IVAS 2022 banner
IVES 9 IVES Conference Series 9 IVAS 9 IVAS 2022 9 Multivariate data analysis applied on Fourier Transform Infrared spectroscopy for the prediction of tannins levels during red wine fermentation

Multivariate data analysis applied on Fourier Transform Infrared spectroscopy for the prediction of tannins levels during red wine fermentation

Abstract

Red wine is a beverage with one of the highest polyphenol concentration, which are extracted during the maceration step of the winemaking process. Sensory perception such as astringency and bitterness are mainly related to tannin concentration and composition. However, quick analytical measurement of polyphenolic compounds can be a real challenge for monitoring their extraction during fermentation. Many methods were developed to analyzed polyphenols in wine, but they are time-consuming and require chemistry skills and equipment, not suitable for a rapid routine analysis. Thus, development of predictive models
using Fourier transform infrared (FTIR) spectroscopy coupled with chemometrics analysis appears to be a reliable and rapid method to determine polyphenolic content during wines fermentation.

For this purpose, this work sought to determine correlation between FTIR analysis and regular quantification methods for tannins, for different samples, covering three different vintages with two different grape varieties, from the beginning to the end of the extraction process. The search for diversity was highlighted during the selection of samples, to provide the best representation of the winemaking process. Total tannin concentration was analyzed by protein and polysaccharide precipitation. Flavanol composition was obtained by HPLC-UV after phloroglucinolysis reaction. FTIR spectra were registered between 925 and 5011 cm-1 using Winescan. Correlation between spectral analyzes and the various analytical information obtained were sought with partial least squares (PLS) multivariate regression analysis, for designing prediction models. The different models were tested with cross validation, and validation with an external set of samples to the calibration. For the external validation, the dataset was split into calibration and validation using Kennard-Stone algorithm.

The objective of this study was to demonstrate the interest of FTIR with PLS multivariate regression analysis to predict tannins concentration during winemaking. Correlations obtained show relevant results for the studied parameters, with models coefficients for cross validation higher than 0.8 for flavanol content (except for epigallocatechin) and higher than 0.9 for total tannins concentrations. The results with external validation are slightly lower for total tannins concentrations, with coefficient of prediction around 0.87, and show a more important decrease for flavanol content, with coefficient of prediction close to 0.7. If models for total tannins already show a high robustness and prediction, models for flavanol content must be improve with other samples. However, the results are encouraging and an
increase of the robustness could allow following flavanol content during winemaking. This work is the first step for the construction of predictive models to quantify different flavanol parameters in red wine fermentation by FTIR spectroscopy.

DOI:

Publication date: June 23, 2022

Issue: IVAS 2022

Type: Article

Authors

Miramont Clément¹, Jourdes Michaël¹, Selberg Torben³, Winther J∅rgensenKasper³, Thiis Heide Søren³and Teissèdre Pierre-Louis¹

¹UR Œnologie EA 4577, Université de Bordeaux, ISVV
²USC 1366 INRAE, IPB, INRAE, ISVV
³FOSS Analytical A/

Contact the author

Keywords

Tannins, Flavanol, Partial least squares regression, Fourier Transform InfraRed

Tags

IVAS 2022 | IVES Conference Series

Citation

Related articles…

Water deficit differentially impacts the performances and the accumulation of grape metabolites of new varieties tolerant to fungi

The use of resistant varieties is a long-term but promising solution to reduce chemical input in viticulture. Several important breeding programs in Europe and abroad are now releasing a range of new hybrids performing well regarding fungi susceptibility and producing good quality wines. Unfortunately, insufficient attention is paid by the breeders to the adaptation of these varieties to climatic changes, notably to the increased climatic demand and water deficit (WD). Thus, prior to the adoption of such varieties by the wine industry in Mediterranean regions, there is a need to consider their suitability to WD. This study aimed to characterize the different drought-strategies adopted by 6 new resistant varieties selected by INRAE in comparison to Syrah. To allow the assessment of long-term impacts of WD, field-grown vines were exposed to contrasted WD from 2018 to 2021 under a semi-arid Mediterranean climate. A gradient of WD was applied in the field and controlled through plant measurements at the single plant level. Grape development was non-destructively monitored to determine the arrest of berry phloem unloading. The impacts of WD on berry composition, including water, primary metabolites (sugars, organic acids), secondary metabolites (anthocyanins, thiols precursors) and main cations contents, were assessed at this specific stage. Results showed different varietal responses during the year and inter-annual acclimation in terms of plant water use efficiency, biomass accumulation, as well as yield components and berry composition. WD differentially reduced the accumulation of primary metabolites at plant and berry levels, but it little changed their concentrations in the fruits at the ripe stage. Moreover, WD differentially impacted the accumulation of secondary metabolites and major cations between the varieties. In the talk, we’ll present the main results regarding the WD impacts on fruit metabolites and enlarge the reflection about the practical assessment of the grapevine acclimation to WD.

Effect of fertigation strategies to adapt PGI Côtes de Gascogne production to hot vintage

The development of fertigation could be a possible solution to adapt PGI Côtes de Gascogne (south-western France) wine production to climate change. The goal would be to limit the negative effects of water stress on yield performance expectation (around 15 tons per hectare) and to make the use of fertilizers more efficient. This study aimed to compare the effects of three strategies of water and minerals supply on grapes and wines qualities. Two fertigation practices were compared to a rainfed control which is the current standard of the local grape growing production. The fertilizers (nitrogen and potassium) were (i) fully brought by irrigation pipe during the season, (ii) partially brought by irrigation pipe and partially on the soil or (iii) fully brought on the soil at the beginning of the season for the non-irrigated control (local standard). The trial was run on cv. Colombard trained on spur pruned with vertical shoot positioning system on a sandy-silty-clay soil over the 2020 vintage which was particularly hot for the region. Moderate to strong water deficit appeared during the growing period of the berries and held on after veraison. Irrigation strategies allowed for maintaining grapevine without water deficit and being significantly different from the control water status. Grapevine with fully or partial fertigation strategies produced 25% more yield mainly due to the increase of the bunch weight. Also, the fully fertigation showed the best ratio between yield and maturity and brought 30% less of fertilizers (both nitrogen and potassium) than the two other strategies. Finally, the analysis of aromatic compounds in Colombard wines, varietal thiols family, showed the same level of concentrations for the 3 treatments, confirming that the yield performance did not impact the aromatic potential in this trial.

Simulating climate change impact on viticultural systems in historical and emergent vineyards

Global climate change affects regional climates and hold implications for wine growing regions worldwide. Although winegrowers are constantly adapting to internal and external factors, it seems relevant to develop tools, which will allow them to better define actual and future agro-climatic potentials. Within this context, we develop a modelling approach, able to simulate the impact of environmental conditions and constraints on vine behaviour and to highlight potential adaptation strategies according to different climate change scenarios. Our modeling approach, named SEVE (Simulating Environmental impacts on Viticultural Ecosystems), provides a generic modeling framework for simulating grapevine growth and berry ripening under different conditions and constraints (slope, aspect, soil type, climate variability…) as well as production strategies and adaptation rules according to climate change scenarios. Each activity is represented by an autonomous agent able to react and adapt its reaction to the variability of environmental constraints. Using this model, we have recently analyzed the evolution of vineyards’ exposure to climatic risks (frost, pathogen risk, heat wave) and the adaptation strategies potentially implemented by the winegrowers. This approach, implemented for two climate change scenarios, has been initiated in France on traditional (Loire Valley) and emerging (Brittany) vineyards. The objective is to identify the time horizons of adaptations and new opportunities in these two regions. Carried out in collaboration with wine growers, this approach aims to better understand the variability of climate change impacts at local scale in the medium and long term.

Grape berry size is a key factor in determining New Zealand Pinot noir wine composition

Making high quality but affordable Pinot noir (PN) wine is challenging in most terroirs and New Zealand’s (NZ) situation is no exception. To increase the probability of making highly typical PN wines producers choose to grow grapes in cool climates on lower fertility soils while adopting labour intensive practices. Stringent yield targets and higher input costs necessarily mean that PN wine cost is high, and profitability lower, in line-priced varietal wine ranges. To understand the reasons why higher yielding vines are perceived to produce wines of lower quality we have undertaken an extensive study of PN in NZ. Since 2018, we established a network of twelve trial sites in three NZ regions to find individual vines that produced acceptable commercial yields (above 2.5kg per vine) and wines of composition comparable to “Icon” labels. Approximately 20% of 660 grape lots (N = 135) were selected from within a narrow juice Total Soluble Solids (TSS) range and made into single vine wines under controlled conditions. Principal Component Analysis of the vine, berry, juice and wine parameters from three vintages found grape berry mass to be most effective clustering variable. As berry mass category decreased there was a systematic increase in the probability of higher berry red colour and total phenolics with a parallel increase in wine phenolics, changed aroma fraction and decreased juice amino acids. The influence of berry size on wine composition would appear stronger than the individual effects of vintage, region, vineyard or vine yield. Our observations support the hypothesis that it is possible to produce PN wines that fall within an “Icon” benchmark composition range at yields above 2.5kg per vine provided that the Leaf Area:Fruit Weight ratio is above 12cm2 per g, mean berry mass is below 1.2g and juice TSS is above 22°Brix.

Variations of soil attributes in vineyards influence their reflectance spectra

Knowledge on the reflectance spectrum of soil is potentially useful since it carries information on soil chemical composition that can be used to the planning of agricultural practices. If compared with analytical methods such as conventional chemical analysis, reflectance measurement provides non-destructive, economic, near real-time data. This paper reports results from reflectance measurements performed by spectroradiometry on soils from two vineyards in south Brazil. The vineyards are close to each other, are on different geological formations, but were subjected to the same management. The objective was to detect spectral differences between the two areas, correlating these differences to variations in their chemical composition, to assess the technique’s potential to predict soil attributes from reflectance data.To that end, soil samples were collected from ten selected vine parcels. Chemical analysis yield data on concentration of twenty-one soil attributes, and spectroradiometry was performed on samples. Chemical differences significant to a 95% confidence level between the two studied areas were found for six soil attributes, and the average reflectance spectra were separated by this same level along most of the observed spectral domain. Correlations between soil reflectance and concentrations of soil attributes were looked for, and for ten soil traits it was possible to define wavelength domains were reflectance and concentrations are correlated to confidence levels from 95% to 99%. Partial Least Squares Regression (PLSR) analyses were performed comparing measured and predicted concentrations, and for fifteen out of 21 soil traits we found Pearson correlation coefficients r > 0.8. These preliminary results, which have to be validated, suggest that variations of concentration in the investigated soil attributes induce differences in reflectance that can be detected by spectroradiometry. Applications of these observations include the assessment of the chemical content of soils by spectroradiometry as a fast, low-cost alternative to chemical analytical methods.