Project Number
IWBT 16-01
Project title
Wine production as a system: Integration and data mining
Project leader
Vivier, M A
Institution
Stellenbosch University. Department of Viticulture and Oenology University of Stellenbosch. Faculty of AgriSciences. Institute for Wine Biotechnology
Team members
Vivier, M A
Bauer, F F
Du Toit, M
Van Rensburg, K
Kullan, J
EXECUTIVE SUMMARY
Objectives and Rationale
We aimed to develop methods and a workflow to do integrative data analysis on vine and wine research projects that generate diverse and multiple datasets. We used large datasets already generated where the effects of specific changes to the bunch microclimate of Sauvignon Blanc grapes in the Elgin area were studied. We wanted to implement multiblock and multimatrix statistical analyses and collaborated with researchers from Umea University, Sweden that
developed appropriate statistical methods towards this goal.
Methods
This study relied on data sets gathered over seven years with grapes/wine from the same vineyard. Defoliation in the bunch zone were used to create different microclimates (High Light [HL] and Low Light [LL]) during grape development. Wine were produced from the grapes and alternative wine making treatments (pre-fermentative skin-contact, fermentation in contact with sediment) were tested. Samples were taken throughout the process (i.e. grapes at three stages of development, juice during juice processing, must and yeast throughout fermentation and wine at different stages of bottle aging). Analytical chemistry, molecular and sensory analysis were implemented. Data
integration were done with a range of advanced chemometric and bioinformatic methods. The algorithms used by our Swedish partners to conduct multiblock modelling, has now (May 2019) been compiled as an application (MOCA) in the latest version of Simca (version 16), the software package from Sartorius Stedim Biotech.
Key Results
Combining chemical analysis data from the grapes and the wine and analysing this with multi-block modelling techniques, we showed that the leaf removal treatment in the vineyard made a lasting imprint on almost all metabolites measured (i.e. amino acids, volatile aroma compounds, polyphenols, photosynthetic pigments). This imprint, that was also evident in the juice composition, elicited a transcriptional response from the yeast during fermentation and could, to a certain extent, be tempered/equalized by certain wine making adaptations (e.g. skin contact).
Key Conclusion of Discussion
A new approach (Wine-as-a-system) was established to integrate and interpret multiple and diverse datasets that characterize all aspects and stages of wine production. This provides a new tool to understand the complexity and interrelatedness of grapes, the environment, fermentation and the interactions of wine-related chemical compounds. The project was done in partnership with Umea University in Sweden and several students and researchers from Stellenbosch University received training on using multivariate data analysis on complex data sets. A database was set up hosting all the data and enabling easy data sharing.
Recommendation to Industry / Key take-home message
The grape and wine metabolite environment are complex and interrelated but complexity can be “tamed”, patterns can be spotted, chaos can be ordered by incorporating good experimental design, matched with robust data analyses pipelines. Proper statistical analysis of complex data sets identified specific key metabolites that enables the grape berry to acclimate to light stress conditions. Key metabolites that play a role throughout all steps of winemaking and/or the acclimation to light stress could be identified, showing that some metabolite footprints persisted until the final product.
Articles
Joubert, P, Young, P R, Eyéghé-Bickong, H A, Vivier, M A. Fortes, A M (ed). 2016. Field-grown grapevine berries use carotenoids and the associated xanthophyll cycles to acclimate to UV exposure differentially in high and low light (shade) conditions. Frontiers in Plant Science, v. 7 (786) (p. 1-17)
http://dx.doi.org/10.3389/fpls.2016.00786
Young, P, Eyéghé-Bickong, H A, Du Plessis, K, Alexandersson, E, Jacobson, D A, Coetzee, Z A, Deloire, A, Vivier, M A. 2016. Grapevine plasticity in response to an altered microclimate: Sauvignon blanc modulates specific metabolites in response to increased berry exposure [Online] Plant Physiology, v. 170 (p. 1235-1254)
http://www.plantphysiol.org/cgi/doi/10.1104/pp.15.01775
Du Plessis, K, Young, P R, Eyéghé-Bickong, H A, Vivier, M A. 2017. The transcriptional responses and metabolic consequences of acclimation to elevated light exposure in grapevine berries, Frontiers in Plant Science, v. 8 (1261) (p. 1-23)
https://doi.org/10.3389/fpls.2017.01261
Eyéghé-Bickong, H A, Young, P, Vivier, M A. 2017. Analytical methods to measure grape metabolites – a review, WineLand Technical, Mnth Jan
http://www.wineland.co.za/analytical-methods-measure-grape-metabolites-review/
Joubert, C, Vivier, M A. 2017. Sugars on the move through the vine [Online] WineLand Technical, Mnth Aug
http://www.wineland.co.za/sugars-move-vine/
Vogel, D, Hills, P N, Moore, J P. 2017. Evaluating the role of natural plant-derived compounds in modifying disease defence mechanisms in and plantlets [Online] South African Journal of Botany, Mnth March v. 109 (p. 374)
http://dx.doi.org/10.1016/j.sajb.2017.01.193
Young, P R, Vivier, M A. 2017. Berry stress and wine quality. [Online] WineLand Technical, Mnth Mar
http://www.wineland.co.za/berry-stress-wine-quality/