terclim by ICS banner
IVES 9 IVES Conference Series 9 Data deluge: Opportunities, challenges, and lessons of big data in a multidisciplinary project

Data deluge: Opportunities, challenges, and lessons of big data in a multidisciplinary project

Abstract

Grapevine powdery mildew resistance is a key target for grape breeders and grape growers worldwide. The driver of the USDA-NIFA-SCRI VitisGen3 project is completing the pipeline from germplasm identification to QTL to candidate gene characterization to new cultivars to vineyards to consumers. This is a common thread across such projects internationally. We will discuss how our objectives and approaches leverage big data to advance this initiative, starting with genomics and computer vision phenotyping for gene discovery and genetic improvement. To manage and maintain resistances for long-term sustainability, growers will be trained through our nation-wide extension and outreach plan. Ultimately, consumers drive adoption of new varieties, and our socioeconomic research using eye-tracking will be briefly described. Across this multi-disciplinary research effort, big data presents opportunities, challenges, and lessons.

DOI:

Publication date: June 13, 2024

Issue: Open GPB 2024

Type: Article

Authors

Lance Cadle-Davidson1,2*, Matt Clark3, Dario Cantu4,5, Chengyan Yue3,6, Kaitlin Gold2, Yu Jiang2, Qi Sun7, Kate Fessler3

1 USDA-ARS Grape Genetics Research Unit, Geneva, NY, USA
2 School of Integrative Plant Science, Cornell AgriTech, Cornell University, Geneva, NY, USA
3 Department of Horticultural Science, Univ. of Minnesota, Saint Paul, MN, USA
4 Department of Viticulture and Enology, University of California Davis, Davis, CA, USA
5 Genome Center, University of California Davis, Davis, CA, USA
6 Department of Applied Economics, Univ. of Minnesota, Saint Paul, MN, USA
7 BRC Bioinformatics Facility, Institute of Biotechnology, Cornell University, Ithaca, NY, USA

Contact the author*

Keywords

Disease resistance, Grape breeding, Genomics, Computer vision, Consumer behavior

Tags

IVES Conference Series | Open GPB | Open GPB 2024

Citation

Related articles…

Terroir aspects of harvest timing in a cool climate wine region: physiology, berry skin phenolic composition and wine quality

Preliminary experiment of harvest timing was carried out in Eger wine district, Hungary in 2009. In situ physiological responses, berry quality parameters and wine quality of the Kékfrankos grapevine were studied at two growing sites (Eger-K6lyuktet6 – non-stressed, flat vineyard, and Eger-Nagyeged hill – water stressed, steep slope vineyard).

Barbera d’Asti: the characterization of the vineyard sites

[English version below]

L’objectif de l’étude est de mettre en évidence les différences rencontrées entre les vins Barbera d’Asti, qui sont produits en AOC. Celles-ci sont imputées aux terroirs caractérisés selon les facteurs pédologiques, climatiques, et qui conduisent à des différents potentiels viticoles et œnologiques. Il est proposé une individualisation des sous-zones.

Vitis v. corvina grapes composition and wine sensory profile as affected by different post harvest withering conditions

Context and purpose of the study – In Valpolicella area (Verona – Italy) Vitis vinifera cv. Corvina is the main wine variety to obtain, after grape withering, Amarone wine: this study was carried out in order to compare two different grape dehydration conditions with the aim of verifying the final composition of Corvina dried grapes and the organoleptic profile of corresponding Amarone wine.

The role of œnology in the enhancement of terroir expression

The reality of terroir is reflected by the typicality that it confers on the wine. The relationship between the origin of wine and its quality did already exist before the appearance of œnological science. Producers and merchants have always tried to improve wine quality in order to satisfy their clients.

Intra-vineyard spatial variability explored over multiple seasons by sensor-based techniques in the Valpolicella area

The identification and management of intra-vineyard variability are key to precision viticulture, and sensors have been proven to be highly efficient tools for detecting these variations.