Qualitative Analysis of Oil Sand Slurries Using On-Line NIR Spectroscopy

1996 ◽  
Vol 50 (12) ◽  
pp. 1535-1540 ◽  
Author(s):  
Waldemar I. Friesen

The development of a reliable on-line method to monitor process streams is important for improved process control in oil sand extraction plants. The suitability of diffuse reflectance near-infrared (NIR) spectroscopy for this purpose has been tested in a pilot plant environment. Spectra of a feed slurry flowing through a pipe were measured with the use of an on-line fiber-optic probe. Data were collected throughout a nine-hour period during which ore type and slurry water content were varied. The feasibility of monitoring feed stream conditions is demonstrated by principal component analysis of the measured spectra. Clustering of these spectra according to ore type and water content enables the detection of deviations from and transitions between steady-state conditions of the process. Estimates are given of characteristic times for the process to reach a steady state after a change in condition has been initiated. The use of artificial neural networks for classifying spectra on the basis of ore type is also illustrated.

2002 ◽  
Vol 10 (3) ◽  
pp. 195-202 ◽  
Author(s):  
Tsuyoshi Furukawa ◽  
Yasuo Kita ◽  
Shigehiro Sasao ◽  
Kimihiro Matsukawa ◽  
Masahiro Watari ◽  
...  

The melt-extrusion transesterification of ethylene/vinylacetate (EVA) copolymer to ethylene/vinylalcohol (EVAL) copolymers has been monitored by on-line near infrared (NIR) spectroscopy. A total of 60 NIR spectra were measured within 37 minutes after the initial addition of octanol (reagent) and catalyst (sodium methoxide) at the exit of the extruder by use of a fibre-optic probe. The most significant intensity change is observed for a band at 7089 cm−1 due to the first overtone of an OH stretching mode of the EVAL copolymers. We can monitor the progress of the reaction by plotting the peak intensity at 7089 cm−1 only. A principal component analysis (PCA) was carried out for the series of NIR spectra in the 7300–6900 cm−1 region. A score plot of PCA factor 1 is almost identical with the plot of the peak intensity at 7089 cm−1. Calibration models for predicting the vinyl acetate content in EVA copolymers have been developed by use of partial least squares (PLS) regression. The correlation coefficient and standard error of prediction are 0.96 and 0.85%, respectively, indicating that the described technique can be used to monitor the transesterification reaction.


1993 ◽  
Vol 47 (11) ◽  
pp. 1852-1870 ◽  
Author(s):  
Paul D. Gossen ◽  
John F. Macgregor ◽  
Robert H. Pelton

The properties of a polymer latex were measured over the course of a semi-batch polymerization with the use of ultraviolet (UV) and near-infrared (NIR) spectroscopy. The spectra were very complex, and their characteristics changed dramatically throughout the course of a batch, so linear calibration models were constructed for groups of similar spectra using Partial Least-Squares (PLS). Principal Component Analysis (PCA) was used as a pattern recognition tool to group spectra before calibration or prediction. UV spectra from 190 to 800 nm were taken of diluted latex. The weight fractions of styrene monomer and poly(styrene) were predicted with a standard error less than 0.5 wt%. NIR spectra from 900 to 1800 nm were taken of undiluted latex with a transflectance fiber-optic probe. Calibrations could predict the concentrations of all the major components [water, poly(styrene), poly(methyl methacrylate), styrene, methyl methacrylate] with a standard error of less than 0.5 wt%. Mean particle size was also well predicted for some of the calibration sets.


2018 ◽  
Vol 158 (4) ◽  
pp. 688-694 ◽  
Author(s):  
Gary Linkov ◽  
Arash Hanifi ◽  
Farzad Yousefi ◽  
Derrick Tint ◽  
Sudheer Bolla ◽  
...  

Objectives To assess the potential of infrared fiber-optic spectroscopy to evaluate the compositional properties of human tracheal cartilage. Study Design Laboratory-based study. Methods Twenty human cadaveric distal tracheas were harvested (age range 20-78 years; 6 females, 14 males) for compositional analysis. Histologic staining, Fourier transform infrared imaging spectroscopy data on collagen and proteoglycan (PG) content, and near-infrared (NIR) fiber-optic probe spectroscopic data that reflect protein and water content were evaluated. NIR fiber-optic probe data were also obtained from the proximal trachea in 4 human cadavers (age range 51-65 years; 2 females, 2 males) in situ for comparison to distal trachea spectral data. Results In the distal trachea cohort, the spectroscopic-determined ratio of PG/amide I, indicative of the relative amount of PG, was significantly higher in the tissues from the younger group compared to the older group (0.37 ± 0.08 vs 0.32 ± 0.05, P = .05). A principal component analysis of the NIR spectral data enabled separation of spectra based on tracheal location, likely due to differences in both protein and water content. The NIR-determined water content based on the 5200-cm−1 peak was significantly higher in the distal trachea compared to the proximal trachea ( P < .001). Conclusions Establishment of normative compositional values and further elucidating differences between the segments of trachea will enable more directed research toward appropriate compositional end points in regenerative medicine for tracheal repair.


2003 ◽  
Vol 48 (4) ◽  
pp. 9-13 ◽  
Author(s):  
M. Hansson ◽  
Å Nordberg ◽  
B. Mathisen

An anaerobic digester (8 l) was fed with the organic fraction of municipal solid waste and monitored intermittently for two years with on-line near-infrared (NIR) spectroscopy and traditional chemical parameters analysed off-line. The dynamics that occurred due to changes in substrate composition (changed C:N ratio) and changes in operating conditions (overloading) could be followed using principal component analysis of the obtained NIR-spectra. In addition, process disturbances such as failed stirring and increased foaming were readily detected by the NIR-spectra. Using PLS regression the propionate concentration could be predicted in the range 0.1-3.6 g/l, RMSEP 0.53 g/l with slope 0.74 and correlation coefficient 0.85. The response on changes in the digester fluid was reproducible and could be detected within 2.5 minutes, which can be considered as real-time monitoring.


2014 ◽  
Vol 07 (06) ◽  
pp. 1450004 ◽  
Author(s):  
Wenlong Li ◽  
Haibin Qu

Homogeneity of powder blend is essential to obtain uniform contents for the tablets and capsules. Near-infrared (NIR) spectroscopy with fiber-optic probe was used as an on-line technique for monitoring the homogeneity of pharmaceutical blend during the blending process instead of the traditional techniques, such as high performance liquid chromatograph (HPLC) method. In this paper NIRS with a SabIR diffuse reflectance fiber-optic probe was used to monitor the blending process of coptis powder and lactose (excipient) with different contents, and further qualitative methods, like similarity, moving block of standard deviation and mean square were used for calculation purposes with the collected spectra after the pretreatment of multiplicative signal correction (MSC) and second derivative. Correlation spectrum was used for the wavelength selection. Four different coptis were blended with lactose separately to validate the proposed method, and the blending process of "liu wei di huang" pill was also simulated in bottles to verify this method on multiple herbal blends. The overall results suggest that NIRS is a simple, effective and noninvasive technique can be successfully applied to the determination of homogeneity in the herbal blend.


2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Elise A. Kho ◽  
Jill N. Fernandes ◽  
Andrew C. Kotze ◽  
Glen P. Fox ◽  
Maggy T. Sikulu-Lord ◽  
...  

Abstract Background Existing diagnostic methods for the parasitic gastrointestinal nematode, Haemonchus contortus, are time consuming and require specialised expertise, limiting their utility in the field. A practical, on-farm diagnostic tool could facilitate timely treatment decisions, thereby preventing losses in production and flock welfare. We previously demonstrated the ability of visible–near-infrared (Vis–NIR) spectroscopy to detect and quantify blood in sheep faeces with high accuracy. Here we report our investigation of whether variation in sheep type and environment affect the prediction accuracy of Vis–NIR spectroscopy in quantifying blood in faeces. Methods Visible–NIR spectra were obtained from worm-free sheep faeces collected from different environments and sheep types in South Australia (SA) and New South Wales, Australia and spiked with various sheep blood concentrations. Spectra were analysed using principal component analysis (PCA), and calibration models were built around the haemoglobin (Hb) wavelength region (387–609 nm) using partial least squares regression. Models were used to predict Hb concentrations in spiked faeces from SA and naturally infected sheep faeces from Queensland (QLD). Samples from QLD were quantified using Hemastix® test strip and FAMACHA© diagnostic test scores. Results Principal component analysis showed that location, class of sheep and pooled versus individual samples were factors affecting the Hb predictions. The models successfully differentiated ‘healthy’ SA samples from those requiring anthelmintic treatment with moderate to good prediction accuracy (sensitivity 57–94%, specificity 44–79%). The models were not predictive for blood in the naturally infected QLD samples, which may be due in part to variability of faecal background and blood chemistry between samples, or the difference in validation methods used for blood quantification. PCA of the QLD samples, however, identified a difference between samples containing high and low quantities of blood. Conclusion This study demonstrates the potential of Vis–NIR spectroscopy for estimating blood concentration in faeces from various types of sheep and environmental backgrounds. However, the calibration models developed here did not capture sufficient environmental variation to accurately predict Hb in faeces collected from environments different to those used in the calibration model. Consequently, it will be necessary to establish models that incorporate samples that are more representative of areas where H. contortus is endemic.


2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Hui Chen ◽  
Zan Lin ◽  
Chao Tan

Near-infrared (NIR) spectroscopy technique offers many potential advantages as tool for biomedical analysis since it enables the subtle biochemical signatures related to pathology to be detected and extracted. In conjunction with advanced chemometrics, NIR spectroscopy opens the possibility of their use in cancer diagnosis. The study focuses on the application of near-infrared (NIR) spectroscopy and classification models for discriminating colorectal cancer. A total of 107 surgical specimens and a corresponding NIR diffuse reflection spectral dataset were prepared. Three preprocessing methods were attempted and least-squares support vector machine (LS-SVM) was used to build a classification model. The hybrid preprocessing of first derivative and principal component analysis (PCA) resulted in the best LS-SVM model with the sensitivity and specificity of 0.96 and 0.96 for the training and 0.94 and 0.96 for test sets, respectively. The similarity performance on both subsets indicated that overfitting did not occur, assuring the robustness and reliability of the developed LS-SVM model. The area of receiver operating characteristic (ROC) curve was 0.99, demonstrating once again the high prediction power of the model. The result confirms the applicability of the combination of NIR spectroscopy, LS-SVM, PCA, and first derivative preprocessing for cancer diagnosis.


Holzforschung ◽  
2008 ◽  
Vol 62 (4) ◽  
Author(s):  
Torbjörn A. Lestander

Abstract Samples of wood pellets were adjusted into six water content classes from 0% to 12%. The water content in single pellets varied between 0.1% and 14.2%. Three equations were constructed to estimate the differential heat of sorption (-ΔH) values from (1) fractal-geometry, (2) isosteric, and (3) calorimetric data. The ranges in calculated -ΔH of single pellets were (1) 133–1475, (2) 315–881, and (3) 195–1188 J g-1 water, respectively, across the studied moisture content range. Partial least squares regression was used to model near-infrared (NIR) spectra from single pellets and to predict -ΔH values and water content. The explained variation in test sets for the different models ranged from 97.1% to 99.9%. The shifts in peak absorbance for two water bands indicated that frequency in overtone vibration of O-H stretching and bending decreased, when water content was raised. Simulations of mixes between pellets of differential heat values showed that released heat was up to 0.03% of the gross calorific value of wood pellets. This heat may be a major contributor to initial temperature increases in pellet stacks during storage. The results indicate that on-line NIR based predictions of differential heat in wood pellets is possible to apply in the pellet industry.


2021 ◽  
pp. 096703352098731
Author(s):  
Adenilton C da Silva ◽  
Lívia PD Ribeiro ◽  
Ruth MB Vidal ◽  
Wladiana O Matos ◽  
Gisele S Lopes

The use of alcohol-based hand sanitizers is recommended as one of several strategies to minimize contamination and spread of the COVID-19 disease. Current reports suggest that the virucidal potential of ethanol occurs at concentrations close to 70%. Traditional methods of verifying the ethanol concentration in such products invite potential errors due to the viscosity of chemical components or may be prohibitively expensive to undertake in large demand. Near infrared (NIR) spectroscopy and chemometrics have already been used for the determination of ethanol in other matrices and present an alternative fast and reliable approach to quality control of alcohol-based hand sanitizers. In this study, a portable NIR spectrometer combined with classification chemometric tools, i.e., partial least square discriminant analysis (PLS–DA) and linear discriminant analysis with successive algorithm projection (SPA–LDA) were used to construct models to identify conforming and non-conforming commercial and laboratory synthesized hand sanitizer samples. Principal component analysis (PCA) was applied in an exploratory data study. Three principal components accounted for 99% of data variance and demonstrate clustering of conforming and non-conforming samples. The PLS–DA and SPA–LDA classification models presented 77 and 100% of accuracy in cross/internal validation respectively and 100% of accuracy in the classification of test samples. A total of 43% commercial samples evaluated using the PLS–DA and SPA–LDA presented ethanol content non-conforming for hand sanitizer gel. These results indicate that use of NIR spectroscopy and chemometrics is a promising strategy, yielding a method that is fast, portable, and reliable for discrimination of alcohol-based hand sanitizers with respect to conforming and non-conforming ethanol concentrations.


2018 ◽  
Vol 10 (4) ◽  
pp. 351
Author(s):  
João S. Panero ◽  
Henrique E. B. da Silva ◽  
Pedro S. Panero ◽  
Oscar J. Smiderle ◽  
Francisco S. Panero ◽  
...  

Near Infrared (NIR) Spectroscopy technique combined with chemometrics methods were used to group and identify samples of different soy cultivars. Spectral data, collected in the range of 714 to 2500 nm (14000 to 4000 cm-1), were obtained from whole grains of four different soybean cultivars and were submitted to different types of pre-treatments. Chemometrics algorithms were applied to extract relevant information from the spectral data, to remove the anomalous samples and to group the samples. The best results were obtained considering the spectral range from 1900.6 to 2187.7 nm (5261.4 cm-1 to 4570.9 cm-1) and with spectral treatment using Multiplicative Signal Correction (MSC) + Baseline Correct (linear fit), what made it possible to the exploratory techniques Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) to separate the cultivars. Thus, the results demonstrate that NIR spectroscopy allied with de chemometrics techniques can provide a rapid, nondestructive and reliable method to distinguish different cultivars of soybeans.


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