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Fractal Approach for 1H-NMR Spectra Simplification and Data Processing

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Abstract

Nuclear magnetic resonance (NMR) is a powerful instrumental technique suited to characterize and identify organic substances, and has been successfully applied in the analysis of complex matrices such as biological and environmental samples. In a previous work, we demonstrated the ability of unsupervised contribution analysis (UCA) to process complex mixtures to identify the number of independent constituents and deconvolute mixed signals into specific signal sources. In this work, we evaluated the deconvolving ability of this algorithm to access underlying spectral information—we used UCA to estimate the number of contributing species and respective contributing sources and scores and with that information performed selective 1H-NMR signal suppression. We found that, in optimal NMR conditions, independently of signal source type, UCA allows us to correctly (a) estimate the number of independent contributions, (b) retrieve specific signal sources and (c) respective mixing information, allowing us to (d) characterize each contribution using signal sources and (e) quantify each specific contribution by means of its mixing information. This unsupervised soft-modeling method allows (f) individual contribution estimation and (g) respective removal from collected spectra, thus (h) enhancing spectra information for minor contributing species.

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Acknowledgements

The Coimbra Chemistry Centre (CQC) is supported by FCT, through the project UI0313/QUI/2013, also co-funded by FEDER/COMPETE 2020-UE. We acknowledge the “Rede Nacional de RMN” (REDE/1517/RMN/2005) facility, also funded by Fundo Europeu de Desenvolvimento Regional (FEDER) Funds through the Operational Competitiveness Program COMPETE and by National Funds through FCT under the project FCOMP 010124FEDER020970 (PTDC/QUIBIQ/120319/2010).

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Authors and Affiliations

  1. CQC, Department of Chemistry, University of Coimbra, 3004 535, Coimbra, Portugal

    Jorge Costa Pereira

  2. CICS-UBI, University of Beira Interior, 6201-506, Covilhã, Portugal

    Ivana Jarak

  3. Centre for Functional Ecology, Faculty of Sciences and Technology, University of Coimbra, 3000 456, Coimbra, Portugal

    Ivana Jarak & Rui Albuquerque Carvalho

  4. Department of Life Sciences, Faculty of Sciences and Technology, University of Coimbra, 3000 456, Coimbra, Portugal

    Rui Albuquerque Carvalho

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  1. Jorge Costa Pereira
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  2. Ivana Jarak
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Correspondence to Jorge Costa Pereira.

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Costa Pereira, J., Jarak, I. & Carvalho, R.A. Fractal Approach for 1H-NMR Spectra Simplification and Data Processing. Appl Magn Reson 49, 975–998 (2018). https://doi.org/10.1007/s00723-018-1010-5

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  • DOI: https://doi.org/10.1007/s00723-018-1010-5

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