Artificial Intelligence in Agriculture: A Review of Current and Emerging Applications

Abstract

Artificial Intelligence (AI) represents the future of agriculture and food security; it will guide farmers to produce food sustainably, protecting the health of our planet. It enables the extraction of value from data, facilitating the transition to a more digitised industry. The need for crop and animal monitoring systems that can assist in decision support is growing, with labour shortages and tighter regulations making it harder to increase productivity. Agronomists and farmers are at the heart of these issues. Despite the large amounts of science-driven knowledge available, productivity growth has slowed in many crops. Key trends include a shift from top-down expert-systems and decision-support systems to data-driven approaches, from monoculture crops to more complex crop rotations requiring analytics and experimentation and the addition of food quality parameters including market-locations and moisture-content. Growth continues to be higher in emerging than in developed economies; within the developing world, constraints are much more severe in Sub-Saharan Africa than in other areas (Chen et al., 2023). Current solutions revolve around crop safety, pest management and yield prediction for primary crops including cotton, maize, rice, soybean and wheat. Ongoing efforts in precision agriculture focus on selective disinfectants to target specific problematic microbiota without disrupting other crop-supporting species (Abiri et al., 2023).

The review presents the latest applications of AI across the entire agriculture value-chain. The focus is on the current and expected state-of-art for the next three to five years, detailing transformative initiatives with far-reaching consequences for farmers, output systems and entire regions.

Keywords: AI, future of agriculture, food security.