IVAS 2022 banner
IVES 9 IVES Conference Series 9 IVAS 9 IVAS 2022 9 Chenin Blanc Old Vine character: evaluating a typicality concept by data mining experts’ reviews and producers’ tasting notes

Chenin Blanc Old Vine character: evaluating a typicality concept by data mining experts’ reviews and producers’ tasting notes

Abstract

Concepts such as typicality are difficult to demonstrate using the limited set of samples that can be subjected to sensory evaluation. This is due both to the complexity of the concept and to the limitations of traditional sensory evaluation (number of samples per session, panel fatigue, the need for multiple sessions and methods, etc.). On the other hand, there is a large amount of data already available, accumulated through many years of consistent evaluation. These data are held in repositories (such as Platter’s Wine Guide in the case of South Africa Wine, wineonaplatter.com) and in technical notes provided by the producers.There are many unknowns regarding the distinguishing features of a commercial Old Vine (OV) Chenin Blanc wine and its comparison to a Young Vine (YV) wine. There is little work done on it and the work has limitations regarding the methodology and number of samples included (Crous, 2016; Mafata, Brand, Panzeri, et al., 2020). Platter’s data contains descriptors for wines produced in South Africa, as well as a quality rating. The producers put technical sheets together – while the expert tasters generate Platter’s data for the same wines.Similar to work done on the general characteristics of South African Chenin Blanc wine (Valente, Bauer, Venter, et al., 2018), the goal of the study is to find the unique features associated with the ‘old vine Chenin Blanc character’ using available data from expert tastings and technical notes. During the initial step, Platter’s data and technical notes are mined for attributes of Chenin Blanc wines (as both sources indicate whether the wines belong to the Old Vine category). The automated process is done using the data gathering and analysis tool developed by the research team. A combined data set from all data sources is also  created.During the analysis step, Agglomerative Hierarchical Clustering (AHC), Multiple Correspondence Analysis (MCA), Fuzzy K-Means clustering (FKM), and Formal Concept Lattice (FCL) are employed to explore the attribute and product space. Clustering algorithms are applied to the data (separate and fused sets) to identify markers (features) for the Old Vine character. As Platter’s data also includes product ratings, the possible correlation of Old Vines vs. Young Vines regarding the perceived quality can also be tested. In addition to finding sensory attributes associated exclusively with Old Vine Chenin Blanc (the typicality issue), the novelty of the work also resides with the creation and development of a new application for the automated data gathering and analysis tool, whose effectiveness and robustness will be tested in the real case scenario.

References

Crous, R. 2016. The sensory characterisation of old-vine Chenin blanc wine: an exploratory study of the dimensions of quality. Stellenbosch University.
Mafata, M., Brand, J., Panzeri, V. & Buica, A. 2020. Investigating the Concept of South African Old Vine Chenin Blanc. South African Journal of Enology and Viticulture. 14(2):168–182.
Valente, C.C., Bauer, F.F., Venter, F., Watson, B. & Nieuwoudt, H.H. 2018. Modelling the sensory space of varietal wines: Mining of large, unstructured text data and visualisation of style patterns. Scientific Reports. 8(1).

DOI:

Publication date: June 27, 2022

Issue: IVAS 2022

Type: Poster

Authors

Kruger Markus1, Brand J.1, Watson B.2, Mafata M.1 and Buica A.1

1Department of Information Science, Stellenbosch University, South Africa; South African Grape and Wine Research Institute, Department of Viticulture and Oenology, Stellenbosch University, South Africa
2 Department of Information Science, Stellenbosch University, South Africa

Contact the author

Keywords

Chenin Blanc, Old Vine, Automation, Multi-source data gathering

Tags

IVAS 2022 | IVES Conference Series

Citation

Related articles…

Simulating climate change impact on viticultural systems in historical and emergent vineyards

Global climate change affects regional climates and hold implications for wine growing regions worldwide. Although winegrowers are constantly adapting to internal and external factors, it seems relevant to develop tools, which will allow them to better define actual and future agro-climatic potentials. Within this context, we develop a modelling approach, able to simulate the impact of environmental conditions and constraints on vine behaviour and to highlight potential adaptation strategies according to different climate change scenarios. Our modeling approach, named SEVE (Simulating Environmental impacts on Viticultural Ecosystems), provides a generic modeling framework for simulating grapevine growth and berry ripening under different conditions and constraints (slope, aspect, soil type, climate variability…) as well as production strategies and adaptation rules according to climate change scenarios. Each activity is represented by an autonomous agent able to react and adapt its reaction to the variability of environmental constraints. Using this model, we have recently analyzed the evolution of vineyards’ exposure to climatic risks (frost, pathogen risk, heat wave) and the adaptation strategies potentially implemented by the winegrowers. This approach, implemented for two climate change scenarios, has been initiated in France on traditional (Loire Valley) and emerging (Brittany) vineyards. The objective is to identify the time horizons of adaptations and new opportunities in these two regions. Carried out in collaboration with wine growers, this approach aims to better understand the variability of climate change impacts at local scale in the medium and long term.

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.

Low-cost sensors as a support tool to monitor soil-plant heat exchanges in a Mediterranean vineyard

Mediterranean viticulture is increasingly exposed to more frequent extreme conditions such as heat waves. These extreme events co-occur with low soil water content, high air vapor pressure deficit and high solar radiant energy fluxes and result in leaf and berry sunburn, lower yield, and berry quality, which is a major constraint for the sustainability of the sector. Grape growers must find ways to proper and effectively manage heat waves and extreme canopy and berry temperatures. Irrigation to keep soil moisture levels and enable adequate plant turgor, and convective and evaporative cooling emerged as a key tool to overcome this major challenge. The effects of irrigation on soil and plant water status are easily quantifiable but the impact of irrigation on soil and canopy temperature and on heat convection from soil to cluster zone remain less characterized. Therefore, a more detailed quantification of vineyard heat fluxes is highly relevant to better understand and implement strategies to limit the effects of extreme weather events on grapevine leaf and berry physiology and vineyards performance. Low-cost sensor technologies emerge as an opportunity to improve monitoring and support decision making in viticulture. However, validation of low-cost sensors is mandatory for practical applicability. A two-year study was carried in a vineyard in Alentejo, south of Portugal, using low-cost thermal cameras (FLIR One, 80×60 pixels and FLIR C5, 160×120 pixels, 8-14 µm, FLIR systems, USA) and pocket thermohygrometers (Extech RHT30, EXTECH instruments, USA) to monitor grapevine and soil temperatures. Preliminary results show that low-cost cameras can detect severe water stress and support the evaluation of vertical canopy temperature variability, providing information on soil surface temperature. All these thermal parameters can be relevant for soil and crop management and be used in decision support systems.

‘Cabernet Sauvignon’ (Vitis vinifera L.) berry skin flavonol and anthocyanin composition is affected by trellis systems and applied water amounts

Trellis systems are selected in wine grape vineyards to mainly maximize vineyard yield and maintain berry quality. This study was conducted in 2020 and 2021 to evaluate six commonly utilized trellis systems including a vertical shoot positioning (VSP), two relaxed VSPs (VSP60 and VSP80), a single high wire (SH), a high quadrilateral (HQ), and a guyot (GY), combined with three levels of irrigation regimes based on different crop evapotranspiration (ETc) replacements, including a 25% ETc, 50% ETc, and 100% ETc. The results indicated SH yielded the most fruits and accumulated the most total soluble solids (TSS) at harvest in 2020, however, it showed the lowest TSS in the second season. In 2020, SH and HQ showed higher concentrations in most of the anthocyanin derivatives compared to the VSPs. Similar comparisons were noticed in 2021 as well. SH and HQ also accumulated more flavonols in both years compared to other trellis systems. Overall, this study provides information on the efficacy of trellis systems on grapevine yield and berry flavonoid accumulation in a currently warming climate.

Adaptation to soil and climate through the choice of plant material

Choosing the rootstock, the scion variety and the training system best suited to the local soil and climate are the key elements for an economically sustainable production of wine. The choice of the rootstock/scion variety best adapted to the characteristics of the soil is essential but, by changing climatic conditions, ongoing climate change disrupts the fine-tuned local equilibrium. Higher temperatures induce shifts in developmental stages, with on the one hand increasing fears of spring frost damages and, on the other hand, ripening during the warmest periods in summer. Expected higher water demand and longer and more frequent drought events are also major concerns. The genetic control of the phenotypes, by genomic information but also by the epigenetic control of gene expression, offers a lot of opportunities for adapting the plant material to the future. For complex traits, genomic selection is also a promising method for predicting phenotypes. However, ecophysiological modelling is necessary to better anticipate the phenotypes in unexplored climatic conditions Genetic approaches applied on parameters of ecophysiological models rather than raw observed data are more than ever the basis for finding, or building, the ideal varieties of the future.