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.

Rapid Differentiation and Identification of Shigella sonnei and Escherichia coli O157: H7 by Fourier Transform Infrared Spectroscopy and Multivariate Statistical Analysis

2014 ◽  
Vol 926-930 ◽  
pp. 1116-1119 ◽  
Author(s):  
Li Jun Yang ◽  
Jing Wang ◽  
Zhao Jie Li ◽  
Xiao Hua Song ◽  
Yu Min Liu ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Statistical Analysis ◽  
Fourier Transform Infrared Spectroscopy ◽  
Multivariate Statistical Analysis ◽  
Principal Component ◽  
Fourier Transform Infrared ◽  
Shigella Sonnei ◽  
Multivariate Statistical ◽  
Simple Method

Fourier transform infrared spectroscopy (FTIR) combined with multivariate statistical analysis was applied to differentiate and identify Shigella sonnei and Escherichiacoli O157: H7. FTIR absorption spectra from 4000-600 cm-1 were collected from sampling 10 μL of bacterial suspention. The spectra between 1800 and 900 cm-1 highlighted the most distinctive variations and were the most useful for characterizing the selected microorganisms. Spectra of the two bacteria were noticeably segregated with distinct clustering by principal component analysis (PCA). Further more, another cluster model of hierarchical cluster analysis (HCA) was established and could also gave a good separation between the two bacteria. These results demonstrate that FTIR technology has considerable potential as a rapid, accurate and simple method for differentiating and identifying bacteria.

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 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.

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.

Fourier-Transform Infrared Spectroscopy Analysis of the Changes in Chemical Composition of Wooden Components: Part II—The Ancient Building of Danxia Temple

2021 ◽  
Vol 71 (3) ◽  
pp. 283-289
Author(s):  
Yan Yang ◽  
He Sun ◽  
Shuang Yang ◽  
Wenye Sun ◽  
Ying Zhao ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Fourier Transform Infrared Spectroscopy ◽  
Brown Rot ◽  
Fourier Transform Infrared ◽  
Absorption Peak ◽  
Chemical Components ◽  
Red Oak ◽  
Cellulose Crystallinity ◽  
Brown Rot Fungi

Abstract To investigate the decay extent of wooden components in the ancient buildings of Danxia Temple, the absorption peak intensities, changes in chemical components, and cellulose crystallinity of red oak (Quercus sp.), birch (Betula sp.), and maple (Pterocarya sp.) wooden components were determined and analyzed using Fourier-transform infrared spectroscopy. The results are as follows: (1) The absorption peak intensities representing cellulose and hemicellulose decreased or disappeared obviously in the decayed red oak wood (DROW); on the contrary, those representing lignin increased. The indexes of the content of cellulose, hemicellulose, and cellulose crystallinity also decreased; on the contrary, those of the content of lignin increased. Those results indicated that cellulose and hemicellulose in DROW were largely degraded by brown-rot fungi. (2) The absorption peak intensities representing cellulose and hemicellulose decreased both in the decayed birch wood (DBW) and the decayed maple wood (DMW), whereas those representing lignin increased. The indexes of the content of cellulose, hemicellulose, and cellulose crystallinity also decreased, whereas those of lignin increased. Those results showed that cellulose and hemicellulose in DBW and DMW were seriously harmed not only by insects but also by brown-rot fungi. By comparison, the extent of fungal damage was lower in DMW than in DBW.

scholarly journals Fourier Transform Infrared Spectroscopy Analysis Of Oil Of Menthaarvensis Grown At Sites Varying With Vehicular Traffic Loads In Lucknow City, India

2013 ◽  
Vol 2 (1) ◽  
pp. 16-25 ◽  
Author(s):  
Nidhi Prakash ◽  
Mohhamad Yumus
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Essential Oil ◽  
Fourier Transform Infrared Spectroscopy ◽  
Heavy Traffic ◽  
Economic Value ◽  
Fourier Transform Infrared ◽  
Chemical Components ◽  
Vehicular Emissions ◽  
Traffic Loads

The demand of the essential oil of mint species; widely used in food, pharmaceutical and cosmetic industries, is growing throughout the world. Owing its significance, it was felt important to know the changes in chemical characteristics of the oil, if any, for economic value when the crop of Mentha is grown near highways, railway tracks or areas having heavy traffic loads. To assess the effect of vehicular emissions on menthol (mint oil), transfer experiment study was conducted. Firstly, within the municipal premises of Lucknow city, five sites (Road stretches) were identified based on survey of Lucknow city and the available data on air pollution loads. Sites were selected which were differing from each other significantly in terms of the number of vehicles (source of pollution) plying on them but were quite similar to each other in other eco-physiological factors. On the select sites equal number of potted Menthaarvensis plants of the same age, height and vigour of saccham variety obtained from CSIR-CIMAP was kept to get exposed to auto-exhaust pollutants for one year. Irrigation regime at all sites was kept uniform to avoid the influence of any other variable other than vehicular emissions. An analysis of hydro-distillated essential oil of Menthaarvensis variety Sascham under FTIR (Fourier Transform Infrared Spectroscopy) revealed some qualitative changes in the organic-compounds of the oil from plants grown at sites of Lucknow city loaded with high vehicular load (auto-exhaust pollutants) over plants kept under relatively pollution free site. Several indicator bands that are pertained to functional groups represent chemical components or metabolic products. The quantity of the peppermint oil extracted from plants of site having highest traffic loads, in turn maximum ambient pollutants (NO2, SO2, O3, SPM & RSPM) was also found less as compared to plants grown in less polluted site. International Journal of Environment, Volume-2, Issue-1, Sep-Nov 2013, Pages 16-25 DOI: http://dx.doi.org/10.3126/ije.v2i1.9204

Discriminant Analysis and Cluster Analysis of Biodiesel Fuel Blends Based on Fourier Transform Infrared Spectroscopy (FTIR)

2016 ◽  
Vol 30 (6) ◽  
pp. 4905-4915 ◽  
Author(s):  
Victor Hugo J. M. dos Santos ◽  
Eduardo Do Canto Bruzza ◽  
Jeane E. de Lima ◽  
Rogerio V. Lourega ◽  
Luiz F. Rodrigues
Keyword(s):  
Cluster Analysis ◽  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Discriminant Analysis ◽  
Fourier Transform Infrared Spectroscopy ◽  
Fourier Transform Infrared ◽  
Biodiesel Fuel ◽  
Fuel Blends ◽  
And Cluster Analysis
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