Two-Dimensional Vibration Spectroscopy: Correlation of Mid- and Near-Infrared Regions

1992 ◽  
Vol 46 (3) ◽  
pp. 420-429 ◽  
Author(s):  
F. E. Barton ◽  
D. S. Himmelsbach ◽  
J. H. Duckworth ◽  
M. J. Smith
Keyword(s):  
Cross Correlation ◽  
Near Infrared ◽  
Lignin Content ◽  
Statistical Correlation ◽  
Two Dimensional ◽  
Mid Infrared ◽  
Spectral Interpretation ◽  
Novel Approach ◽  
Near Infrared Spectra ◽  
Vibration Spectroscopy

A novel approach, utilizing a two-dimensional (2D) statistical correlation of mid- and near-infrared spectra, is presented as a means to assist with qualitative spectral interpretation. The method utilizes cross-correlation by least-squares to assess changes in both regions that result from changes in sample composition. The technique has been applied to complex agricultural samples that differ in wax (cuticle), carbohydrate, protein, and lignin content. Dispersive near-infrared (NIR) and interferometric mid-infrared (FT-IR) diffuse reflectance spectra were obtained on each of the samples, and point-for-point 2D cross-correlation was obtained. The technique permits the correlation of the combination and overtone region of the NIR to the fundamental vibrations in the mid-infrared (MIR) region. This allows the determination of the most probable source of NIR signals and verification of the “real” information content of the purely statistically derived signals whose intensities currently are used for quantitative analysis in this spectral region.

Two-Dimensional Vibrational Spectroscopy II: Correlation of the Absorptions of Lignins in the Mid- and Near-Infrared

1993 ◽  
Vol 47 (11) ◽  
pp. 1920-1925 ◽  
Author(s):  
F. E. Barton ◽  
D. S. Himmelsbach
Keyword(s):  
Cross Correlation ◽  
Near Infrared ◽  
Lignin Content ◽  
Statistical Correlation ◽  
Two Dimensional ◽  
Plant Materials ◽  
Mid Infrared ◽  
Spectral Interpretation ◽  
Near Infrared Spectra ◽  
Ft Ir

Two-dimensional (2D) statistical correlation of mid- and near-infrared spectra was used as a means to assist with qualitative spectral interpretation of the lignin carbohydrate fractions from plant materials. Cross-correlation by least-squares is used to assess changes in both regions that result from changes in the set of sample spectra. The technique has been applied to a set of specially prepared “lignin” samples that differ in lignin content, species of origin, and method of preparation. Dispersive near-infrared (NIR) and Fourier transformed mid-infrared (FT-IR) diffuse reflectance spectra (DRIFTS) were obtained on each of the samples, and point-for-point 2D cross-correlation was obtained. The technique permits the correlation of the combination and overtone bands of the NIR region with the fundamental vibrations in the mid-infrared (MIR) region. The results show a broad correlation of aromatic C-H stretch at 3022 cm−1 in the MIR to 1666-nm location in the NIR region and other locations to a lesser extent all across the NIR from 1400 to 2500 nm. A narrower region of correlation was found for the phenolic O-H stretch in the MIR at 3663 cm−1 to 1428 nm and 1938 nm in the MIR. Multiple narrow correlations occur in the area of the summation bands from 1450 to 1650 cm−1, indicative of substitution patterns and correlated areas of C-H and O-H stretch in the NIR.

Mid and near Infrared Study of Carbohydrates by Canonical Correlation Analysis

1993 ◽  
Vol 1 (2) ◽  
pp. 99-108 ◽  
Author(s):  
P. Robert ◽  
M.F. Devaux ◽  
A. Qannari ◽  
M. Safar
Keyword(s):  
Correlation Analysis ◽  
Infrared Spectra ◽  
Canonical Correlation ◽  
Near Infrared ◽  
Sugar Content ◽  
Infrared Region ◽  
Total Sugar ◽  
Mid Infrared ◽  
Total Sugar Content ◽  
Near Infrared Spectra

Multivariate data treatments were applied to mid and near infrared spectra of glucose, fructose and sucrose solutions in order to specify near infrared frequencies that characterise each carbohydrate. As a first step, the mid and near infrared regions were separately studied by performing Principal Component Analyses. While glucose, fructose and sucrose could be clearly identified on the similarity maps derived from the mid infrared spectra, only the total sugar content of the solutions was observed when using the near infrared region. Characteristic wavelengths of the total sugar content were found at 2118, 2270 and 2324 nm. In a second step, the mid and near infrared regions were jointly studied by a Canonical Correlation Analysis. As the assignments of frequencies are generally well known in the mid infrared region, it should be useful to study the relationships between the two infrared regions. Thus, the canonical patterns obtained from the near infrared spectra revealed wavelengths that characterised each carbohydrate. The OH and CH combination bands were observed at: 2088 and 2332 nm for glucose, 2134 and 2252 nm for fructose, 2058 and 2278 nm for sucrose. Although a precise assignment of the near infrared bands to chemical groups within the molecules was not possible, the present work showed that near infrared spectra of carbohydrates presented specific features.

Use of Near-Infrared–Mid-Infrared Dual-Wavelength Spectrometry to Obtain Two-Dimensional Difference Spectra of Sesame Oil as Inactive Drug Ingredient

2020 ◽  
pp. 000370282096919
Author(s):  
Masahiro Watari ◽  
Akifumi Nagamoto ◽  
Takuma Genkawa ◽  
Shigeaki Morita
Keyword(s):  
Room Temperature ◽  
Near Infrared ◽  
Sesame Oil ◽  
Partial Least Square ◽  
Dual Wavelength ◽  
Two Dimensional ◽  
Difference Spectra ◽  
Mid Infrared ◽  
Starting Point ◽  
Drug Ingredient

The present study has investigated the transformation of sesame oil kept at low temperature during a definite period of time for refinement (called winterization) as an inactive drug ingredient by using two-dimensional difference spectra (2D-DS) analysis of spectra collected using a near-infrared (NIR) and mid-infrared (MIR) dual-wavelength spectrometer (NIR–MIR-DWS). The NIR and MIR spectra were measured nearly simultaneously from samples of sesame oil before and after winterization. The difference spectrum analysis of the obtained NIR–MIR data elucidated that, after the winterization process, the absorbances at peaks attributed to C=O, C=C, and OH groups decrease while the absorbances arising from the main chain (CH2) increase. The result indicated the removal of lignan and the fatty acids with relatively short main chains. Moreover, sesame oil unwinterized was cooled from room temperature to near 1 ℃ and subsequently warmed to room temperature. And the cycle was repeated two times. Real-time monitoring during the cooling and warming processes were carried out using the NIR-MIR-DWS. The prediction results obtained from partial least square calibration model for the temperature suggests that there are subtle differences in the oil composition between the first cooling process and after the warming and cooling cycle. For the more detailed analysis, the 2D-DS method is proposed. The results of the analyses using 2D-DS revealed that the starting point of the transformation is around 15 ℃. It can be estimated that sesame oil is mainly transformed by the first cooling down. Moreover, it was implied that the structure of methylene (CH2) was significantly related to the modifications in sesame oil with temperature change. A series of experimental results elucidated that the winterization of sesame oil removed its impurities and stabilized its conditions. These results are probably the first report on the effect of the winterization process on sesame oil.

The Effect of Chain Length on Mid-Infrared and Near-Infrared Spectra of Aliphatic 1-Alcohols

2017 ◽  
Vol 72 (2) ◽  
pp. 288-296 ◽  
Author(s):  
Michał Kwaśniewicz ◽  
Mirosław A. Czarnecki
Keyword(s):  
Correlation Analysis ◽  
Chain Length ◽  
Near Infrared ◽  
Hydrophobic Interactions ◽  
Principal Component ◽  
Butyl Alcohol ◽  
Two Dimensional ◽  
Data Set ◽  
Mid Infrared ◽  
Spectral Changes

Effect of the chain length on mid-infrared (MIR) and near-infrared (NIR) spectra of aliphatic 1-alcohols from methanol to 1-decanol was examined in detail. Of particular interest were the spectra-structure correlations in the NIR region and the correlation between MIR and NIR spectra of 1-alcohols. An application of two-dimensional correlation analysis (2D-COS) and chemometric methods provided comprehensive information on spectral changes in the data set. Principal component analysis (PCA) and cluster analysis evidenced that the spectra of methanol, ethanol, and 1-propanol are noticeably different from the spectra of higher 1-alcohols. The similarity between the spectra increases with an increase in the chain length. Hence, the most similar are the spectra of 1-nonanol and 1-decanol. Two-dimensional hetero-correlation analysis is very helpful for identification of the origin of bands and may guide selection of the best spectral ranges for the chemometric analysis. As shown, normalization of the spectra pronounces the intensity changes in various spectral regions and provides information not accessible from the raw data. The spectra of alcohols cannot be represented as a sum of the CH3, CH2, and OH group spectra since the OH group is involved in the hydrogen bonding. As a result, the spectral changes of this group are nonlinear and its spectral profile cannot be properly resolved. Finally, this work provides a lot of evidence that the degree of self-association of 1-alcohols decreases with the increase in chain length because of the growing meaning of the hydrophobic interactions. For butyl alcohol and higher 1-alcohols the hydrophobic interactions are more important than the OH OH interactions. Therefore, methanol, ethanol, and 1-propanol have unlimited miscibility with water, whereas 1-butanol and higher 1-alcohols have limited miscibility with water.

Determination of Protein in Ground Wheat Samples by Mid-Infrared Diffuse Reflectance Spectroscopy

1997 ◽  
Vol 51 (8) ◽  
pp. 1200-1204 ◽  
Author(s):  
James B. Reeves ◽  
Stephen R. Delwiche
Keyword(s):  
Protein Content ◽  
Infrared Spectra ◽  
Diffuse Reflectance ◽  
Near Infrared ◽  
Diffuse Reflectance Spectroscopy ◽  
Reflectance Spectroscopy ◽  
Mid Infrared ◽  
Near Infrared Spectra ◽  
Hard Red Winter Wheat ◽  
Ground Wheat

The objective of this study was to determine whether mid-infrared diffuse reflectance spectroscopy could be used in the same manner as near-infrared diffuse reflectance spectroscopy to quantitatively determine the protein content of ground wheat samples. One hundred and thirty hard red winter wheat samples were assayed for protein by combustion and scanned in the near- and mid-infrared. Samples (UDY ground) were scanned neat in the near-infrared from 1100 nm (9091 cm−1) to 2498 nm (4003 cm−1) on a scanning monochromator and in the mid-infrared from 4000 cm−1 (2500 nm) to 400 cm−1 (25,000 nm) on a Fourier transform spectrometer at 4-and 16-cm−1 resolutions. Protein content varied from a low of 8.98% to a high of 18.70% (average of 12.86% with a standard deviation of 1.66%). Calibrations developed with the use of partial least-squares gave an R2 and bias-corrected standard error of performance of 0.999 and 0.054 for the near-infrared and 0.997 and 0.085 for the mid-infrared (4 cm−1 resolution). Calibration results based on mid-infrared spectra, while not as good as those for near-infrared spectra, were nevertheless quite good. These results demonstrate that it is possible to develop satisfactory calibrations for protein in ground wheat with the use of mid-infrared spectra without the need for sample dilution with KBr.

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