Efforts to Quantify Changes in Near-Infrared Spectra Caused by the Influence of Water, pH, Ionic Strength, and Differences in Physical State

1995 ◽  
Vol 49 (2) ◽  
pp. 181-187 ◽  
Author(s):  
James B. Reeves
Keyword(s):  
Amino Acids ◽  
Ionic Strength ◽  
Infrared Spectra ◽  
Physical State ◽  
Near Infrared ◽  
Near Ir ◽  
Near Infrared Spectra ◽  
Influence Of Water ◽  
Water Ph ◽  
Crystalline Sugars

The application of near-infrared spectroscopy to high-moisture samples has shown that the accuracy does not match that found for dried materials. The objective of this work was to attempt to quantify the effects of water, pH, ionic strength, and differences in physical state on near-infrared spectra with the use of model compounds. Spectra were compared by regression analysis of second derivatives after spectral subtraction of water. Spectra from 4900 to 4100 cm−1 at a resolution of 4 cm−1 were examined. Regression results showed spectra to be more similar among amorphous sugars and among dissolved sugars than among crystalline sugars. Also, spectra of amorphous sugars were statistically more similar to spectra of dissolved sugars than to spectra of crystalline sugars. While the spectra of one dissolved or amorphous sugar were statistically similar, this was not true for amino acids. Spectra of amorphous amino acids were similar to those of crystalline forms and neither were similar to those of dissolved forms. Spectrally, polymeric carbohydrates appeared very similar to one another when dry and behaved like amino acids when wet. Finally, efforts to directly relate these findings to near-IR spectroscopy calibration problems will require further research.

Influence of Water on the Near Infrared Spectra of Model Compounds

1993 ◽  
Vol 76 (4) ◽  
pp. 741-748 ◽  
Author(s):  
James B Reeves III
Keyword(s):  
Amino Acids ◽  
Infrared Spectra ◽  
Physical State ◽  
Near Infrared ◽  
Spectral Features ◽  
Fourier Transform Spectrometer ◽  
High Moisture ◽  
Model Compounds ◽  
Near Infrared Spectra ◽  
Influence Of Water

Abstract The application of near infrared spectroscopy (NIRS) to high-moisture samples (i.e., silages) has shown that accuracy does not match that of dried materials. Examination of spectra does not indicate absorbance levels to be the problem. The objective of this effort was to determine the effect of water on the spectra of model compounds. Near infrared spectra were taken using a Digi-Lab FTS-65 Fourier transform spectrometer. Liquids were examined by transmission and solids by reflectance. Examination of organic acids, alcohols, ketones, amines, and amides showed that the presence of water causes shifts in spectral wavelengths not related to OH or NH groups. The most significant shifts were for alcohols and ketones (up to 10+ nm at 90% H2O) and least for acids. These peak shifts increased with increasing amounts of water and varied within individual spectra and among the compounds tested. As solids, sugars and amino acids had many sharp peaks in their spectra. As solutions, however, the sharp spectral features disappeared, resulting in large broad peaks. The spectra of polymers such as starch, cellulose, and casein did not appear to be significantly altered by the presence of water (0-50%, w/w), although they often appear to alter the water spectra. Variations in water content, physical state, and concentrations of components, when combined with these results, may help

Near- versus Mid-Infrared Spectroscopy: Relationships between Spectral Changes Induced by Water and Relative Information Content of the Two Spectral Regions in Regard to High-Moisture Samples

1995 ◽  
Vol 49 (3) ◽  
pp. 295-303 ◽  
Author(s):  
James B. Reeves
Keyword(s):  
Infrared Spectra ◽  
Near Infrared ◽  
High Moisture ◽  
Mid Infrared ◽  
Spectral Changes ◽  
Near Infrared Spectra ◽  
Infrared Spectral ◽  
Water Ph ◽  
Relative Information Content ◽  
Relationship Of

The objectives of this work were to examine similarities and differences in the near-infrared and mid-infrared spectral regions when one is working with high-moisture materials and to study spectral changes in these regions as a method to identify the relationship of spectral information in the near-IR to fundamental absorptions in the mid-IR. Near- and mid-infrared spectra were taken with a Digilab FTS-65 Fourier transform spectrometer. Liquids were examined by transmission and solids by reflectance. Results with solutions showed that less spectral distortion arises when one is subtracting water from mid- rather than from near-infrared spectra. It was also easier to produce high-quality spectra in the mid-infrared by using attenuated total reflectance than by using transmission in the near-infrared. While mid-infrared spectra showed changes (induced by water, pH, physical state, and ionic strength) similar to those found in the near-infrared, there appeared to be more information available in the mid-infrared, even in the presence of water.

Calibration Transfer for Predicting Lake-Water pH from near Infrared Spectra of Lake Sediments

1999 ◽  
Vol 7 (4) ◽  
pp. 251-264 ◽  
Author(s):  
Paul Geladi ◽  
Hans Bärring ◽  
Eigil Dåbakk ◽  
Johan Trygg ◽  
Henrik Antti ◽  
...  
Keyword(s):  
Lake Sediments ◽  
Infrared Spectra ◽  
Lake Water ◽  
Near Infrared ◽  
Calibration Transfer ◽  
Near Infrared Spectra ◽  
Water Ph

Fuzzy Optimal Associative Memory for Background Prediction of Near-Infrared Spectra

1996 ◽  
Vol 50 (1) ◽  
pp. 35-42 ◽  
Author(s):  
Busolo Wa Wabuyele ◽  
Peter De B. Harrington
Keyword(s):  
Associative Memory ◽  
Infrared Spectra ◽  
Plasma Glucose ◽  
Near Infrared ◽  
Second Derivative ◽  
Derivative Spectra ◽  
Near Ir ◽  
Near Infrared Spectra ◽  
Calibration Models ◽  
Second Derivative Spectra

A fuzzy optimal associative memory (FOAM) has been devised for background correction of near-infrared spectra. The FOAM yields improved predicted background scans for calculation of near-IR absorbance spectra of glucose in plasma matrices from single-beam data. The FOAM is an enhanced optimal associative memory (OAM) that uses a fuzzy function for encoding the spectra. The FOAM can predict a matching reference spectrum for a near-IR absorbance spectrum with low glucose absorbances by using second-derivative spectra. Glucose concentrations were predicted from calibration models furnished by partial least-squares (PLS). The FOAM stored reference spectra obtained from either water/phosphate buffer or plasma/glucose solutions. Both of these associative memories were evaluated. The standard error of prediction (SEP) for glucose concentration from an optimal PLS calibration model based on FOAM-corrected spectra was 0.60 mM for the water/phosphate buffer spectra. For FOAM-corrected spectra from plasma/glucose reference spectra, the SEP was 0.68 mM. The SEP of conventionally corrected double-beam second-derivative spectra was 0.81 mM. FOAM-corrected spectra generally furnish improved calibration models.

scholarly journals Evolution of Brown Dwarf Atmospheres: Investigating Physical Parameters from Near-IR Spectra

2003 ◽  
Vol 211 ◽  
pp. 417-418
Author(s):  
Nadya Gorlova ◽  
Michael R. Meyer ◽  
Jim Liebert ◽  
George H. Rieke
Keyword(s):  
Ir Spectra ◽  
Infrared Spectra ◽  
Near Infrared ◽  
Surface Gravity ◽  
Physical Parameters ◽  
Brown Dwarf ◽  
Near Ir ◽  
Near Infrared Spectra ◽  
Low Mass

We obtained near–infrared spectra of a sample of very low mass objects as a function of age in order to investigate the temperature and surface gravity sensitivity of several features in the J– and K–bands.

Influence of pH, Ionic Strength, and Physical State on the Near-Infrared Spectra of Model Compounds

1994 ◽  
Vol 77 (4) ◽  
pp. 814-820 ◽  
Author(s):  
James B Reeves
Keyword(s):  
Ionic Strength ◽  
Physical State ◽  
Near Infrared ◽  
Water Concentration ◽  
Model Compounds ◽  
Near Infrared Spectra ◽  
Freeze Dried ◽  
Crystalline Forms ◽  
Influence Of Ph ◽  
Saturated Naci Solution

Abstract The accuracy of near-infrared spectroscopy (NIRS) when applied to high-moisture samples (i.e., silages) does not match that with dried materials. Previous work showed that the presence of water could cause shifts in the spectra of organic compounds, the degree of which depended on the material and the water concentration. For some solids, such as sugars, large spectral changes occur on dissolution. The objective of this study was to determine the effect of pH, ionic strength, and physical state on the NIR spectra of model compounds. The results show that pH has large effects on the spectra of amines and acids but little if any on the spectra of ketones, alcohols, and sugars. The spectra of peptides and proteins also were pH dependent, but that of cellulose was not. Ionic strength differences (deionized water vs saturated NaCI solution as the diluting media) had only minor or no effect on the spectra of the materials studied. The effect of physical state was far more complicated; the spectra of freeze-dried glucose and glycine were different from that of the crystalline forms, but the spectrum of serine was not. The spectra of molten compounds often appeared like those of solutions. These results, in agreement with earlier work, may explain the poorer performance of NIRS with wet materials compared with dry samples. They also have serious implications for the analysis of dried samples, if pH, ionic strength, or drying method varies among samples.

Rapid Determining Contents of the Rhubarb Anthraquinones Compounds by Support Vector Machines Modeling based on Near Infrared Spectra

2020 ◽  
Vol 16 ◽  
Author(s):  
Linqi Liu ◽  
JInhua Luo ◽  
Chenxi Zhao ◽  
Bingxue Zhang ◽  
Wei Fan ◽  
...  
Keyword(s):  
Infrared Spectra ◽  
Near Infrared ◽  
Mean Squared Error ◽  
Rapid Determination ◽  
Partial Least Square ◽  
Least Square ◽  
Support Vector ◽  
Near Infrared Spectra ◽  
Aloe Emodin ◽  
Relative Differences

BACKGROUND: Measuring medicinal compounds to evaluate their quality and efficacy has been recognized as a useful approach in treatment. Rhubarb anthraquinones compounds (mainly including aloe-emodin, rhein, emodin, chrysophanol and physcion) are its main effective components as purgating drug. In the current Chinese Pharmacopoeia, the total anthraquinones content is designated as its quantitative quality and control index while the content of each compound has not been specified. METHODS: On the basis of forty rhubarb samples, the correlation models between the near infrared spectra and UPLC analysis data were constructed using support vector machine (SVM) and partial least square (PLS) methods according to Kennard and Stone algorithm for dividing the calibration/prediction datasets. Good models mean they have high correlation coefficients (R2) and low root mean squared error of prediction (RMSEP) values. RESULTS: The models constructed by SVM have much better performance than those by PLS methods. The SVM models have high R2 of 0.8951, 0.9738, 0.9849, 0.9779, 0.9411 and 0.9862 that correspond to aloe-emodin, rhein, emodin, chrysophanol, physcion and total anthraquinones contents, respectively. The corresponding RMSEPs are 0.3592, 0.4182, 0.4508, 0.7121, 0.8365 and 1.7910, respectively. 75% of the predicted results have relative differences being lower than 10%. As for rhein and total anthraquinones, all of the predicted results have relative differences being lower than 10%. CONCLUSION: The nonlinear models constructed by SVM showed good performances with predicted values close to the experimental values. This can perform the rapid determination of the main medicinal ingredients in rhubarb medicinal materials.

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