Authors: Eugene Koh, Rohan Shawn Sunil, Hilbert Yuen In Lam, Malavika SujaMdharan, Monika Chodasiewicz, Marek Mutwil
Published on: April 24, 2024
Impact Score: 7.8
Arxiv code: Arxiv:2404.15776
Summary
- What is new: Utilization of artificial intelligence (AI) to rapidly screen through massive datasets for developing stress-resilient plant varieties.
- Why this is important: The need to develop crops that can thrive in diverse environments to feed the growing global population.
- What the research proposes: Employing AI to uncover patterns in massive datasets, enabling faster development of robust models for predicting plant responses to environmental stresses.
- Results: Acceleration of scientific discovery in the development of stress-resilient plant varieties, complementing the advances from the Green Revolution and genomics era.
Technical Details
Technological frameworks used: AI-based screening and predictive analysis
Models used: Proprietary and open-source AI models for pattern recognition and prediction
Data used: Massive and complex datasets related to plant genomics and environmental responses
Potential Impact
Agriculture technology companies, seed production companies, biotech firms focusing on crop resilience and yield improvement
Want to implement this idea in a business?
We have generated a startup concept here: AgriGrowth AI.
Leave a Reply