Integrating AI in seed science: Toward an intelligent design paradigm

Area of Science:

• Agricultural Science
• Biotechnology
• Artificial Intelligence

Background:

• Global food security is threatened by climate change, population growth, and land degradation, necessitating increased agricultural productivity.
• Current productivity gains are insufficient to meet the projected global demand of 9.7 billion by 2050.
• Seed innovation is critical for enhancing crop yield, resilience, and quality to achieve sustainable production.

Purpose of the Study:

• To review the evolution of seed science from ancient practices to intelligent seed design.
• To summarize recent advances in AI-based methodologies and applications within seed science.
• To introduce the paradigm of AI-driven seed design and outline future technological pathways.

Main Methods:

• Literature review of seed science evolution and AI applications.
• Analysis of AI-based methodological innovations in seed science.
• Exploration of core scientific questions, key technologies, and challenges in AI-driven seed design.

Main Results:

• Significant advances in AI applications are transforming seed science.
• The emerging paradigm of AI-driven seed design integrates advanced methodologies for improved outcomes.
• Identification of key technologies and scientific questions crucial for future seed innovation.

Conclusions:

• AI-driven seed design represents a paradigm shift towards sustainable and high-quality seed resources.
• Establishing an "AI for Science" approach in seed science is vital for meeting future global demands.
• Addressing challenges and pursuing future directions will accelerate progress in AI-enhanced seed innovation.