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…

Sustaining wine identity through intra-varietal diversification

With contemporary climate change, cultivated Vitis vinifera L. is at risk as climate is a critical component in defining ecologically fitted plant materiel. While winegrowers can draw on the rich diversity among grapevine varieties to limit expected impacts (Morales-Castilla et al., 2020), replacing a signature variety that has created a sense of local distinctiveness may lead to several challenges. In order to sustain wine identity in uncertain climate outcomes, the study of intra-varietal diversity is important to reflect the adaptive and evolutionary potential of current cultivated varieties. The aim of this ongoing study is to understand to what extent can intra-varietal diversity be a climate change adaptation solution. With a focus on early (Sauvignon blanc, Riesling, Grolleau, Pinot noir) to moderate late (Chenin, Petit Verdot, Cabernet franc) ripening varieties, data was collected for flowering and veraison for the various studied accessions (from conservatory plots) and clones. For these phenological growing stages, heat requirements were established using nearby weather stations (adapted from the GFV model, Parker et al., 2013) and model performances were verified. Climate change projections were then integrated to predict the future behaviour of the intra-varietal diversity. Study findings highlight the strong phenotypic diversity of studied varieties and the importance of diversification to enhance climate change resilience. While model performances may require improvements, this study is the first step towards quantifying heat requirements of different clones and how they can provide adaptation solutions for winegrowers to sustain local wine identity in a global changing climate. As genetic diversity is an ongoing process through point mutations and epigenetic adaptations, perspective work is to explore clonal data from a wide variety of geographic locations.

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.

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.

Combining effect of leaf removal and natural shading on grape ripening under two irrigation strategies in Manto negro (Vitis vinifera L.)

The increasingly frequent heat waves during grape ripening pose challenges for high quality wine grape production. Defoliation is a common practice that can improve the control of diseases in bunches, but also it increases the exposure to sunlight. Grapes exposed to solar radiation reach temperatures over the optimum for berry development and maturation. This makes the development of irrigation and canopy management techniques of great importance to maximize yield and grape quality. A field experiment was carried out during 2021 using Manto negro wine grapes to study the effect of applied irrigation and different light exposure levels on grape quality. Two irrigation treatments were imposed based on the frequency and amount of water doses in a four-block experimental vineyard at Bodega Ribas (Mallorca). Three light exposure treatments were randomly applied in each irrigation plot. The light treatments included exposed clusters from pea size, non-exposed clusters, and shaded clusters after softening. Leaf area index and canopy porosity was estimated every 2 weeks. Midday leaf water potential was measured weekly. Additionally, apparent electrical conductivity was measured between rows to estimate the soil water content variability. Light and temperature sensors were installed at the bunch level to quantify the differences in bunch temperature and light intensity among treatments. The effect of irrigation and cluster light exposure on berry weight, TSS, TA, malic acid, tartaric acid, K+, and pH were analysed at 5 moments along grape ripening. During different heat waves, the natural shading technique decreased the maximum bunch temperature around 10 °C respect to the exposed bunches in both irrigation strategies. The combination of defoliation and shading techniques after softening decreased TSS at harvest and affected most of the quality parameters during the last stages of ripening, showing an interesting technique to delay ripening in warm viticulture areas.

Mesoclimate impact on Tannat in the Atlantic terroir of Uruguay

The study of climate is relevant as an element conditioning the typicity of a product, its quality and sustainability over the years. The grapevine development and growth and the final grape and wine composition are closely related to temperature, while climate components vary at mesoscale according to topography and/or proximity to large bodies of water. The objective of this work is to assess the mesoclimate of the Atlantic region of Uruguay and to determine the effect of topography and the ocean on temperature and consequently on Tannat grapevine behavior.