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.

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.

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 the mechanical properties of wood from Eucalyptus urophylla using near infrared spectroscopy

CERNE ◽  
2010 ◽  
Vol 16 (3) ◽  
pp. 291-298 ◽  
Author(s):  
Carlos Rogério Andrade ◽  
Paulo Fernando Trugilho ◽  
Alfredo Napoli ◽  
Renato da Silva Vieira ◽  
José Tarcísio Lima ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Diffuse Reflectance ◽  
Near Infrared ◽  
Solid Wood ◽  
Modulus Of Rupture ◽  
Limiting Factor ◽  
Variation Pattern ◽  
Nondestructive Technique

Mechanical properties studies of wood usually involve destructive wood assessments, with time-consuming tests that use large amounts of resource (wood). Although this is not a limiting factor, it could be attenuated by the use of a nondestructive technique known as near infrared spectroscopy (NIRS). This technique has been applied to evaluate compounds containing C-H, N-H, S-H or O-H bonds, and involves quick analyses and can be applied to process control tasks. The objective of this work is to use the NIRS technique to obtain calibrations for mechanical properties of Eucalyptus sp. wood. A natural E. urophylla hybrid at age 7 was used as obtained from V&M Florestal crops. Spectra were measured directly in solid wood (radial, tangential and transverse faces) and in ground wood, in diffuse reflectance mode, using a Bruker spectrometer in the 800 to 1,500 nm range. The NIRS technique proved suitable to estimate modulus of elasticity in solid wood, with values r=0.91 and RPD=2.6, and in ground wood, with values r=0.87 and RPD=2.0. Modulus of rupture and compressive strength presented r values below 0.9. First and second derivative pretreatments provided a slight increase in correlation values for the properties in question. Calibrations for different plank faces did not present a defined variation pattern. Solid wood and ground wood presented similar correlation values for all properties.

scholarly journals Rancidity Estimation of Perilla Seed Oil by Using Near-Infrared Spectroscopy and Multivariate Analysis Techniques

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Suk-Ju Hong ◽  
Shin-Joung Rho ◽  
Ah-Yeong Lee ◽  
Heesoo Park ◽  
Jinshi Cui ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Seed Oil ◽  
Prediction Models ◽  
Oxidation Process ◽  
Analysis Techniques ◽  
Peroxide Values ◽  
Perilla Seed

Near-infrared spectroscopy and multivariate analysis techniques were employed to nondestructively evaluate the rancidity of perilla seed oil by developing prediction models for the acid and peroxide values. The acid, peroxide value, and transmittance spectra of perilla seed oil stored in two different environments for 96 and 144 h were obtained and used to develop prediction models for different storage conditions and time periods. Preprocessing methods were applied to the transmittance spectra of perilla seed oil, and multivariate analysis techniques, such as principal component regression (PCR), partial least squares regression (PLSR), and artificial neural network (ANN) modeling, were employed to develop the models. Titration analysis shows that the free fatty acids in an oil oxidation process were more affected by relative humidity than temperature, whereas peroxides in an oil oxidation process were more significantly affected by temperature than relative humidity for the two different environments in this study. Also, the prediction results of ANN models for both acid and peroxide values were the highest among the developed models. These results suggest that the proposed near-infrared spectroscopy technique with multivariate analysis can be used for the nondestructive evaluation of the rancidity of perilla seed oil, especially the acid and peroxide values.

scholarly journals Near-infrared spectroscopy used to predict soybean seed germination and vigour

2018 ◽  
Vol 28 (3) ◽  
pp. 245-252 ◽  
Author(s):  
Maythem Al-Amery ◽  
Robert L. Geneve ◽  
Mauricio F. Sanches ◽  
Paul R. Armstrong ◽  
Elizabeth B. Maghirang ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Seed Germination ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Prediction Models ◽  
Soybean Seed ◽  
Seed Vigour ◽  
Near Infrared Spectra ◽  
High Germination ◽  
Qualitative Models

AbstractRapid, non-destructive methods for measuring seed germination and vigour are valuable. Standard germination and seed vigour were determined using 81 soybean seed lots. From these data, seed lots were separated into high and low germinating seed lots as well as high, medium and low vigour seed lots. Near-infrared spectra (950–1650 nm) were collected for training and validation samples for each seed category and used to create partial least squares (PLS) prediction models. For both germination and vigour, qualitative models provided better discrimination of high and low performing seed lots compared with quantitative models. The qualitative germination prediction models correctly identified low and high germination seed lots with an accuracy between 85.7 and 89.7%. For seed vigour, qualitative predictions for the 3-category (low, medium and high vigour) models could not adequately separate high and medium vigour seeds. However, the 2-category (low, medium plus high vigour) prediction models could correctly identify low vigour seed lots between 80 and 100% and the medium plus high vigour seed lots between 96.3 and 96.6%. To our knowledge, the current study is the first to provide near-infrared spectroscopy (NIRS)-based predictive models using agronomically meaningful cut-offs for standard germination and vigour on a commercial scale using over 80 seed lots.

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.

Near infrared spectroscopy to evaluate change in color and chemical composition in heat-treated bamboo

2020 ◽  
Vol 28 (4) ◽  
pp. 214-223
Author(s):  
Junqian Mo ◽  
Wenbo Zhang ◽  
Xiaohui Fu ◽  
Wei Lu
Keyword(s):  
Infrared Spectroscopy ◽  
Chemical Composition ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Prediction Models ◽  
Chemical Components ◽  
Outer Side ◽  
Heating Process ◽  
Least Squares Regression ◽  
Heat Treated

This study investigated the feasibility of using near infrared spectroscopy technology to predict color and chemical composition in the heat-treated bamboo processing industry. The quantitative presentations of the changes in the chemical components were discussed using the difference spectra method of the 2nd derivative NIR spectra of the heat-treated bamboo samples. Then, the relationships between the color changes of the heat-treated bamboo and its near infrared spectra were constructed using the changes in the chemical components of the bamboo samples during the heating process. The prediction of color and chemical composition of both the outer and inner sides of the heat-treated bamboo surface were constructed using partial least squares regression method combined with a leave-one-out cross-validation process. Then, the results were validated by independent sample sets. The proposed prediction models were found to produce high r2P (above 0.93), RPD (above 3.13), and low RMSEP for both the outer and inner sides of the heat-treated bamboo samples. These studies’ results confirmed that the proposed models, especially outer side models, were perfectly suitable for the in-process inspections of the color and chemical content changes of heat-treated bamboo.

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