In Situ Attenuated Total Reflectance Fourier Transform Infrared (ATR FT-IR) Spectroscopy Monitoring of 1,2-Butylene Oxide Polymerization Reaction by Using Iterative Concentration-Guided Classical Least Squares

2013 ◽  
Vol 67 (8) ◽  
pp. 940-948 ◽  
Author(s):  
Xiaoyun Chen ◽  
Randy Pell ◽  
Sagar Sarsani ◽  
Brian Cramm ◽  
Carlos Villa ◽  
...  
2015 ◽  
Vol 7 (2) ◽  
pp. 736-746 ◽  
Author(s):  
S. Assi ◽  
A. Guirguis ◽  
S. Halsey ◽  
S. Fergus ◽  
J. L. Stair

Three handheld spectrometers, near-infrared (NIR), Raman and attenuated total reflectance Fourier transform-infrared (ATR-FT-IR) spectroscopy, were used for the identification of ‘legal high’ model mixtures and Internet products.


2019 ◽  
Vol 62 (1) ◽  
pp. 75-81 ◽  
Author(s):  
Yong He ◽  
Yong He ◽  
Yiying Zhao ◽  
Chu Zhang ◽  
Chanjun Sun ◽  
...  

Abstract. The feasibility of using Fourier transform infrared (FT-IR) spectroscopy combined with chemometrics to determine the ß-carotene and lutein contents in green tea was investigated in this study. The relationship between pigment contents and spectral responses was explored by partial least squares (PLS), least squares support vector machine (LS-SVM), and extreme learning machine (ELM) methods. Next, 30 and 29 effective wavenumbers (EWs) for ß-carotene and lutein, respectively, were selected according to the weighted regression coefficients of the PLS regression models, and simplified determinant models were built on the extracted EWs. The ELM models based on the EWs obtained the best results, with correlation coefficients of calibration (rc) and prediction (rp), and residual prediction deviation (RPD) of 0.977, 0.946, and 2.84, respectively, for ß-carotene and 0.975, 0.937, and 2.88, respectively, for lutein. The overall results indicate that FT-IR spectroscopy combined with chemometrics could be a rapid and accurate alternative method for determining carotenoid pigments in green tea. Keywords: ß-carotene, Chemometrics, Fourier transform infrared spectroscopy, Green tea, Lutein.


OENO One ◽  
2019 ◽  
Vol 53 (4) ◽  
Author(s):  
Clément Miramont ◽  
Michael Jourdes ◽  
Torben Selberg ◽  
Henrik Vilstrup Juhl ◽  
Lars Nørgaard ◽  
...  

Aim: The aim of the present study was to use Fourier transform infrared (FT–IR) spectroscopy with chemometrics to develop partial least squares (PLS) models to predict the concentrations of various anthocyanins during red wine fermentation.Methods and results: Must and wine samples were collected during fermentation. To maximize diversity, 12 different fermentations, of two different vintages and two different varieties, were followed. The anthocyanin composition of the samples was characterized by using different methods described in the literature: the concentration of free anthocyanins was determined by bisulphite bleaching, the concentration of molecular anthocyanins was determined by high-performance liquid chromatography with ultraviolet–visible detection, and the ratio of monomeric anthocyanins to polymeric anthocyanins was determined using the Adams–Harbertson assay. Finally, the data were analysed statistically by PLS regression to quantify laboratory-determined anthocyanin from FT–IR spectra. The correlations obtained showed good results for a large percentage of parameters studied, with the determination coefficient (R2) for both calibration and cross-validation exceeding 0.8. The models for molecular anthocyanins appeared to overestimate their prediction, owing to intercorrelation with other parameters. Comparison of the data for each vintage indicated no apparent matrix effect per year, and data for other vintages should be compared to validate this hypothesis. The best models were those for monomeric or polymeric pigments and free anthocyanins.Conclusions: By using FT–IR spectroscopy coupled with chemometrics, it is possible to create predictive models to estimate concentrations of anthocyanins and changes in global anthocyanin parameters during winemaking.Significance and impact of the study: These results improve our understanding of anthocyanin prediction using FT–IR spectroscopy with chemometrics and pave the way for its use as a process control tool for the winemaker. They also highlight the propensity of chemometrics to overestimate certain predicted values when close parameters intercorrelate.


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