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…

Pruned vine biomass exclusion from a clay loam vineyard soil – examining the impact on physical/chemical properties

The wine industry worldwide faces increasing challenges to achieve sustainable levels of carbon emission mitigation. This project seeks to establish the feasibility of harvesting winter pruned vineyard biomass (PVB) for potential use in carbon footprint reduction, through its use as a renewable biofuel for energy production. In order to make this recommendation, technical issues such as the potential environmental impact, chemical composition and fuel suitability, and logistical challenges of harvesting biomass needs to be understood to compare with the results from similar studies. Of particular interest is the role PVB plays as a carbon source in vineyard soils and what effect annual removal might have on soil carbon sequestration. A preliminary trial was established in the Waite Campus vineyard (University of Adelaide) to test current management strategies. Vines are grown in a Eutrophic, Red Dermosol clay loam soil with well managed midrow swards. A comparison was undertaken of mid-row treatments in two 0.25 Ha blocks (Shiraz and Semillon), including annual cultivation for seed bed preparation, the deliberate exclusion of PVB (25 years) and incorporation of PVB (13 years) at an average of 3.4 and 5.5 Mg/Ha-1 for Shiraz and Semillon respectively. In both 0-10cm and 10-30cm soil core sample depths, combined soil carbon % measures in the desired range of 1.80 to 3.50, were not significantly different between treatments or cultivars and yielded an estimated 42 Mg/ha-1 of sequestered soil carbon. Other key physical and chemical measures were likewise not significantly different between treatments. Preliminary results suggest that in a temperate zone vineyard, managed such as the one used in this study, there is no long term negative impact on soil carbon sequestration through removing PVB. This implies that growers could confidently harvest PVB for use in several end fates including as a bio fuel.

Grapevine varietal diversity as mitigation tool for climate change: Agronomic and oenologic potential of 14 foreign varieties grown in Languedoc region (France)

Climate change effects in Languedoc include an expected rise in temperatures, increased evapotranspiration as well as more severe and frequent climatic hazards, such as frost, drought periods and heat waves. For winegrowers theses phenomena impact both yield and quality, resulting in more frequent unbalanced wines. Research on identified mitigation tools for vineyard management is necessary to improve resilience of grapevine agrosystems. Varietal assortment is one of them. This study focuses on agronomic and oenologic potential of 14 foreign varieties grown in Languedoc French region. Fourteen grapevine varieties were monitored during 2021 from June until harvest on eight different sites, some of which occurring on more than one site adding up to 21 different modalities: 7 white varieties Alvarinho B, Assyrtiko B (2), Malvasia Istriana B, Parellada B, Verdejo B, Verdelho B, Xarello B, and 7 black varieties Saperavi N (2), Touriga nacional N, Baga N, Aleatico N, Montepulciano N (2), Primitivo N (3), Calabrese N (3). Varietals were compared through the following parameters: phenology was assessed by using the information collected in the Database Network of French Vine Conservatories (INRAE-SupAgro-IFV, 2005-2015). The number of inflorescences for shoots from secondary buds and bourillons and suckers were observed to assess post-bud break frost tolerance potential. Grapevine water status was studied through stem water potential measurement, observation of foliage symptoms of drought, and 𝛿13C on must. Frequencies and intensities of downy mildew, powdery mildew, and black rot attacks were estimated before harvest on leaves and clusters and botrytis at harvest to assess disease susceptibilities. Berry composition was monitored from end of veraison until harvest. Yield and mean bunch weight were also calculated. Varieties were then ranked on a 1-4 scale for each parameter and compared through PCA. Forty two stations of the Mediterranean basin were compared by PCA with the Multicriteria Climatic Classification indicators in order to confront the collected information during 2021 campaign to the hypothesis that plants coming from dry and hot regions are genetically adapted to such climatic conditions.

Differential responses of red and white grape cultivars trained to a single trellis system – the VSP

Commercial grape production relies on training grapevine cultivars onto a variety of trellis systems. Training allows for well-lit leaves and clusters, maximizing fruit quality in addition to facilitating cultivation, harvesting, and diseases control. Although grapevines can be trained onto an infinite variety of trellis systems, most red and white cultivars are trained to the standard VSP (Vertical Shoot Positioning) system. However, red and white cultivars respond differently to VSP in fruit composition and growth characteristics, which are yet to be fully understood. Therefore, the objective of this study was to examine the influence of the VSP trellis system on fruit composition of three red, Cabernet Sauvignon, Merlot and Syrah, and three white, Chardonnay, Riesling, and Gewurztraminer cultivars grown under uniform growing conditions in the same vineyard. All cultivars were monitored for maturity and harvested at their physiologically maximum possible sugar concentration to compare various fruit quality attributes such as Brix, pH, TA, malic and tartaric acids, glucose and fructose, potassium, YAN, and phenolic compounds including total anthocyanins, anthocyanin profile, and tannins. A distinct pattern in fruit composition was observed in each cultivar. In regards to growth characteristics, Syrah grew vigorously with the highest cluster weight. Although all cultivars developed pyriform seeds, the seed size and weight varied among all cultivars. Also varied were mesocarp cell viability, brush morphology, and cane structure. This knowledge of the canopy architectural characteristics assessed by the widely employed fruit compositional attributes and growth characteristics will aid the growers in better management of the vines in varied situations.

The potential of multispectral/hyperspectral technologies for early detection of “flavescence dorée” in a Portuguese vineyard

“Flavescence dorée” (FD) is a grapevine quarantine disease associated with phytoplasmas and transmitted to healthy plants by insect vectors, mainly Scaphoideus titanus. Infected plants usually develop symptoms of stunted growth, unripe cane wood, leaf rolling, leaf yellowing or reddening, and shrivelled berries. Since plants can remain symptomless up to four years, they may act as reservoirs of FD contributing to the spread of the disease. So far, conventional management strategies rely mainly on the insecticide treatments, uprooting of infected plants and use of phytoplasma-free propagation material. However, these strategies are costly and could have undesirable environmental impacts. Thus, the development of sustainable and noninvasive approaches for early detection of FD and its management are of great importance to reduce disease spread and select the best cultural practices and treatments. The present study aimed to evaluate if multispectral/hyperspectral technologies can be used to detect FD before the appearance of the first symptoms and if infected grapevines display a spectral imaging fingerprint. To that end, physiological parameters (leaf area, chlorophyll content and photosynthetic rate) were collected in concomitance to the measurements of plant reflectance (using both a portable apparatus and a remote sensing drone). Measurements were performed in two leaves of 8 healthy and 8 FD-infected grapevines, at four timepoints: before the development of disease symptoms (21st June); and after symptoms appearance (ii) at veraison (2nd August); at post-veraison (11th September); and at harvest (25th September). At all timepoints, FD infected plants revealed a significant decrease in the studied physiological parameters, with a positive correlation with drone imaging data and portable apparatus analyses. Moreover, spectra of either drone imaging and portable apparatus showed clear differences between healthy and FD-infected grapevines, validating multispectral/ hyperspectral technology as a potential tool for the early detection of FD or other grapevine-associated diseases.

Grapevine yield estimation in a context of climate change: the GraY model

Grapevine yield is a key indicator to assess the impacts of climate change and the relevance of adaptation strategies in a vineyard landscape. At this scale, a yield model should use a number of parameters and input data in relation to the information available and be able to reproduce vineyard management decisions (e.g. soil and canopy management, irrigation). In this study, we used data from six experimental sites in Southern France (cv. Syrah) to calibrate a model of grapevine yield limited by water constraint (GraY). Each yield component (bud fertility, number of berries per bunch, berry weight) was calculated as a function of the soil water availability simulated by the WaLIS water balance model at critical phenological phases. The model was then evaluated in 10 grapegrowers’ plots, covering a diversity of biophysical and technical contexts (soil type, canopy size, irrigation, cover crop). We identified three critical periods for yield formation: after flowering on the previous year for the number of bunches and berries, around pre-veraison and post-veraison of the same year for mean berry weight. Yields were simulated with a model efficiency (EF) of 0.62 (NRMSE = 0.28). Bud fertility and number of berries per bunch were more accurately simulated (EF = 0.90 and 0.77, NRMSE = 0.06 and 0.10, respectively) than berry weight (EF = -0.31, NRMSE = 0.17). Model efficiency on the on-farm plots reached 0.71 (NRMSE = 0.37) simulating yields from 1 to 8 kg/plant. The GraY model is an original model estimating grapevine yield evolution on the basis of water availability under future climatic conditions.  It allows to evaluate the effects of various adaptation levers such as planting density, cover crop management, fruit/leaf ratio, shading and irrigation, in various production contexts.