Fourier chemometrics

Dixit, V. et al.. Identification and qnantification of industrial grade glycerol adulteration in red wine with Fourier transform infrared spectroscopy using chemometrics and artificial neural networks, Appl. Spectros., 59, 1553, 2005. 

Kansiz, M. Heraud, P. Wood, B. Burden, F. Beardall, J. McNaughton, D. Fourier transform infrared microspectroscopy and chemometrics as a tool for the discrimination of cyanobacterial strains. Phytochemistry 1999,52,407-417. 

McGovern, A. C. Ernill, R. Kara, B. V. Kell, D. B. Goodacre, R. Rapid analysis of the expression of heterologous proteins in Escherichia coli using pyrolysis mass spectrometry and Fourier transform infrared spectroscopy with chemometrics Application to a2- interferon production. J. Biotechnol. 1999, 72,157-167. 

The Analysis of Extraterrestrial Materials. By Isidore Adler Chemometrics. By Muhammad A. Sharaf, Deborah L. Illman, and Bruce R. Kowalski Fourier Transform Infrared Spectrometry. By Peter R. Griffiths and James A. de Haseth Trace Analysis Spectroscopic Methods for Molecules. Edited by Gary Christian and James B. Callis... 

Figure 4.9 FTRS spectrum of mammalian ivory. Letters show regions of the spectrum which were quantified to discriminate between ivory from different species. Reprinted from Analytica Chimica Acta 427, Brody, R. H., Edwards, H. G. M., and Pollard, A. M., Chemometric methods applied to the differentiation of Fourier-transform Raman spectra of ivories , pp. 223-32, copyright 2001, with permission from Elsevier.

Autoscaling can also be used when all of the variables have the same units and come from the same instrument. However, it can be detrimental if the total variance information is relevant to the problem being solved. For example, if one wants to do an exploratory chemometric analysis of a series of FTIR (Fourier transform infrared) spectra in order to determine the relative sensitivities of different wavenumbers (X-variables) to a property of interest, then it would be wise to avoid autoscaling and retain the total variance information because this information is relevant for assessing the sensitivities of different X-variables. 

To shed light on the mechanism of formation of silsesquioxane a7b3, to identify the species formed during the process, and to try to explain the high selectivity towards structure a7b3 of the optimised synthetic method described above (64% yield in 18 h), the synthesis of cyclopentyl silsesquioxane a7b3 was monitored by electrospray ionisation mass spectrometry (ESI MS) [50-52] and in situ attenuated total reflection Fourier-transform infrared (ATR FTIR) spectroscopy [53, 54]. Spectroscopic data from the latter were analysed using chemometric methods to identify the pure component spectra and relative concentration profiles. 

The feasibility of diffuse reflectance NIR, Fourier transform mid-IR and FT-Raman spectroscopy in combination with multivariate data analysis for in/ on-line compositional analysis of binary polymer blends found in household and industrial recyclates has been reported [121, 122]. In addition, a thorough chemometric analysis of the Raman spectral data was performed. 

A new rapid mid-infrared spectroscopic method called diffuse reflectance infrared Fourier transform spectra (DRIFTS), coupled with chemometrics, has been developed by Janik, Merry, and Skjemstad (1998) and routinely applied to rapidly screen and compare crime scene samples (Figure 1.1). Added to these rapid methods and techniques are the use of rapid mass and volume magnetic susceptibility methods, which should also always be used before moving to the more costly methods (Figure 1.1). Mineral magnetic techniques are a relatively recent development (post-1971) and have now become a very powerful and widely used research tool to characterize natural materials in landscapes (e.g., Thompson and Oldfield 1986). 

The ultimate selectivity of gas chromatography is determined by the detector. The most selective detectors are spectroscopic, such as Fourier-Transform Infrared or Mass Spectrometer. Automated systems can employ chemometric algorithms to discriminate unresolved chromatographic peaks. These combinations are expensive and require significant computer support. As such, they are more likely to be used in a laboratory for confirmation. Efforts to convert this approach to field units are still under development. The MiniCAMS described above, based on a FPD is a reliable monitor but requires 3-5 min to make a determination. Gas chromatographs also require a source of purified gas for operation and the flame detector requires additional hydrogen and air for operation. This device will have the fewest false positives and the most... 

One of the emerging biological and biomedical application areas for vibrational spectroscopy and chemometrics is the characterization and discrimination of different types of microorganisms [74]. A recent review of various FTIR (Fourier transform infrared spectrometry) techniques describes such chemometrics methods as hierarchical cluster analysis (HCA), principal component analysis (PCA), and artificial neural networks (ANN) for use in taxonomical classification, discrimination according to susceptibility to antibiotic agents, etc. [74],... 

This book intends to supply the basic information necessary to apply the methods of vibrational spectroscopy, to design experimental procedures, to perform and evaluate experiments. It does not intend to provide a market survey of the instruments which are available at present, because such information would very soon be outdated. However, the general principles of the instruments and their accessories, which remain valid, are discussed. Details concerning sample preparation and the recording of the spectra, which is the subject of introductory courses, are assumed to be known. Special procedures which are described in monographs, such as Fourier transformation or chemometric methods, are also not exhaustively described. This book has been written for graduate students as well as for experienced scientists who intend to update their knowledge. 

Schneider, R., Charrier, R, Moutounet, M., Baumes, R. (2005). Rapid analysis of grape aroma gfycoconjugates using Fourier-transform infrared spectrometry and chemometric techniques. Anal. Chim. Acta, 513, 91-96. 

For the chemometric analysis of NMR spectral data it is generally assumed that the observed NMR data matrix is composed of spectra, (w), where each different yth spectrum covers a frequency range observable window (spectral window). It is also possible to perform chemometric analysis on the complex time domain signal, (t), which is the original form of the NMR data following quadrature detection. The time-domain signal and the frequency spectrum are related through a Fourier transformation... 

For the example in Fig. 2, the Fourier transformed NMR spectra (variables or descriptors being intensity as a function of frequency) were utilized for the creation of the data matrix D. It should be noted that many different descriptors can be used to create D, with the descriptor selection depending on the analysis method and the information to be extracted. For example, in the spectral resolution methods (Section 6), the desired end result is the determination of the true or pure component spectra and relative concentrations present within the samples or mixtures [Eq. (4)]. For this case, the unmodified real spectra Ij co) are commonly used for the chemometric analysis. In contrast, for the non-supervised and supervised methods described in Sections 3 and 4, the classification of a sample into different categories is the desired outcome. For these types of non-supervised and supervised methods the original NMR spectrum can manipulated or transformed to produce new descriptors including... 

As stated previously, with most applications in analytical chemistry and chemometrics, the data we wish to transform are not continuous and infinite in size but discrete and finite. We cannot simply discretise the continuous wavelet transform equations to provide us with the lattice decomposition and reconstruction equations. Furthermore it is not possible to define a MRA for discrete data. One approach taken is similar to that of the continuous Fourier transform and its associated discrete Fourier series and discrete Fourier transform. That is, we can define a discrete wavelet series by using the fact that discrete data can be viewed as a sequence of weights of a set of continuous scaling functions. This can then be extended to defining a discrete wavelet transform (over a finite interval) by equating it to one period of the data length and generating a discrete wavelet series by its infinite periodic extension. This can be conveniently done in a matrix framework. 

L.J. Bao, Z.Y. Tang and J.Y. Mo, The Application of Spline Wavelet and Fourier Transform in Analytical Chemistry, In New Trends in Chemometrics, First International Conference on Chemometrics in China, Zhangjiajie, China, October 17-22, 1997, (Y.Z. Liang, R. Nortvedt, O.M. Kvalheim, H.L. Shen, Eds) Hunan University Press, Changsha, (1997), pp. 197-198. 

B.K. Alsberg. W.G. Wade and R. Goodacre. Chemometric Analysis of Diffuse reflectance-absorbance Fourier Transform Infrared Spectra Using Rule Induction Methods Application to the Classification of Eubacterium Species, Applied Spectroscopy, 52(6) (1998), 823-832. 

Small, G. W. Barber, A. S. (1992) Application of digital filtering and pattern recognition techniques to interferogram based Fourier transform infrared qualitative analysis. Investigation of special interferences. Chemometrics and intelligent laboratory systems 15, 203-217. 

Shaffer, R. E., Small, G. W., Combs, R. J., Knapp, R. B. Kroutil, R. T. (1995) Experimental-Design Protocol For the Pattern-Recognition Analysis of Bandpass Filtered Fourier-Transform Infrared Interferograms. Chemometrics and Intelligent Laboratory Systems 29,89-108. 

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