IVAS 2022 banner
IVES 9 IVES Conference Series 9 IVAS 9 IVAS 2022 9 Combined high-resolution chromatography techniques and sensory analysis as a support decision system tool for the oenologist

Combined high-resolution chromatography techniques and sensory analysis as a support decision system tool for the oenologist

Abstract

One of the main challenges in the wine industry is to understand how different wine processing techniques and practices can influence the overall quality of the final product. Winemakers base the decision process mostly on their personal experience, which is often influenced by emotional aspects not always scientifically supported. Other issues come from the terroir and climate change, which are affecting the quality and production techniques, both in vineyards and wineries. In addition, it is important to consider that wine culture in the different production areas is also extremely variegated, even within the same country. Relying on analytical methods is a necessary step taken in many parts of the winemaking process, starting from the determination of the optimal time for the harvest. Monitoring the fermentation is usually performed by controlling the density or the residual sugars: secondary metabolites are usually not determined. This means that in some cases the fermentation can get stuck without really knowing the reason.

This research project aims to create a predictive multivariate statistical tool in order to support the winemaker during the workflow in the winery. So, the oenologist can obtain the desired style of wine by extracting information from correlating basic oenological parameters with high resolution and sensory analysis.

Pinot Noir cultivar is a very important variety for South Tyrol representing 9.1% of the local vineyard (source: vinialtoadige.com). The experimental scheme shown in figure 1 was developed in collaboration with a South Tyrolean winery. The study plan was aimed at ensuring control over the winemaking protocols while still working at the winery production scale (90 hL per experiment).

The experimental plan included four vineyards. Besides, for one of these vineyards, the plan included the study of a viticultural technique (treatment of the canopy with chitosan prior to harvest), and two different oenological treatments: pre fermentative 4-days cryo-maceration and 7-days grape freezing. The samples were analyzed by HS-SPME-GCxGC-ToF/MS for volatile compounds, HPLC-DAD-FLD for phenolic compounds with off-line HPLC-MS/MS to identify the components, and sensory analysis by quantitative descriptive analysis (QDA®) (Poggesi, et al., 2021). The study was repeated in two different vintages (2019 and 2020) with three replicates.

As a result, multivariate statistic models showed good separations between vineyards, frozen grapes, and the cryo-macerated treatment, and separation between chitosan treatment and the control treatment. Furthermore, the time evolution of the main chemical markers was evaluated. Finally, the results obtained on the 2019 vintage were supported by the 2020 ones

References

Alto Adige Wine – Exquisite Wines from Northern Italy (altoadigewines.com)
Poggesi, S., de Matos, A. D., Longo, E., Chiotti, D., Pedri, U., Eisenstecken, D., Robatscher, P., & Boselli, E. (2021). Chemosensory profile of South Tyrolean pinot blanc wines: A multivariate regression approach. Molecules, 26(20), 1–18. https://doi.org/10.3390/molecules26206245

DOI:

Publication date: June 23, 2022

Issue: IVAS 2022

Type: Article

Authors

Poggesi Simone¹, Darnal¹, Merkyte¹, Longo¹, Montali²and Boselli ¹

¹Faculty of Science and Technology, Free University of Bozen-Bolzano
²Faculty of Computer Science, Free University of Bozen-Bolzano

Contact the author

Keywords

Pinot Noir, bidimensional gas chromatography, non-volatile phenols, support decision tool, sensory analysis

Tags

IVAS 2022 | IVES Conference Series

Citation

Related articles…

Impact of changes in pruning practices on vine growth and yield

A gradual decline in vineyards has been observed over the past twenty years worldwide. This might be explained by the climate change, practices change or the increase of dieback diseases. To increase the longevity of vines, we studied the impact of different pruning strategies in four adult and four young vineyards located in France and Spain. In France, vineyards were planted with Cabernet franc on 3309C while Spanish trials were planted with Tempranillo grafted on 110R. Vegetative expression, yield, quality of berries and wood vessels conductivity were measured. The distribution of vegetative expression, yield and berry composition between primary and secondary vegetation were quantified. Finally, tomography was used to evaluate the implication of the treatments on sap flows.
First results show that i) the respectful pruning leads to an increase of 30 to 50% more secondary shoots than the aggressive pruning in France and between 15 and 20% in Spain, ii) there is no major effect on the yield over the first two years following the implementation of the new pruning practices, although the proportion of clusters from suckers is higher on the respectful pruning method. On young vines, the development of the trunk according to a respectful pruning leads to a loss of harvest 2 years after planting. This is due to the removal, on the future trunk, of the green suckers which carrying bunches. This operation carried out in spring rather than during winter pruning, would promote a better leaf / fruit balance when the plant comes into production, and could lead to better hydraulic conduction in the vessels of the trunk. Maintaining these trials for several years will provide more robust data to assess the impact of these practices on the vines over the long term.

Delaying irrigation initiation linearly reduces yield with little impact on maturity in Pinot noir

When to initiate irrigation is a critical annual management decision that has cascading effects on grapevine productivity and wine quality in the context of climate change. A multi-site trial was begun in 2021 to optimize irrigation initiation timing using midday stem water potential (ψstem) thresholds characterized as departures from non-stressed baseline ψstemvalues (Δψstem). Plant material, vine and row spacing, and trellising systems were concomitant among sites, while vine age, soil type, and pruning systems varied. Five target Δψstem thresholds were arranged in an RCBD and replicated eight times at each site: 0.2, 0.4, 0.6, 0.8, and 1.0 MPa (T1, T2, T3, T4, and T5, respectively). When thresholds were reached, plots were irrigated weekly at 70% ETc. Yield components and berry composition were quantified at harvest. To better generalize inferences across sites, data were analyzed by ANOVA using a mixed model including site as a random factor. Across sites, irrigation was initiated at Δψstem = 0.24, 0.50, 0.65, 0.93, and 0.98 MPa for T1, T2, T3, T4, and T5, respectively. Consistent significant negative linear trends were found for several key yield and berry composition variables. Yield decreased by 12.9, 15.9, 19.5, and 27.4% for T2, T3, T4, and T5, respectively, compared to T1 (p < 0.0001) across sites that were driven by similarly linear reductions in berry weight (p < 0.0001). Comparatively, berry composition varied little among treatments. Juice total soluble solids decreased linearly from T1 to T5 – though only ranged 0.9 Brix (p = 0.012). Because producers are paid by the ton, and contracts simply stipulate a target maturity level, first-year results suggest that there is no economic incentive to induce moderate water deficits before irrigation initiation, regardless of vineyard site. Subsequent years will further elucidate the carryover effects of delaying irrigation initiation on productivity over the long term.

Underpinning terroir with data: rethinking the zoning paradigm

Agriculture, natural resource management and the production and sale of products such as wine are increasingly data-driven activities. Thus, the use of remote and proximal crop and soil sensors to aid management decisions is becoming commonplace and ‘Agtech’ is proliferating commercially; mapping, underpinned by geographical information systems and complex methods of spatial analysis, is widely used. Likewise, the chemical and sensory analysis of wines draws on multivariate statistics; the efficient winery intake of grapes, subsequent production of wines and their delivery to markets relies on logistics; whilst the sales and marketing of wines is increasingly driven by artificial intelligence linked to the recorded purchasing behaviour of consumers. In brief, there is data everywhere!

Opinions will vary on whether these developments are a good thing. Those concerned with the ‘mystique’ of wine, or the historical aspects of terroir and its preservation, may find them confronting. In contrast, they offer an opportunity to those interested in the biophysical elements of terroir, and efforts aimed at better understanding how these impact on vineyard performance and the sensory attributes of resultant wines. At the previous Terroir Congress, we demonstrated the potential of analytical methods used at the within-vineyard scale in the development of Precision Viticulture, in contributing to a quantitative understanding of regional terroir. For this conference, we take this approach forward with examples from contrasting locations in both the northern and southern hemispheres. We show how, by focussing on the vineyards within winegrowing regions, as opposed to all of the land within those regions, we might move towards a more robust terroir zoning than one derived from a mixture of history, thematic mapping, heuristics and the whims of marketers. Aside from providing improved understanding by underpinning terroir with data, such methods should also promote improved management of the entire wine value chain.

Comparison of imputation methods in long and varied phenological series. Application to the Conegliano dataset, including observations from 1964 over 400 grape varieties

A large varietal collection including over 1700 varieties was maintained in Conegliano, ITA, since the 1950s. Phenological data on a subset of 400 grape varieties including wine grapes, table grapes, and raisins were acquired at bud break, flowering, veraison, and ripening since 1964. Despite the efforts in maintaining and acquiring data over such an extensive collection, the data set has varying degrees of missing cases depending on the variety and the year. This is ubiquitous in phenology datasets with significant size and length. In this work, we evaluated four state-of-the-art methods to estimate missing values in this phenological series: k-Nearest Neighbour (kNN), Multivariate Imputation by Chained Equations (mice), MissForest, and Bidirectional Recurrent Imputation for Time Series (BRITS). For each phenological stage, we evaluated the performance of the methods in two ways. 1) On the full dataset, we randomly hold-out 10% of the true values for use as a test set and repeated the process 1000 times (Monte Carlo cross-validation). 2) On a reduced and almost complete subset of varieties, we varied the percentage of missing values from 10% to 70% by random deletion. In all cases, we evaluated the performance on the original values using normalized root mean squared error. For the full dataset we also obtained performance statistics by variety and by year. MissForest provided average errors of 17% (3 days) at budbreak, 14% (4 days) at flowering, 14.5% (7 days) at veraison, and 17% (3 days) at maturity. We completed the imputations of the Conegliano dataset, one of the world’s most extensive and varied phenological time series and a steppingstone for future climate change studies in grapes. The dataset is now ready for further analysis, and a rigorous evaluation of imputation errors is included.

Modeling the suitability of Pinot Noir in Oregon’s Willamette Valley in a changing climate

Air temperature is the key driver of grapevine phenology and a significant environmental factor impacting yield and quality for a winegrape growing region. In this study the optimal downscaled CMIP5 ensemble for computing thegrowing season average temperature (GST) viticulture climate classification index was determined to spatially compute on a decadal basis predictions of the GST climate index and the grapevine sugar ripeness (GSR) model for Pinot Noir throughout the Willamette Valley (WV) American Viticultural Area (AVA). Forecasts for average temperature and a 220 g/L target sugar concentration level were computed using daily Localized Constructed Analogs (LOCA) downscaled CMIP5 historic and Representative Concentration Pathways (RCP) future climate projections of minimum and maximum daily temperature. We explore spatiotemporal trends of the GST climate classification index and Pinot Noir specific applications of the GSR phenology model for the WV AVA. Spatiotemporal computations of the GST climate index and Pinot Noir specific applications of the GSR model enable the opportunity to explore relationships between their computed values with one intent being to provide updated GST ranges that better align with current temperature-based modeling understanding of Pinot Noir grapevine phenology and the viticultural application of LOCA CMIP5 climate projections for the WV AVA. The Pinot Noir specific applications of the GSR model or the GST index with updated bounds indicate that the percent of the WV AVA area suitable for Pinot Noir production is currently at or near its peak value in the upper 80s to lower 90s of this century.