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SelWineQ3

Predictive Breeding for Wine Quality (Phase 3)


Term

2023-02-01 bis 2026-01-31

Project management

  • Florian, Schwander


Responsible institute

Institut für Rebenzüchtung


Project preparer

  • Reinhard, Töpfer
  • Tom, Heinekamp

Cooperation partner

  • DLR Rheinland-Pfalz
  • Technische Universität Dresden, Institut für Botanik
  • Institut Heidger


Overall objective of the project

Evaluation of new grapevine cultivars regarding their quality potential is the time limiting factor during grapevine breeding. Small-scale vinification (micro-vinification) for the quality assessment of individual grapevines is possible at the earliest after 3 to 4 years when the plant carries enough grapes. The wine rating is based on the sensory perception of qualified judges and requires repetitions over 15 to 20 years due to the impact of differing annual weather conditions on the wine’s flavor. »SelWineQ« aims at developing robust models and tools to predict wine quality on a genetic and molecular level, leading to increased breeding efficiency. To achieve this goal, we investigate different aspects: (1) the genetic quality potential (GQP; irrespective of the environment), (2) the metabolic quality potential (MQP; genotype by environment interaction) of the primary product (grape must), and (3) the quality of the end product wine (analytical and sensory properties). The different domains of quality (GQP - MQP - wine quality) are connected in mathematical models to develop genetic and metabolic markers for quality traits. Molecular markers applied in marker-assisted selection (MAS) during grapevine breeding will result in more efficient screening for new cultivars. The backbone of »SelWineQ« is a white wine F1 population (150 F1 plants = POP150; ‘Calardis Musqué’ x ‘Villard blanc’), which is planted at two different locations representing different micro-climatic conditions (Geilweilerhof Gf; Neustadt/Weinstraße Nw). Wines of these genotypes were produced in standardized micro-vinification over several seasons and resulted in a reliable data set. A predictive model based on the results from genetic, metabolic and sensory analyses was established and is subject of further improvement and validation. The model already resulted in the identification of important ingredients, including aroma compounds showing positive impact on wine quality perception. The identification of more quality determining compounds are expected from the two non-targeted metabolomic analysis approaches. Data of additional vintages and additional genotypes are crucial for further model optimization and validation. A high-density genetic map consisting of mainly full informative (80 %) haplotype-based markers (HBMs) resulting from an efficient genotyping by sequencing (GBS) approach was developed and will be further improved by the addition of genotypes. The map is used for QTL analysis of quality relevant traits, as already successfully demonstrated for véraison (onset of ripening) and linalool content (flowery bouquet). Genetic markers derived in this way, are to be tested on a broad genetic background and on relevant breeding material in order to validate their usability for breeding. The combination of genomic data, sensory evaluation scores and quantitative chemical data (targeted and non-targeted) of multiple vintages provides new insights into the factors determining the GQP of a grapevine. »SelWineQ« will be able to provide descriptors for improving wine quality in the short term and MAS-markers for quality traits for direct application in the breeding program in the medium term. In the long term, this will result in improved high quality and climate-adapted grapevine varieties with fungal disease resistances to be cultivated in a pesticide-reduced and sustainable viticulture.


Funder

Federal Ministry of Education and Research