 IVES 9 IVES Conference Series 9 Determination of quality related polyphenols in chilean wines by absorbance-transmission and fluorescence excitation emission matrix (a-teem) analyses

Determination of quality related polyphenols in chilean wines by absorbance-transmission and fluorescence excitation emission matrix (a-teem) analyses

Abstract

Phenolic composition is essential to wine quality (Cleary et al., 2015; Bindon et al., 2020; Niimi et al., 2020) and its assessment is a strong industrial need to quality management. Objective of this work was to develop a rapid analysis method using the Absorbance-Transmission and fluorescence Excitation-Emission Matrix (A-TEEM) technique. Polyphenols exhibit characteristic and high fluorescence quantum yields, which makes them highly suitable for this technique. The method’s automatic real-time Inner Filter Effect (IFE) correction allows the quantification of minor compounds (Gilmore et al., 2016). IFE-corrected fluorescence EEM data and the absorbance data were combined, and the spectral data were regressed against the concentrations of 34 anthocyanins, flavan-3-ols, tannins, polymeric pigments, flavonols and hydroxycinnamic acids measured independently by HPLC-DAD and UV-vis. The study focused on comparing Partial Least Squares Regression (PLSR) and Extreme Gradient Boost Regression (XGBR) for the single- (fluorescence EEM or absorbance) and multi- (combined) block data. The calibration set comprised 1133 files acquired from 126 diverse experimental and commercial wines. Validation was carried out on two data sets, first by a 14% randomized sample split from the calibration data keeping instrument replicates together, and thereafter by another independent set of 96 files from 16 wines. As a general trend, validation of the multi-block data models with independent data using XGBR, compared to PLSR, yielded higher prediction correlation coefficients (R2P) and lower Root Mean Square Errors for Prediction (RMSEP). Considering all 34 compound fits, mean R2P of 0.947 with XGBR and of 0.899 with PLSR were obtained. The highest fits were obtained for compounds of the anthocyanin family with mean R2P of 0.974 (XGBR) and 0.954 (PLSR), respectively, while lower fits were found for flavan-3-oles with R2P of 0.878 (XGBR) and 0.771 (PLSR), indicating compound effects due to extraction and chromatographic and spectral analysis methods affecting repeatability and quantification limits. In general, precise model fits were found for compounds > 10 mg/L with R2P between 0.929 and 0.992 (XGBR) and between 0.875 and 0.992 (PLSR). Supplementary, all individual compounds could be identified according to their family by spectral fingerprints. However, these multi-block data sets were also associated with significantly higher R2P (and lower RMSEP) compared to a single block evaluation of the fluorescence EEM or absorbance data only. By using mean-centering and an Extended Mixture Model filter the multi-block data sets fit robustly using both XGBR and PLSR without the need to apply secondary variable selection algorithms. We conclude that analyzing the A-TEEM data using the multi-block organization and the XGBR algorithm facilitates a robust prediction of the key phenolic compound concentrations that strongly influence the Chilean wine quality.

DOI:

Publication date: September 7, 2021

Issue: Macrowine 2021

Type: Article

Authors

Doreen Schober

Center for Research and Innovation, Viña Concha y Toro, Ruta k-650 km 10, Pencahue, Región de Maule, Chile,Adam Gilmore, HORIBA Instruments Inc. 20 Knightsbridge Rd., Piscataway, NJ 08854, USA Jorge Zincker, Center for Research and Innovation, Viña Concha y Toro, Ruta k-650 km 10, Pencahue, Región de Maule, Chile Alvaro Gonzalez, Center for Research and Innovation, Viña Concha y Toro, Ruta k-650 km 10, Pencahue, Región de Maule, Chile

Contact the author

Keywords

quality, polyphenols, spectroscopy, a-teem, wine, machine learning

Citation

VineyardFACE: Investigation of a moderate (+20%) increase of ambient CO2 level on berry ripening dynamics and fruit composition

Climate change and rising atmospheric carbon dioxide concentration is a concern for agriculture, including viticulture. Studies on elevated carbon dioxide have already been on grapevines, mainly taking place in greenhouses using potted plants or using field grown vines under higher CO2 enrichment, i.e. >650 ppm. The VineyardFACE, located at Hochschule Geisenheim University, is an open field Free Air CO2 Enrichment (FACE) experimental set-up designed to study the effects of elevated carbon dioxide using field grown vines (Vitis vinifera L. cvs. Riesling and Cabernet Sauvignon). As the carbon dioxide fumigation started in 2014, the long term effects of elevated carbon dioxide treatment can be investigated on berry ripening parameters and fruit metabolic composition.
The present study aims to investigate the effect on fruit composition under a moderate increase (+20%; eCO2) of carbon dioxide concentration, as predicted for 2050 on both Riesling and Cabernet Sauvignon. Berry composition was determined for primary (sugars, organic acids, amino acids) and secondary metabolites (anthocyanins). Special focus was given on monitoring of berry diameter and ripening rates throughout three growing seasons. Compared to previous results of the early adaptative phase of the vines [1], our results show little effect of eCO2 treatment on primary metabolites composition in berries. However, total anthocyanins concentration in berry skin was lower for eCO2 treatment in 2020, although the ratio between anthocyanins derivatives did not differ.
[1] Wohlfahrt Y., Tittmann S., Schmidt D., Rauhut D., Honermeier B., Stoll M. (2020) The effect of elevated CO2 on berry development and bunch structure of Vitis vinifera L. cvs. Riesling and Cabernet Sauvignon. Applied Science Basel 10: 2486

Impact of climate change on the viticultural climate of the Protected Designation of Origin “Jumilla” (SE Spain)

Protected Designation of Origin “Jumilla” (PDO Jumilla) is located in the Spanish provinces of Albacete and Murcia, in the South-eastern part of the Iberian Peninsula, where most of the models predict a severe impact of climate change in next decades. PDO Jumilla covers an area of 247,054 hectares, of which more than 22,000 hectares

Impact of geographical location on the phenolic profile of minority varieties grown in Spain. II: red grapevines

Because terroir and cultivar are drivers of wine quality, is essential to investigate theirs effects on polyphenolic profile before promoting the implantation of a red minority variety in a specific area. This work, included in MINORVIN project, focuses in the polyphenolic profile of 7 red grapevines minority varieties of Vitis vinifera L. (Morate, Sanguina, Santafe, Terriza Tinta Jeromo Tortozona Tinta) and Tempranillo) from six typical viticulture Spanish areas: Aragón (A1), Cataluña (A2), Castilla la Mancha (A3), Castilla –León (A4), Madrid (A5) and Navarra (A6) of 2020 season. Polyphenolic substances were extracted from grapes. 35 compounds were identified and quantified (mg subtance/kg fresh berry) by HPLC and grouped in anthocyanins (ANT) flavanols (FLAVA), flavonols (FLAVO), hydroxycinnamic (AH), benzoic (BA) acids and stilbenes (ST). Antioxidant activity (AA, mmol TE /g fresh berry) was determined by DPPH method. The results were submitted to a two-way ANOVA to investigate the influence of variety, area and their interaction for each polyphenolic family and cluster analysis was used to construct hierarchical dendrograms, searching the natural groupings among the samples. Sanguina (A3) had the most of total polyphenols while Tempranillo (A5) those of ANT. Sanguina (A2) and (A3) reached the highest values of FLAVO, FLAVA and AA. These two last samples had also the maximum of AA. The effect cultivar and area were significant for all polyphenolic families analyzed. A high variability due to variety (>50%) was observed in FLAVA and the maximum value of variability due to growing area was detected in AA (86.41%), ANT and FLAVO (51%); the interaction variety*zone was significant only for ANT, FLAVO, EST and AA. Finally, dendrograms presented five cluster: i) Sanguina (A2); ii) Sanguina (A3); iii) Tempranillo (A5); iv) Tempranillo (A3); Terriza (A3,A5), Morate (A5,A6); v) Santafé (A1,A6); Tortozona tinta (A1,A3,A6); Tinta Jeromo (A3,A4).

Effects of graft quality on growth and grapevine-water relations

Climate change is challenging viticulture worldwide compromising its sustainability due to warmer temperatures and the increased frequency of extreme events. Grafting Vitis vinifera L.

A blueprint for managing vine physiological balance at different spatial and temporal scales in Champagne

In Champagne, the vine adaptation to different climatic and technical changes during these last 20 years can be seen through physiological balance disruptions. These disruptions emphasize the general grapevine decline. Since the 2000s, among other nitrogen stress indicators, the must nitrogen has been decreasing. The combination of restricted mineral fertilizers and herbicide use, the growing variability of spring rainfall, the increasing thermal stress as well as the soil type heterogeneity are only a few underlying factors that trigger loss of physiological balance in the vineyards. It is important to weigh and quantify the impact of these factors on the vine. In order to do so, the Comité Champagne uses two key-tools: networking and modelization. The use of quantitative and harmonized ecophysiological indicators is necessary, especially in large spatial scales such as the Champagne appellation. A working group with different professional structures of Champagne has been launched by the Comité Champagne in order to create a common ecophysiology protocol and thus monitor the vine physiology, yearly, around 100 plots, with various cultural practices and types of soil. The use of crop modelling to follow the vine physiological balance within different pedoclimatic conditions enables to understand the present balance but also predict the possible disruptions to come in future climatic scenarios. The physiological references created each year through the working group, benefit the calibration of the STICS model used in Champagne. In return, the model delivers ecophysiology indicators, on a daily scale and can be used on very different types of soils. This study will present the bottom-up method used to give accurate information on the impacts of soil, climate and cultural practices on vine physiology.