Effect of Temperature on Near-infrared Spectra ofn-Alkanes

2016 ◽  
Vol 74 (2) ◽  
pp. 172 ◽  
Author(s):  
Lihua Qi ◽  
Wensheng Cai ◽  
Xueguang Shao
Keyword(s):  
Infrared Spectra ◽  
Near Infrared ◽  
Effect Of Temperature ◽  
Near Infrared Spectra

The use of two-dimensional spectroscopy to interpret the effect of temperature on the near infrared spectra of whisky

2020 ◽  
Vol 28 (3) ◽  
pp. 148-152 ◽  
Author(s):  
Ishita Joshi ◽  
Vi Khanh Truong ◽  
J Chapman ◽  
D Cozzolino
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Infrared Spectra ◽  
Near Infrared ◽  
Infrared Region ◽  
Correlation Spectroscopy ◽  
Alcoholic Beverages ◽  
Effect Of Temperature ◽  
Two Dimensional ◽  
Near Infrared Spectra

The variations in temperature during the analysis of alcoholic beverages are of importance to develop protocols based on near infrared spectroscopy. The objective of this study was to evaluate the effect of increasing temperature on the near infrared spectra of whisky samples using two-dimensional correlation spectroscopy. Whisky samples from different commercial labels were analyzed at four different temperatures (25°C, 35°C, 45°C, and 55°C) using a UV–VIS–NIR instrument. Asynchronous and synchronous two-dimensional correlation spectroscopy was used to reveal the effect of temperature on the near infrared spectra of the samples. The results of this study indicated that temperatures between 40°C and 55°C alter absorption at specific wavelengths in the near infrared region of the whisky samples analyzed. The combination of near infrared spectroscopy with two-dimensional correlation spectroscopy has the potential to dramatically improve the efficiency of analytical laboratories, considering the range of data that can be collected.

Effect of temperature and age on near infrared spectra of amino resins

2021 ◽  
pp. 096703352098236
Author(s):  
M Gonçalves ◽  
NT Paiva ◽  
JM Ferra ◽  
J Martins ◽  
F Magalhães ◽  
...  
Keyword(s):  
Infrared Spectra ◽  
Near Infrared ◽  
Effect Of Temperature ◽  
Molar Ratio ◽  
Near Infrared Spectra ◽  
Scattering Correction ◽  
Before And After ◽  
Two Factors ◽  
Different Temperatures ◽  
Linear Fit

Quality control of amino resins must be based on reproducible and rapid methods. Fourier-transform near infrared spectroscopy (FT-NIR) has been gaining increasing interest in this context. However, it is not always possible to perform the analysis under the same conditions. Temperature and storage time, in particular, are two factors that often vary. However, their influence on the FT-NIR results is not yet well understood. This work describes how temperature and resin ageing affect the near infrared spectra of amino resins. It is shown that a previously calibrated near infrared model to assess the molar ratio of amino resins has a linear response with temperature. To counter-act this effect and improve the speed of analysis, the spectral pre-processing of extended multiplicative scattering correction was used in conjunction with the loadings of water at different temperatures. This procedure was able to diminish the dependency of the model in relation to temperature for two amino resins (an R2 above 95 % of a linear fit went down to below 1%). With respect to the ageing of amino resins, NIR spectra of two resins were examined for a period of 9 days. It was found that the spectra are influenced by the continuation of the condensation reactions and the formation of aggregates, which causes increase in absorbance with resin ageing. This was proven by checking the differences between NIR spectra of amino resins before and after being subjected to ultrasonic treatment to promote deagglomeration.

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.

Discrimination of transgenic tomatoes based on visible/near-infrared spectra

2007 ◽  
Vol 584 (2) ◽  
pp. 379-384 ◽  
Author(s):  
Lijuan Xie ◽  
Yibin Ying ◽  
Tiejin Ying ◽  
Haiyan Yu ◽  
Xiaping Fu
Keyword(s):  
Infrared Spectra ◽  
Near Infrared ◽  
Near Infrared Spectra ◽  
Transgenic Tomatoes

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.

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