Artificial Intelligence in seed science

Srikantha, J K and Ashoka, K S and Shubha, J K and kumar, Punith S R (2025) Artificial Intelligence in seed science. World Journal of Advanced Research and Reviews, 27 (1). pp. 852-866. ISSN 2581-9615

The accelerating global population growth, as highlighted by the United Nations Food and Agriculture Organization (UNFAO), intensifies the demand for sustainable food production, particularly in land-constrained regions like India. Despite the historical gains of the Green Revolution, modern Indian agriculture grapples with persistent challenges such as soil degradation, plant diseases, and diminishing crop yields—plant diseases alone account for nearly 40% of losses. In this context, Artificial Intelligence (AI) presents a transformative opportunity to address these issues through precision, speed, and data-driven adaptability. This paper offers a comprehensive review of AI's applications in modern agriculture, with a focused lens on seed science and technology. Key AI components—including machine learning, neural networks, expert systems, and IoT—enable advancements in precision farming, pest control, irrigation, and predictive analytics. In seed science, AI is revolutionizing seed production, quality control, grading, germination testing, and genetic purity assessments through advanced tools like the Rice Seed Germination Evaluation System (RSGES) and image-based diagnostic platforms. Additionally, AI aids in seed marketing and demand forecasting. While the benefits are significant, challenges such as high costs, data security, and accessibility remain. Nevertheless, AI's expanding role promises to enhance agricultural efficiency, seed quality, and resilience, offering a path toward sustainable food security in a changing global climate.