scholarly journals Application of Fourier Transform Infrared Spectroscopy (FTIR) for assessing biogenic silica sample purity in geochemical analyses and palaeoenvironmental research

2011 ◽  
Vol 7 (1) ◽  
pp. 65-74 ◽  
Author(s):  
G. E. A. Swann ◽  
S. V. Patwardhan
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Mass Balance ◽  
Fourier Transform Infrared Spectroscopy ◽  
Biogenic Silica ◽  
Fourier Transform Infrared ◽  
Ftir Spectra ◽  
Balance Model ◽  
Diatom Frustule ◽  
End Members

Abstract. The development of a rapid and non-destructive method to assess purity levels in samples of biogenic silica prior to geochemical/isotope analysis remains a key objective in improving both the quality and use of such data in environmental and palaeoclimatic research. Here a Fourier Transform Infrared Spectroscopy (FTIR) mass-balance method is demonstrated for calculating levels of contamination in cleaned sediment core diatom samples from Lake Baikal, Russia. Following the selection of end-members representative of diatoms and contaminants in the analysed samples, a mass-balance model is generated to simulate the expected FTIR spectra for a given level of contamination. By fitting the sample FTIR spectra to the modelled FTIR spectra and calculating the residual spectra, the optimum best-fit model and level of contamination is obtained. When compared to X-ray Fluorescence (XRF) the FTIR method portrays the main changes in sample contamination through the core sequence, permitting its use in instances where other, destructive, techniques are not appropriate. The ability to analyse samples of <1 mg enables, for the first time, routine analyses of small sized samples. Discrepancies between FTIR and XRF measurements can be attributed to FTIR end-members not fully representing all contaminants and problems in using XRF to detect organic matter external to the diatom frustule. By analysing samples with both FTIR and XRF, these limitations can be eliminated to accurately identify contaminated samples. Future, routine use of these techniques in palaeoenvironmental research will therefore significantly reduce the number of erroneous measurements and so improve the accuracy of biogenic silica/diatom based climate reconstructions.

scholarly journals Application of Fourier Transform Infrared Spectroscopy (FTIR) for assessing biogenic silica sample purity in geochemical analyses and palaeoenvironmental research

2010 ◽  
Vol 6 (5) ◽  
pp. 1629-1653 ◽  
Author(s):  
G. E. A. Swann ◽  
S. V. Patwardhan
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Mass Balance ◽  
Fourier Transform Infrared Spectroscopy ◽  
Biogenic Silica ◽  
Fourier Transform Infrared ◽  
Ftir Spectra ◽  
Balance Model ◽  
Diatom Frustule ◽  
End Members

Abstract. The development of a rapid and non-destructive method to assess levels of purity in samples of biogenic silica prior to geochemical/isotope analysis remains a key objective in improving both the quality and use of such data in environmental and palaeoclimatic research. Here a Fourier Transform Infrared Spectroscopy (FTIR) mass-balance method is demonstrated for calculating levels of contamination in cleaned sediment core diatom samples from Lake Baikal Russia. Following the selection of end-members representative of diatoms and contaminants in the analysed samples, a mass-balance model is generated to simulate the expected FTIR spectra for a given level of contamination. By fitting the sample FTIR spectra to the modelled FTIR spectra and calculating the Euclidean distance, the optimum “best-fit” model and level of contamination is obtained. When compared to X-ray Fluorescence (XRF), FTIR method results portray the main changes in sample contamination through the core sequence, permitting its use in instances where other, destructive, techniques are not appropriate. The ability to analyses samples of <1 mg enables, for the first time, routine analyses of small sized samples. Discrepancies between FTIR and XRF measurements can be attributed to FTIR end-members not fully representing all contaminants and problems in using XRF to detect organic matter external to the diatom frustule. By analysing samples with both FTIR and XRF, these limitations can be eliminated to accurately identify contaminated samples and improve the accuracy of climate reconstructions. Future, routine, use of these techniques in palaeoenvironmental research will significantly reduce the number of erroneous measurements and so improve the accuracy of biogenic silica/diatom based reconstructions.

scholarly journals Application of open-path Fourier transform infrared spectroscopy (OP-FTIR) to measure greenhouse gas concentrations from agricultural fields

2019 ◽  
Vol 12 (6) ◽  
pp. 3403-3415 ◽  
Author(s):  
Cheng-Hsien Lin ◽  
Richard H. Grant ◽  
Albert J. Heber ◽  
Cliff T. Johnston
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Least Squares ◽  
Fourier Transform Infrared Spectroscopy ◽  
Fourier Transform Infrared ◽  
Point Sources ◽  
Ftir Spectra ◽  
Diurnal Changes ◽  
Open Path ◽  
Co2 Concentrations

Abstract. Open-path Fourier transform infrared spectroscopy (OP-FTIR) has often been used to measure hazardous or trace gases from hot point sources (e.g. volcano, industrial, or agricultural facilities) but seldom used to measure greenhouse gases (GHGs) from field-scale sources (e.g. agricultural soils). Closed-path mid-IR laser-based N2O, nondispersive-IR CO2 analysers, and OP-FTIR were used to measure concentrations of N2O and CO2 at a maize cropping system during 9–19 June 2014. To measure N2O and CO2 concentrations accurately, we developed a quantitative method of N2O∕CO2 analysis that minimized interferences from diurnal changes of humidity and temperature. Two chemometric multivariate models, classical least squares (CLS) and partial least squares (PLS), were developed. This study evaluated various methods to generate the single-beam background spectra and different spectral regions for determining N2O and CO2 concentrations from OP-FTIR spectra. A standard extractive method was used to measure the actual path-averaged concentrations along an OP-FTIR optical path in situ, as a benchmark to assess the feasibilities of these quantitative methods. Within an absolute humidity range of 5000–20 000 ppmv and a temperature range of 10–35 ∘C, we found that the CLS model underestimated N2O concentrations (bias =-4.9±3.1 %) calculated from OP-FTIR spectra, and the PLS model improved the accuracy of calculated N2O concentrations (bias =1.4±2.3 %). The bias of calculated CO2 concentrations was -1.0±2.8 % using the CLS model. These methods suggested that environmental variables potentially lead to biases in N2O and CO2 estimations from OP-FTIR spectra and may help OP-FTIR users avoid dependency on extractive methods of calibrations.

scholarly journals Efficient Discrimination of Some Moss Species by Fourier Transform Infrared Spectroscopy and Chemometrics

2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
Zhen Cao ◽  
Yongying Liu ◽  
Jiancheng Zhao
Keyword(s):  
Cluster Analysis ◽  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Fourier Transform Infrared Spectroscopy ◽  
Principal Component ◽  
Fourier Transform Infrared ◽  
Ftir Spectra ◽  
Chemical Components ◽  
Discrete Wavelet ◽  
Moss Species

Fourier transform infrared spectroscopy (FTIR) technique was used to classify 16 species from three moss families (Mielichhoferiaceae, Bryaceae, and Mniaceae). The FTIR spectra ranging from 4000 cm−1to 400 cm−1of the 16 species were obtained. To group the spectra according to their spectral similarity in a dendrogram, cluster analysis and principal component analysis (PCA) were performed. Cluster analysis combined with PCA was used to give a rough result of classification among the moss samples. However, some species belonging to the same genus exhibited very similar chemical components and similar FTIR spectra. Fourier self-deconvolution (FSD) was used to enhance the differences of the spectra. Discrete wavelet transform (DWT) was used to decompose the FTIR spectra ofMnium laevinerveandM. spinosum. Three scales were selected as the feature extracting space in the DWT domain. Results showed that FTIR spectroscopy combined with DWT was suitable for distinguishing different species of the same genus.

scholarly journals Fourier Transform Infrared Spectroscopy vibrational bands study of Spinacia oleracea and Trigonella corniculata under biochar amendment in naturally contaminated soil

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0253390
Author(s):  
Uzma Younis ◽  
Ashfaq Ahmad Rahi ◽  
Subhan Danish ◽  
Muhammad Arif Ali ◽  
Niaz Ahmed ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Fourier Transform Infrared Spectroscopy ◽  
Functional Groups ◽  
Structural Changes ◽  
Spinacia Oleracea ◽  
Fourier Transform Infrared ◽  
Ftir Spectra ◽  
Leaf Chlorophyll ◽  
Vibrational Bands

Fourier transform infrared spectroscopy (FTIR) spectroscopy detects functional groups such as vibrational bands like N-H, O-H, C-H, C = O (ester, amine, ketone, aldehyde), C = C, C = N (vibrational modes of a tetrapyrrole ring) and simply C = N. The FTIR of these bands is fundamental to the investigation of the effect of biochar (BC) treatment on structural changes in the chlorophyll molecules of both plants that were tested. For this, dried leaf of Spinacia oleracia (spinach) and Trigonella corniculata (fenugreek) were selected for FTIR spectral study of chlorophyll associated functional groups. The study’s primary goal was to investigate the silent features of infrared (IR) spectra of dried leave samples. The data obtained from the current study also shows that leaf chlorophyll can mask or suppress other molecules’ FITR bands, including proteins. In addition, the C = O bands with Mg and the C9 ketonic group of chlorophyll are observed as peaks at1600 (0%BC), 1650 (3%BC) and 1640, or near to1700 (5%BC) in spinach samples. In fenugreek, additional effects are observed in the FTIR spectra of chlorophyll at the major groups of C = C, C = O and C9 of the ketonic groups, and the vibrational bands are more evident at C-H and N-H of the tetrapyrrole ring. It is concluded that C-N bands are more visible in 5% BC treated spinach and fenugreek than in all other treatments. These types of spectra are useful in detecting changes or visibility of functional groups, which are very helpful in supporting biochemical data such as an increase in protein can be detected by more visibility of C-N bands in FTIR spectra.

scholarly journals Mineral Heterogeneity Characterization of the Lacustrine Yanchang Shales, Ordos Basin Using Micro-Fourier Transform Infrared Spectroscopy (Micro-FTIR) Technique

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Bing Luo ◽  
Zhiguo Shu ◽  
Yalin Chen ◽  
Zhuo Li ◽  
Yufei Hou ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Fourier Transform Infrared Spectroscopy ◽  
Ordos Basin ◽  
Fourier Transform Infrared ◽  
Ftir Spectra ◽  
Fine Grained ◽  
Ftir Technique ◽  
Mineral Compositions

Shale is a typical fine-grained sedimentary rock with small grain sizes of matrix components, significant lithofacies variation of rock texture and structure, and strong heterogeneity of organic matter and mineral compositions. Characterization of mineral compositions and their heterogeneity in micro- to nanoscale are the key parameters to gas shale pore structure and rock physical properties. In order to study the microscale mineralogy heterogeneity of the lacustrine shales in the Triassic Yanchang Formation in the Ordos Basin, the micro-Fourier transform infrared spectroscopy (micro-FTIR) technique was conducted. Based on the specific micro-FTIR spectra peaks, the abundance of mineral compositions can be quantitatively determined in the selected microscale areas. The results show that within the range of 80 μm micro-FTIR test interval, both massive argillaceous shale and silty interlayered shale show obvious heterogeneity; in particular, the relatively homogeneous shale observed by the naked eyes also has strong mineral heterogeneity. The results of micro-FTIR spectra are basically consistent with the bulk X-ray diffraction (XRD) data. The advantage of this micro-FTIR technique includes higher resolution (less than 100 μm) and in situ mineral characterization of shale samples at micro- and nanoscale.

Identification of Propionibacteria to the species level using Fourier transform infrared spectroscopy and artificial neural networks

2013 ◽  
Vol 16 (2) ◽  
pp. 351-357 ◽  
Author(s):  
B. Dziuba
Keyword(s):  
Neural Networks ◽  
Fourier Transform ◽  
Artificial Neural Networks ◽  
Infrared Spectroscopy ◽  
Fourier Transform Infrared Spectroscopy ◽  
Fourier Transform Infrared ◽  
Species Level ◽  
Ftir Spectra ◽  
Multilayer Perceptrons ◽  
Artificial Neural

Abstract Fourier transform infrared spectroscopy (FTIR) and artificial neural networks (ANN’s) were used to identify species of Propionibacteria strains. The aim of the study was to improve the methodology to identify species of Propionibacteria strains, in which the differentiation index D, calculated based on Pearson’s correlation and cluster analyses were used to describe the correlation between the Fourier transform infrared spectra and bacteria as molecular systems brought unsatisfactory results. More advanced statistical methods of identification of the FTIR spectra with application of artificial neural networks (ANN’s) were used. In this experiment, the FTIR spectra of Propionibacteria strains stored in the library were used to develop artificial neural networks for their identification. Several multilayer perceptrons (MLP) and probabilistic neural networks (PNN) were tested. The practical value of selected artificial neural networks was assessed based on identification results of spectra of 9 reference strains and 28 isolates. To verify results of isolates identification, the PCR based method with the pairs of species-specific primers was used. The use of artificial neural networks in FTIR spectral analyses as the most advanced chemometric method supported correct identification of 93% bacteria of the genus Propionibacterium to the species level.

scholarly journals Application of Open Path Fourier Transform Infrared Spectroscopy (OP-FTIR) to Measure Greenhouse Gas Concentrations from Agricultural Soils

2018 ◽  
Author(s):  
Cheng-Hsien Lin ◽  
Cliff T. Johnston ◽  
Richard H. Grant ◽  
Albert J. Heber
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Least Squares ◽  
Fourier Transform Infrared Spectroscopy ◽  
Agricultural Soils ◽  
Fourier Transform Infrared ◽  
Point Sources ◽  
Ftir Spectra ◽  
Open Path ◽  
Co2 Concentrations

Abstract. Open-path Fourier transform infrared spectroscopy (OP-FTIR) has often been used to measure hazardous or trace gases from the "hot" point sources (e.g., volcano, industrial or agricultural facilities) but seldom used in the field-scale source areas, such as soil emissions. OP-FTIR, the close-path mid-IR laser-based N2O, and the nondispersive-IR CO2 analyzers were used to measure the concentrations of greenhouse gases (e.g., N2O and CO2) emitted from agricultural soils over a period of 9−19 June in 2014. We developed a quantitative method of N2O/CO2 analysis that minimized the interferences from diurnal changes of humidity and temperature in order to measure N2O/CO2 concentrations accurately. Two chemometric multivariate models were developed, a classical least squares (CLS) and a partial least squares (PLS), respectively. This study evaluated different methods to generate the single beam background spectra, and different spectral regions to determine N2O/CO2 concentrations from OP-FTIR spectra. A standard extractive method was used to measure the "actual" path-averaged concentrations along an OP-FTIR optical path in situ, as a benchmark to assess the feasibilities of these quantitative methods. Within the absolute humidity of 5000−20 000 ppmv and the temperature of 10−35 °C, we found that the CLS model underestimated N2O concentrations (Bias = −4.9 ± 3.1 %) calculated from OP-FTIR spectra, and the PLS model improved the accuracy of the calculated N2O (Bias = 1.4 ± 2.3 %). The bias of the calculated CO2 was −1.0 ± 2.8 % using the CLS model. These methods suggested that the changed ambient factors potentially led to biases in N2O/CO2 estimations from OP-FTIR spectra, and may help the OP-FTIR user to escape from the dependency of extractive methods used to calibrate the concentration determined by OP-FTIR.

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