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…

Updating the Winkler index: An analysis of Cabernet sauvignon in Napa Valley’s varied and changing climate

This study aims to create an updated, agile viticultural climate index (similar to the Winkler Index) by performing in-depth analyses of current and historical data from industry partners in several major winegrowing regions. The Winkler Index was developed in the early twentieth century based on analysis of various grape-growing regions in California. The index uses heat accumulation (i.e. Growing Degree Days) throughout the growing season to determine which grape varieties are best suited to each region. As viticultural regions are increasingly subject to the complexity and uncertainty of a changing climate, a more rigorous, agile model is needed to aid grape growers in determining which cultivars to plant where. For the first phase of this study, 21 industry partners throughout Napa Valley shared historical phenology, harvest, viticultural practice, and weather data related to their Cabernet sauvignon vineyard blocks. To complement this data, berry samples were collected throughout the 2021 growing season from 50 vineyard blocks located throughout 16 American Viticultural Areas that were then analyzed for basic berry chemistry and phenolics. These blocks have been mapped using a Geographic Information System (GIS), enabling analysis of altitude, vineyard row orientation, slope, and remotely sensed climate data. Sampling sites were also chosen based on their proximity to a weather station. By analyzing historical data from industry partners and data specifically collected for this study, it is possible to identify key parameters for further analysis. Initial results indicate extreme variability at a high spatial resolution not currently accounted for in modern viticultural climate indices and suggest that viticultural practices play a major role. Using the structure of data collection and analyses developed for the first phase, this project will soon be expanded to other wine regions globally, while continuing data collection in Napa Valley.

Downscaling of remote sensing time series: thermal zone classification approach in Gironde region

In viticulture, the challenges of local climate modelling are multiple: taking into account the local environment, fine temporal and spatial scales, reliable time series of climate data, ease of implementation and reproducibility of the method. At the local scale, recent studies have demonstrated the contribution of spatialization methods for ground-based climate observation data considering topographic factors such as altitude, slope, aspect, and geographic coordinates (Le Roux et al, 2017; De Rességuier et al, 2020). However, these studies have shown questions in terms of the reproducibility and sustainability of this type of climate study. In this context, we evaluated the potential of MODIS thermal satellite images validated with ground-based climate data (Morin et al, 2020). Previous studies have been encouraging, but questions remain to be explored at the regional scale, particularly in the dynamics of the massive use of bioclimatic indices to classify the climate of wine regions. The results at the local scale were encouraging, but this approach was tested in the current study at the regional scale. Several objectives were set: 1) to evaluate the downscaling method for land surface temperature time series, 2) to identify regional thermal structure variations. We used weekly minimum and maximum surface temperature time series acquired by MODIS satellites at a spatial resolution of 1000 m and downscaled at 500 m using topographical variables. Two types of analyses were performed:

Mobile device to induce heat-stress on grapevine berries

Studying heat stress response of grapevine berries in the field often relies on weather conditions during the growing season. We constructed a mobile heating device, able to induce controlled heat stress on grapes in vineyards. The heater consisted of six 150 W infrared lamps mounted in a profile frame. Heating power of the lamps could be controlled individually by a control unit consisting of a single board computer and six temperature sensors to reach a pre-set temperature. The heat energy applied to individual berries within a cluster decreases by the squared distance to the heat source, enabling the establishment of temperature profiles within individual clusters. These profiles can be measured by infrared thermography once a steady state has been reached. Radiant flux density received by a berry depending on the distance was calculated based on a view factor and measured lamp surface temperature and resulted to 665 Wm-2 at 7cm. Infrared thermography of the fruit surface was in good agreement with measurements conducted with a thermocouple inserted at epidermis level. In combination with infrared thermography, the presented device offers possibilities for a wide range of applications like phenotyping for heat tolerance in the field to proceed in the understanding of the complex response of plants to heat stress. Sunburn necrosis symptoms were artificially induced with the aid of the device for cv. Bacchus and cv. Sylvaner in the 2020 and 2021 growing season. Threshold temperatures for sunburn induction (LT5030min) were derived from temperature data of single berries and visual sunburn assessment, applying logistic regression. A comparison of threshold temperatures for the occurrence of sunburn necrosis confirmed the higher susceptibility of cv. Bacchus. The lower susceptibility of cv. Sylvaner did not seem to be related to its phenolic composition, rendering a thermoprotective role of berry phenolic compounds unlikely.

Effect of one-year cover crop and arbuscular mycorrhiza inocululation in the microbial soil community of a vineyard

The microbial composition of the soil is an important factor to consider in viticulture, since its influence on the “terroir” and on the organoleptic properties of the wine have been demonstrated. Different agronomic techniques have the potential to modify the composition and functionality of the soil microbial community. Maintaining green covers is known to increase soil microbial diversity. The direct application of inoculum of beneficial microorganisms to the soil has also been used to increase their abundance. However, the environmental conditions of each site seem to have a determining weight in the result of these practices. In this study, we compared the effect on the microbial community of a cover crop with legumes in autumn and the inoculation of grapevines with commercial inoculum bases on Rhizophagus irregularis and Funeliformis mosseae in the previous spring. The study has been carried out in a vineyard in Binissalem, Mallorca, Spain. After applying the treatments, we will analyze the soil microbial communities using the data obtained from Illumina amplification of soil DNA from the 16S and ITS regions to analyze bacteria and fungi community, respectively. In addition, we will record the physicochemical characteristics of the soil at each sampling point. The result showed that agronomic management, in the short term, has less influence than soil characteristics on the composition of the soil microbiome. With these results, we can conclude that in a vineyard, agricultural techniques should focus on improving the characteristics of the soil to improve the biodiversity of the soil microbiota.

Analysis of Cabernet Sauvignon and Aglianico winegrape (V. vinifera L.) responses to different pedo-climatic environments in southern Italy

Water deficit is one of the most important effects of climate change able to affect agricultural sectors. In general, it determines a reduction in biomass production, and for some plants, as in the case of grapevine, it can endorse fruit quality. The monitoring and management of plant water stress in the vineyard