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The Role of Multivariant Analysis on the Interpretation of FTIR and Raman Spectra

The Role of Multivariant Analysis on the Interpretation of FTIR and Raman Spectra

Sefa Celik, Ali Tugrul Albayrak, Sevim Akyuz, Aysen E. Ozel
Copyright: © 2020 |Pages: 26
ISBN13: 9781799815181|ISBN10: 1799815188|ISBN13 Softcover: 9781799815198|EISBN13: 9781799815204
DOI: 10.4018/978-1-7998-1518-1.ch005
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MLA

Celik, Sefa, et al. "The Role of Multivariant Analysis on the Interpretation of FTIR and Raman Spectra." Design of Experiments for Chemical, Pharmaceutical, Food, and Industrial Applications, edited by Eugenia Gabriela Carrillo-Cedillo, et al., IGI Global, 2020, pp. 104-129. https://doi.org/10.4018/978-1-7998-1518-1.ch005

APA

Celik, S., Albayrak, A. T., Akyuz, S., & E. Ozel, A. (2020). The Role of Multivariant Analysis on the Interpretation of FTIR and Raman Spectra. In E. Carrillo-Cedillo, J. Rodríguez-Avila, K. Arredondo-Soto, & J. Cornejo-Bravo (Eds.), Design of Experiments for Chemical, Pharmaceutical, Food, and Industrial Applications (pp. 104-129). IGI Global. https://doi.org/10.4018/978-1-7998-1518-1.ch005

Chicago

Celik, Sefa, et al. "The Role of Multivariant Analysis on the Interpretation of FTIR and Raman Spectra." In Design of Experiments for Chemical, Pharmaceutical, Food, and Industrial Applications, edited by Eugenia Gabriela Carrillo-Cedillo, et al., 104-129. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-7998-1518-1.ch005

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Abstract

FTIR and Raman spectroscopy are complementary spectroscopic techniques that play an important role in the analysis of molecular structure and the determination of characteristic vibrational bands. Vibrational spectroscopy has a wide range of applications including mainly in physics and biology. Its applications have gained tremendous speed in the field of biological macromolecules and biological systems, such as tissue, blood, and cells. However, the vibrational spectra obtained from the biological systems contain a large number of data and information that make the interpretation difficult. To facilitate the analysis, multivariant analysis comprising the reduction of the dimension of spectrum data and classification of them by eliminating redundancy data, which are obtained from the spectra and does not have any role, becomes critical. In this chapter, the applications of Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and their combination PCA-LDA, which are widely used among multivariant techniques on biological systems will be disclosed.

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