Project description
Machine learning-based technology for resilient crop production
Frequent and intense extreme weather conditions resulting from climate change are threatening global food security and disrupting crop production at a local level. This has created an urgent need for plant breeders to develop climate-resilient and resource-efficient crops. Machine learning-based technologies hold promise in addressing these challenges and facilitating the production of stable and value added products. However, these technologies are still in the developmental stage and are not yet available for commercial use. To address this gap, the EU funded TRAIT4.0 project proposes xSeedScore, a revolutionary machine learning based technology that has the potential to enable the development of more climate-resilient crop varieties while also reducing land and water use and shortening the time to market.
Objective
Global food security challenges, due to exposure to more frequent and intense climate extremes, are threatening to erode and reverse gains made in ending hunger and malnutrition globally, and to shake the foundations of crop production locally. Therefore, plant breeders are under pressure to tackle climate resiliency and resource efficiency. Machine learning-based technologies have the potential to address these challenges and enable breeders to produce stable, value-added products, which contribute to resource-efficient agriculture that can feed the world, but are so far still under development and not commercially available. Computomics has developed xSeedScore, the first disruptive machine learning-based technology enabling more climate-resilient varieties, decreased land and water use, reduced time-to-market and a competitive alternative to genetic modification. With help of the EIC Accelerator, Computomics expects to reach by 2026 a turnover of 18M and 50 employees.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
- Food security
- Computer sciences
- information science and bioinfo
- climate change
- climate-resilient food production
- genomics
- phenotype
- phenotyping
- breeding companies
- plant
- breeders
- Computational engineering
- crop
- biotechnology
- metagenomics
- machine learning
- data science
- Bioinformatics
- computational biology
- supply chain continuity
- Plant breeding and plant protection
- new plant varieties
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.3.1 - The European Innovation Council (EIC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-EIC-ACC-BF - HORIZON EIC Accelerator Blended Finance
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-EIC-2022-ACCELERATOR-01
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
72072 Tubingen
Germany
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.