IVAS 2022 banner
IVES 9 IVES Conference Series 9 IVAS 9 IVAS 2022 9 Predictive Breeding for Wine Quality: From Sensory Traits to Grapevine Genome

Predictive Breeding for Wine Quality: From Sensory Traits to Grapevine Genome

Abstract

New pathogen resistant varieties allow an efficient and greatly reduced use of fungicides. These new varieties promise, therefore, an enormous potential to reach the European Green Deal aim of a 50% reduction of pesticides in EU agriculture by 2030. The selection process, and particularly quality evaluation of the wines produced, are a bottleneck slowing down the breeding of new pathogen resistant grapevine varieties. Our major aim is therefore the development of predictive models for wine quality traits. Their implementation in the selection process would considerably increase the efficacy of grapevine breeding.The centrepiece of our study is a segregating white wine F1-population of ‘Calardis Musqué’ and ‘Villard Blanc’ consisting of 150 genotypes with 13 plants per genotype at two locations. A ‘Genotyping by Sequencing’ approach with a novel bioinformatics pipeline delivered a high-density genetic map of the breeding population. Experimental winemaking in a 4-liter scale (micro-vinification) provided authentic wines for comprehensive sensory evaluation and chemical analysis of major and minor metabolites including aroma compounds such as monoterpenoids. Moreover, five annual repetitions at two locations allow robust modelling and an estimation of environmental impact on the phenotypic data. Genetic, metabolic, and sensory data for multiple vintages combine into a comprehensive data base for predictive modelling. The descriptive and quality score card was adapted to the large number of wine samples and the unusual broad range of wine qualities resulting from an unselected set of grapevine genotypes. Based on evaluation of all 150 genotypes we differentiated a set of best and worst wines reproducibly over years. Environmental-related differences among vintages were still present. Intensity of the descriptive attribute “floral” played a crucial role for total quality within this population and correlates with linalool and cis-rose oxide concentration of the wines in all vintages measured by SIDA-SPE-GC-MS. In addition, total concentrations of linalool enabled the discovery of several genomic regions (quantitative trait loci, QTLs) that collocate with putative genes associated with terpene biosynthesis. Multi seasonal data allowed refinement and validation of models predicting these wine quality traits. Further exploitation of the large data set will provide more insights into genomic regions related to other wine quality traits and will allow an early selection of genotypes of promising genetic quality potential or sorting out of poor candidates during grape vine breeding.

DOI:

Publication date: June 23, 2022

Issue: IVAS 2022

Type: Article

Authors

Siebert, Annemarie1, Vestner Jochen1, Röckel Franco2, Schwander Florian2, Frenzke Lena3, Wenke Torsten4, Wanke Stefan3, Töpfer Reinhard2 and Fischer Ulrich1

1Dienstleistungszentrum Ländlicher Raum (DLR) Rheinpfalz, Institute for Viticulture and Oenology
2Julius Kühn-Institute (JKI), Institute for Grapevine Breeding, Geilweilerhof
4ASGEN GmbH & Co. KG

Contact the author

Keywords

Wine quality, metabolic quality potential, monoterpenes, genetic quality potential, quantitative trait loci

Tags

IVAS 2022 | IVES Conference Series

Citation

Related articles…

Different soil types and relief influence the quality of Merlot grapes in a relatively small area in the Vipava Valley (Slovenia) in relation to the vine water status

Besides location and microclimatic conditions, soil plays an important role in the quality of grapes and wine. Soil properties influence…

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.

Biodiversity in the vineyard agroecosystem: exploring systemic approaches

Biodiversity conservation and restoration are essential for guarantee the provision of ecosystem services associated to vineyard agroecosystem such as climate regulation trough carbon sequestration and control of pests and diseases. Most of published research dealing with the complexity of the vineyard agroecosystems emphasizes the necessity of innovative approaches, including the integration of information at different temporal and spatial scales and development of systemic analysis based on modelling. A biodiversity survey was conducted in the Franciacorta wine-growing area (Lombardy, Italy), one of the most important Italian wine-growing regions for sparkling wine production, considering a portion of the territory of 112 ha. The area was divided into several Environmental Units (EUs), defined as a whole vineyard or portion of vineyard homogenous in terms of four agronomic characteristics: planting year, planting density, cultivar, and training system. In each EU a set of compartments was identified and characterised by specific variables. The compartments are meteorology, morphology (altitude, slope, aspect, row orientation, and solar irradiance), ecological infrastructures and management. The landscape surrounding EU was also characterised in terms of land-use in a buffer zone of 500 m. For each component a specific methodology was identified and applied. Different statistical approaches were used to evaluate the method to integrate the information related to different compartments within the EU and related to the buffer zone. These approaches were also preliminarily evaluated for their ability to describe the contribution of biodiversity and landscape components to ecosystem services. This methodological exploration provides useful indication for the development of a fully systemic approach to structural and functional biodiversity in vineyard agroecosystems, contributing to promote a multifunctional perspective for the all wine-growing sector.

Anthocyanin profile is differentially affected by high temperature, elevated CO2 and water deficit in Tempranillo (Vitis vinifera L.) clones

Anthocyanin potential of grape berries is an important quality factor in wine production. Anthocyanin concentration and profile differ among varieties but it also depends on the environmental conditions, which are expected to be greatly modified by climate change in the future. These modifications may significantly modify the biochemical composition of berries at harvest, and thus wine typicity. Among the diverse approaches proposed to reduce the potential negative effects that climate change may have on grape quality, genetic diversity among clones can represent a source of potential candidates to select better adapted plant material for future climatic conditions. The effects of individual and combined factors associated to climate change (increase of temperature, rise of air CO2 concentration and water deficit) on the anthocyanin profile of different clones of Tempranillo that differ in the length of their reproductive cycle were studied. The aim was to highlight those clones more adapted to maintain specific Tempranillo typicity in the future. Fruit-bearing cuttings were grown in controlled conditions under two temperatures (ambient temperature versus ambient temperature + 4ºC), two CO2 levels (400 ppm versus 700 ppm) and two water regimes (well-watered versus water deficit), both in combination or independently, in order to simulate future climate change scenarios. Elevated temperature increased anthocyanin acylation, whereas elevated CO2 and water deficit favoured the accumulation of malvidin derivatives, as well as the acylation and tri-hydroxylation level of anthocyanins. Although the changes in anthocyanin profile observed followed a common pattern among clones, such impact of environmental conditions was especially noticeable in one of the most widely distributed Tempranillo clones, the accession RJ43.

An analytical framework to site-specifically study climate influence on grapevine involving the functional and Bayesian exploration of farm data time series synchronized using an eGDD thermal index

Climate influence on grapevine physiology is prevalent and this influence is only expected to increase with climate change. Although governed by a general determinism, climate influence on grapevine physiology may present variations according to the terroir. In addition, these site-specific differences are likely to be enhanced when climate influence is studied using farm data. Indeed, farm data integrate additional sources of variation such as a varying representativity of the conditions actually experienced in the field. Nevertheless, there is a real challenge in valuing farm data to enable grape growers to understand their own terroir and consequently adapt their practices to the local conditions. In such a context, this article proposes a framework to site-specifically study climate influence on grapevine physiology using farm data. It focuses on improving the analysis of time series of weather data. The analytical framework includes the synchronization of time series using site-specific thermal indices computed with an original method called Extended Growing Degree Days (eGDD). Synchronized time series are then analyzed using a Bayesian functional Linear regression with Sparse Steps functions (BLiSS) in order to detect site-specific periods of strong climate influence on yield development. The article focuses on temperature and rain influence on grape yield development as a case study. It uses data from three commercial vineyards respectively situated in the Bordeaux region (France), California (USA) and Israel. For all vineyards, common periods of climate influence on yield development were found. They corresponded to already known periods, for example around veraison of the year before harvest. However, the periods differed in their precise timing (e.g. before, around or after veraison), duration and correlation direction with yield. Other periods were found for only one or two vineyards and/or were not referred to in literature, for example during the winter before harvest.