Multivariate Calibration by Variable Selection for Blends of Raw Soybean Oil/Biodiesel from Different Sources Using Fourier Transform Infrared Spectroscopy (FTIR) Spectra Data

2008 ◽  
Vol 22 (3) ◽  
pp. 2079-2083 ◽  
Author(s):  
Itânia P. Soares ◽  
Thais F. Rezende ◽  
Renzo C. Silva ◽  
Eustáquio Vinícius R. Castro ◽  
Isabel C. P. Fortes
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Variable Selection ◽  
Soybean Oil ◽  
Fourier Transform Infrared Spectroscopy ◽  
Multivariate Calibration ◽  
Fourier Transform Infrared ◽  
Ftir Spectra ◽  
Selection For ◽  
Different Sources

Real-Time Monitoring of the Transesterification of Soybean Oil and Methanol by Fourier-Transform Infrared Spectroscopy

2013 ◽  
Vol 27 (10) ◽  
pp. 5957-5961 ◽  
Author(s):  
Feng Zhang ◽  
Daisuke Adachi ◽  
Sriappareddy Tamalampudi ◽  
Akihiko Kondo ◽  
Keisuke Tominaga
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Soybean Oil ◽  
Real Time ◽  
Fourier Transform Infrared Spectroscopy ◽  
Fourier Transform Infrared ◽  
Real Time Monitoring

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 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.

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