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…

Simgi® platform as a tool for the study of wine active compounds in the  gastrointestinal tract

Simgi® platform pursues the need for dynamic in vitro simulation of the human gastrointestinal tract optimized and adapted to food safety and health fields. The platform has confirmed the model’s suitability since its first’s studies with the consistency between the simulated colonic metabolism of wine polyphenols and the metabolic evolution observed with the intake of wine in human intervention studies [1]. 

Terroir and Typicity: proposed definitions for two essential concepts in the understanding of Geographical Indications and sustainable development

The content of this communication arises from the deliberations of a working group mandated within the framework of the INRA-INAO 2000-2003 research convention, which brought together INAO representatives and researchers who had worked on AOCs or PGIs, in disciplines from the sphere of the humanities (consumer science, marketing, rural development) and biotechnical sciences (agronomy, animal production science, technology, biochemistry).

Moderated consumption of alcoholic beverages and cancer risk

One on three cases of cancer is associated with lifestyle and nutritional patterns, and the excessive intake of alcoholic beverages is a well established risk factor. Moderate drinking has been associated with reduced or increased risk of various types of cancer, but the clinical relevance of the risk rates has not been evaluated in ad hoc prospective investigations.

New molecular evidence of wine yeast-bacteria interaction unraveled by untargeted metabolomic profiling

Bacterial malolactic fermentation (MLF) has a considerable impact on wine quality. The yeast strain used for primary fermentation can consistently stimulate (MLF+ phenotype) or inhibit (MLF- phenotype) malolactic bacteria and the MLF process as a function of numerous winemaking practices, but the molecular evidence behind still remains a mystery. In this study, such evidence was elucidated by the direct comparison of extracellular metabolic profiles of MLF+ and MLF- yeast phenotypes. Untargeted metabolomics combining ultrahigh-resolution FT-ICR-MS analysis, powerful machine learning methods and a comprehensive wine metabolite database, discovered around 800 putative biomarkers and 2500 unknown masses involved in phenotypic distinction.

Comportement de différents clones de Sauvignon blanc dans certains terroirs viticoles du Friuli-Venezia Giulia (Nord-Est de l’Italie)

The worldwide reputation of Sauvignon Blanc has led technicians to ask themselves various questions about the cultivation of this variety: choice of the most suitable localities, the most effective agronomic strategies and the most appropriate wine-growing techniques, to bring out its particular aroma.