Correcting Attenuated Total Reflection—Fourier Transform Infrared Spectra for Water Vapor and Carbon Dioxide

Abstract

Fourier transform infrared (FT-IR) spectroscopy is a valuable technique for characterization of biological samples, providing a detailed fingerprint of the major chemical constituents. However, water vapor and CO(2) in the beam path often cause interferences in the spectra, which can hamper the data analysis and interpretation of results. In this paper we present a new method for removal of the spectral contributions due to atmospheric water and CO(2) from attenuated total reflection (ATR)-FT-IR spectra. In the IR spectrum, four separate wavenumber regions were defined, each containing an absorption band from either water vapor or CO(2). From two calibration data sets, gas model spectra were estimated in each of the four spectral regions, and these model spectra were applied for correction of gas absorptions in two independent test sets (spectra of aqueous solutions and a yeast biofilm (C. albicans) growing on an ATR crystal, respectively). The amounts of the atmospheric gases as expressed by the model spectra were estimated by regression, using second-derivative transformed spectra, and the estimated gas spectra could subsequently be subtracted from the sample spectra. For spectra of the growing yeast biofilm, the gas correction revealed otherwise hidden variations of relevance for modeling the growth dynamics. As the presented method improved the interpretation of the principle component analysis (PCA) models, it has proven to be a valuable tool for filtering atmospheric variation in ATR-FT-IR spectra.

Spectroscopic and chemometric approaches to radiobiological analyses

“…Corrections for this effect may be provided with the extended multiplicative scatter correction (EMSC) [67,68]. Other contaminating effects in FTIRM spectra occur due to aborptions of water vapour and CO 2 , which may also be removed by existing embedded machine-dependent software corrections or machine-dependent in-house correction algorithms [69], while simple filtering and normalization procedures may correct for spectral noise and remove point-to-point variations in sample concentration.…”

“…Approximately 300 spectra were recorded at each dose and time point. Outliers were removed using a multivariate test of the dissimilarity between the spectral data within a given dose and time class, and the contributions of water and carbon dioxide were removed from each spectral set [69]. Each spectral set was then corrected using EMSC [68], and were vector normalised.…”

Vibrational spectroscopy as a tool for studying drug-cell interaction: Could high throughput vibrational spectroscopic screening improve drug development?

“…This helps remove the effects of instrument-to-instrument and sample-to-sample variation, therefore standardising the technique for translation into clinical and HTS applications. Particular pre processing considerations for IR spectroscopy involve applying Mie scattering correction algorithms [40] and water correction algorithms [41] for aqueous samples (see section 4 for a full discussion). A major consideration for both IR and Raman spectroscopy is substrate, with different substrates creating different background contributions in the spectra.…”

“…Even when the aqueous environment of the cells is removed, contributions from water vapor, as well as CO2, in the atmosphere can affect spectra. [41] Much of this water and CO2 vapor contribution can be removed by purging instruments. It is likely, however, that water contributions will still be observed, and water correction algorithms need to be employed to remove these.…”

Infrared imaging in histopathology: Is a unified approach possible?

“…The most advanced ones consider a large variability in the water vapor spectrum related to environmental changes (temperature, pressure). PCA and EMSC in particular were used to model the variability present in water vapor spectrum [17,26,27,41].…”