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.

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.

scholarly journals Histamine Control in Raw and Processed Tuna: A Rapid Tool Based on NIR Spectroscopy

Foods ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 885
Author(s):  
Sergio Ghidini ◽  
Luca Maria Chiesa ◽  
Sara Panseri ◽  
Maria Olga Varrà ◽  
Adriana Ianieri ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Coefficient Of Determination ◽  
Mean Square ◽  
Tuna Fish ◽  
Mean Square Errors

The present study was designed to investigate whether near infrared (NIR) spectroscopy with minimal sample processing could be a suitable technique to rapidly measure histamine levels in raw and processed tuna fish. Calibration models based on orthogonal partial least square regression (OPLSR) were built to predict histamine in the range 10–1000 mg kg−1 using the 1000–2500 nm NIR spectra of artificially-contaminated fish. The two models were then validated using a new set of naturally contaminated samples in which histamine content was determined by conventional high-performance liquid chromatography (HPLC) analysis. As for calibration results, coefficient of determination (r2) > 0.98, root mean square of estimation (RMSEE) ≤ 5 mg kg−1 and root mean square of cross-validation (RMSECV) ≤ 6 mg kg−1 were achieved. Both models were optimal also in the validation stage, showing r2 values > 0.97, root mean square errors of prediction (RMSEP) ≤ 10 mg kg−1 and relative range error (RER) ≥ 25, with better results showed by the model for processed fish. The promising results achieved suggest NIR spectroscopy as an implemental analytical solution in fish industries and markets to effectively determine histamine amounts.

Evaluation of swelling properties and drug release from mechanochemical pre-gelatinized glutinous rice starch matrix tablets by near infrared spectroscopy

2021 ◽  
pp. 096703352098235
Author(s):  
Tomomi Takaku ◽  
Yusuke Hattori ◽  
Tetsuo Sasaki ◽  
Tomoaki Sakamoto ◽  
Makoto Otsuka
Keyword(s):  
Drug Release ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Matrix Tablets ◽  
Rice Starch ◽  
Release Time ◽  
Swelling Properties ◽  
X Ray ◽  
Glutinous Rice ◽  
Pharmaceutical Properties

The effect of grinding on the pharmaceutical properties of matrix tablets consisting of ground glutinous rice starch (GRS) and theophylline (TH) was predicted by near infrared (NIR) spectroscopy. Ground GRS samples were prepared by grinding GRS in a planetary ball mill for 0-120 min, measured by X-ray diffractometry (XRD) and NIR, and then evaluated for crystallinity (%XRD) based on XRD profiles. Tablets containing TH (5 w/w%), ground GRS (94 w/w%), and magnesium stearate (1 w/w%) were formed by compression. Gel-forming and drug-release processes of the tablets were measured using a dissolution instrument with X-ray computed tomography (XCT). Swelling ratio (SWE) and mean drug-release time (MDT) were evaluated based on XCT and drug-release profiles, respectively. Calibration models for predicting percent %XRD, MDT, and SWE were constructed based on the NIR of ground GRS using partial least-squares. The results indicated the possibility of controlling the pharmaceutical properties of matrix tablets by altering the pre-gelatinization of GRS based on changes in their NIR spectra during the milling process.

Prediction of Fatty Acid Content in Beef Neck Lean by near Infrared Reflectance Analysis

1998 ◽  
Vol 6 (1) ◽  
pp. 229-234 ◽  
Author(s):  
William R. Windham ◽  
W.H. Morrison
Keyword(s):  
Fatty Acids ◽  
Fatty Acid ◽  
Near Infrared ◽  
Fatty Acid Content ◽  
Reference Method ◽  
Nir Spectroscopy ◽  
Coefficient Of Determination ◽  
Longissimus Dorsi ◽  
Near Infrared Reflectance ◽  
Total Fatty Acids

Near infrared (NIR) spectroscopy in the prediction of individual and total fatty acids of bovine M. Longissimus dorsi neck muscles has been studied. Beef neck lean was collected from meat processing establishments using advanced meat recovery systems and hand-deboning. Samples ( n = 302) were analysed to determine fatty acid (FA) composition and scanned from 400 to 2498 nm. Total saturated and unsaturated FA values ranged from 43.2 to 62.0% and 38.3 to 56.2%, respectively. Results of partial least squares (PLS) modeling shown reasonably accurate models were attained for total saturate content [standard error of performance ( SEP = 1.10%); coefficient of determination on the validation set ( r2 = 0.77)], palmitic ( SEP = 0.94%; r2 = 0.69), unsaturate ( SEP = 1.13%; r2 = 0.77), and oleic ( SEP = 0.97; r2 = 0.78). Prediction of other individual saturated and unsaturated FAs was less accurate with an r2 range of 0.10 to 0.53. However, the sum of individual predicted saturated and unsaturated FA was acceptable compared with the reference method ( SEP = 1.10 and 1.12%, respectively). This study shows that NIR can be used to predict accurately total fatty acids in M. Longissimus dorsi muscle.

Application of near Infrared Spectroscopy On-Combine in Corn Grain Breeding

2005 ◽  
Vol 13 (2) ◽  
pp. 69-75 ◽  
Author(s):  
Roland Welle ◽  
Willi Greten ◽  
Thomas Müller ◽  
Gary Weber ◽  
Hartwig Wehrmann
Keyword(s):  
Grain Yield ◽  
Dry Matter ◽  
Near Infrared ◽  
Reference Method ◽  
Nir Spectroscopy ◽  
Coefficient Of Determination ◽  
Successful Implementation ◽  
Grain Moisture ◽  
Yield Determination ◽  
Corn Grain

Improving maize ( Zea mays L.) grain yield and agronomic properties are major goals for corn breeders in northern Europe. In order to facilitate field grain yield determination we measured corn grain moisture content with near infrared (NIR) spectroscopy directly on a harvesting machine. NIR spectroscopy, in combination with harvesting, significantly improved quality and speed of yield determination within the very narrow harvest time window. Moisture calibrations were developed with 2117 samples from the 2001 to 2003 crop seasons using six diode array spectrometers mounted on combines. These models were derived from databases containing spectra from all instruments. Spectrometer-specific calibrations cannot be used to predict samples measured on other instruments of the same type. Standard error of cross-validation ( SECV) and coefficient of determination ( R2) were 0.56 and 0.99%, respectively. Moisture standard errors of prediction ( SEPs) for the six instruments, using varying independent sample sets from the 2004 harvest, ranged between 0.59% and 0.99% with R2 values between 0.92 to 0.98. The six instruments produced the same dry matter predictions on a common sample set as indicated by high R2 and low biases among them, hence there was no need to apply specific standardisation algorithms. Moisture NIR spectroscopy determinations were significantly more precise than those obtained using the reference method. Analysis of variance revealed low least significant differences and high heritabilities. High precision and heritability demonstrate successful implementation of on-combine NIR spectroscopy for routine dry matter (yield) measurements.

scholarly journals Predicting terpene content in dried conifer shoots using near infrared spectroscopy

2020 ◽  
Vol 28 (5-6) ◽  
pp. 308-314
Author(s):  
Emilie Champagne ◽  
Michaël Bonin ◽  
Alejandro A Royo ◽  
Jean-Pierre Tremblay ◽  
Patricia Raymond
Keyword(s):  
Gas Chromatography ◽  
Picea Glauca ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Calibration Method ◽  
Wide Distribution ◽  
Coefficient Of Determination ◽  
Calibration Model ◽  
Freeze Dried ◽  
Terpene Content

Terpenes are phytochemicals found in multiple plant genera, especially aromatic herbs and conifers. Terpene content quantification is costly and complex, requiring the extraction of oil content and gas chromatography analyses. Near infrared (NIR) spectroscopy could provide an alternative quantitative method, especially if calibration can be developed with the spectra of dried plant material, which are easier and faster to acquire than oil-based spectra. Here, multispecies NIR spectroscopy calibrations were developed for total terpene content (mono- and sesquiterpenes) and for specific terpenes (α-pinene, β-pinene and myrcene) with five conifers species ( Picea glauca, Picea rubens, Pinus resinosa, Pinus strobus and Thuja occidentalis). The terpene content of fresh shoot samples was quantified with gas chromatography. The NIR spectra were measured on freeze-dried samples (n = 137). Using a subset of the samples, modified partial least squares regressions of total terpene and the three individual terpenes content were generated as a functions of the NIR spectra. The standard errors of the internal cross-validations (values between 0.25 and 2.28) and the ratio of prediction to deviation ratios (RPD values between 2.20 and 2.38) indicate that all calibrations have similar accuracy. The independent validations, however, suggest that the calibrations for total terpene and α-pinene content are more accurate (respective coefficient of determination: r2 = 0.85 and 0.82). In contrast, calibrations for β-pinene and myrcene had a low accuracy (respectively: r2 = 0.62 and 0.08), potentially because of the low concentration of these terpenes in the species studied. The calibration model fits (i.e., r2) are comparable to previously published calibration using the spectra of dried shoot samples and demonstrate the potential of this method for terpenes in conifer samples. The calibration method used could be useful in several other domains (e.g. seedling breeding program, industrial), because of the wide distribution of terpenes and especially of pinenes.

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.

scholarly journals Nondestructive Detection of Weight Loss Rate, Surface Color, Vitamin C Content, and Firmness in Mini-Chinese Cabbage with Nanopackaging by Fourier Transform-Near Infrared Spectroscopy

Foods ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 2309
Author(s):  
Qiang Liu ◽  
Shaoxia Chen ◽  
Dandan Zhou ◽  
Chao Ding ◽  
Jiahong Wang ◽  
...  
Keyword(s):  
Weight Loss ◽  
Fourier Transform ◽  
Chinese Cabbage ◽  
Loss Rate ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Prediction Performance ◽  
Surface Color ◽  
Weight Loss Rate ◽  
Plsr Model

A nondestructive optical method is described for the quality assessment of mini-Chinese cabbage with nanopackaging during its storage, using Fourier transform-near infrared (FT-NIR) spectroscopy. The sample quality attributes measured included weight loss rate, surface color index, vitamin C content, and firmness. The level of freshness of the mini-Chinese cabbage during storage was divided into three categories. Partial least squares regression (PLSR) and the least squares support vector machine were applied to spectral datasets in order to develop prediction models for each quality attribute. For a comparative analysis of performance, the five preprocessing methods applied were standard normal variable (SNV), first derivative (lst), second derivative (2nd), multiplicative scattering correction (MSC), and auto scale. The SNV-PLSR model exhibited the best prediction performance for weight loss rate (Rp2 = 0.96, RMSEP = 1.432%). The 1st-PLSR model showed the best prediction performance for L* value (Rp2 = 0.89, RMSEP = 3.25 mg/100 g), but also the lowest accuracy for firmness (Rp2 = 0.60, RMSEP = 2.453). The best classification model was able to predict freshness levels with 88.8% accuracy in mini-Chinese cabbage by supported vector classification (SVC). This study illustrates that the spectral profile obtained by FT-NIR spectroscopy could potentially be implemented for integral assessments of the internal and external quality attributes of mini-Chinese cabbage with nanopacking during storage.

scholarly journals Overall precision test of near infrared spectroscopy on mango fruits (Mangifera indica CV. ‘Nam Dok Mai Si Thong’) by on-line and off-line systems

2020 ◽  
Vol 187 ◽  
pp. 04006
Author(s):  
Wachiraya Lekhawattana ◽  
Panmanas Sirisomboon
Keyword(s):  
Near Infrared ◽  
Mangifera Indica ◽  
Nir Spectroscopy ◽  
Soluble Solids ◽  
Coefficient Of Determination ◽  
Online Systems ◽  
On Line ◽  
Line Scanning ◽  
Brix Value ◽  
Precision Test

The near infrared (NIR) spectroscopy both on-line and off-line scanning was applied on mango fruits (Mangifera indica CV. ‘Nam dok mai- si Thong’) for the overall precision test. The reference parameter was total soluble solids content (Brix value). The results showed that the off-line scanning had a higher accuracy than on-line scanning. The scanning repeatability of the off-line and on-line systems were 0.00199 and 0.00993, respectively. The scanning reproducibility of the off-line and online systems were 0.00279 and 0.00513, respectively. The reference of measurement repeatability was 0.2. The maximum coefficient of determination (R2max) of the reference measurement was 0.894.

scholarly journals Revealing the Nature of the Highly Obscured Galactic Source IGR J16318-4848

2004 ◽  
Vol 194 ◽  
pp. 65-66
Author(s):  
S. Chaty ◽  
P. Filliatre
Keyword(s):  
Near Infrared ◽  
Spectral Energy Distribution ◽  
Nir Spectroscopy ◽  
High Mass ◽  
Spectral Energy ◽  
X Ray ◽  
Circumstellar Material ◽  
New Class ◽  
Galactic Source ◽  
Early Type Star

AbstractThe X-ray source IGR J16318-4848 was the first source discovered by INTEGRAL on 2003, January 29. We carried out optical and near-infrared (NIR) observations at the European Southern Observatory (ESO La Silla) in the course of a Target of Opportunity (ToO) programme. We discovered the optical counterpart and confirmed an already proposed NIR candidate. NIR spectroscopy revealed a large amount of emission lines, including forbidden iron lines and P-Cygni profiles. The spectral energy distribution of the source points towards a high luminosity and a high temperature, with an absorption greater than the interstellar absorption, but two orders of magnitude lower than the X-ray absorption. We show that the source is an High Mass X-ray binary (HMXB) at a distance between ~ 1 and ~ 6 kpc, the mass donor being an early-type star, probably a sgB[e] star, surrounded by a rich and absorbing circumstellar material. This would make the second High Mass X-ray Binary (HMXB) with a sgB[e] star after CI Cam, indicating that a new class of strongly absorbed X-ray binaries is being unveiled by INTEGRAL.

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