Analysis of Pinus radiata D. Don Bark by Near Infrared Spectroscopy

Holzforschung ◽  
2003 ◽  
Vol 57 (5) ◽  
pp. 520-526 ◽  
Author(s):  
L. R. Schimleck ◽  
Y. Yazaki
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Pinus Radiata ◽  
Near Infrared ◽  
Practical Importance ◽  
Nir Spectroscopy ◽  
Hot Water ◽  
Standard Errors ◽  
Test Set

Summary The estimation of a range of Pinus radiata D. Don bark properties by calibrated near infrared (NIR) spectroscopy is reported. A series of P. radiata samples were characterised in terms of hot water extractives, NaOH extractives and Stiasny value. NIR spectra were obtained from the milled bark of each sample and used to develop calibrations for each parameter. Coefficients of determination (R2) ranged from 0.84 (NaOH extractives) to 0.94 (Stiasny value). Standard errors of calibration ranged from 0.96 (NaOH extractives) to 2.47 (Stiasny value). When applied to a separate test set, the hot water extractives and Stiasny value calibrations performed well, while the NaOH calibration was disappointing. The calibration developed for Stiasny value could be of considerable practical importance as the method used to determine Stiasny value is particularly time consuming.

Stiffness Prediction of Radiata Pine Clearwood Test Pieces Using near Infrared Spectroscopy

2001 ◽  
Vol 9 (2) ◽  
pp. 117-122 ◽  
Author(s):  
Armin Thumm ◽  
Roger Meder
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Pinus Radiata ◽  
Modulus Of Elasticity ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Radiata Pine ◽  
Model Based ◽  
Test Pieces ◽  
The Mean

Near infrared (NIR) spectroscopy has been used to predict the modulus of elasticity (stiffness) of samples taken from knot-free sapwood specimens of radiata pine ( Pinus radiata D. Don). The method shows the potential of using NIR spectroscopy for assessment of lumber stiffness. A model based on NIR spectra taken on the radial face of 404 samples of radiata pine clearwood was established to predict stiffness. Samples were moved past the detector at a rate of 900 mm min−1. This model then was used to predict the stiffness of a further 80 samples and the results show an error in prediction of 14% of the mean measured value.

Measuring Potassium in Plant Tissues Using near Infrared Spectroscopy

1998 ◽  
Vol 6 (A) ◽  
pp. A63-A66 ◽  
Author(s):  
Susan Ciavarella ◽  
Graeme D. Batten ◽  
Anthony B. Blakeney
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Nitrogen Fertilizer ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Essential Elements ◽  
Cereal Crops ◽  
Standard Errors ◽  
Plant Tissues

Near infrared (NIR) spectroscopy is routinely used to determine constituents with organic bonds which absorb electromagnetic radiation in the region 1100 to 2500 nm. The nitrogen fertilizer requirements of cereal crops are determined from the analysis of vegetative samples by NIR spectroscopy. Simultaneous determination of other plant-essential elements would enhance the value of the analysis. Compared to nitrogen, other essential elements are either present at a lower concentration in the tissue or present largely in an inorganic form which is not detectable by NIR spectroscopy. In this paper we report NIR spectroscopic calibrations for potassium in grape petioles, grape leaves, rice shoots and orange leaves. When tested against a set of verification samples the NIR spectroscopic calibrations accounted for 96, 89, 93 and 85% of the concentration of K with standard errors of performance of 0.16, 0.12, 0.18 and 0.17%K respectively.

scholarly journals Textile Recognition and Sorting for Recycling at an Automated Line Using Near Infrared Spectroscopy

Recycling ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 11
Author(s):  
Kirsti Cura ◽  
Niko Rintala ◽  
Taina Kamppuri ◽  
Eetta Saarimäki ◽  
Pirjo Heikkilä
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Automated Recognition ◽  
Textile Materials ◽  
Input Material ◽  
Adequate Quality ◽  
Automated Line

In order to add value to recycled textile material and to guarantee that the input material for recycling processes is of adequate quality, it is essential to be able to accurately recognise and sort items according to their material content. Therefore, there is a need for an economically viable and effective way to recognise and sort textile materials. Automated recognition and sorting lines provide a method for ensuring better quality of the fractions being recycled and thus enhance the availability of such fractions for recycling. The aim of this study was to deepen the understanding of NIR spectroscopy technology in the recognition of textile materials by studying the effects of structural fabric properties on the recognition. The identified properties of fabrics that led non-matching recognition were coating and finishing that lead different recognition of the material depending on the side facing the NIR analyser. In addition, very thin fabrics allowed NIRS to penetrate through the fabric and resulted in the non-matching recognition. Additionally, ageing was found to cause such chemical changes, especially in the spectra of cotton, that hampered the recognition.

Rapid Determination of Heartwood Extractives in Larix sp. by Means of Fourier Transform near Infrared Spectroscopy

2002 ◽  
Vol 10 (3) ◽  
pp. 203-214 ◽  
Author(s):  
N. Gierlinger ◽  
M. Schwanninger ◽  
B. Hinterstoisser ◽  
R. Wimmer
Keyword(s):  
Fourier Transform ◽  
Near Infrared ◽  
Cross Validation ◽  
Nir Spectroscopy ◽  
Solid Wood ◽  
Hot Water ◽  
Extractive Content ◽  
Fast Method ◽  
Wood Powder ◽  
Test Set

The feasibility of Fourier transform near infrared (FT-NIR) spectroscopy to rapidly determine extractive and phenolic content in heartwood of larch trees ( Larix decidua MILL., L. leptolepis (LAMB.) CARR. and the hybrid L. x eurolepis) was investigated. FT-NIR spectra were collected from wood powder and solid wood using a fibre-optic probe. Partial Least Squares (PLS) regression analyses were carried out describing relationships between the data sets of wet laboratory chemical data and the FT-NIR spectra. Besides cross and test set validation the established models were subjected to a further evaluation step by means of additional wood samples with unknown extractive content. Extractive and phenol contents of these additional samples were predicted and outliers detected through Mahalanobis distance calculations. Models based on the whole spectral range and without data pre-processing performed well in cross-validation and test set validation, but failed in the evaluation test, which is based on spectral outlier detection. But selection of data pre-processing methods and manual as well as automatic restriction of wavenumber ranges considerably improved the model predictability. High coefficients of determination ( R2) and low root mean square errors of cross-validation ( RMSECV) were obtained for hot water extractives ( R2 = 0.96, RMSECV = 0.86%, range = 4.9–20.4%), acetone extractives ( R2 = 0.86, RMSECV = 0.32%, range = 0.8–3.6%) and phenolic substances ( R2 = 0.98, RMSECV = 0.21%, range = 0.7–4.9%) from wood powder. The models derived from wood powder spectra were more precise than those obtained from solid wood strips. Overall, NIR spectroscopy has proven to be an easy to facilitate, reliable, accurate and fast method for non-destructive wood extractive determination.

Measurement of the Ratio of Tea Polyphenols to Amino Acids in Green Tea Infusion Based on near Infrared Spectroscopy

2011 ◽  
Vol 301-303 ◽  
pp. 1093-1097 ◽  
Author(s):  
Shi Rong Ai ◽  
Rui Mei Wu ◽  
Lin Yuan Yan ◽  
Yan Hong Wu
Keyword(s):  
Amino Acids ◽  
Infrared Spectroscopy ◽  
Correlation Coefficient ◽  
Green Tea ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Tea Polyphenols ◽  
Strong Absorption ◽  
Tea Infusion

This study attempted the feasibility to determine the ratio of tea polyphenols to amino acids in green tea infusion using near infrared (NIR) spectroscopy combined with synergy interval PLS (siPLS) algorithms. First, SNV was used to preprocess the original spectra of tea infusion; then, siPLS was used to select the efficient spectra regions from the preprocessed spectra. Experimental results showed that the spectra regions [7 8 18] were selected, which were out of the strong absorption of H2O. The optimal PLS model was developed with the selected regions when 6 PCs components were contained. The RMSEP value was equal to 0.316 and the correlation coefficient (R) was equal to 0.8727 in prediction set. The results demonstrated that NIR can be successfully used to determinate the ration of tea polyphenols to amino acids in green tea infusion.

Near infrared spectroscopy as an alternative method for rapid determination of the solidification point of 2,4,6-trinitrotoluene in production

2019 ◽  
Vol 27 (4) ◽  
pp. 286-292
Author(s):  
Chongchong She ◽  
Min Li ◽  
Yunhui Hou ◽  
Lizhen Chen ◽  
Jianlong Wang ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Rapid Determination ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Quality Parameter ◽  
Solidification Point ◽  
Fast Analysis ◽  
Online Application

The solidification point is a key quality parameter for 2,4,6-trinitrotoluene (TNT). The traditional solidification point measurement method of TNT is complicated, dangerous, not environmentally friendly and time-consuming. Near infrared spectroscopy (NIR) analysis technology has been applied successfully in the chemical, petroleum, food, and agriculture sectors owing to its characteristics of fast analysis, no damage to the sample and online application. The purpose of this study was to study near infrared spectroscopy combined with chemometric methods to develop a fast and accurate quantitative analysis method for the solidification point of TNT. The model constructed using PLS regression was successful in predicting the solidification point of TNT ([Formula: see text] = 0.999, RMSECV = 0.19, RPDCa = 33.5, [Formula: see text] = 0.19, [Formula: see text] = 0.999). Principal component analysis shows that the model could identify samples from different reactors. The results clearly demonstrate that the solidification point can be measured in a short time by NIR spectroscopy without any pretreatment for the sample and skilled laboratory personnel.

scholarly journals Determination Residues of Penicillin G and Cloxacillin in Raw Cow Milk Using Fourier Transform Near Infrared Spectroscopy

2009 ◽  
Vol 78 (4) ◽  
pp. 685-690 ◽  
Author(s):  
Michaela Dračková ◽  
Pavlína Navrátilová ◽  
Luboš Hadra ◽  
Lenka Vorlová ◽  
Lenka Hudcová
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Raw Milk ◽  
Partial Least Square ◽  
Penicillin G ◽  
Standard Errors ◽  
Calibration And Validation ◽  
Calibration Models

The objective of this study was to study the use of Fourier transform near infrared spectroscopy (FTNIR) combined with the partial least square (PLS) method for determining the residues of penicillin and cloxacillin in raw milk. The spectra were measured in the reflectance mode with transflectance cell in the spectral range of 10,000 – 4,000 cm-1 with 100 scans. Calibration models were developed. They were assessed statistically based on correlation coefficients (R) and standard errors of calibration (SEC). For penicillin, the following values were established: R = 0.951 and SEC = 0.004. For cloxacillin, they were R = 0.871 and SEC = 0.007. These calibration models were verified later with cross-validation. Better results were obtained in the calibration and validation models that were developed on milk samples coming from one farm. Using FT-NIR, the maximum residue limit (MRL) of cloxacillin in milk can be determined. However, standard errors of calibration and validation for penicillin G exceed the fixed MRL. FT-NIR spectroscopy is not a suitable method for accurate determination of these substances in raw milk. Variability in milk composition has a major influence on detection of substances present at very low concentrations.

Seeing the light: NIR at the coalface (the inaugural Blakeney Address)

NIR news ◽  
2018 ◽  
Vol 29 (5) ◽  
pp. 7-11
Author(s):  
Peter Flinn
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Scientific Development ◽  
Unique Contribution ◽  
Learned Societies ◽  
To Receive ◽  
Highly Cited

Anthony Bernard (Tony) Blakeney (1948–2015) made a unique contribution to near infrared (NIR) spectroscopy in Australia and to the development of the Australian Near Infrared Spectroscopy Group (ANISG). An eminent and highly cited grain scientist and carbohydrate chemist, in the 1980s he recognised that NIR-based analyses could aid the production of more and higher quality cereals. Tony was ANISG Treasurer from its inception in 1988 until 2015 and was recognised as a champion of learned societies and their importance in scientific development. This presentation is in honour of Tony’s achievements, and it is a great honour to receive the inaugural award in his name.

scholarly journals Near-infrared spectroscopy and hyperspectral imaging: non-destructive analysis of biological materials

2014 ◽  
Vol 43 (24) ◽  
pp. 8200-8214 ◽  
Author(s):  
Marena Manley
Keyword(s):  
Infrared Spectroscopy ◽  
Hyperspectral Imaging ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Biological Materials ◽  
Destructive Analysis ◽  
Non Destructive

Principles, interpretation and applications of near-infrared (NIR) spectroscopy and NIR hyperspectral imaging are reviewed.

scholarly journals Near-Infrared Spectroscopy as a classification tool for agraz (Vaccinium meridionale Swartz)

DYNA ◽  
2020 ◽  
Vol 87 (213) ◽  
pp. 17-21
Author(s):  
Nathalia María Forero-Cabrera ◽  
Carolina Maria Sánchez-Sáenz
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Agricultural Products ◽  
Maturity Stage ◽  
New Techniques ◽  
Classification Tool ◽  
Suitable Technique

The importance of the selection and classification processes in the industry of agricultural products and the increase in the production of fruits make necessary the development and implementation of new techniques to efficiently perform these tasks. Techniques such as NIR spectroscopy have proved to have potential to accomplish this purpose. The aim of this research was to evaluate the performance of near infrared spectroscopy as a classification tool for agraz (Vaccinium meridionale Swartz), according to its state of maturity. In order to obtainthe classification models, the PCA and SIMCA methods were used. Results were obtained close to 100% accuracy in the classification for maturity stages 4 and 5 and between 81 and 90% for maturity stage 3. The NIR spectroscopy appears as a suitable technique for the classification of fruits of agraz according to their state of maturity.

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