no infravermelho próximo (NIRS) é uma técnica não-destrutiva, rápida e utilizada para avaliação, caracterização e classificação de materiais, sobretudo de origem biológica. A obtenção de informações contida nos espectros NIR é complexa e requer a utilização de métodos quimiométricos. Assim, por meio de regressão multivariada, os espectros de absorbância podem ser associados às propriedades da madeira, tornando possível a sua predição em amostras desconhecidas. Existem algumas ferramentas quimiométricas que melhoram o ajuste dos modelos preditivos. Assim, o objetivo deste trabalho foi simular regressões dos mínimos quadrados parciais baseados nas informações espectrais e de laboratório e estudar a influência da aplicação de tratamentos matemáticos, do descarte de amostras anômalas e da seleção de comprimentos de onda no ajuste dos modelos para estimativa da densidade básica e do módulo de elasticidade em ensaio de compressão paralela às fibras da madeira de Eucalyptus. A aplicação da primeira e segunda derivada nos espectros, o descarte de amostras anômalas e a seleção de algumas das variáveis espectrais melhorou significativamente o ajuste do modelo, reduzindo o erro padrão e aumentando o coeficiente de determinação e a relação de desempenho do desvio.Palavras-chave:  Espectroscopia no infravermelho próximo; predição; densidade básica; MOE; madeira; Eucalyptus. AbstractOptimization of calibrations based on near infrared spectroscopy for estimation of Eucalyptus wood properties. Near infrared spectroscopy (NIRS) is a non-destructive technique used for rapid evaluation, characterization and classification of biological materials. The extraction of the information contained in the NIR spectrum is complex and requires the use of chemo metric methods. Thus, by means of multivariate regression, the absorbance spectra are correlated to wood properties, making possible the prediction in unknown samples. There are some chemo metric tools that can improve the adjustment of the predictive models. The aim of this work was to simulate partial least squares regression based on NIR spectra and laboratory data and to study the influence of the application of mathematical treatment, the removal of outliers and the wavelengths selection in the adjustment of models to estimate the density and modulus of elasticity in Eucalyptus wood. The use of the first and second derivative spectra, the disposal of outliers, and the variables selection improved significantly the model fit, reducing the standard error and increasing the coefficient of determination and the ratio of performance to deviation.Keywords: Near infrared; spectroscopy; prediction; density; MOE; wood; Eucalyptus.

Success in Using near Infrared Spectroscopy to Estimate Wood Properties of Pinus Taeda Radial Strips Not Due to Autocorrelation

2005 ◽  
Vol 13 (1) ◽  
pp. 47-51 ◽  
Author(s):  
Laurence R. Schimleck ◽  
P. David Jones ◽  
Gary F. Peter ◽  
Richard F. Daniels ◽  
Alexander Clark
Keyword(s):  
Infrared Spectroscopy ◽  
Pinus Taeda ◽  
Rapid Method ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Wood Properties

Near infrared (NIR) spectroscopy provides a rapid method for estimating several important wood properties of 10 mm sections of radial wooden strips. Successful calibrations have been obtained with NIR spectra collected from 3 to 16 consecutive 10 mm sections of the same wood core. The success of these calibrations might be due to an autocorrelation that exists between the adjacent sections of a core. In this study, we compared calibrations with spectra collected from consecutive 10 mm sections to calibrations obtained with spectra collected from unrelated 10 mm sections. Very similar calibration statistics were obtained with both sets of spectra, demonstrating that existing calibration success is not due to an autocorrelation.

Estimation of Crystallinity of Poplar Cellulose Using Near Infrared Spectroscopy

2012 ◽  
Vol 622-623 ◽  
pp. 1532-1535
Author(s):  
Zhen Bo Liu ◽  
Wen Yang Kong ◽  
Yi Xing Liu ◽  
Zhan Chuan Xue ◽  
Xiao Yan Shen ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Partial Least Squares Regression ◽  
Near Infrared ◽  
Correlation Coefficients ◽  
Nir Spectroscopy ◽  
Wood Properties ◽  
Least Squares Regression ◽  
Cellulose Crystallinity ◽  
Test Models

Many studies have successfully applied near infrared (NIR) spectroscopy to estimate important wood properties. In this paper, the use of NIR (350–2500 nm) spectroscopy to predict the cellulose crystallinity of Poplar (Populus nigra var.) was investigated. The calibration and test models were constructed using partial least squares regression (PLS). The correlations were significant both the calibration and the test samples using six factors, and the correlation coefficients (R2) were 0.9367, 0.9472 respectively. The results suggest that NIR spectroscope may provide a useful tool for rapid and accurate prediction of the cellulose crystallinity of Poplar.

Near-infrared spectroscopy and hyperspectral imaging can aid in the prediction and mapping of polyploid acacia hybrid wood properties in tree improvement programs

Holzforschung ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Dang Duc Viet ◽  
Te Ma ◽  
Tetsuya Inagaki ◽  
Nguyen Tu Kim ◽  
Satoru Tsuchikawa
Keyword(s):  
Infrared Spectroscopy ◽  
Hyperspectral Imaging ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Wood Property ◽  
Wood Properties ◽  
Tree Improvement ◽  
Partial Least Square ◽  
Important Species ◽  
Improvement Programs

Abstract Acacia, including Acacia hybrids, are some of the most important species grown as part of the Vietnamese wood industry. Rapid methods to identify the variations in the wood properties of Acacia hybrids however, are a currently lacking and creating limits for their breeding programs. In this study, nine Acacia hybrid clones, including those that were diploid, triploid, and tetraploid were evaluated using near-infrared spectroscopy (NIR) and hyperspectral imaging (HSI). The standard normal variate (SNV) and second derivative (SP2D) were applied to compare the performances of NIR and HSI using partial least square regression. The HSI images were acquired at wavelengths from 1033 to 2230 nm and the SNV and SP2D described the variations in the wood properties. The NIR predicted the wood physical properties better than HSI, while they provided similar predictions for the mechanical properties. The mapping results showed low densities around the pith area and high densities near the bark. They also revealed that the air-dry moisture content changed at different positions within a disk and was dependent on its position within the tree. Overall, NIR and HSI were found to be potential wood property prediction tools, suitable for use in tree improvement programs.

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.

Non-Destructive Estimation of Pernambuco (Caesalpinia Echinata) Clear Wood Properties Using near Infrared Spectroscopy

2011 ◽  
Vol 19 (5) ◽  
pp. 411-419 ◽  
Author(s):  
Laurence R. Schimleck ◽  
Jorge Luis Monteiro de Matos ◽  
José Tarcisio da Silva Oliveira ◽  
Graciela Inez Bolzon Muniz
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Wood Properties ◽  
Clear Wood ◽  
Caesalpinia Echinata ◽  
Non Destructive
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