NIR spectroscopy in simulation – a new way for augmenting near-infrared phytoanalysis

Near-infrared (NIR) spectroscopy is a powerful tool for qualitative and quantitative phytoanalysis. The backbone of NIR spectroscopy, multi-variate data analysis, provides no physical insight into the molecular system. In our research [1] we employ the methods of computational chemistry to unveil the origins of NIR bands, and to establish the basic relationship between the wavenumbers influential in quantitative models, and the underlying molecular background. Examples of substances with importance in phytoanalysis are presented, rosmarinic acid [2],[3] and thymol [4], as prototypic polyphenol and monoterpene.

NIR spectra simulations not only provide deep understanding of the spectral bands. In addition, the features of quantitative models obtained in analytical routines may be interpreted. Fundamental relationships with the basic factors may be established, e.g. how the sensitivity of the molecule to its chemical environment is reflected in the models, and thus an understanding of how these factors affect the analytical spectroscopy is obtained.

This work was supported by the Austrian Science Fund (FWF), M2729-N28.

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• References

• 1 Beć KB, Huck CW. Breakthrough potential in near-infrared spectroscopy: spectra simulation. A review of recent developments. Front Chem 2019; 7 (Article 48): 1-22.
• 2 Kirchler CG, Pezzei CK, Beć KB, Mayr S, Ishigaki M, Ozaki Y. , et al. Critical evaluation of spectral information of benchtop vs. portable near-infrared spectrometers: quantum chemistry and two dimensional correlation spectroscopy for a better understanding of PLS regression models of the rosmarinic acid content in Rosmarini folium . Analyst 2017; 142: 455-464.
• 3 Kirchler CG, Pezzei CK, Beć KB, Henn R, Ishigaki M, Ozaki Y. et al. Critical evaluation of NIR and ATR-IR spectroscopic quantifications of rosmarinic acid in Rosmarini folium supported by quantum chemical calculations. Planta Med 2017; 83 (12/13) : 1076-1084.
• 4 Beć KB, Grabska J, Kirchler CG, Huck CW. NIR spectra simulation of thymol for better understanding of the spectra forming factors, phase and concentration effects and PLS regression features. J Mol Liq 2018; 268: 895-902.