Determination of ß-Carotene and Lutein in Green Tea Using Fourier Transform Infrared Spectroscopy

2019 ◽  
Vol 62 (1) ◽  
pp. 75-81 ◽  
Author(s):  
Yong He ◽  
Yong He ◽  
Yiying Zhao ◽  
Chu Zhang ◽  
Chanjun Sun ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Ir Spectroscopy ◽  
Least Squares ◽  
Fourier Transform Infrared Spectroscopy ◽  
Green Tea ◽  
Fourier Transform Infrared ◽  
Support Vector ◽  
Ft Ir ◽  
Ft Ir Spectroscopy

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.

scholarly journals Classification of Five Kinds of Moss Plants with the Use of Fourier Transform Infrared Spectroscopy and Chemometrics

2011 ◽  
Vol 25 (6) ◽  
pp. 271-285 ◽  
Author(s):  
Tao Hu ◽  
Wen-Ying Jin ◽  
Cun-Gui Cheng
Keyword(s):  
Cluster Analysis ◽  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Ir Spectroscopy ◽  
Ir Spectra ◽  
Fourier Transform Infrared Spectroscopy ◽  
Moss Species ◽  
Ft Ir ◽  
And Cluster Analysis ◽  
Ft Ir Spectroscopy

Fourier transform infrared spectroscopy (FT-IR) with Horizontal Attenuated Total Reflectance (HATR) techniques is used to obtain the FT-IR spectra of five kinds of mosses, such asPtychomitrium dentatum(Mitt.) Jaeg.,Ptychomitrium polyphylloides(C. Muell.) Par.,Ptychomitrium sinense(Mitt.) Jaeg.,Macromitrium syntrichophyllumTher. Etp. Vard., andMacromitrium ferrieiCard. Sz Ther. Based on the comparison of the above mosses in the FT-IR spectra, the region ranging from 4000 to 650 cm−1was selected as the characteristic spectra for analysis. Principal component analysis (PCA) and cluster analysis are considered to identify the five moss species. Because they belong to the homogeneous plants, and have similar chemical components and close FT-IR spectroscopy, PCA and cluster analysis can only give a rough result of classification among the five moss species, Fourier self-deconvolution (FSD) and discrete wavelet transform (DWT) methods are used to enhance the differences between them. We use these methods for further study. Results show that it is an excellent method to use FT-IR spectroscopy combined with FSD and DWT to classify the different species in the same family. FT-IR spectroscopy combined with chemometrics, such as FSD and DWT, can be used as an effective tool in systematic research of bryophytes.

Fourier Transform Infrared Spectroscopy (FT-IR) in Archaeological Ceramic Analysis

2016 ◽  
pp. 508-530
Author(s):  
Shlomo Shoval
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Fourier Transform Infrared Spectroscopy ◽  
Mineralogical Composition ◽  
Fourier Transform Infrared ◽  
Ceramic Analysis ◽  
Archaeological Ceramic ◽  
Ft Ir ◽  
Non Destructive ◽  
Ft Ir Spectroscopy

The chapter reviews the use of Fourier Transform Infrared Spectroscopy (FT-IR) in study of ancient pottery and its applications to archaeology. FT-IR is a powerful technique for assessing the mineralogical composition of ancient ceramics and is, almost, non-destructive for the pottery. This method can be applied in analyses of the composition of the bulk ceramic as well as of particular pottery attributes, such as separated pastes, temper particles, binders, glazes, slips, paints, and pigments. FT-IR spectroscopy has the advantage of being able to detect both, the crystalline minerals as well as the pseudo-amorphous fired-clay in the ceramic fabric. The assessing of the mineralogical composition of the ceramics can be used in their classification, sourcing, and estimation of firing temperature. Applying spectral analysis by second-derivative and curve-fitting techniques is adding a quantitative dimension to the mineralogical analysis.

scholarly journals Exploratory Study on Screening Chronic Renal Failure Based on Fourier Transform Infrared Spectroscopy and a Support Vector Machine Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Yushuai Yuan ◽  
Li Yang ◽  
Rui Gao ◽  
Cheng Chen ◽  
Min Li ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Renal Failure ◽  
Fourier Transform ◽  
Chronic Renal Failure ◽  
Ir Spectroscopy ◽  
Fourier Transform Infrared ◽  
Diagnostic Methods ◽  
Support Vector ◽  
Ft Ir ◽  
Ft Ir Spectroscopy

Chronic renal failure (CRF) is a clinically serious kidney disease. If the patient is not treated in a timely manner, CRF will develop into uremia. However, current diagnostic methods, such as routine blood examinations and medical imaging, have low sensitivity. Therefore, it is important to explore new and effective diagnostic methods for CRF, such as serum spectroscopy. This study proposes a cost-effective and reliable method for detecting CRF based on Fourier transform infrared (FT-IR) spectroscopy and a support vector machine (SVM) algorithm. We measured and analyzed the FT-IR spectra of serum from 44 patients with CRF and 54 individuals with normal renal function. The partial least squares (PLS) algorithm was applied to reduce the dimensionality of the high-dimensional spectral data. The samples were input into the SVM after division by the Kennard–Stone (KS) algorithm. Compared with other models, the SVM optimized by a grid search (GS) algorithm performed the best. The sensitivity of our diagnostic model was 93.75%, the specificity was 100%, and the accuracy was 96.97%. The results demonstrate that FT-IR spectroscopy combined with a pattern recognition algorithm has great potential in screening patients with CRF.

scholarly journals Discrimination of Enterobacterial Repetitive Intergenic Consensus PCR Types of Campylobacter coli and Campylobacter jejuni by Fourier Transform Infrared Spectroscopy

2005 ◽  
Vol 71 (8) ◽  
pp. 4318-4324 ◽  
Author(s):  
D. J. M. Mouwen ◽  
M. J. B. M. Weijtens ◽  
R. Capita ◽  
C. Alonso-Calleja ◽  
M. Prieto
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Discriminant Analysis ◽  
Ir Spectroscopy ◽  
Fourier Transform Infrared Spectroscopy ◽  
Campylobacter Jejuni ◽  
Campylobacter Coli ◽  
Enterobacterial Repetitive Intergenic Consensus ◽  
Ft Ir ◽  
Ft Ir Spectroscopy

ABSTRACT Fourier transform infrared spectroscopy (FT-IR) has been used together with pattern recognition methodology to study isolates belonging to the species Campylobacter coli and Campylobacter jejuni and to compare FT-IR typing schemes with established genomic profiles based on enterobacterial repetitive intergenic consensus PCR (ERIC-PCR). Seventeen isolates were cultivated under standardized conditions for 2, 3, and 4 days to study variability and improve reproducibility. ERIC-PCR profiles and FT-IR spectra were obtained from strains belonging to the species Campylobacter coli and C. jejuni, normalized, and explored by hierarchical clustering and stepwise discriminant analysis. Strains could be differentiated by using mainly the first-derivative FT-IR spectral range, 1,200 to 900 cm−1 (described as the carbohydrate region). The reproducibility index varied depending on the ages of the cultures and on the spectral ranges investigated. Classification obtained by FT-IR spectroscopy provided valuable taxonomic information and was mostly in agreement with data from the genotypic method, ERIC-PCR. The classification functions obtained from the discriminant analysis allowed the identification of 98.72% of isolates from the validation set. FT-IR can serve as a valuable tool in the classification, identification, and typing of thermophilic Campylobacter isolates, and a number of types can be differentiated by means of FT-IR spectroscopy.

scholarly journals Prediction of anthocyanin concentrations during red wine fermentation: development of Fourier transform infrared spectroscopy partial least squares models

OENO One ◽  
2019 ◽  
Vol 53 (4) ◽  
Author(s):  
Clément Miramont ◽  
Michael Jourdes ◽  
Torben Selberg ◽  
Henrik Vilstrup Juhl ◽  
Lars Nørgaard ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Ir Spectroscopy ◽  
Least Squares ◽  
Partial Least Squares ◽  
High Performance ◽  
Red Wine ◽  
Fourier Transform Infrared ◽  
Ft Ir ◽  
Predicted Values ◽  
Ft Ir Spectroscopy

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.

Quick determination of melamine in infant powder and liquid milk by Fourier transform infrared spectroscopy

2014 ◽  
Vol 6 (14) ◽  
pp. 5269-5273 ◽  
Author(s):  
Sana Jawaid ◽  
Farah N. Talpur ◽  
Hassan Imran Afridi ◽  
Shafi M. Nizamani ◽  
Abid A. Khaskheli ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Ir Spectroscopy ◽  
Cost Effective ◽  
Fourier Transform Infrared ◽  
Ft Ir ◽  
Liquid Milk ◽  
Quick Determination ◽  
Ft Ir Spectroscopy

A simple, cost-effective and environmentally friendly analytical method was developed for the quantification of melamine (MEL) in liquid milk and infant powder by using transmission Fourier transform infrared (FT-IR) spectroscopy.

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