ai-agriculture
AI-agriculture refers to the application of artificial intelligence and machine learning techniques to optimize crop production, disease detection, yield prediction, and resource management in farming systems. For plant science, these tools enable researchers to analyze vast datasets from sensors, satellite imagery, and genomic sources to uncover patterns in plant growth, stress responses, and environmental interactions that would be impossible to detect manually. This accelerates breeding programs, supports precision agriculture, and deepens our understanding of how plants adapt to changing conditions.
PubMed · 2026-01-01
Researchers built a blockchain-based tracking system for wheat in Tunisia using IOTA technology, combining smart contracts, AI yield prediction, and digital identity verification to make the wheat supply chain more transparent and fraud-resistant.
The framework integrates IOTA's feeless, scalable blockchain with smart contracts to automate and record every transaction in the wheat supply chain.
AI is used within the system to predict crop yields, improving planning and reducing waste across the supply chain.
A government-issued mobile app enables real-time verification of transportation credentials by silo managers and police, directly targeting contraband and fraud.
