Estimating mechanical properties and specific gravity for five-year-old Eucalyptus tereticornis having broad moisture content range by NIR spectroscopy

Holzforschung ◽  
2011 ◽  
Vol 65 (5) ◽  
Author(s):  
Vimal Kothiyal ◽  
Aasheesh Raturi
Keyword(s):  
Specific Gravity ◽  
Moisture Content ◽  
Near Infrared ◽  
Wood Property ◽  
Nir Spectroscopy ◽  
Modulus Of Rupture ◽  
Bending Test ◽  
Coefficient Of Determination ◽  
Eucalyptus Tereticornis ◽  
Least Squares Regression

Abstract Near infrared spectroscopy coupled with multivariate data analysis has been used to predict the specific gravity, modulus of rupture, modulus of elasticity, and fiber stress at elastic limit in bending tests on radial and tangential strip wood samples obtained from five-year-old Eucalyptus tereticornis. Moisture content of samples was 6–21% for bending test and 7–16% for specific gravity. Partial least squares regression calibrations were developed for each wood property. Calibrations had good relationships between values measured in laboratory and NIR predicted values obtained from small clear samples. The coefficient of determination (R2) for calibration ranged from 0.76 to 0.83 and for prediction (Rp 2) it was between 0.58 and 0.77. Both radial and tangential faces are equally suited for calibration (for radial face R2 was 0.77–0.83 and for tangential it was 0.76–0.83). Standard errors of predictions were slightly higher compared to standard error of calibration.

Rapid analysis of chemical composition in intact and milled rice cookies using near infrared spectroscopy

2017 ◽  
Vol 25 (5) ◽  
pp. 330-337 ◽  
Author(s):  
Latthika Wimonsiri ◽  
Pitiporn Ritthiruangdej ◽  
Sumaporn Kasemsumran ◽  
Nantawan Therdthai ◽  
Wasaporn Chanput ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Near Infrared ◽  
Wheat Gluten ◽  
Nir Spectroscopy ◽  
Rice Flour ◽  
Coefficient Of Determination ◽  
Gluten Free ◽  
Least Squares Regression ◽  
Milled Rice ◽  
Control Programs

This study has investigated the potential of near infrared (NIR) spectroscopy to predict the content of moisture, protein, fat and gluten in rice cookies in different sample forms (intact and milled samples). Gluten-free (n = 48) and gluten (n = 48) rice cookies were formulated with brown and white rice flours in which butter was substituted with fat replacer at 0, 15, 30 and 45%. With regard to gluten cookies, rice flour was substituted with wheat gluten at 1, 3 and 5%. Partial least squares regression modeling produced models with coefficient of determination (R2) values greater than 0.88 from NIR spectra of intact samples and greater than 0.92 for milled samples. These models were able to predict the four components with a ratio of prediction to deviation greater than 2.7 and 3.8 in intact and milled samples, respectively. The results suggest that the models obtained from the intact samples can be successfully applied for chemical composition of rice cookies and are reliable enough use for potential quality control programs.

Analytical tools to predict changes in properties of oriented strandboard exposed to the fungus Postia placenta

Holzforschung ◽  
2006 ◽  
Vol 60 (3) ◽  
pp. 332-338 ◽  
Author(s):  
Scott M. Kent ◽  
Robert J. Leichti ◽  
Jeffrey J. Morrell ◽  
David V. Rosowsky ◽  
Stephen S. Kelley
Keyword(s):  
Weight Loss ◽  
Shear Strength ◽  
Specific Gravity ◽  
Near Infrared ◽  
Oriented Strand Board ◽  
Nir Spectroscopy ◽  
Coefficient Of Determination ◽  
Multivariate Statistical ◽  
X Ray ◽  
Bearing Strength

Abstract Weight loss, specific gravity and strength are traditional measures of how wood changes after fungal exposure. This study investigated the effects of fungal decay on properties of oriented strand board (OSB) made of aspen including weight loss, specific gravity, dowel-bearing strength, shear strength, and alkali solubility. Shear strength and alkali solubility were strongly correlated with specific gravity. In addition, X-ray densitometry and near-infrared (NIR) spectroscopy were used to study the decay process. X-Ray densitometry was used to assess localized density around the dowel-bearing embedment zone of a nail. A statistical model using the specific gravity directly under the nail from dowel-bearing strength tests as the explanatory variable had a higher coefficient of determination than models using the gross specific gravity of the sample. Predictive models using NIR spectro-scopy, in combination with multivariate statistical methods, showed promise as predictors of weight loss, shear strength, dowel-bearing strength, and solubility.

scholarly journals Application of visible-near infrared spectroscopy to evaluate the quality of button mushrooms

2018 ◽  
Vol 27 (1) ◽  
pp. 38-45 ◽  
Author(s):  
Valentina Giovenzana ◽  
Alessio Tugnolo ◽  
Andrea Casson ◽  
Riccardo Guidetti ◽  
Roberto Beghi
Keyword(s):  
Moisture Content ◽  
Near Infrared ◽  
Distribution Channel ◽  
Nir Spectroscopy ◽  
Quality Standard ◽  
Quality Parameters ◽  
Soluble Solids ◽  
Least Squares Regression ◽  
Physical Damage ◽  
Reference Quality

The Agaricus bisporus mushroom is one of the most cultivated and consumed mushrooms in the world, thanks to its delicacy, nutritional value and flavour. The quality evaluation of the A. bisporus during the harvest is generally established by a visual check by trained operators. This method complies with the request of the Distribution Channel (DC) to retailers and guarantees very low physical damage to the mushrooms; nevertheless, it is subjective and it does not guarantee the highest quality standard for the consumer. The aim of this study was to test the use of visible/near infrared (vis/NIR) reflectance spectroscopy (400–1000 nm) to objectively evaluate the quality parameters of A. bisporus mushrooms. A total of 167 samples of A. bisporus mushrooms were harvested according to the main DC purchasing standards. The vis/NIR analyses were performed the day of sampling just before the physico-chemical analyses (sizes, firmness, soluble solids content and moisture content) used as reference quality parameters. The vis/NIR spectra were correlated to reference measures in order to build predictive models using the partial least squares regression method. Calculated models gave positive results regarding the prediction of the moisture content (r2(pred) = 0.78) and firmness (r2(pred) = 0.78). Results of this explorative study could be considered encouraging and demonstrate the applicability of vis/NIR spectroscopy on A. bisporus as a rapid technique (i) to monitor the productive process directly at the company, (ii) to standardize the harvest moment, and (iii) to support DC’s buyers’ choices, nowadays exclusively based on product external characteristics.

A survey of moisture distribution in two sets of Scots pine logs by NIR-spectroscopy

Holzforschung ◽  
2008 ◽  
Vol 62 (4) ◽  
Author(s):  
Kyösti Karttunen ◽  
Asta Leinonen ◽  
Matti-Paavo Sarén
Keyword(s):  
Moisture Content ◽  
Scots Pine ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Optical Probe ◽  
Moisture Distribution ◽  
Least Squares Regression ◽  
Step Procedure ◽  
Surface Drying ◽  
Automated Scanning

Abstract Moisture content distributions of Scots pine logs in the green state were measured by a novel multi-step procedure. After sample preparation, the transverse sections of the wood surfaces were scanned by an automated scanning device with a fiber optical probe connected to a Fourier transform near-infrared spectroscope. In the course of the measurement sequences, several issues were addressed, such as surface drying, measurement geometry, ease of automation and interconnected data handling. The near-infrared (NIR) data were first modeled separately for heartwood and sapwood by means of multivariate partial least squares regression. The models for moisture content were evaluated by root mean square error of prediction, the result being 0.8% for heartwood and 10% for sapwood. The two models were then applied to the NIR data collected from sets of disks cut from nine logs. The results of the calculated moisture contents were evaluated by methods of descriptive statistics, and they indicated clear differences and trends in the distribution of moisture content in transverse or longitudinal regions of a log. Additionally, inter-tree variation in moisture content was detected.

scholarly journals Nondestructive Prediction of Optimal Harvest Time of Cherry Tomatoes Using VIS-NIR Spectroscopy and PLSR Calibration

2011 ◽  
Vol 1 ◽  
pp. 92-96 ◽  
Author(s):  
Hai Qing Yang
Keyword(s):  
Near Infrared ◽  
Nir Spectroscopy ◽  
Coefficient Of Determination ◽  
Harvest Time ◽  
Least Squares Regression ◽  
Calibration Models ◽  
Optimal Harvest ◽  
Leave One Out

In situ determination of optimal harvest time of tomatoes is of value for growers to optimize fruit picking schedule. This study evaluates the feasibility of using visible and near infrared (VIS-NIR) spectroscopy to make an intact estimation of harvest time of tomatoes. A mobile, fibre-type, AgroSpec VIS-NIR spectrophotometer (Tec5, Germany), with a spectral range of 350-2200 nm, was used for spectral acquisition of tomatoes in reflection mode. The harvest time of tomatoes was measured by the days before harvest. After dividing spectra into a calibration set (70%) and an independent prediction set (30%), spectra in the calibration set were subjected to a partial least-squares regression (PLSR) with leave-one-out cross validation to establish calibration models. Validation of calibration models on the independent prediction set indicates that the best model can produce excellent prediction accuracy with coefficient of determination (R2) of 0.90, root-mean-square error of prediction (RMSEP) of 2.5 days and residual prediction deviation (RPD) of 3.01. It is concluded that VIS-NIR spectroscopy coupled with PLSR models can be adopted successfully for in situ determination of optimal harvest time of tomatoes, which allows for automatic fruit harvest by a horticultural robot.

Developing near infrared spectroscopy models for predicting chemistry and responses to stress in Pinus radiata (D. Don)

2021 ◽  
pp. 096703352110065
Author(s):  
Judith S Nantongo ◽  
BM Potts ◽  
T Rodemann ◽  
H Fitzgerald ◽  
NW Davies ◽  
...  
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Pinus Radiata ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Coefficient Of Determination ◽  
Individual Plant ◽  
Least Squares Regression ◽  
Plant Parts ◽  
Quantitative Genetic

Incorporating chemical traits in breeding requires the estimation of quantitative genetic parameters, especially the levels of additive genetic variation. This requires large numbers of samples from pedigreed populations. Conventional wet chemistry procedures for chemotyping are slow, expensive and not a practical option. This study focuses on the chemical variation in Pinus radiata, where the near infrared (NIR) spectral properties of the needles, bark and roots before and after exposure to methyl jasmonate (MJ) and artificial bark stripping (strip) treatments were investigated as an alternative approach. The aim was to test the capability of NIR spectroscopy to (i) discriminate samples exposed to MJ and strip assessed 7, 14, 21 and 28 days after treatment from untreated samples, and (ii) quantitatively predict individual chemical compounds in the three plant parts. Using principal components analysis (PCA) on the spectral data, we differentiated between treated and untreated samples for the individual plant parts. Based on partial least squares–discriminant analysis (PLS-DA) models, the best discrimination of treated from non-treated samples with the smallest root mean square error cross-validation (RMSECV) and highest coefficient of determination (r2) was achieved in the fresh needles (r2 = 0.81, RMSECV= 0.24) and fresh inner bark (r2 = 0.79, RMSECV = 0.25) for MJ-treated samples 14 days and 21 days after treatment, respectively. Using partial least squares regression, models for individual compounds gave high (r2), residual predictive deviation (RPD), lab to NIR error (PRL) or range error ratio (RER) for fructose (r2 = 0.84, RPD = 1.5, PRL = 0.71, RER = 7.25) and glucose (r2 = 0.83, RPD = 1.9, PRL = 1.14, RER = 8.50) and several diterpenoids. This provides an optimistic outlook for the use of NIR spectroscopy-based models for the larger-scale prediction of the P. radiata chemistry needed for quantitative genetic studies.

scholarly journals Softening Behaviour of Indonesian Wood Species

2021 ◽  
Vol 6 (2) ◽  
pp. 42-48
Author(s):  
Wahyu Dwianto ◽  
Ikuho Iida ◽  
Kazuya Minato
Keyword(s):  
Specific Gravity ◽  
Moisture Content ◽  
Wood Species ◽  
Water Saturation ◽  
Load Capacity ◽  
Testing Machine ◽  
Modulus Of Rupture ◽  
Bending Test ◽  
Chemical Compositions ◽  
Softening Behaviour

This paper deals with softening behaviour measurements of Indonesian wood species by static bending tests. Wood samples with a size of 110mm (R) x 10mm (T) x 4mm (L) were bending tested in air-dry at 20°C and 65% relative humidity (RH), in water saturation at 20°C, and in water saturation at 80°C to know the decreasing of modulus of elasticity (MOE) and modulus of rupture (MOR) due to moisture content (MC) and both moisture content and temperature (MCT) changes. The wood samples represented Randu (Bombax ceiba. L) as the lowest specific gravity, i.e. 0.27 to Lamtoro (Leucaena glauca (Willd) Benth) as the highest specific gravity, i.e. 0.81. The three-point static bending test was carried out by a mechanical testing machine with a load capacity of 100kgf, loading deflection speed of 5mm/min, a span distance of 80mm at a room with a temperature of 20°C and 65% RH for air-dry wood samples, and that for wet wood samples were conducted in a water bath at 20°C (change in MC) and 80°C (change in MCT), respectively. MOE and MOR increased linearly with specific gravity regardless of wood species. On the other hand, maximum deflection did not correlate with specific gravity for any MCT conditions. The relative MOE and MOR which were calculated in wet 20°C to air-dry were affected from hardly to strongly depending on the wood species. Meanwhile, they decreased extremely when saturated in water at 80°C regardless of wood species. The relative MOE and MOR due to the change in MC or MCT was independent of specific gravity, as well. Furthermore, chemical compositions of the wood species were analysed to clarify the main factors that affected the decreasing of MOE and MOR due to MC and MCT changes. The results showed that the percentage of lignin and hemicelluloses in each wood played an important role in decreasing the static bending properties. Relative MOE and MOR decreased with increasing lignin and hemicellulose contents. It can be concluded that the hygrothermal properties of lignin and hemicelluloses significantly affect the changes of elastic and strength properties of wood in softening conditions.

Using Fourier Transform Near-Infrared Spectroscopy to Predict the Mechanical Properties of Thermally Modified Southern Pine Wood

2016 ◽  
Vol 70 (10) ◽  
pp. 1676-1684
Author(s):  
Li Tong ◽  
Wenbo Zhang
Keyword(s):  
Mechanical Properties ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Modulus Of Rupture ◽  
Coefficient Of Determination ◽  
Southern Pine ◽  
Pine Wood ◽  
Close Relationship ◽  
Thermally Modified Wood ◽  
Modified Wood

This study seeks to estimate the mechanical properties of thermally modified wood (TMW) using near-infrared (NIR) spectroscopy to measure 80 samples in three-point bending tests. Near-infrared spectra collected from the transverse, radial, and tangential sections of wood, coupled with chemometric techniques, were used to predict the mechanical properties of southern pine wood, from which NIR models were constructed based on partial least squares and corresponding cross-validation. The coefficient of determination between NIR transverse section spectra, as well as two mechanical properties of wood samples, modulus of rupture (MOR) and modulus of elasticity (MOE), were above 0.92 and greater than values for other sections. Spectral data from the transverse sections were richer than data from other sections, and thus, a model based on transverse sections better predicts the mechanical properties of wood. A close relationship between the values for mechanical properties (MOE and MOR) and the NIR spectra of thermally modified southern pine wood can be demonstrated, which provides the potential to predict the mechanical properties of untreated and thermally modified wood.

scholarly journals Spectral Range and Wood Surface Impacts on Equilibrium Moisture Content Estimation in Thermally Modified Beech Wood by FT-NIR Spectroscopy

2021 ◽  
Vol 1208 (1) ◽  
pp. 012022
Author(s):  
Nebojša Todorović
Keyword(s):  
Moisture Content ◽  
Equilibrium Moisture Content ◽  
Cross Section ◽  
Near Infrared ◽  
Prediction Models ◽  
Beech Wood ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Least Squares Regression ◽  
The Cross

Abstract Fourier transform near-infrared (FT-NIR) spectroscopy and partial least squares regression (PLS-R) were tested for the possibility of equilibrium moisture content (EMC) prediction in thermally modified beech wood (Fagus moesiaca C.). The samples were modified for 4h at temperatures of 170, 190 and 210 °C. After thermal modification, the samples were kept in a climatic chamber until EMC was reached. FT-NIR spectra (100 scans and 4 cm-1) were collected on the cross-section and radial surfaces at four points. PLS – R models were developed for four spectral regions: the first overtone, the second overtone, the third overtone and the combination band region. Applied thermal treatment caused a decrease of EMC by 42 % at 170 °C, by 53 % at 190 °C, and by 62 % at 210 °C. Principal component analysis (PCA) indicated that there is a difference both between treatments and between wood surfaces. The results of the spectra taken from the radial surface were, in all models, better than the spectra of the cross-section. Related to chemical changes, the first and second overtone region play an important role in the calibrations. The best prediction models for EMC of thermally modified beech wood were obtained from radial surface spectra in the first (Rp2=0.86, RPD=2.69) and second overtone region (Rp2=0.87, RPD=2.70). The obtain results could contribute to the development of predictive models in monitoring of EMC which could significantly improve the quality of industrial production of thermally modified wood.

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