Periodic Reporting for period 1 - TRAIT4.0 (TRansition to agriculture 4.0: increasing crop resiliency with Artificial Intelligence Technology)
Période du rapport: 2023-01-01 au 2023-12-31
The EU-funded TRAIT4.0 project introduces Computomics' revolutionary ⨉SeedScore® technology to address these challenges. ⨉SeedScore® utilizes bioinformatical algorithms to identify superior plants based on genotype, environment, and management factors, achieving predictions ten times more accurate than traditional methods. This empowers breeders to select climate-resilient crops, optimize crosses, and make data-driven decisions, ultimately contributing to sustainable and efficient agriculture.
The project's objectives are to tackle global food security issues, empower breeders with innovative technology, and offer a sustainable alternative to genetic modification. With EIC Accelerator support, Computomics aims to reach a €18 million turnover and employ 50 individuals by 2026, marking a significant impact on agriculture's future resilience and resource efficiency.
- Legal Framework and Data Sharing: Successful development and negotiation of legal agreements like NDAs and MTAs to ensure secure data sharing with customers. Tailored data sharing interfaces are in progress.
- Environmental Data Exploration: Utilization of various environmental databases, including NASA POWER, Copernicus, Harmonized World Soil, and SoilGrids, to gain critical insights into environmental factors affecting crop performance.
- Computomics Platform for Data Sharing: Implementation of the Computomics Platform, a secure web application enabling project creation and segregated data storage. Robust security measures, file sharing, and report publishing have been integrated, with ongoing database development.
- Data Collection and Integration: Successful data collection efforts from diverse sources, resulting in comprehensive datasets for five target species, meeting project requirements.
- Database Development: Design of an in-house SQL database schema and REST API for seamless data integration.
- Computational Modeling: Commencement of computational modeling using collected data for European crop varieties. The modeling process follows best practices in machine learning and is ongoing for five species.
- Simulation Enhancement: Generation of breeding line and hybrid simulations using improved workflow efficiency through algorithm re-implementation.
- Automated Data Processing and Error Checking: Development of a methodology and dedicated software solution for automated data processing, error detection, and correction. Customized process routines have streamlined data processing and minimized errors, facilitating global scalability of ⨉SeedScore® technology.
To ensure further uptake and success, several key needs must be addressed. Market access and commercialization are critical to scale up production and reach a broader customer base. Intellectual property rights support is essential to protect the technology's innovations and maintain Computomics' competitive advantage. Internationalization efforts and partnerships are necessary to expand the technology's reach beyond the EU into global markets. Collaboration with regulatory authorities is crucial to ensure alignment with existing agricultural regulations and standards. Continuous research and development efforts are needed to refine ⨉SeedScore®, enhance its capabilities, and adapt it to additional crop species. Demonstrating the technology's effectiveness through pilot projects and validation studies will be instrumental in building trust and credibility among potential customers and stakeholders.