Macrowine 2021
IVES 9 IVES Conference Series 9 Quantification of red wine phenolics using ultraviolet-visible, near and mid-infrared spectroscopy combined with chemometrics

Quantification of red wine phenolics using ultraviolet-visible, near and mid-infrared spectroscopy combined with chemometrics

Abstract

The use of multivariate statistics to correlate chemical data to spectral information seems as a valid alternative for the quantification of red wine phenolics. The advantages of these techniques include simplicity and cost effectiveness together with the limited time of analysis required. Although many publications on this subject are nowadays available in the literature most of them only reported feasibility studies. In this study 400 samples from thirteen fermentations including five different cultivars plus 150 wine samples from a varying number of vintages were submitted to spectrophotometric and chromatographic phenolic analysis. Anthocyanins, total phenolics, tannins, colour density and the most representative compounds within the main phenolic families (hydroxicinnamic acids, flavan-3-ols, flavonols and anthocyanins) were quantified. Spectra were recorded in different regions of the electromagnetic spectrum. Particularly the information contained in the ultraviolet-visible region as well as in the near and mid-infrared regions was collected. Regression models were built and validated. The interpretation of the loadings and coefficients of regression, the evaluation and analysis of the correlation among variables and the measured phenolic compounds as well as the chemistry basis behind each quantified compound was extensively investigated and reported. Spectral pre-processing techniques as well as variable selection tools were also investigated and selected based on model performance. Accurate models for most of the phenolic compounds and spectroscopies were obtained with residual predictive deviation (RPD) values higher than 2.5. The results obtained showed UV-visible and infrared spectroscopy as valid approaches for the quantification of the phenolic content throughout the winemaking process. Considerations such as easiness of use and the economical and human resources involved in the analysis will also be discussed.

Publication date: May 17, 2024

Issue: Macrowine 2016

Type: Poster

Authors

Jose Luis Aleixandre-Tudo*, Helene Nieuwoudt, Wessel du Toit

*Stellenbosch University

Contact the author

Tags

IVES Conference Series | Macrowine | Macrowine 2016

Citation

Related articles…

Analysis of peptide fraction from white wines

Among nitrogen compounds included in white wines, the peptide fraction is certainly the least studied, however this fraction is quantitatively the most important (Feuillat, 1974). Existing studies concern the fraction below 1 kDa and only for white and sparkling wines (Bartolomé et al, 1997, Desportes et al 2000). In this report, we have developed methods to isolate peptides from reference white wines. Then, we have applied this methodology with bitter wine to answer a research question: is there a relation between peptides and the bitterness of white wine as for some cheese for example (Furtado, 1984)?

To a better understanding of the impact of vine nitrogen status on volatile thiols from plot to transcriptome level

Volatile thiols contribute largely to the organoleptic characteristics and typicity of Sauvignon blanc wines. Among this family of odorous compounds, 3-sulfanylhexan-1-ol (3SH) and 4-methyl-4-sulfanylpentan-2-one (4MSP) have a major impact on wine flavor. These thiols are formed during alcoholic fermentation by the yeast from odorless and non-volatile precursors found in the berry and the must. The effect of vine nitrogen status on 3SH and 4MSP in Sauvignon blanc wine and on the glutathionylated and cysteinylated precursors of 3SH (Glut-3SH and Cys-3SH) was investigated in this study.

The moment of preharvest elicitor application influence its final effect on winegrapes quality

Phenolic compounds are secondary metabolites of grapes. Plants produce a wide variety of this type of metabolites through diverse biosynthesis pathways and their production is sometimes a response to external stimuli, either environmental or biotic stresses. Some of them may act as chemical defenses against pathogens or herbivores and their synthesis is increased when the attack exists. However, it is remarkable that the synthesis of these interesting compounds can be activated even when the stimulus is not present, with the use of elicitors. These are substances that when applied exogenously trigger the biosynthetic pathways conducting to the synthesis of these defense compounds.

Novel analytical technologies for wine fingerprinting in and beyond the laboratory

For characterization, sensory designing and authentication rapid analytical technologies have become available. Some, like Proton Transfer Reaction Mass Spectrometry allow a rapid spectrum of the volatile compounds of wines. Combined with chemometrics wines can be characterized. The same approach can be used to calculate the results of virtual mixtures and allow formulation of constant quality blends. Other new techniques and portable devices based on spectroscopy allow measurements on production sites and in grocery stores, even for the smart consumer. We will present some examples of the application of these techniques for authentication of wines, both in the laboratory and on site.

IBMP-Polypenol interactions: Impact on volatility and sensory perception in model wine solution

3-Isobutyl-2-methoxypyrazine (IBMP) is one of the key molecules in wine aroma with a bell pepper aroma and a very low threshold in wine, 1-6 ng/L for white wine and 10-16 ng/L in red wine1. The differences in these thresholds are likely due to IBMP-non volatile matrix interactions. It has indeed been shown that polyphenols may influence the volatility of flavor compounds2. In the present study, we focus on IBMP-polyphenols interactions in relation to volatility and sensory perception in model wine solution. Methods: 1. GC-MS Static Headspace Analysis: Samples were analyzed by Static headspace analysis with an Agilent 7890A gas chromatograph coupled to HP 5975C mass spectrometry detector (Agilent Technologies, Santa Clara, CA, USA).