Integrated biotechnological and AI innovations for crop improvement

Area of Science:

• Agricultural Science
• Biotechnology
• Genomics

Background:

• Global population growth necessitates enhanced crop yield, quality, and sustainability.
• Environmental factors and limited genetic resources constrain current crop improvement efforts.
• A paradigm shift is needed to overcome these limitations.

Purpose of the Study:

• To analyze the integrated use of omics technologies, genome editing, protein design, and high-throughput phenotyping in crop improvement.
• To discuss emerging applications and challenges of these advanced technologies.
• To propose a perspective on incorporating elite alleles into crop genomes using AI.

Main Methods:

• Review of omics technologies (genomics, transcriptomics, proteomics, metabolomics).
• Analysis of genome editing techniques (e.g., CRISPR-Cas9).
• Integration of high-throughput phenotyping and artificial intelligence (AI)-enabled tools.

Main Results:

• Demonstrates the synergistic potential of combining diverse biotechnological approaches.
• Highlights AI's role in data integration and predictive modeling for crop breeding.
• Identifies key challenges in implementing these integrated strategies.

Conclusions:

• Integrating advanced technologies offers a revolutionary path for crop improvement.
• This integrated approach is crucial for achieving sustainable agriculture and ensuring global food security.
• Future directions include incorporating AI-generated elite alleles into crop genomes.