High-Throughput Analyses of Microplastic Samples Using Fourier Transform Infrared and Raman Spectrometry

2020 ◽  
Vol 74 (9) ◽  
pp. 1185-1197 ◽  
Author(s):  
Josef Brandt ◽  
Lars Bittrich ◽  
Franziska Fischer ◽  
Elisavet Kanaki ◽  
Alexander Tagg ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Open Source Software ◽  
Fourier Transform Infrared ◽  
Particle Analysis ◽  
Particle Detection ◽  
Raman Spectrometry ◽  
Open Source Software Package ◽  
Ft Ir ◽  
Ir Microspectroscopy ◽  
Ir And Raman

Determining microplastics in environmental samples quickly and reliably is a challenging task. With a largely automated combination of optical particle analysis, Fourier transform infrared (FT-IR), and Raman microscopy along with spectral database search, particle sizes, particle size distributions, and the type of polymer including particle color can be determined. We present a self-developed, open-source software package for realizing a particle analysis approach with both Raman and FT-IR microspectroscopy. Our software GEPARD (Gepard Enabled PARticle Detection) allows for acquiring an optical image, then detects particles and uses this information to steer the spectroscopic measurement. This ultimately results in a multitude of possibilities for efficiently reviewing, correcting, and reporting all obtained results.

scholarly journals Identification of a Glass Substrate to Study Cells Using Fourier Transform Infrared Spectroscopy: Are We Closer to Spectral Pathology?

2019 ◽  
Vol 74 (2) ◽  
pp. 178-186 ◽  
Author(s):  
Abigail V. Rutter ◽  
Jamie Crees ◽  
Helen Wright ◽  
Marko Raseta ◽  
Daniel G. van Pittius ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Cancer Cells ◽  
Cell Line ◽  
Glass Substrate ◽  
Fourier Transform Infrared ◽  
Leukemia Cell Line ◽  
Different Types ◽  
Ft Ir ◽  
Fingerprint Region ◽  
Ir Microspectroscopy

The rising incidence of cancer worldwide is causing an increase in the workload in pathology departments. This, coupled with advanced analysis methodologies, supports a developing need for techniques that could identify the presence of cancer cells in cytology and tissue samples in an objective, fast, and automated way. Fourier transform infrared (FT-IR) microspectroscopy can identify cancer cells in such samples objectively. Thus, it has the potential to become another tool to help pathologists in their daily work. However, one of the main drawbacks is the use of glass substrates by pathologists. Glass absorbs IR radiation, removing important mid-IR spectral data in the fingerprint region (1800 cm−1 to 900 cm−1). In this work, we hypothesized that, using glass coverslips of differing compositions, some regions within the fingerprint area could still be analyzed. We studied three different types of cells (peripheral blood mononuclear cells, a leukemia cell line, and a lung cancer cell line) and lymph node tissue placed on four different types of glass coverslips. The data presented here show that depending of the type of glass substrate used, information within the fingerprint region down to 1350 cm−1 can be obtained. Furthermore, using principal component analysis, separation between the different cell lines was possible using both the lipid region and the fingerprint region between 1800 cm−1 and 1350 cm−1. This work represents a further step towards the application of FT-IR microspectroscopy in histopathology departments.

Revealing Covariance Structures in Fourier Transform Infrared and Raman Microspectroscopy Spectra: A Study on Pork Muscle Fiber Tissue Subjected to Different Processing Parameters

2007 ◽  
Vol 61 (10) ◽  
pp. 1032-1039 ◽  
Author(s):  
Ulrike Böcker ◽  
Ragni Ofstad ◽  
Zhiyun Wu ◽  
Hanne Christine Bertram ◽  
Ganesh D. Sockalingum ◽  
...  
Keyword(s):  
Heat Treatment ◽  
Fourier Transform ◽  
Raman Spectra ◽  
Muscle Tissue ◽  
Salt Content ◽  
Fourier Transform Infrared ◽  
Spectroscopic Techniques ◽  
Ft Ir ◽  
Ir And Raman ◽  
Ir Bands

The aim of this study was to investigate the correlation patterns between Fourier transform infrared (FT-IR) and Raman microspectroscopic data obtained from pork muscle tissue, which helped to improve the interpretation and band assignment of the observed spectral features. The pork muscle tissue was subjected to different processing factors, including aging, salting, and heat treatment, in order to induce the necessary degree of variation of the spectra. For comparing the information gained from the two spectroscopic techniques with respect to the experimental design, multiblock principal component analysis (MPCA) was utilized for data analysis. The results showed that both FT-IR and Raman spectra were mostly affected by heat treatment, followed by the variation in salt content. Furthermore, it could be observed that IR amide I, II, and III band components appear to be effected to a different degree by brine-salting and heating. FT-IR bands assigned to specific protein secondary structures could be related to different Raman C–C stretching bands. The Raman C–C skeletal stretching bands at 1031, 1061, and 1081 cm−1 are related to the IR bands indicative of aggregated β-structures, while the Raman bands at 901 cm−1 and 934 cm−1 showed a strong correlation with IR bands assigned to α-helical structures. At the same time, the IR band at 1610 cm−1, which formerly was assigned to tyrosine in spectra originating from pork muscle, did not show a correlation to the strong tyrosine doublet at 827 and 852 cm−1 found in Raman spectra, leading to the conclusion that the IR band at 1610 cm−1 found in pork muscle tissue is not originating from tyrosine.

Screening of Astaxanthin-Hyperproducing Haematococcus pluvialis Using Fourier Transform Infrared (FT-IR) and Raman Microspectroscopy

2016 ◽  
Vol 70 (10) ◽  
pp. 1639-1648 ◽  
Author(s):  
Jinghua Liu ◽  
Qing Huang
Keyword(s):  
Fourier Transform ◽  
High Throughput Screening ◽  
Haematococcus Pluvialis ◽  
Fourier Transform Infrared ◽  
Raman Microspectroscopy ◽  
Screening Methods ◽  
Ir Absorption ◽  
New Approach ◽  
Ft Ir ◽  
Ir And Raman

Haematococcus pluvialis has promising applications owing to its ability to accumulate astaxanthin under stress conditions. In order to acquire higher astaxanthin productivity from H. pluvialis, it is critical not only to develop efficient mutagenesis techniques, but also to establish rapid and effective screening methods which are highly demanded in current research and application practice. In this work, we therefore attempted to develop a new approach to screening the astaxanthin-hyperproducing strains based on spectroscopic tools. Using Fourier transform infrared (FT-IR) and Raman microspectroscopy, we have achieved rapid and quantitative analysis of the algal cells in terms of astaxanthin, β-carotene, proteins, lipids, and carbohydrates. In particular, we have found that the ratio of the IR absorption band at 1740 cm−1 to the band at 1156 cm−1 can be utilized for identifying astaxanthin-hyperproducing strains. This work may therefore open a new avenue for developing high-throughput screening methods necessary for the microbial mutant breeding industry.

Forensic Analysis of Architectural Finishes Using Fourier Transform Infrared and Raman Spectroscopy, Part II: White Paint

2005 ◽  
Vol 59 (11) ◽  
pp. 1340-1346 ◽  
Author(s):  
Steven E. J. Bell ◽  
Louise A. Fido ◽  
S. James Speers ◽  
W. James Armstrong ◽  
Sharon Spratt
Keyword(s):  
Raman Spectroscopy ◽  
Fourier Transform ◽  
Fourier Transform Infrared ◽  
Forensic Analysis ◽  
The Other ◽  
Large Group ◽  
Ir Microscopy ◽  
Infrared And Raman Spectroscopy ◽  
Ft Ir ◽  
Ir And Raman

White household paints are commonly encountered as evidence in the forensic laboratory but they often cannot be readily distinguished by color alone so Fourier transform infrared (FT-IR) microscopy is used since it can sometimes discriminate between paints prepared with different organic resins. Here we report the first comparative study of FT-IR and Raman spectroscopy for forensic analysis of white paint. Both techniques allowed the 51 white paint samples in the study to be classified by inspection as either belonging to distinct groups or as unique samples. FT-IR gave five groups and four unique samples; Raman gave seven groups and six unique samples. The basis for this discrimination was the type of resin and/or inorganic pigments/extenders present. Although this allowed approximately half of the white paints to be distinguished by inspection, the other half were all based on a similar resin and did not contain the distinctive modifiers/pigments and extenders that allowed the other samples to be identified. The experimental uncertainty in the relative band intensities measured using FT-IR was similar to the variation within this large group, so no further discrimination was possible. However, the variation in the Raman spectra was larger than the uncertainty, which allowed the large group to be divided into three subgroups and four distinct spectra, based on relative band intensities. The combination of increased discrimination and higher sample throughput means that the Raman method is superior to FT-IR for samples of this type.

Fourier Transform Infrared (FT-IR) Microspectroscopy of 20th Century Russian Oil Paintings: Problem of Dating

2016 ◽  
Vol 70 (7) ◽  
pp. 1150-1156 ◽  
Author(s):  
Irina A. Balakhnina ◽  
Nikolay N. Brandt ◽  
Andrey Yu Chikishev ◽  
Yurii I. Grenberg ◽  
Irina A. Grigorieva ◽  
...  
Keyword(s):  
Fourier Transform ◽  
20Th Century ◽  
Fourier Transform Infrared ◽  
Oil Paintings ◽  
Ft Ir ◽  
Ir Microspectroscopy

scholarly journals Fourier-Transform Infrared Microspectroscopy, a Novel and Rapid Tool for Identification of Yeasts

2002 ◽  
Vol 68 (10) ◽  
pp. 4717-4721 ◽  
Author(s):  
Mareike Wenning ◽  
Herbert Seiler ◽  
Siegfried Scherer
Keyword(s):  
Fourier Transform ◽  
Agar Plate ◽  
Debaryomyces Hansenii ◽  
Fourier Transform Infrared ◽  
Strain Level ◽  
Correct Identification ◽  
Ft Ir ◽  
Small Model ◽  
Ir Microspectroscopy ◽  
Rapid Tool

ABSTRACT Fourier-transform infrared (FT-IR) microspectroscopy was used in this study to identify yeasts. Cells were grown to microcolonies of 70 to 250 μm in diameter and transferred from the agar plate by replica stamping to an IR-transparent ZnSe carrier. IR spectra of the replicas on the carrier were recorded using an IR microscope coupled to an IR spectrometer, and identification was performed by comparison to reference spectra. The method was tested by using small model libraries comprising reference spectra of 45 strains from 9 genera and 13 species, recorded with both FT-IR microspectroscopy and FT-IR macrospectroscopy. The results show that identification by FT-IR microspectroscopy is equivalent to that achieved by FT-IR macrospectroscopy but the time-consuming isolation of the organisms prior to identification is not necessary. Therefore, this method also provides a rapid tool to analyze mixed populations. Furthermore, identification of 21 Debaryomyces hansenii and 9 Saccharomyces cerevisiae strains resulted in 92% correct identification at the strain level for S. cerevisiae and 91% for D. hansenii, which demonstrates that the resolution power of FT-IR microspectroscopy may also be used for yeast typing at the strain level.

Pollen discrimination and classification by Fourier transform infrared (FT-IR) microspectroscopy and machine learning

2009 ◽  
Vol 394 (5) ◽  
pp. 1443-1452 ◽  
Author(s):  
R. Dell’Anna ◽  
P. Lazzeri ◽  
M. Frisanco ◽  
F. Monti ◽  
F. Malvezzi Campeggi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Fourier Transform ◽  
Fourier Transform Infrared ◽  
Ft Ir ◽  
Ir Microspectroscopy
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