DRIVE

Data-driven and genome-edited breeding of locally adapted wheat varieties to enhance agricultural biodiversity, sustainable climate resilience, and resource efficiency

Term

2024-11-01 bis 2028-10-31

Project management

Philipp, Schulz
Kerstin, Flath

Responsible institute

Institut für Pflanzenschutz in Ackerbau und Grünland

Cooperation partner

Leibniz-Institut für Pflanzengenetik und Kulturpflanzenforschung
Rheinische Friedrich-Wilhelms-Universität Bonn
Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF) e.V.
Max-Planck-Institut für Molekulare Pflanzenphysiologie
KWS Lochow GmbH
W. von Borries-Eckendorf GmbH & Co. KG
Deutsche Saatveredlung AG
infotraX GmbH
Gemeinschaft zur Förderung von Pflanzeninnovation e. V.
Secobra Saatzucht GmbH
Saatzucht Streng-Engelen GmbH & Co. KG
RAGT 2n -France
Nordic Seed
Technische Universität München

Overall objective of the project

Data science augments many economic and scientific activities. Plant breeding has not been one of them yet. That is because crop scientists lack Big Data, curated and machine-readable datasets large enough for artificial intelligence (AI) to crunch. The DRIVE project will implement a data trusteeship platform populated with one of the world’s most comprehensive Big Data in crops, to facilitate data-driven breeding of climate and locally-adapted wheat varieties. Results from large-scale allele mining will be used for genome editing to combat biotic stress factors with putative resistance genes discovered in genetic wheat resources lost in elite breeding.

Funder

Federal Ministry of Education and Research