 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

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Keywords

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

Citation

Phenolic composition of Tempranillo Blanco grapes changes after foliar application of urea

Our research aimed to determine the effect and efficiency of foliar application of urea on the phenolic composition of Tempranillo Blanco grapes. The field experiment was carried out in 2019 and 2020 seasons and the plot was located in D.O.Ca Rioja (North of Spain). The vineyard was Vitis vinifera L. Tempranillo Blanco and grafted on Richter-110 rootstock. The treatments were control (C), whose plants were sprayed with water and three doses of urea: plants were sprayed with urea 3 kg N/ha (U3), 6 kg N/ha (U6) and 9 kg N/ha (U9). The applications were performed in two phenological stages, pre-veraison (Pre) and veraison (Ver). Also, each of the treatments was repeated one week later. Control and treatments were performed in triplicate and arranged in a randomised block design. Grapes were harvested at optimum ripening stage. High-performance liquid chromatography was used to analyse the phenolic composition of the grapes. Finally, the results obtained from the analytical determinations – flavonols, flavanols and non-flavonoid (hydroxybenzoic acids, hydroxycinnamic acids and stilbenes) – were studied statistically by analysis of variance. The results showed that, in 2019, U6-Pre and U9-Pre treatments increased the hydroxybenzoic acid content in grapes, and also all foliar treatments applied at Pre enhanced the stilbene concentration. Moreover, U3-Ver was the only treatment that rose flavonol and stilbene contents in the Tempranillo Blanco grapes. In 2020, all treatments applied at Pre enhanced the flavonol concentration in grapes. Furthermore, U3-Pre and U9-Pre treatments increased stilbene content in grapes. Nevertheless, the hydroxybenzoic acid content was improved by U6-Ver and U9-Ver and besides, hydroxycinnamic acid concentration in grapes was increased by all treatments applied at Ver. In conclusion, the lower and highest dose of urea (U3 and U9), applied at pre-veraison, were the best treatments to improve the Tempranillo Blanco grape phenolic composition.

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

Adaptability of grapevines to climate change: characterization of phenology and sugar accumulation of 50 varieties, under hot climate conditions

Climate is the major factor influencing the dynamics of the vegetative cycle and can determine the timing of phenological periods. Knowledge of the phenology of varieties, their chronological duration, and thermal requirements, allows not only for the better management of interventions in the vineyard, but also to predict the varieties’ behaviour in a scenario of climate change, giving the wine producer the possibility of selecting the grape varieties that are best adapted to the climatic conditions of a certain terroir. In 2014, Symington Family Estates, Vinhos, established two grape variety libraries in two different places with distinctive climate conditions (Douro Superior, and Cima Corgo), with the commitment of contributing to a deeper agronomic and oenological understanding of some grape varieties, in hot climate conditions. In these research vineyards are represented local varieties that are important in the regional and national viticulture, but also others that have over time been forgotten — as well as five international reference cultivars. From 2017 to 2021, phenological observations have been made three times a week, following a defined protocol, to determine the average dates of budbreak, flowering and veraison. With the climate data of each location, the thermal requirements of each variety and the chronological duration of each phase have been calculated. During maturation, berry samples have been gathered weekly to study the dynamics of sugar accumulation, between other parameters. The data was analysed applying phenological and sugar accumulation models available in literature. The results obtained show significant differences between the varieties over several parameters, from the chronological duration and thermal requirements to complete the various stages of development, to the differences between the two locations, confirming the influence of the climate on phenology and the stages of maturation, in these specific conditions.

Using δ13C and hydroscapes as a tool for discriminating cultivar specific drought response

Measurement of carbon isotope discrimination in berry juice sugars at maturity (δ13C) provides an integrated assessment of water use efficiency (WUE) during the period of berry ripening, and when collected over multiple seasons can be used as an indication of drought stress response. Berry juice δ13C measurements were carried out on 48 different varieties planted in a common garden experiment in Bordeaux, France from 2014 through 2021 and were paired with midday and predawn leaf water potential measurements on the same vines in a subset of six varieties. The aim was to discriminate a large panel of varieties based on their stomatal behaviour and potentially identify hydraulic traits characterizing drought tolerance by comparing δ13C and hydroscapes (the visualisation of plant stomatal behaviour as a response to predawn water potential). Cluster analysis found that δ13C values are likely affected by the differing phenology of each variety, resulting in berry ripening of different varieties taking place under different stress conditions within the same year. We accounted for these phenological differences and found that cluster analysis based on specific δ13C metrics created a classification of varieties that corresponds well to our current empirical understanding of their relative drought tolerances. In addition, we analysed the water potential regulation of the subset of six varieties (using the hydroscape approach) and found that it was well correlated with some δ13C metrics. Surprisingly, a variety’s water potential regulation (specifically its minimum critical leaf water potential under water deficit) was strongly correlated to δ13C values under well-watered conditions, suggesting that base WUE may have a stronger impact on drought tolerance than WUE under water deficit. These results give strong insights on the innate WUE of a very large panel of varieties and suggest that studies of drought tolerance should include traits expressed under non-limiting conditions.

Mapping and tracking canopy size with VitiCanopy

Understanding vineyard variability to target management strategies, apply inputs efficiently and deliver consistent grape quality to the winery is essential. However, despite inherent vineyard variability, the majority are managed as if they are uniform. VitiCanopy is a simple, grower-friendly tool for precision/digital viticulture that allows users to collect and interpret objective spatial information about vineyard performance. After four years of field and market research, an upgraded VitiCanopy has been created to achieve a more streamlined, technology-assisted vine monitoring tool that provides users with a set of superior new features, which could significantly improve the way users monitor their grapevines. These new features include:
• New user interface
• User authentication
• Batch analysis of multiple images
• Ease the learning curve through enhanced help features
• Reporting via the creation of colour maps that will allow users to assess the spatial differences in canopies within a vineyard.
Use-case examples are presented to demonstrate the quantification and mapping of vineyard variability through objective canopy measurements, ground-truthing of remotely sensed measurements, monitoring of crop conditions, implementation of disease and water management decisions as well as creating a history of each site to forecast quality. This intelligent tool allows users to manage grapevines and make informed management choices to achieve the desired production targets and remain profitable.