Development of UV-vis and FTIR Partial Least Squares models: comparison and combination of two spectroscopy techniques with chemometrics for polyphenols quantification in red wine

Abstract

Polyphenolic compounds are considered to have a major impact on the quality of red wines. Sensory perception, such as astringency and bitterness, are mainly related to condensed tannin, while colour intensity and evolution is due to anthocyanin composition. Therefore, the quick analytical measurement of phenolic compounds appears to be a real challenge for wine monitoring. Fourier transform infrared (FTIR) and ultraviolet-visible (UV-vis) spectroscopy with chemometrics are good candidates for predicting polyphenolic contents in wines, but they have not yet been compared in terms of efficiency of each wavelength area. Thus, the possibility of combining the two areas has not been investigated.This work sought to determine the tannin and anthocyanin content of ninety-two wines. The wine selection covered different vintages, varieties and regions. Tannin concentration was analysed by precipitation with protein and polysaccharide and by the Bate-Smith assay. Free anthocyanin concentration was analysed by bisulfite bleaching and the monomers/polymers ratio was analysed using the Adams-Harbertson method. Molecular anthocyanin concentration was also obtained by HPLC/UV-vis. Two spectra were collected using UV-vis and FTIR devices. The data collected were statistically analysed using the partial least squares (PLS) regression method.The correlations obtained were relevant to both of the spectrum areas studied, with a coefficient of determination for cross validation larger than 0.7 for most parameters studied. While the two spectroscopic methods gave almost identical results, FTIR indicated higher robustness for the prediction of tannin concentration. Conversely, UV-vis appeared to be more relevant when determining anthocyanin concentration and evolution. Finally, the models obtained when combining the two spectrum areas gave slightly better results. When a selection of different visible wavelengths were added to the FTIR spectrum, the results showed that the prediction of anthocyanin parameters improved considerably, thus highlighting the importance of the visible area when estimating these compounds.

Fourier transform infrared spectroscopy in monitoring the wine production

“…In a comparison study between FTIR and UV-vis spectroscopy, FTIR showed more accurate results for the prediction of tannin concentration, while UV-vis stood out for the prediction of anthocyanins. However, the analysis of some wavelengths in the visible region in combination with FTIR spectrum contributed to a better determination of anthocyanin content (Miramont et al, 2020). The quantification of hydrolysable tannins is of great importance for the wine industry because they are responsible for very important modifications in the wine's organoleptic characteristics (Michel et al, 2011).…”

Accurate varietal classification and quantification of key quality compounds of grape extracts using the absorbance-transmittance fluorescence excitation emission matrix (A-TEEM) method and machine learning

“…Whereas High-Performance Liquid Chromatography (HPLC) is recognised as the primary reference method for wine phenolic analysis, it may be too expensive, time-consuming and complex for effective implementation scale-up. Hence secondary methods, including Fourier Transform Infrared (FTIR), Near and Mid-Infrared (NIR and MIR), Nuclear Magnetic Resonance (NMR) and UV-VIS spectroscopies, have been examined with respect to their ability to be calibrated against HPLC and other reference chemistry methods (Aleixandre-Tudo et al, 2017;Harbertson et al, 2003;Harbertson and Spayd, 2006;Miramont et al, 2020;Rouxinol et al, 2022;Sen et al, 2016). The consensus is that while these secondary spectroscopic techniques provide generalised compound class information, they do not exhibit highly correlated molecular specificity for the key phenolic compounds generally regarded as quality parameters.…”