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…

Co-design and evaluation of spatially explicit strategies of adaptation to climate change in a Mediterranean watershed

Climate change challenges differently wine growing systems, depending on their biophysical, sociological and economic features. Therefore, there is a need to locally design and evaluate adaptation strategies combining several technical options, and considering the local opportunities and constraints (e.g. water access, wine typicity). The case study took place in a typical and heterogeneous Mediterranean vineyard of 1,500 ha in the South of France. We developed a participatory modeling approach to (1) conceptualize local climate change issues and design spatially explicit adaptation strategies with stakeholders, (2) numerically evaluate their effects on phenology, yield and irrigation needs under the high-emissions climate change scenario RCP 8.5, and (3) collectively discuss simulation results. We organized five sets of workshops, with in-between modeling phases. A process-based model was developed that allowed to evaluate the effects of six technical options (late varieties, irrigation, water saving by reducing canopy size, adjusting cover cropping, reducing density, and shading) with various distributions in the watershed, as well as vineyard relocation. Overall, we co-designed three adaptation strategies. Delay harvest strategy with late varieties showed little effects on decreasing air temperature during ripening. Water constraint limitation strategy would compensate for production losses if disruptive adaptations (e.g. reduced density) were adopted, and more land got access to irrigation. Relocation strategy would foster high premium wine production in the constrained mountainous areas where grapevine is less impacted by climate change. This research shows that a spatial distribution of technical changes gives room for adaptation to climate change, and that the collaboration with local stakeholders is a key to the identification of relevant adaptation. Further research should explore the potential of adaptation strategies based on soil quality improvement and on water stress tolerant varieties.

‘Cabernet Sauvignon’ (Vitis vinifera L.) berry skin flavonol and anthocyanin composition is affected by trellis systems and applied water amounts

Trellis systems are selected in wine grape vineyards to mainly maximize vineyard yield and maintain berry quality. This study was conducted in 2020 and 2021 to evaluate six commonly utilized trellis systems including a vertical shoot positioning (VSP), two relaxed VSPs (VSP60 and VSP80), a single high wire (SH), a high quadrilateral (HQ), and a guyot (GY), combined with three levels of irrigation regimes based on different crop evapotranspiration (ETc) replacements, including a 25% ETc, 50% ETc, and 100% ETc. The results indicated SH yielded the most fruits and accumulated the most total soluble solids (TSS) at harvest in 2020, however, it showed the lowest TSS in the second season. In 2020, SH and HQ showed higher concentrations in most of the anthocyanin derivatives compared to the VSPs. Similar comparisons were noticed in 2021 as well. SH and HQ also accumulated more flavonols in both years compared to other trellis systems. Overall, this study provides information on the efficacy of trellis systems on grapevine yield and berry flavonoid accumulation in a currently warming climate.

Impact of climate variability and change on grape yield in Italy

Viticulture is entangled with weather and climate. Therefore, areas currently suitable for grape production can be challenged by climate change. Winegrowers in Italy already experiences the effect of climate change, especially in the form of warmer growing season, more frequent drought periods, and increased frequency of weather extremes.
The aim of this study is to investigate the impact of climate variability and change on grape yield in Italy to provide winegrowers the information needed to make their business more sustainable and resilient to climate change. We computed a specific range of bioclimatic indices, selected by the International Organisation of Vine and Wine (OIV), and correlated them to grape yield data. We have worked in collaboration with some wine consortiums in northern and central Italy, which provided grape yield data for our analysis.
Using climate variables from the E-OBS dataset we investigate how the bioclimatic indices changed in the past, and the impact of this change on grape productivity in the study areas. The climate impact on productivity is also investigated by using high-resolution convection-permitting models (CPMs – 2.2 horizontal resolution), with the purpose of estimating productivity in future emission scenarios. The CPMs are likely the best available option for this kind of impact studies since they allow a better representation of small-scale processes and features, explicitly resolve deep convection, and show an improved representation of extremes. In our study, we also compare CPMs with regional climate models (RCMs – 12 km horizontal resolution) to assess the added value of high-resolution models for impact studies. Further development of our study will lead to assessing the future suitability for vine cultivation and could lead to the construction of a statistical model for future projection of grape yield.

Spatiotemporal patterns of chemical attributes in Vitis vinifera L. cv. Cabernet Sauvignon vineyards in Central California

Spatial variability of vine productivity in winegrapes is important to characterise as both yield and quality are relevant for the production of different wine styles and products. The objectives were to understand how patterns of variability of Cabernet Sauvignon fruit composition changed over time and space, how these patterns could be characterised with indirect measurements, and how spatial patterns of the variation in fruit compositional attributes can aid in improving management. Prior to the 2017 vintage, 125 data vines were distributed across each of four vineyards in the Lodi American Viticultural Area (AVA) of California. Each data vine was sampled at commercial harvest in 2017, 2018, and 2019. Yield components and fruit composition were measured at harvest for each data vine, and maps of yield and fruit composition were produced for eight ‘objective measures of fruit quality’: total anthocyanins, polymeric tannins, quercetin glycosides, malic acid, yeast assimilable nitrogen, β-damascenone, C6 alcohols and aldehydes, and 3-isobutyl-2-methoxypyrazine. Patterns of variation in anthocyanins and phenolic compounds were found to be most stable over time. Given this relative stability, management decisions focused on fruit quality could be based on zonal descriptions of anthocyanins or phenolics to increase profitability in some vineyards. In each vineyard, dormant season pruning weights and soil cores were collected at each location, elevation and soil apparent electrical conductivity surveys were completed, and remotely sensed imagery was captured by fixed wing aircraft and two satellite platforms at major phenological stages. The data collected were used to develop relationships among biophysical data, soil, imagery, and fruit composition. The standardised and aggregated samples from four vineyards over three seasons were included in the estimation of ‘common variograms’ to assess how this technique could aid growers in producing geostatistically rigorous maps of fruit composition variability without cumbersome, single season sampling efforts.

Climate modeling at local scale in the Waipara winegrowing region in the climate change context

In viticulture, a warming climate can have a very significant impact on grapevine development and therefore on the quality and characteristics of wines across different spatial scales, ranging from global to local. In order to adapt wine-growing to climate change, global climate models can be used to define future scenarios, but only at the scale of major wine regions. Despite the huge progress made over the last ten years in terms of the spatial resolution of climate models (now downscaled to a few square kilometres), they are not yet sufficiently precise to account for the local climate variability associated with such parameters as local topography, in spite of these parameters being decisive for vine and wine characteristics. This study describes a method to downscale future climate scenarios to vineyard scale. Networks of data loggers have been used to collect air temperature at canopy level in the Waipara winegrowing region (New Zealand) over five growing seasons. These measurements allow the creation of fine-scale geostatistical models and maps of temperature (at 100 m resolution) for the growing season. In order to model climate change at pilot site scale, these geostatistical models have been combined with regional climate change predictions for the periods 2031-2050 and 2081-2100 based on the RCP8.5 climate change scenario. The integration of local climate variability with regionalized climate change simulations allows assessment of the impacts of climate change at the vineyard scale. The improved knowledge gained using this methodology results from the increased horizontal resolution that better addresses the concerns of winegrowers. The results provide the local winegrowers with information necessary to understand current processes, as well as historical and future viticulture trends at the scale of their site, thereby facilitating decisions about future response strategies.