Method for the Classification of Biological FT-IR Spectra Prior to Quantitative Analysis

1996 ◽  
Vol 50 (12) ◽  
pp. 1590-1596 ◽  
Author(s):  
Frédéric Cadet
Keyword(s):  
Ir Spectra ◽  
Principal Component Regression ◽  
Principal Component ◽  
Quantitative Measurements ◽  
Raw Sugar ◽  
Qualitative Classification ◽  
Ft Ir ◽  
The Mean ◽  
Euclidian Distances

Several methods have been proposed with the aim of improving the precision of quantitative measurements of biological components (baseline correction, classification, elimination of unwanted components, etc.). In this context, we propose a classification method of biological samples (raw sugar cane juices) before sucrose content prediction is performed. The method consisted of isolating the two most dissimilar individuals from a large calibration family of mid-FT-IR spectra, and, by successive principal component analysis (PCA) and principal component regression (PCR), a family composed of a few individuals was constituted. Each individual from this family represented the first spectrum of the corresponding classes that were ultimately formed. The classification of the remaining samples from the calibration family was carried out by the mobile centers method, that is, by the measurements of the Euclidian distances. This procedure improved the precision of the predictions. The mean and standard deviation (SD) of the differences between predicted and reference values were, respectively, −1.62 × 10−3 and 0.308 before classification and 2.38 × 10−3 and 0.254 after classification. The procedure developed in this paper first allowed a qualitative classification of spectra without knowledge of their chemical composition, and second, improved the precision of the quantitative predictions.

Classification of Vegetable Oils by FT-IR

1997 ◽  
Vol 51 (8) ◽  
pp. 1118-1124 ◽  
Author(s):  
Donald B. Dahlberg ◽  
Shawn M. Lee ◽  
Seth J. Wenger ◽  
Julie A. Vargo
Keyword(s):  
Ir Spectra ◽  
Principal Component ◽  
Fast Detection ◽  
Signal Correction ◽  
Ft Ir ◽  
Ir Detection ◽  
The Fourier Transform ◽  
Cooking Oils ◽  
Cis And Trans

The Fourier transform infrared (FT-IR) spectra of 27 brands of 10 types of cooking oils and margarines were measured without temperature control. Attempts to predict the vegetable source and physical properties of these oils failed until wavelength selection and multiplicative signal correction (MSC) were applied to the FT-IR spectra. After pretreatment of the data, principal component analysis (PCA) was totally successful at oil identification, and partial least-squares (PLS) models were able to predict both the refractive indices [standard error of estimation (SEE) 0.0002] and the viscosities (SEE 0.52 cP) of the oils. These models were based predominately on the FT-IR detection of the cis and trans double-bond content of the oils, as well as small amounts of defining impurities in sesame oils. Efforts to use selected wavelengths to discriminate oil sources were only partially successful. These results show the potential utility of FT-IR in the fast detection of substitution or adulteration of products like cooking oils.

scholarly journals Spectroscopy as a useful tool for the identification of changes with time in post-mortem vitreous humor for forensic toxicology purposes

2021 ◽  
Author(s):  
Anna Wójtowicz ◽  
Agata Mitura ◽  
Renata Wietecha-Posłuszny ◽  
Rafał Kurczab ◽  
Marcin Zawadzki
Keyword(s):  
Ir Spectra ◽  
Forensic Toxicology ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Vitreous Humor ◽  
Attenuated Total Reflection ◽  
Glass Slides ◽  
Added Benefit ◽  
Ft Ir ◽  
Non Destructive

AbstractVitreous humor (VH) is an alternative biological matrix with a great advantage of longer availability for analysis due to the lack of many enzymes. The use of VH in forensic toxicology may have an added benefit, however, this application requires rapid, simple, non-destructive, and relatively portable analytical analysis methods. These requirements may be met by Fourier transform infrared spectroscopy technique (FT-IR) equipped with attenuated total reflection accessory (ATR). FT-IR spectra of vitreous humor samples, deposited on glass slides, were collected and subsequent chemometric data analysis by means of Hierarchical Cluster Analysis and Principal Component Analysis was conducted. Differences between animal and human VH samples and human VH samples stored for diverse periods of time were detected. A kinetic study of changes in the VH composition up to 2 weeks showed the distinction of FT-IR spectra collected on the 1st and 14th day of storage. In addition, data obtained for the most recent human vitreous humor samples—collected 3 and 2 years before the study, presented successful discrimination of all time points studied. The method introduced was unable to detect mephedrone addition to VH in the concentration of 10 µg/cm3. Graphic abstract

Chemometric Approach to a Rapid Attenuated Total Reflection Fourier Transform Infrared Analysis of Complex Heroin-Based Mixtures

2020 ◽  
pp. 000370282096971
Author(s):  
Nataša Radosavljević Stevanović ◽  
Milena Jovanović ◽  
Federico Marini ◽  
Slavica Ražić
Keyword(s):  
Principal Component Analysis ◽  
Fourier Transform ◽  
Principal Component ◽  
Fourier Transform Infrared ◽  
Total Reflection ◽  
Attenuated Total Reflection ◽  
Illegal Market ◽  
Ft Ir

Heroin is one of the most frequently seized drugs in Southeastern Europe. Due to the position in the Balkan route, the Republic of Serbia keeps important role in suppression of the trafficking of heroin for domestic and foreign illegal market. This research is aimed to provide a good scientific approach in the field of seized heroin analysis. Two different forms of heroin are present in the illegal market, mostly in mixtures with typical “cutting” agents: caffeine, paracetamol, and sugars. It was observed that the quantity of pure heroin in seized samples slightly increases from year to year. The aim of this study was to produce a reliable and fast procedure for classification of illicit heroin samples and determination of the concentration range of heroin in the samples. For that purpose, the attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR) technique was used and combined with such chemometric methods as principal component analysis, cluster analysis, and partial least squares. Principal component analysis (PCA) as an unsupervised model was used for exploratory purposes to identify trends, similarities, and differences between samples by reducing the dimensionality of the data. The cluster classification of examined samples turned out to be extremely useful to evaluate the possibilities of the ATR FT-IR technique to classify the samples appropriately into the patterns, the constituted clusters. Additionally, partial least square was the suitable method for the purpose of determination of the heroin hydrochloride concentration range in examined samples. It is proved that the joined application of spectroscopy and chemometrics can be extremely convenient and useful for forensic and drugs control laboratories.

Identification of Electrolytes in Aqueous Solutions from Near-IR Spectra

1996 ◽  
Vol 50 (4) ◽  
pp. 444-448 ◽  
Author(s):  
Jie Lin ◽  
Jing Zhou ◽  
Chris W. Brown
Keyword(s):  
Aqueous Solutions ◽  
Ir Spectra ◽  
Principal Component Regression ◽  
Principal Component ◽  
Transition Metal Ions ◽  
Water Molecules ◽  
Spectral Library ◽  
Dipole Interactions ◽  
Near Ir ◽  
Solutions Of Electrolytes

Dissolution of electrolytes causes characteristic changes in the near-IR spectrum of water. These changes result from a decrease in the concentration of water; charge-dipole interactions between ions and water molecules; formation of hydrogen bonds between oxygen or nitrogen atoms in some ions and water molecules; production of H+ and OH− ions from dissociation and hydrolysis; absorptions due to OH, NH, and CH groups in some ions; and intrinsic colors of some transition metal ions. Changes in spectra were used for identification of electrolytes in aqueous solutions. Near-IR spectra of 71 solutions of single electrolytes were measured and used to develop a spectral library. This near-IR spectral library was processed with principal component regression (PCR) and used for the identification of single and multiple electrolytes in aqueous solutions with the use of their spectra. Most of the unknown electrolytes were identified correctly. For the others, very similar electrolytes were selected with one ion identified correctly. The near-IR spectral library of aqueous solutions of electrolytes can be used as a simple and fast approach for the identification of electrolytes.

Cluster Analysis of Gallstone FT-IR Spectra: Tests on Simulated Mixture Spectra and Comparison between Spectral and Morphological Classification of Human Gallstones

1998 ◽  
Vol 52 (9) ◽  
pp. 1210-1221 ◽  
Author(s):  
Eric Laloum ◽  
Nguyen Quy Dao ◽  
Michel Daudon
Keyword(s):  
Cluster Analysis ◽  
Ir Spectra ◽  
Black Pigment ◽  
Brown Pigment ◽  
Morphological Classification ◽  
Single Linkage ◽  
Homogeneous Groups ◽  
Ft Ir ◽  
Pure Cholesterol

Sixty-four combination spectra of three major gallstone components [i.e., cholesterol, calcium bilirubinate, and calcium carbonate (aragonite)] were simulated in accordance with a “fractal” ternary diagram. Comparison between the original pattern of composition and factorial maps of pretreated spectra makes it possible to show the effects of different normalization procedures (Euclidean norm, spectrum maximum, and area under spectrum set to 1). Cluster analysis of these spectra, depending on different agglomerative links (single linkage, complete linkage, average linkage, and Ward's criterion), was carried out. All the resultant trees yield the same groups, but Ward's criterion best preserves the pattern of the data. More than 100 gallstones from France and Vietnam were classified by using cluster analysis of their FT-IR spectra with Ward's criterion. Seven homogeneous groups of spectra were extracted, which have been significantly correlated to the four morphological types of gallstones: pure cholesterol, mixed cholesterol, brown pigment, and black pigment stones. This analysis also reveals that the morphological groups are not homogeneous in composition, in particular for black pigment stones.

scholarly journals Application of Spectroscopic UV-Vis and FT-IR Screening Techniques Coupled with Multivariate Statistical Analysis for Red Wine Authentication: Varietal and Vintage Year Discrimination

Molecules ◽  
2019 ◽  
Vol 24 (22) ◽  
pp. 4166 ◽  
Author(s):  
Elisabeta-Irina Geană ◽  
Corina Teodora Ciucure ◽  
Constantin Apetrei ◽  
Victoria Artem
Keyword(s):  
Discriminant Analysis ◽  
Principal Component ◽  
Total Variance ◽  
Red Wines ◽  
Linear Discriminant ◽  
Vis Spectroscopy ◽  
Ft Ir ◽  
Wine Authentication ◽  
Analytical Approaches

One of the most important issues in the wine sector and prevention of adulterations of wines are discrimination of grape varieties, geographical origin of wine, and year of vintage. In this experimental research study, UV-Vis and FT-IR spectroscopic screening analytical approaches together with chemometric pattern recognition techniques were applied and compared in addressing two wine authentication problems: discrimination of (i) varietal and (ii) year of vintage of red wines produced in the same oenological region. UV-Vis and FT-IR spectra of red wines were registered for all the samples and the principal features related to chemical composition of the samples were identified. Furthermore, for the discrimination and classification of red wines a multivariate data analysis was developed. Spectral UV-Vis and FT-IR data were reduced to a small number of principal components (PCs) using principal component analysis (PCA) and then partial least squares discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) were performed in order to develop qualitative classification and regression models. The first three PCs used to build the models explained 89% of the total variance in the case of UV-Vis data and 98% of the total variance for FR-IR data. PLS-DA results show that acceptable linear regression fits were observed for the varietal classification of wines based on FT-IR data. According to the obtained LDA classification rates, it can be affirmed that UV-Vis spectroscopy works better than FT-IR spectroscopy for the discrimination of red wines according to the grape variety, while classification of wines according to year of vintage was better for the LDA based FT-IR data model. A clear discrimination of aged wines (over six years) was observed. The proposed methodologies can be used as accessible tools for the wine identity assurance without the need for costly and laborious chemical analysis, which makes them more accessible to many laboratories.

scholarly journals Measurements of Urea and Glucose in Aqueous Solutions with Dual-Beam Near-Infrared Fourier Transform Spectroscopy

2002 ◽  
Vol 56 (12) ◽  
pp. 1593-1599 ◽  
Author(s):  
Peter Snoer Jensen ◽  
Jimmy Bak
Keyword(s):  
Aqueous Solutions ◽  
Near Infrared ◽  
Principal Component Regression ◽  
Principal Component ◽  
Prediction Errors ◽  
Single Beam ◽  
Dual Beam ◽  
Calibration Models ◽  
Ft Ir ◽  
Beam Technique

This study investigates the use of a dual-beam, optical null, FT-IR spectrometer to measure trace organic components in aqueous solutions in the combination band region 5000–4000 cm−1. The spectrometer may be used for both single- and dual-beam measurements, thereby facilitating comparison of these two modes of operation. The concentrations of aqueous solutions of urea and glucose in the ranges 0–40 mg/dL and 0–250 mg/dL, respectively, were determined by principal component regression using both modes. The dual-beam technique eliminated instrumental variations present in the single-beam measurements that must be taken into account when quantifying trace components from single-beam spectra. The data obtained with the dual-beam technique resulted in more stable calibration models based on principal component regression. These calibration models need fewer factors and yield lower prediction errors than those based on traditional single-beam data.

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