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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: 13/06/2024

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

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